When Does Static Willingness to Pay Mislead? A Framework for Dynamic Hedonic Valuation

Abstract: Many policy counterfactuals depend on how consumers value product attributes such as sugar, sodium, caffeine, alcohol, or emissions. Standard hedonic and differentiated-products models interpret these valuations statically. That interpretation is restrictive when attributes are habit forming: observed prices then reflect both contemporaneous marginal value and the continuation value generated by current consumption. I develop a nonparametric revealed-preference framework for dynamic hedonic valuation, deriving necessary and sufficient conditions for rationalising observed prices and choices. Using household scanner data on cereal purchases, I show that the hedonic representation places real


Bounded Rationality, Societal Progress, Inclusive Institutions: Sustainability and Satisficing Choice

Abstract: <jats:p>Globalization and market-oriented policies have elevated metrics of efficiency, such as income level and profit maximization, to the status of primary indicators of societal progress. However, these maximization rules often misrepresent decision processes that are bounded, multi-attribute, and sensitive to long-term environmental limits. This paper develops a basic framework-and an expanded one via agent-based model (ABM)-for satisficing choice that integrates agents' aspiration thresholds and institutional constraints, showing that satisficing equilibria-stable outcomes where agents reach predefined aspiration thresholds-exist under certain conditions and can systematically differ f


Decision-Making Models for Client-Centred Interior Architecture Solutions

Tabassum Afifa
Rajib Mehedi Hasan
Masuk Yasin Jamil
Akter Tamanna
Mannan Kazi Abdul

Abstract: This paper examines decision-making models applicable to client-centred interior architecture solutions. Drawing on decision theory, human-centred design, evidence-based design, and multi-criteria decision analysis, the study synthesises theoretical perspectives and proposes a qualitative research framework for investigating how designers make, negotiate, and implement decisions that prioritise client needs, constraints, and aspirations. The theoretical framework integrates Herbert A. Simon’s bounded rationality and satisficing, user-centred and participatory design principles, and Multi-Criteria Decision Analysis (MCDA) tools such as the Analytic Hierarchy Process (AHP) to offer an integrat


Quantifying Bounded Rationality: Formal Verification of Simon's Satisficing Through Flexible Stochastic Dominance

Abstract: This paper introduces Flexible First-Order Stochastic Dominance (FFSD), a mathematically rigorous framework that formalizes Herbert Simon's concept of bounded rationality using the Lean 4 theorem prover. We develop machine-verified proofs demonstrating that FFSD bridges classical expected utility theory with Simon's satisficing behavior through parameterized tolerance thresholds. Our approach yields several key results: (1) a critical threshold $\varepsilon < 1/2$ that guarantees uniqueness of reference points, (2) an equivalence theorem linking FFSD to expected utility maximization for approximate indicator functions, and (3) extensions to multi-dimensional decision settings. By encoding


From Constraints to Cognition: Integrating Bounded Rationality into AI Design for Realistic Decision-Making

The Critical Review of Social Sciences Studies

Abstract: This study explores how bounded rationality through the mechanisms of satisficing and heuristics can be systematically embedded into AI system design to enhance human-likeness, cognitive realism, and decision-making efficiency under uncertainty, time pressure, and information overload. While prior work has largely focused on optimizing accuracy or speed, this research addresses the gap in aligning AI behavior with realistic human cognitive constraints. Using a cross-sectional quantitative design, data were collected via structured questionnaires from domain-relevant respondents. Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed to test hypothesized mediation relations


Bounded Rationality and Cognitive Bias: A Meta-Synthetic Framework for Behavioral Economics

Abstract: : The classical economic model of homo economicus has shaped modern economics through its mathematical elegance but at the cost of psychological realism. Over seven decades, an alternative vision has emerged: the human decision-maker as a boundedly rational organism who adapts to uncertainty through heuristics, satisficing, and selective attention. This paper develops a comprehensive meta-synthesis linking bounded rationality and cognitive bias across theoretical, empirical, and institutional domains. It traces the evolution from Simon’s procedural rationality to Gigerenzer’s ecological heuristics, Kahneman’s dual-process framework, Rabin’s confirmatory bias, and Thaler’s behavioural policy


Unleashing the Machine : Exploring the Dual Power of AI's Agentic Behavior and Anthropomorphic Design in an Agents Decision-Making

Jayabhushan Praneeth Pallepogu
Saurabh Gupta

Abstract: Artificial intelligence (AI) use is transforming organizational decision-making. Much of the focus of existing decision-making research has been on AI models' ability to process vast datasets, automate routine tasks, and allow individuals to focus on higher-order thinking [1, 2]. This focus has primarily drawn on the bounded rationality model, which implies that human decision-makers operate within limits of cognitive capacity, time, and accessible information, often leading to satisficing rather than optimal decisions [3]. AI agents, though, unlike traditional decision-making tools, have two added unique characteristics: Agentic Behavior and Anthropomorphic presentation [4]. Agentic behavio


Air pollution and housing market valuation: a spatial hedonic pricing approach to welfare loss estimation

International Journal of Housing Markets and Analysis

Abstract:
Purpose
This study aims to explore three key questions: How does air pollution affect real estate prices across markets, considering income, demographics and urban density? How do spatial econometrics improve air pollution impact estimation compared to traditional hedonic pricing models (HPM)? What are the welfare implications of air pollution, particularly in terms of compensating surplus (CS), and how can a multistage HPM framework enhance economic loss assessment? By addressing these, the research aims to refine property valuation, inform urban policy and support sustainable housing and environmental regulations.

Design/methodology/approach
This study uses a multistage HPM combined with


Bounded Rationality for LLMs: Satisficing Alignment at Inference-Time

Mohamad Chehade
Soumya Suvra Ghosal
Souradip Chakraborty
Avinash Reddy
Dinesh Manocha
Hao Zhu

Abstract: Aligning large language models with humans is challenging due to the inherently multifaceted nature of preference feedback. While existing approaches typically frame this as a multi-objective optimization problem, they often overlook how humans actually make decisions. Research on bounded rationality suggests that human decision making follows satisficing strategies-optimizing primary objectives while ensuring others meet acceptable thresholds. To bridge this gap and operationalize the notion of satisficing alignment, we propose SITAlign: an inference time framework that addresses the multifaceted nature of alignment by maximizing a primary objective while satisfying threshold-based constrai


Sustainability labels in the Spanish coffee market: A hedonic price approach

Spanish Journal of Agricultural Research

Abstract:
Aim of study: Focused on the coffee sector, the purpose of this paper was to determine the implicit price paid for the main sustainability certifications (Fairtrade, Organic, Rainforest Alliance and UTZ certifications) using the hedonic price approach.
Area of study: Spain.
Material and methods: The total sample included 645 coffees. The characteristics were collected between the months of September and October 2021 from coffee packs sold in the main five supermarkets of retail chains in Spain. A log-log price/attribute function was used to estimate the hedonic price function.
Main results: The attributes UTZ certification, origin, and coffee intensity received significant positive effect


Bounded Rationality, Satisficing, Artificial Intelligence, and Decision‐Making in Public Organizations: The Contributions of Herbert Simon

Abstract: In honor of the 75th anniversary of the publication of Herbert Simon's seminal book Administrative Behavior: A Study of Decision-Making Processes in Administrative Organizations, first published in 1947, PAR held a special symposium (Simon 1997). The Royal Swedish Academy of Sciences, which awarded Herbert Simon the Nobel Prize in Economics in 1978, considered Administrative Behavior to be “epoch-making.” The book has a special relationship with PAR, as two of its chapters appeared in PAR prior to its publication (Simon 1944, 1946). Moreover, when PAR selected its half-century's “Great Books” in public administration for its own 50th anniversary, Administrative Behavior was selected as the o


House Price Determinants and Market Segmentation in Boulder, Colorado: A Hedonic Price Approach

Abstract: In this research we perform hedonic regression model to examine the residential property price determinants in the city of Boulder in the state of Colorado, USA. The urban housing markets are too compounded to be considered as homogeneous markets. The heterogeneity of an urban property market requires creation of market segmentation. To test whether residential properties in the real estate market in the city of Boulder are analyzed and predicted in the disaggregate level or at an aggregate level we stratify the housing market based on both property types and location and estimate separate hedonic price models for each submarket. The results indicate that the implicit values of the property


A hedonic pricing method to estimate the value of waterfronts in the Gulf of Mexico

Abstract: Seed ref. Applied hedonic valuation, environmental amenity.


The Architecture of Complexity: Hierarchic Systems

The Sciences of the Artificial (MIT Press, reprint)

Abstract: Seed ref / ANCHOR (Simon). Near-decomposability of complex engineered systems.


Impacts of Street-Visible Greenery on Housing Prices: A Hedonic Price Model and a Massive Street View Image Dataset in Beijing

ISPRS International Journal of Geo-Information

Abstract: Seed ref. Hedonic pricing with large attribute dataset.


The Continuing Impact of Sherwin Rosen's Hedonic Prices and Implicit Markets

Abstract: Seed ref. Retrospective on Rosen's hedonic legacy.


Value-Driven Design

Journal of Spacecraft and Rockets / AIAA

Abstract: Seed ref / ANCHOR-adjacent. Value-driven design replaces requirements flowdown with an economic value objective.


Hedonic Prices and Implicit Markets: Estimating Marginal Willingness to Pay for Differentiated Products Without Instrumental Variables


Herbert A. Simon and the concept of rationality: boundaries and procedures

Abstract: Seed ref / ANCHOR (Simon). Bounded and procedural rationality.


Assessing Changeability in Aerospace Systems Architecting and Design Using Dynamic Multi-Attribute Tradespace Exploration

Abstract: Seed ref. Dynamic tradespace exploration, changeability.


Demand Estimation with Heterogeneous Consumers and Unobserved Product Characteristics: A Hedonic Approach

Abstract: We study the identification and estimation of Gorman-Lancaster style hedonic models of demand for differentiated products for the case when one product characteristic is not observed. Our identification and estimation strategy is a two-step approach in the spirit of Relative to Rosen's approach, we generalize the first stage estimation to allow for a single dimensional unobserved product characteristic, and also allow the hedonic pricing function to have a general, non-additive structure. In the second stage, if the product space is continuous and the functional form of utility is known then there exists an inversion between the consumer's choices and her preference parameters. This inversio


Bounding rationality to the world

Abstract: Seed ref. Ecological/bounded rationality, fast-and-frugal heuristics.


Multi-Attribute Tradespace Exploration with Concurrent Design as a Value-Centric Framework for Space System Architecture and Design

A. M. Ross
D. E. Hastings
J. M. Warmkessel
N. P. Diller

Abstract: Seed ref. MATE value-centric tradespace exploration.


Hedonic Prices and Implicit Markets: Estimating Demand and Supply Functions for Differentiated Products

Abstract: Seed ref. Identification of demand/supply in hedonic markets.


Prospect Theory: An Analysis of Decision under Risk

Abstract: Brain (Kahneman HoS). Decision under risk; supports behavioral prior that designers do not optimize, complementing Simon's satisficing.


Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition

Abstract: Seed ref / ANCHOR. Foundational hedonic framework: price as function of attributes; implicit marginal prices.


Cost Overrun and Financial Risk in Infrastructure Projects: An Overview

Abstract: <jats:p>Cost overruns and financial risks are major challenges in infrastructure project management and frequently affect project performance, investment feasibility, and financial sustainability. This study aims to provide an overview of the major factors contributing to cost overruns and financial risks in infrastructure projects based on previous studies and current industry issues. The study uses a qualitative literature review approach by analyzing relevant literature related to construction management, project finance, and infrastructure development. The findings indicate that inadequate project planning, inaccurate cost estimation, design changes, project delays, cash flow instability


Examining of Project Cost Overrun in Project Management: A Case Study of the Road Development Agency in Lusaka

International Journal of Advanced Multidisciplinary Research and Studies

Abstract: This study investigated the persistent problem of cost overruns in road construction projects managed by the Road Development Agency (RDA) in Lusaka. Recent evidence showed that 78% of projects had exceeded their budgets by an average of 52%, with flagship projects such as the Lusaka-Ndola dual carriageway, Kafue Road expansion, and the Lusaka Decongestion Project recording significant financial escalations. These overruns not only consumed a large share of Zambia’s infrastructure budget but also resulted in delays, reduced quality, and premature defects, raising concerns about long-term sustainability. Guided by Agency Theory, the study examined the causes and consequences of these overruns


Predictive Cost Estimation Using Machine Learning for Proactive Cost Overrun Mitigation in Project Management (Case Study: PT XYZ)

Afganta Chezar Enhartana
Teguh Raharjo
Anita Nur Fitriani

2025 International Conference on Applied Artificial Intelligence, Data Engineering and Sciences (ICAIDES)

Abstract: Project management at PT XYZ is related to Operational, IT, and product development. However, the company faces significant problems in project management: 67% of the total number of projects implemented experience cost overruns. One of the root problems in the technology dimension is the absence of tools to forecast the cost of the project to be implemented. This research is deliberately scoped to projects governed by a traditional waterfall methodology, which represents the dominant framework within the organization. We propose a solution to overcome the root cause through leveraging machine learning (ML) for regression problems as a project cost prediction system. This study found that XG


Variations of parametric cost models for ground and space telescopes

Astronomical Telescopes + Instrumentation

Abstract: Parametric cost models can be used by designers and managers to compare between major architectural cost drivers and allow high-level design trades; enable cost-benefit analysis for technology development investment; and, provide a basis for estimating total project cost between related concepts. Previously, NASA Marshall Space Flight Center developed two parametric first-article optical telescope assembly cost models – one based on aperture diameter and the other based on primary mirror segmentation – using a database with 47 total ground and space telescopes. This paper updates these models to FY23 current dollar and develops a new volume-based model. The purpose of the volume model is to


Minimizing Cost Overrun in Rail Projects through 5D-BIM: A Conceptual Governance Framework

Osama A. I. Hussain
R. Moehler
Stuart D. C. Walsh
D. Ahiaga-Dagbui

Abstract: Integration of 5D Building Information Modeling (BIM) into large rail projects has the potential to significantly enhance cost management and control. Nevertheless, 5D-BIM implementation has encountered difficulties stemming from technical, functional, and governance-related factors. This paper builds a conceptual framework to support financial decision making, enhances project management, and promotes efficient project delivery. The framework encompasses a set of interrelated elements that include project governance, BIM policies and standards, digital platforms, BIM LOD, cost-estimation classification, and continuous improvement. The proposed framework acknowledges the significance of proj


MACHINE LEARNING FOR PARAMETRIC COST ESTIMATION OF AXISYMMETRIC COMPONENTS

Luca Manuguerra
M. Mandolini
M. Germani
Mikhailo Sartini

Abstract: Abstract Machine learning (ML) is a well-established research topic in Industry 4.0 is boosting its adoption. ML is also used for manufacturing cost estimation during design. Such approaches are commonly used to estimate the cost of mass-produced parts. Many consolidated historical data are available for training the regression models. Unfortunately, very often, such a database of data is not available. The paper defines an ML approach for parametric cost estimation of axisymmetric components. The data for training the ML model derives from automatic software for analytically estimating the manufacturing cost. With a proper set of simulations, the tool can generate a large amount of data for


Methodological approach to spacecraft development cost calculation

V. T. Marchenko
O.A. Petliak
N. P. Sazina
P. P. Khorolskyi

Abstract: The aim of this work is to develop a methodological approach to the development of a unified, common for all developers, computer-aided branch procedure for spacecraft development cost estimation based on a spacecraft cost model and practical recommendations on computer-aided branch procedure development. The cost parameters of the development, manufacturing, and operation of new spacecraft and their technical level (perfection) are the determining factors in competitiveness assessment. To decide on the advisability of starting or resuming the development of a new spacecraft, one has to correctly estimate the development cost. Using the standardized calculation method in estimating the devel


Parametric cost model for ground and space telescopes

Abstract: Parametric cost models can be used by designers and project managers to compare cost between major architectural cost drivers and allow high-level design trades; enable cost-benefit analysis for technology development investment; and, provide a basis for estimating total project cost between related concepts. The NASA Marshall Space Flight Center has developed a 5-parameter first-article optical telescope assembly cost model OTA$ (FY17) = $20M x 30 (S/G) x D (1.7) x λ (-0.5) x T (-0.25) x e (-0.028) (Y-1960) Where S/G = 1 for space and 0 for ground telescopes, D = diameter, λ = diffraction limited wavelength, T = operating temperature and Y


Blind validation study of parametric cost estimation tool SEER-H for NASA space missions

Paul D. Friz
Serhat Hosder
Benjamin B. Leser
Benjamin C. Towle


Comparison of Product Life Cycle Cost Estimating Models Based on Neural Networks and Parametric Techniques—A Case Study for Induction Motors

Abstract: The cost estimation of a product’s life cycle is a key factor in the product design process. The research is based on an innovative model of artificial neural networks (ANNs) compared to a parametric estimation. Introducing modern elements of information technologies in the area of cost estimation for a production company is a vital element of its sustainability in the era of Industry 4.0. The presented modern product life cycle cost estimation tool in the form of ANN is a reliable source of forecast that is the basis for the product life cycle cost reduction program, which is a crucial element of sustainability. Research shows that ANNs are a viable alternative to parametric cost estimation


NASA Instrument Cost Model: NICM 8.5

NASA Jet Propulsion Laboratory (NTRS 20210012565)

Abstract: Seed ref. NICM 8.5 instrument cost model update.


Five Things You Should Know About Cost Overrun

Abstract: Brain (Kahneman HoS). Empirics of cost overrun distributions; relevant to cost-variable measurement error and survivorship discussion.


Parametric cost models for space telescopes

H. Philip Stahl
Todd Henrichs
Courtnay Dollinger

Abstract: Multivariable parametric cost models for space telescopes provide several benefits to designers and space system project managers. They identify major architectural cost drivers and allow high-level design trades. They enable cost-benefit analysis for technology development investment. And, they provide a basis for estimating total project cost. A survey of historical models found that there is no definitive space telescope cost model. In fact, published models vary greatly [1]. Thus, there is a need for parametric space telescopes cost models. An effort is underway to develop single variable [2] and multi-variable [3] parametric space telescope cost models based on the latest available data


A Survey of Cost Estimating Methodologies for Distributed Spacecraft Missions

Veronica Foreman
Jacqueline Le Moigne
Olivier de Weck

Abstract: Satellite constellations and Distributed Spacecraft Mission (DSM) architectures offer unique benefits to Earth observation scientists and unique challenges to cost estimators. The Cost and Risk (CR) module of the Tradespace Analysis Tool for Constellations (TAT-C) being developed by NASA Goddard seeks to address some of these challenges by providing a new approach to cost modeling, which aggregates existing Cost Estimating Relationships (CER) from respected sources, cost estimating best practices, and data from existing and proposed satellite designs. Cost estimation through this tool is approached from two perspectives: parametric cost estimating relationships and analogous cost estimation


Multivariable parametric cost model for space and ground telescopes

Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE

Abstract: Parametric cost models can be used by designers and project managers to perform relative cost comparisons between major architectural cost drivers and allow high-level design trades; enable cost-benefit analysis for technology development investment; and, provide a basis for estimating total project cost between related concepts. This paper hypothesizes a single model, based on published models and engineering intuition, for both ground and space telescopes: OTA Cost ~ (X) D (1.75 ± 0.05) λ (-0.5 ± 0.25) T-0.25 e (-0.04) Y Specific findings include: space telescopes cost 50X to 100X more ground telescopes; diameter is the


Latest NASA Instrument Cost Model (NICM): Version VI

NASA Jet Propulsion Laboratory (NTRS 20160008251)

Abstract: Seed ref. NASA instrument-level cost-estimating relationship, version VI; cost predicted from design attributes.


NASA Instrument Cost Model for Explorer-Like Mission Instruments (NICM-E)

NASA Jet Propulsion Laboratory (NTRS 20150007881)

Abstract: Seed ref. NICM-E variant for Explorer-class instruments.


Update on multivariable parametric cost models for ground and space telescopes

H. P. Stahl
T. Henrichs
A. Luedtke
M. West

Abstract: Seed ref. Multivariable parametric telescope cost models.


Update on parametric cost models for space telescopes

H. Philip Stahl
Todd Henrichs
Alexander R. Luedtke
Miranda West

Abstract: Parametric cost models are used to plan missions, compare concepts and justify technology investments. This paper updates an ongoing effort to develop cost modes for space telescopes and summarizes how recent database changes have changed previously published preliminary results. While the models are evolving, the previously published findings are valid: telescope cost increases with aperture diameter; it costs less per square meter of collecting aperture to build a large telescope than a small telescope; lower areal density telescopes cost more than more massive telescopes.


Survey of cost models for space telescopes

Abstract: Seed ref. Survey of space-telescope cost models.


Single-variable parametric cost models for space telescopes

Abstract: Seed ref. Single-variable parametric telescope cost models.


Preliminary multivariable cost model for space telescopes

Abstract: Parametric cost models are routinely used to plan missions, compare concepts and justify technology investments. This paper reviews the methodology used to develop space telescope cost models; summarizes recently published single variable models; and presents preliminary results for two and three variable cost models. Some of the findings are that increasing mass reduces cost; it costs less per square meter of collecting aperture to build a large telescope than a small telescope; and technology development as a function of time reduces cost at the rate of 50% per 17 years.


Preliminary Multi-Variable Cost Model for Space Telescopes


Parametric cost estimation for space science missions

Abstract: Seed ref. Parametric mission cost estimation.


Curbing Optimism Bias and Strategic Misrepresentation in Planning: Reference Class Forecasting

Abstract: Brain (Kahneman HoS). Optimism bias and reference-class forecasting in large project cost estimation; bears on cost-record reliability and the cost regressor.


Ground-Based Telescope Parametric Cost Model

Abstract: A parametric cost model for ground-based telescopes is developed using multi-variable statistical analysis, The model includes both engineering and performance parameters. While diameter continues to be the dominant cost driver, other significant factors include primary mirror radius of curvature and diffraction limited wavelength. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e.. multi-telescope phased-array systems). Additionally, single variable models based on aperture diameter are derived. This analysis indicates that recent mirror technology advances have indeed reduced the historical telescope cost curve.


Vicarious Calibration of Ocean Color Satellite Sensors Based on AERONET-OC Measurements

Xinhao Shi
Shuguo Chen
Junwei Wang
Lianbo Hu
Chaofei Ma
Hailong Peng

Journal of Atmospheric and Oceanic Technology

Abstract: Accurate radiometric calibration is crucial for various applications of ocean color satellite sensors. However, tracking the radiometric performance of sensors after satellites enter orbit using ground-based sources is challenging, as well as effectively evaluating the accuracy of onboard calibration systems. This study attempted to use the Ocean Color component of the Aerosol Robotic Network (AERONET-OC) data to perform vicarious calibration (VC) of ocean color satellite sensors. Through rigorous analysis of in situ AERONET-OC data, several field measurements that meet the predefined stability thresholds were identified as having the potential to be used for VC. Then, the field multispectra


Evaluating the Performance of Satellite-Derived Soil Moisture Products Across South America Using Minimal Ground-Truth Assumptions in Spatiotemporal Statistical Analysis

Abstract: South America (SA) features diverse land cover types and varied climate conditions, both of which significantly influence the variability of soil moisture (SMO). Obtaining ground-truth measurements for SMO is often costly and labor-intensive, and the limited number of ground SMO stations in SA further complicates the evaluation of satellite-derived SMO products. In this work, we proposed an approach that integrates some statistical methods to assess the reliability of Soil Moisture Active Passive (SMAP), the H113 dataset from the Advanced Scatterometer (ASCAT), and Soil Moisture and Ocean Salinity (SMOS) satellite-derived SMO products in SA from 14 May 2015 to 31 December 2016. The integrate


Enhancing landsat 8 land surface temperature retrieval in coastal regions using MODIS atmospheric water vapor data

Tianyi Wang
Zhiqiang Gao
Jicai Ning
Xinpeng Tian
De Wang
Yueqi Wang

Abstract: ABSTRACT The Landsat series has long served as a critical data source for remote sensing-based land surface temperature (LST) retrieval. Accurate LST estimation requires parameters like emissivity and atmospheric transmittance, whose uncertainties can introduce significant errors. This study presents the MODIS three-channel weighted algorithm, which offers robust atmospheric water vapour retrieval capabilities, particularly in regions with high spatial variability such as coastal areas. By analysing variations in atmospheric water vapour across different land cover types, we incorporate these values into Qin’s mono-window algorithm for LST calculation and validate the results through two app


Early Radiometric Assessment of NOAA-21 Visible Infrared Imaging Radiometer Suite Reflective Solar Bands Using Vicarious Techniques

A. Wu
Xiaoxiong Xiong
Qiaozhen Mu
A. Angal
R. Bhatt
Y. Shea

Abstract: The VIIRS instrument on the JPSS-2 (renamed NOAA-21 upon reaching orbit) spacecraft was launched in November 2022, making it the third sensor in the VIIRS series, following those onboard the SNPP and NOAA-20 spacecrafts, which are operating nominally. As a multi-disciplinary instrument, the VIIRS provides the worldwide user community with high-quality imagery and radiometric measurements of the land, atmosphere, cryosphere, and oceans. This study provides an early assessment of the calibration stability and radiometric consistency of the NOAA-21 VIIRS RSBs using the latest NASA SIPS C2 L1B products. Vicarious approaches are employed, relying on reflectance data obtained from the Libya-4 dese


Microwave Radiometer Calibration Using Deep Learning With Reduced Reference Information and 2-D Spectral Features

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Abstract: The accuracy of geophysical retrievals from radiometers relies on calibration quality, encompassing both absolute radiometric accuracy and spectral consistency. Radiometers have employed various calibration techniques, including external targets, vicarious sources, and internal calibrators like noise diodes or matched reference loads. Calibration techniques face challenges like frequency dependence, instrumental effects, environmental influences, drift, aging, and radio frequency interference. Recent hardware advancements enable radiometers to collect raw samples containing both temporal and spectral information. Leveraging advanced modeling techniques like deep learning (DL) enables detecti


An Operational Global Near-Real-Time High-Resolution Seamless Sea Surface Temperature Products From Satellite-Based Thermal Infrared Measurements

IEEE Transactions on Geoscience and Remote Sensing

Abstract: A machine learning-driven algorithm was developed to generate a near-real-time (NRT), high-resolution (1-km), all-sky global SST product using the thermal infrared measurements of MODIS Terra. The algorithm can generate the NRT SST under all-sky conditions, while most current operational algorithms only derive NRT SST for pixels without clouds. Meanwhile, the previous algorithms typically constructed seamless SST products by integrating data from multiple satellites and in situ SST sources with a high computational cost, which are not suitable NRT applications. The current algorithm uses a single sensor dataset to deliver NRT seamless SST. The model has outstanding accuracy in retrieving SST


Passive Only Microwave Soil Moisture Retrieval in Indian Cropping Conditions: Model Parameterization and Validation

D. Gupta
P. Srivastava
D. Pandey
S. Chaudhary
R. Prasad
P. O’neill

Abstract: The present study carried out to parameterize the single channel soil moisture active passive (SMAP) passive soil moisture (SM) retrieval algorithm, over Indian conditions. The moderate resolution imaging spectroradiometer (MODIS) data products and soil texture data were used for an improved parameterization of the algorithm. The bias correction was applied to the MODIS leaf area index (LAI) for accurate computation of vegetation optical depth. The necessary vegetation and roughness parameter were calibrated through minimization of the error between model retrieved and ground measured SM. The value of root mean square error (RMSE) for retrieved SM was found as <inline-formula> <tex-math nota


A Novel Index for Daily Flood Inundation Retrieval from CYGNSS Measurements

Abstract: Since flood inundation hampers human life and the economy, flood inundation retrieval with high temporal resolution and accuracy is essential for the projection of the environmental impact. In this study, a novel cyclone global navigation satellite system (CYGNSS)-based index, named the annual threshold flood inundation index (ATFII) for flood inundation retrieval, is proposed, and the grades of flood inundation are quantified. First, the CYGNSS surface reflectivity with land surface properties (i.e., vegetation and surface roughness) calibration is derived based on the zeroth-order radiative transfer model. Then, an index named ATFII is proposed to achieve inundation retrieval, and the inun


A Pre-Operational System Based on the Assimilation of MODIS Aerosol Optical Depth in the MOCAGE Chemical Transport Model

L. E. Amraoui
M. Plu
V. Guidard
Flavien Cornut
Mickaël Bacles

Abstract: In this study we present a pre-operational forecasting assimilation system of different types of aerosols. This system has been developed within the chemistry-transport model of Météo-France, MOCAGE, and uses the assimilation of the Aerosol Optical Depth (AOD) from MODIS (Moderate Resolution Imaging Spectroradiometer) onboard both Terra and Aqua. It is based on the AOD assimilation system within the MOCAGE model. It operates on a daily basis with a global configuration of 1∘×1∘ (longitude × latitude). The motivation of such a development is the capability to predict and anticipate extreme events and their impacts on the air quality and the aviation safety in the case of a huge volcanic erupt


Spatiotemporal Analysis of MODIS Aerosol Optical Depth Data in the Philippines from 2010 to 2020

N. Caido
P. M. Ong
O. Rempillo
M. C. Galvez
E. Vallar

Abstract: Satellite remote sensing for air quality assessment provides information over a large spatial coverage and time period that shows the trends and effects of anthropogenic activities. Using data collected from the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra satellite from the years 2010 to 2020, the spatiotemporal variations to aerosol optical depth (AOD) in Koronadal City and Quezon City were studied. Validation showed a strong relationship between the MODIS AOD values and the Aerosol Robotic Network (AERONET) AOD values (R2 = 0.83) and a low root mean square error (RMSE) of 0.26. Annual variation in the AOD of the two study areas showed a peak AOD value in 2015 due to an imme


Validation of Multi-Source Satellite Sea Surface Temperature in Southeast Asia and Its Adjacent Seas

Yuanchi Jiang
Weifu Sun
Lei Chen
Jie Zhang

IEEE International Geoscience and Remote Sensing Symposium

Abstract: The accuracy of SST derived from passive-microwave (AMSR2, GMI, and WindSat) and infrared (AVHRR, MODIS onboard Terra and Aqua and VIIRS) radiometers in Southeast Asia and its adjacent seas is evaluated using Argo observations. The results show that the root mean square errors (RMSEs) of the differences between SST from passive-microwave radiometers (AMSR2, GMI, and WindSat) and Argo SST are 0.46°C, 0.42°C, and 0.50°C, respectively. The RMSEs of the SST differences between infrared radiometers (VIIRS, AVHRR, MODIS onboard Aqua and Terra) and Argo buoy are 0.54°C, 0.63°C, 0.65°C, and 0.64°C, respectively. In addition, the spatial coverage of the satellite SST products in Southeast Asia and it


Thermal Hydraulic Disaggregation of SMAP Soil Moisture Over the Continental United States

Abstract: Thermal Hydraulic disaggregation of Soil Moisture (THySM) algorithm was implemented to downscale NASA’s Soil Moisture Active Passive (SMAP) Enhanced soil moisture (SM) product to 1 km over the continental United States (CONUS). This algorithm was developed by combining thermal inertia theory with a soil hydraulic-based approach that considers fine-scale SM spatial distribution driven by both heat fluxes and hydraulic conductivity in  soils. Relative soil wetness values were estimated using  land surface temperature and normalized difference vegetation index for the thermal inertia model and using soil properties for the hydraulic model. The relative soil wetness values at 1 km from both mode


Validation of IMERG Oceanic Precipitation over Kwajalein

Jianxin Wang
David B. Wolff
Jackson Tan
David A. Marks
Jason L. Pippitt
George J. Huffman

Abstract: <jats:p>The integrated Multi-satellitE Retrievals for GPM (IMERG) Version V05B and V06B precipitation products from the Global Precipitation Measurement (GPM) mission are validated against ground-based observations from the Kwajalein Polarimetric S-band Weather Radar (KPOL) deployed at Kwajalein Atoll in the central Pacific Ocean. Such a validation is particularly important as comprehensive surface measurements over the oceans are practically infeasible, which hampers the identification of possible errors, and improvement of future versions of IMERG and other satellite-based retrieval algorithms. The V05B and V06B IMERG products are validated at their native 0.1°, 30 min resolution from 2014


Calibration and Validation of the TEMPEST-D CubeSat Radiometer

W. Berg
Shannon T. Brown
B. Lim
S. Reising
Y. Goncharenko
C. Kummerow

Abstract: Temporal Experiment for Storms and Tropical Systems—Demonstration (TEMPEST-D) is a 6U CubeSat satellite with a cross-track scanning millimeter-wave radiometer measuring at five frequencies from 87 to 181 GHz. It employs a direct-detection architecture with InP HEMT monolithic microwave integrated circuit (MMIC) low-noise amplifiers and related new technologies. An end-to-end two-point external calibration is performed every 2-s rotation of the scanning mirror, based on observations of the cosmic microwave background and an internal blackbody calibration target, with three thermistors to monitor the target physical temperature. Corrections for antenna pattern effects and cross-scan biases bas


Assessing Disaggregated SMAP Soil Moisture Products in the United States

Abstract: A soil moisture (SM) disaggregation algorithm based on thermal inertia (TI) theory was implemented to downscale the Soil Moisture Active Passive (SMAP) Enhanced product(SPL2SMPE) from 9 km to 1 km over the continental United States. The algorithm applies land surface temperature and normalized difference vegetation index from Moderate Resolution  Imaging Spectroradiometer (MODIS) at higher spatial resolution to estimate relative soil wetness within a coarse SMAP grid -this MODIS-derived relative wetness is then used to produce the downscaled SMAP SM. Results from the algorithm were evaluated in terms of their spatiotemporal coverage and accuracy using in  situ measurements from SMAP Core Val


Computation Approach for Quantitative Dielectric Constant from Time Sequential Data Observed by CYGNSS Satellites

Junchan Lee
S. Bisnath
Regina S. K. Lee
Narin Gavili Kilane

Abstract: This paper describes a computation method for obtaining dielectric constant using Global Navigation Satellite System reflectometry (GNSS-R) products. Dielectric constant is a crucial component in the soil moisture retrieval process using reflected GNSS signals. The reflectivity for circular polarized signals is combined with the dielectric constant equation that is used for radiometer observations. Data from the Cyclone Global Navigation Satellite System (CYGNSS) mission, an eight-nanosatellite constellation for GNSS-R, are used for computing dielectric constant. Data from the Soil Moisture Active Passive (SMAP) mission are used to measure the soil moisture through its radiometer, and they a


SEVIRI Aerosol Optical Depth Validation Using AERONET and Intercomparison with MODIS in Central and Eastern Europe

N. Ajtai
Alexandru Mereuță
Stefanie Horatiu
A. Radovici
Camelia Botezan
O. Zawadzka‐Manko

Abstract: This paper presents the validation results of Aerosol Optical Depth (AOD) retrieved from the Spinning Enhanced Visible Infrared Radiometer (SEVIRI) data using the near-real-time algorithm further developed in the frame of the Satellite-based Monitoring Initiative for Regional Air quality (SAMIRA) project. The SEVIRI AOD was compared against multiple data sources: six stations of the Aerosol Robotic Network (AERONET) in Romania and Poland, three stations of the Aerosol Research Network in Poland (Poland–AOD) and Moderate Resolution Imaging Spectroradiometer (MODIS) data overlapping Romania, Czech Republic and Poland. The correlation values between a four-month dataset (June–September 2014) fr


The Contributions of Gauge-Based Precipitation and SMAP Brightness Temperature Observations to the Skill of the SMAP Level-4 Soil Moisture Product

Abstract: Soil Moisture Active Passive (SMAP) mission L-band brightness temperature (Tb) observations are routinely assimilated into the Catchment land surface model to generate Level-4 Soil Moisture (L4_SM) estimates of global surface and root-zone soil moisture at 9-km, 3-hourly resolution with ~2.5-day latency.  The Catchment model in the L4_SM algorithm is driven with ¼-degree, hourly surface meteorological forcing data from the Goddard Earth Observing System (GEOS).  Outside of Africa and the high latitudes, GEOS precipitation is corrected using Climate Prediction Center Unified (CPCU) gauge-based, ½-degree, daily precipitation.  L4_SM soil moisture was previously shown to improve over land model


Validation Assessment for the Soil Moisture Active Passive (SMAP) Level 4 Carbon (L4_C) Data Product Version 5

Abstract: The post-launch Cal/Val phase of the SMAP mission is guided by two primary objectives for each science  product  team:  1)  to  calibrate,  verify,  and  improve  the  performance  of  the  science  algorithms, and 2) validate accuracies of the science data products as specified in the SMAP Level-1 mission science requirements. Algorithm science and product maintenance activities during the SMAP  extended  mission  phase  have  also  involved  periodic  algorithm  calibration  and  product  refinements to maintain or enhance product consistency and performance as well as science utility. This  report  provides  an  assessment  of  the  latest  (Version  5)  SMAP  Level  4  Carbon  (L4_C)  pr


Evaluation of GEOS Precipitation Flagging for SMAP Soil Moisture Retrieval Accuracy

Abstract: The precipitation flag in the Soil Moisture Active Passive (SMAP) Level 2 passive soil moisture (L2SMP) retrieval product indicates the presence or absence of heavy precipitation at the time of the SMAP overpass. The flag is based on precipitation estimates from the Goddard Earth Observing System (GEOS) Forward Processing numerical weather prediction system. An error in flagging during an active or recent precipitation event can produce either 1) an overestimation of soil moisture due to short-term surface wetting of vegetation and/or surface ponding (if soil moisture retrieval was attempted in the presence of rain) or 2) an unnecessary nonretrieval of soil moisture and loss of data (if retr


Half a century of satellite remote sensing of sea-surface temperature

Abstract: Seed ref. SST validation record, bias and standard-deviation statistics over decades.


Observational Needs of Sea Surface Temperature

Abstract: Seed ref. SST observational requirements and accuracy needs.


MODIS Collection 6.1 aerosol optical depth products over land and ocean: validation and comparison

Abstract: Abstract Recently, the newest Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6.1 (C6.1) aerosol optical depth (AOD) products were available with various refinements and improvements made to both the radiation calibration and Dark Target (DT) and Deep Blue (DB) algorithms. A combined DT and DB dataset (DTB) was also added based on piecewise fixed thresholds using the Normalized Difference Vegetation Index (NDVI) for taking advantage of one's merits. This study provides a cross-comparison and evaluation of these Terra MODIS aerosol products with reference to the enhanced ground-based AOD measurements by the Aerosol Robotic Network (AERONET) Level 3 Version 2.0 data at 384 gro


Initial Assessment of Radiometric Performance of N20 VIIRS Reflective Solar Bands Using Vicarious Approaches

Abstract: The newly launched (November 18, 2017) polar-orbiting satellite of the Joint Polar Satellite System (JPSS-1), now transitioned to NOAA-20, is the follow-on mission to the SNPP (Suomi National Polar-orbiting Partnership) satellite, launched six years ago. NOAA-20 leads SNPP by a half orbit or about 50 minutes. The Visible Infrared Imaging Radiometer Suite (VIIRS) is a key sensor onboard both NOAA-20 and SNPP spacecraft with nearly identical band spectral responses. Similar to the heritage sensor MODIS, VIIRS has on-board calibration components including a solar diffuser (SD) and a solar diffuser stability monitor (SDSM) for the reflective solar bands (RSB), a V-groove blackbody for the therma


Validation of SMAP surface soil moisture products with core validation sites

Abstract: Seed ref. SMAP soil moisture validation, RMSE and unbiased RMSE against core sites.


Assessment of the SMAP Level-4 Surface and Root-Zone Soil Moisture Product Using In Situ Measurements

Rolf H. Reichle
Gabriëlle De Lannoy
Qing Liu
J. Ardizzone
Andreas Colliander
Austin Conaty

Abstract: Abstract The Soil Moisture Active Passive (SMAP) mission Level-4 Surface and Root-Zone Soil Moisture (L4_SM) data product is generated by assimilating SMAP L-band brightness temperature observations into the NASA Catchment land surface model. The L4_SM product is available from 31 March 2015 to present (within 3 days from real time) and provides 3-hourly, global, 9-km resolution estimates of surface (0–5 cm) and root-zone (0–100 cm) soil moisture and land surface conditions. This study presents an overview of the L4_SM algorithm, validation approach, and product assessment versus in situ measurements. Core validation sites provide spatially averaged surface (root zone) soil moisture measurem


The Global Precipitation Measurement (GPM) Mission for Science and Society

Bulletin of the American Meteorological Society

Abstract: Seed ref. GPM mission, precipitation products and validation.


Effect of MODIS Terra Radiometric Calibration Improvements on Collection 6 Deep Blue Aerosol Products: Validation and Terra/Aqua Consistency

Abstract: The Deep Blue (DB) algorithm's primary data product is midvisible aerosol optical depth (AOD). DB applied to Moderate Resolution Imaging Spectroradiometer (MODIS) measurements provides a data record since early 2000 for MODIS Terra and mid-2002 for MODIS Aqua. In the previous data version (Collection 5, C5), DB production from Terra was halted in 2007 due to sensor degradation; the new Collection 6 (C6) has both improved science algorithms and sensor radiometric calibration. This includes additional calibration corrections developed by the Ocean Biology Processing Group to address MODIS Terra's gain, polarization sensitivity, and detector response versus scan angle, meaning DB can now be app


Validation and uncertainty estimates for MODIS Collection 6 “Deep Blue” aerosol data

A. M. Sayer
N. Christina Hsu
C. Bettenhausen
Myeong-Jae Jeong

Journal of Geophysical Research Atmospheres

Abstract: The “Deep Blue” aerosol optical depth (AOD) retrieval algorithm was introduced in Collection 5 of the Moderate Resolution Imaging Spectroradiometer (MODIS) product suite, and complemented the existing “Dark Target” land and ocean algorithms by retrieving AOD over bright arid land surfaces, such as deserts. The forthcoming Collection 6 of MODIS products will include a “second generation” Deep Blue algorithm, expanding coverage to all cloud‐free and snow‐free land surfaces. The Deep Blue dataset will also provide an estimate of the absolute uncertainty on AOD at 550 nm for each retrieval. This study describes the validation of Deep Blue Collection 6 AOD at 550 nm ( τ M ) from MODIS Aqua agains


SMOS/SMAP Synergy for SMAP Level 2 Soil Moisture Algorithm Evaluation

Abstract: Soil Moisture Active Passive (SMAP) satellite has been proposed to provide global measurements of soil moisture and land freeze/thaw state at 10 km and 3 km resolutions, respectively. SMAP would also provide a radiometer-only soil moisture product at 40-km spatial resolution. This product and the supporting brightness temperature observations are common to both SMAP and European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission. As a result, there are opportunities for synergies between the two missions. These include exploiting the data for calibration and validation and establishing longer term L-band brightness temperature and derived soil moisture products. In this investiga


Performance Metrics for Soil Moisture Retrievals and Application Requirements

Abstract: Seed ref. Formalized soil-moisture performance metrics and requirements.


In-Flight Validation of Mid and Thermal Infrared Remotely Sensed Data Using the Lake Tahoe and Salton Sea Automated Validation Sites

Abstract: The presentation includes an introduction, Lake Tahoe site layout and measurements, Salton Sea site layout and measurements, field instrument calibration and cross-calculations, data reduction methodology and error budgets, and example results for MODIS. Summary and conclusions are: 1) Lake Tahoe CA/NV automated validation site was established in 1999 to assess radiometric accuracy of satellite and airborne mid and thermal infrared data and products. Water surface temperatures range from 4-25C.2) Salton Sea CA automated validation site was established in 2008 to broaden range of available water surface temperatures and atmospheric water vapor test cases. Water surface temperatures range from


The MODIS Aerosol Algorithm, Products, and Validation

Abstract: Seed ref. MODIS aerosol retrieval algorithm and validated expected-error envelope.


The Version-2 Global Precipitation Climatology Project (GPCP) Monthly Precipitation Analysis

Abstract: Seed ref. GPCP precipitation analysis and validation.


AERONET, A Federated Instrument Network and Data Archive for Aerosol Characterization

Abstract: Seed ref. AERONET ground reference network underpinning aerosol validation.


DFW: A Novel Weighting Scheme for Covariate Balancing and Treatment Effect Estimation

Ahmad Saeed Khan
Erik Schaffernicht
J. A. Stork

Abstract: Estimating causal effects from observational data is challenging due to selection bias, which leads to imbalanced covariate distributions across treatment groups. Propensity score-based weighting methods are widely used to address this issue by reweighting samples to simulate a randomized controlled trial (RCT). However, the effectiveness of these methods heavily depends on the observed data and the accuracy of the propensity score estimator. For example, inverse propensity weighting (IPW) assigns weights based on the inverse of the propensity score, which can lead to instable weights when propensity scores have high variance—either due to data or model misspecification—ultimately degrading


Inference on Variable Importance for Treatment Effect Heterogeneity: Shapley Values and Beyond

Pawel Morzywolek
Peter B. Gilbert
Alex Luedtke

Abstract: We provide an inferential framework to assess variable importance for heterogeneous treatment effects. This assessment is especially useful in high-risk domains such as medicine, where decision makers hesitate to rely on black-box treatment recommendation algorithms. The variable importance measures we consider are local in that they may differ across individuals, while the inference is global in that it tests whether a given variable is important for any individual. Our approach builds on recent developments in semiparametric theory for function-valued parameters, and is valid even when statistical machine learning algorithms are employed to quantify treatment effect heterogeneity. We demon


Evaluating Different Covariate Balancing Methods: A Monte Carlo Simulation

Abstract: Abstract We investigate the effectiveness of five weighting and matching techniques, including propensity score matching (PSM), in improving covariate balance and reducing bias when estimating treatment effects in finite-sample situations through Monte Carlo simulations. King and Nielsen (2019. “Why Propensity Scores Should Not Be Used for Matching.” Political Analysis 27 (4): 435–54) argue that pruning observations based on PSM with 1-to-1 greedy matching can worsen rather than improve covariate balance and can increase the bias in the estimates of treatment effects. In our simulations, we observed this phenomenon not only in PSM with 1-to-1 greedy matching but also in other covariate balan


Revisiting the propensity score's central role: Towards bridging balance and efficiency in the era of causal machine learning

Abstract: About forty years ago, in a now--seminal contribution, Rosenbaum & Rubin (1983) introduced a critical characterization of the propensity score as a central quantity for drawing causal inferences in observational study settings. In the decades since, much progress has been made across several research fronts in causal inference, notably including the re-weighting and matching paradigms. Focusing on the former and specifically on its intersection with machine learning and semiparametric efficiency theory, we re-examine the role of the propensity score in modern methodological developments. As Rosenbaum & Rubin (1983)'s contribution spurred a focus on the balancing property of the prope


Estimation and Inference on Treatment Effects Under Treatment-Based Sampling Designs

Abstract: Causal inference in a program evaluation setting faces the problem of external validity when the treatment effect in the target population is different from the treatment effect identified from the population of which the sample is representative. This paper focuses on a situation where such discrepancy arises by a stratified sampling design based on the individual treatment status and other characteristics. In such settings, the design probability is known from the sampling design but the target population depends on the underlying population share vector which is often unknown, and except for special cases, the treatment effect parameters are not identified. In this paper, we propose a met


Entropy balancing for causal generalization with target sample summary information

Abstract: In this paper, we focus on estimating the average treatment effect (ATE) of a target population when individual‐level data from a source population and summary‐level data (e.g., first or second moments of certain covariates) from the target population are available. In the presence of the heterogeneous treatment effect, the ATE of the target population can be different from that of the source population when distributions of treatment effect modifiers are dissimilar in these two populations, a phenomenon also known as covariate shift. Many methods have been developed to adjust for covariate shift, but most require individual covariates from a representative target sample. We develop a weight


Using Synthetic Controls: Feasibility, Data Requirements, and Methodological Aspects

Abstract: Brain (Abadie HoS). The anchor methodologist's own review: convex weighting, common support, no extrapolation, pre-registration of donor pool and predictors. Anchor citation for the identification chapter.


Stronger instruments and refined covariate balance in an observational study of the effectiveness of prompt admission to intensive care units

L. Keele
S. Harris
Samuel D. Pimentel
R. Grieve

Journal of the Royal Statistical Society: Series A (Statistics in Society)

Abstract: Instrumental variable methods, subject to appropriate identification assumptions, enable consistent estimation of causal effects in the presence of unobserved confounding. Near–far matching has been proposed as one analytic method to improve inference by strengthening the effect of the instrument on the exposure and balancing observable characteristics between groups of subjects with low and high values of the instrument. However, in settings with hierarchical data (e.g. patients nested within hospitals), or where several covariate interactions must be balanced, conventional near–far matching algorithms may fail to achieve the requisite covariate balance. We develop a new matching algorithm,


Estimation of treatment effects under endogenous heteroskedasticity

Abstract: The empirical literature on program evaluation limits its scope almost exclusively to models where treatment effects are homogenous for observationally identical individuals. This paper considers a treatment effect model in which treatment effects may be heterogeneous, even among observationally identical individuals. Specifically, extending the classical instrumental variables (IV) model with an endogenous binary treatment and a binary instrument, we allow the heteroskedasticity of the error disturbance to also depend upon the treatment variable so that treatment has both mean and variance effects on the outcome. In this endogenous heteroskedasticity IV (EHIV) model with heterogeneous indiv


Semiparametric Regression using Variational Approximations

Francis K. C. Hui
Chong You
Han Lin Shang
Samuel Müller

Abstract: Semiparametric regression offers a flexible framework for modeling non-linear relationships between a response and covariates. A prime example are generalized additive models where splines (say) are used to approximate non-linear functional components in conjunction with a quadratic penalty to control for overfitting. Estimation and inference are then generally performed based on the penalized likelihood, or under a mixed model framework. The penalized likelihood framework is fast but potentially unstable, and choosing the smoothing parameters needs to be done externally using cross-validation, for instance. The mixed model framework tends to be more stable and offers a natural way for choos


Covariate balancing propensity score for a continuous treatment: Application to the efficacy of political advertisements

Abstract: Propensity score matching and weighting are popular methods when estimating causal effects in observational studies. Beyond the assumption of unconfoundedness, however, these methods also require the model for the propensity score to be correctly specified. The recently proposed covariate balancing propensity score (CBPS) methodology increases the robustness to model misspecification by directly optimizing sample covariate balance between the treatment and control groups. In this paper, we extend the CBPS to a continuous treatment. We propose the covariate balancing generalized propensity score (CBGPS) methodology, which minimizes the association between covariates and the treatment. We deve


Entropy Balancing is Doubly Robust

Abstract: Abstract Covariate balance is a conventional key diagnostic for methods estimating causal effects from observational studies. Recently, there is an emerging interest in directly incorporating covariate balance in the estimation. We study a recently proposed entropy maximization method called Entropy Balancing (EB), which exactly matches the covariate moments for the different experimental groups in its optimization problem. We show EB is doubly robust with respect to linear outcome regression and logistic propensity score regression, and it reaches the asymptotic semiparametric variance bound when both regressions are correctly specified. This is surprising to us because there is no attempt


The State of Applied Econometrics - Causality and Policy Evaluation

Abstract: In this paper we discuss recent developments in econometrics that we view as important for empirical researchers working on policy evaluation questions. We focus on three main areas, where in each case we highlight recommendations for applied work. First, we discuss new research on identification strategies in program evaluation, with particular focus on synthetic control methods, regression discontinuity, external validity, and the causal interpretation of regression methods. Second, we discuss various forms of supplementary analyses to make the identification strategies more credible. These include placebo analyses as well as sensitivity and robustness analyses. Third, we discuss recent ad


Entropy Balancing for Causal Effects: A Multivariate Reweighting Method to Produce Balanced Samples in Observational Studies

Abstract: Brain (Abadie HoS). Maximum-entropy reweighting calibrates unit weights to satisfy prespecified covariate-moment balance, removing iterative balance-checking. Directly operationalizes the prospectus covariate-balancing-across-instrument-classes step.


Genetic Matching for Estimating Causal Effects: A General Multivariate Matching Method for Achieving Balance in Observational Studies

Abstract: This paper presents genetic matching, a method of multivariate matching that uses an evolutionary search algorithm to determine the weight each covariate is given. Both propensity score matching and matching based on Mahalanobis distance are limiting cases of this method. The algorithm makes transparent certain issues that all matching methods must confront. We present simulation studies that show that the algorithm improves covariate balance and that it may reduce bias if the selection on observables assumption holds. We then present a reanalysis of a number of data sets in the LaLonde (1986) controversy.


Synth: An R Package for Synthetic Control Methods in Comparative Case Studies

Abstract: Brain (Abadie HoS). Software/practitioner reference for balancing-weight estimation; placebo inference.


Sieve M-estimation for semiparametric varying-coefficient partially linear regression

Abstract: Seed ref. Semiparametric partially linear estimation theory.


Recent Developments in the Econometrics of Program Evaluation

Abstract: Seed ref / ANCHOR (Abadie tradition). Selection-on-observables, matching, program evaluation.


Econometric Evaluation of Social Programs, Part II: Using the Marginal Treatment Effect to Organize Alternative Econometric Estimators to Evaluate Social Programs, and to Forecast their Effects in New Environments

Abstract: This chapter uses the marginal treatment effect (MTE) to unify and organize the econometric literature on the evaluation of social programs. The marginal treatment effect is a choice-theoretic parameter that can be interpreted as a willingness to pay parameter for persons at a margin of indifference between participating in an activity or not. All of the conventional treatment parameters as well as the more economically motivated treatment effects can be generated from a baseline marginal treatment effect. All of the estimation methods used in the applied evaluation literature, such as matching, instrumental variables, regression discontinuity methods, selection and control function methods,


Econometric Evaluation of Social Programs, Part III: Distributional Treatment Effects, Dynamic Treatment Effects, Dynamic Discrete Choice, and General Equilibrium Policy Evaluation

Abstract: This chapter develops three topics. (1) Identification of the distributions of treatment effects and the distributions of agent subjective evaluations of treatment effects. Methods for identifying ex ante and ex post distributions are presented and empirical examples are given. (2) Identification of dynamic treatment effects. The relationship between the statistical literature on dynamic causal inference based on sequential-randomization and the dynamic discrete-choice literature is exposited. The value of well posed economic choice models for decision making under uncertainty in analyzing and interpreting dynamic intervention studies is developed. A survey of the dynamic discrete-choice lit


Efficient Semiparametric Estimation of a Partially Linear Quantile Regression Model

Abstract: Seed ref. Partially linear quantile regression estimation.


The Economic Costs of Conflict: A Case Study of the Basque Country

Abstract: Brain (Abadie HoS). Foundational synthetic-control application; comparable-unit construction logic underpins the common-support restriction.


Econometric issues of estimating hedonic price functions

Abstract: Seed ref. Functional-form, omitted-attribute, multicollinearity hazards in hedonics.


Joint retrieval of atmospheric temperature and humidity profiles using spaceborne hyperspectral microwave radiometer

Chao Zhang
Jieying He
Gang Ma
Shengwei Zhang
Minjie Zhang

Abstract: ABSTRACT This paper explores the performance advantages of spaceborne hyperspectral microwave radiometers for jointly retrieving atmospheric temperature and humidity profiles under clear-sky conditions. It utilizes 4,440 channels at a spectral resolution of 10 MHz and 444 channels at a spectral resolution of 100 MHz across the 60 GHz, 118 GHz, and 183 GHz bands. The Atmospheric Radiative Transfer Simulator (ARTS) was employed as the forward model to generate virtual high-spectral-resolution observational data, based on 10,745 marine profiles from the ECMWF-137 dataset. Channel selection eliminated about half of the channels with spectral resolutions of both 10 MHz and of 100 MHz while retain


Sensitivity, Uncertainty, Information Content, and Channel Selection for Hyperspectral Reflective Solar Retrievals of Cirrus Cloud Properties

Abstract: Inferring cirrus cloud properties from spaceborne observations inevitably involves uncertainties from both forward models and measurements. These uncertainties are present in the retrieval products and propagate to downstream data-ingesting applications in atmospheric and climate modeling. Satellite reflective solar hyperspectral instruments are highly information dense and offer a means to reduce uncertainties in cirrus cloud property retrieval products. However, hyperspectral instruments contain a large number of channels imposing large computational expenses both with measurement data and radiative transfer modeling needed to perform cirrus cloud property retrievals. While using all the c


Supplementary material to "Synthetic mapping of XCO
                  2
                  retrieval performance from shortwave infrared measurements: impact of spectral resolution, signal-to-noise ratio and spectral band selection"


Channel selection of high-spectral resolution interferometer sounder for use in temperature retrieval

Congming Dai
XIN WU
Heili Wei
Xikui Miao

Fourth Seminar on Novel Optoelectronic Detection Technology and Application


Evaluation of the PROSAIL Model Capabilities for Future Hyperspectral Model Environments: A Review Study

Katja Berger
Clement Atzberger
Martin Danner
Guido D’Urso
Wolfram Mauser
Francesco Vuolo

Abstract: Upcoming satellite hyperspectral sensors require powerful and robust methodologies for making optimum use of the rich spectral data. This paper reviews the widely applied coupled PROSPECT and SAIL radiative transfer models (PROSAIL), regarding their suitability for the retrieval of biophysical and biochemical variables in the context of agricultural crop monitoring. Evaluation was carried out using a systematic literature review of 281 scientific publications with regard to their (i) spectral exploitation, (ii) vegetation type analyzed, (iii) variables retrieved, and (iv) choice of retrieval methods. From the analysis, current trends were derived, and problems identified and discussed. Our a


Multispectral information from TANSO-FTS instrument - Part 1: Application to greenhouse gases (CO 2 and CH 4 ) in clear sky conditions

Abstract: Abstract. The Greenhouse gases Observing SATellite (GOSAT) mission, and in particular the Thermal And Near infrared Sensor for carbon Observations–Fourier Transform Spectrometer (TANSO-FTS) instrument, has the advantage of being able to measure simultaneously the same field of view in different spectral ranges with a high spectral resolution. These features allow studying the benefits of using multispectral measurements to improve the CO2 and CH4 retrievals. In order to quantify the impact of the spectral synergy on the retrieval accuracy, we performed an information content (IC) analysis from simulated spectra corresponding to the three infrared bands of TANSO-FTS. The advantages and limita


Methodology and Information Content of the NOAA NESDIS Operational Channel Selection for the Cross-Track Infrared Sounder (CrIS)

Abstract: The Cross-track Infrared Sounder (CrIS) was launched on October 28, 2011 aboard the Suomi National Polar-orbiting Partnership platform and is scheduled to become operational in 2012. The purpose of this paper is to describe the National Oceanic and Atmospheric Administration/National Environmental Satellite and Information Service (NOAA/NESDIS) channel selection methodology applied to the CrIS instrument and to present the main spectral characteristics of the final channel subset that will be operationally distributed to the scientific community for near-real-time data assimilation and retrieval applications. We perform an information content analysis and show that this selection, composed o


Global Land Surface Emissivity Retrieved From Satellite Ultraspectral IR Measurements

Abstract: Ultraspectral resolution infrared (IR) radiances obtained from nadir observations provide information about the atmosphere, surface, aerosols, and clouds. Surface spectral emissivity (SSE) and surface skin temperature from current and future operational satellites can and will reveal critical information about the Earth s ecosystem and land-surface-type properties, which might be utilized as a means of long-term monitoring of the Earth s environment and global climate change. In this study, fast radiative transfer models applied to the atmosphere under all weather conditions are used for atmospheric profile and surface or cloud parameter retrieval from ultraspectral and/or hyperspectral spac


Understanding the aerosol information content in multi-spectral reflectance measurements using a synergetic retrieval algorithm

D. Martynenko
T. Holzer-Popp
H. Elbern
M. Schroedter-Homscheidt

Abstract: <jats:p>Abstract. The multi-wavelength SYNergetic AErosol Retrieval algorithm SYNAER (Holzer-Popp et al., 2002) is used to retrieve aerosol parameters from the Advanced Along Tracking Scanning Radiometer (AATSR) and the Scanning Imaging Absorption Spectrometer for Atmospheric CHartographY (SCIAMACHY). An information content analysis (Holzer-Popp et al., 2008) was performed to quantify the number of independent pieces of information can be retrieved from the combined reflectance measurements of aerosols by both instruments. In particular, the capability of SYNAER to discern various aerosol types is assessed. The focus of this work is further placed on an information content analysis with emph


Channel selection using information content analysis: A case study of CO2 retrieval from near infrared measurements

L. Kuai
V. Natraj
R. Shia
C. Miller
Y. Yung


Predicted errors of tropospheric emission spectrometer nadir retrievals from spectral window selection

John R. Worden
S. S. Kulawik
Mark W. Shephard
S. A. Clough
H. M. Worden
K. W. Bowman

Abstract: Error covariances and vertical resolutions are reported for Tropospheric Emission Spectrometer (TES) nadir‐view retrievals of surface temperature, atmospheric temperature, H 2 O, O 3 , CO, and CH 4 . These error covariances are computed as a result of selecting spectral windows that maximize the information content of simulated, TES nadir‐view atmospheric retrievals of four regions representative of northern midlatitude, southern midlatitude, tropical, and polar climates. The information content of a retrieval is a function of an a priori and an a posteriori covariance matrix where the a posteriori covariance depends on an estimated smoothing error, measurement error, and systematic errors f


Information content and optimisation of high spectral resolution remote measurements


Information content and optimization of high-spectral-resolution measurements

Abstract: A remote measurement of the atmosphere with high spectral resolution form the ground or from space, such as might be made form one of the new generation of instruments such as the Fourier transform or grating spectrometers AIRS, MIPAS, TES, or IASI, would appear to contain a large amount of information about the atmosphere, but it is not immediately obvious how to quantify it or to use it efficiently or effectively. The usefulness of a particular remote measurement can be described by a wide range of parameters including the spatial resolution, precision and accuracy of the retrieved product. For optimization of a measurement method, however, a single scalar figure of merit is required, wher


Experimental study on the impact of long communication delays on autonomous decision-making in deep space habitats

Abstract: Space vehicles and habitats are complex systems with tightly coupled interdependencies. They operate under extreme, unforgiving conditions that challenge system performance and crew safety. Effective health management in such systems demands strong architectural and situational knowledge, leading to heavy reliance on ground control. As missions venture deeper into space, growing communication delays make such support impractical, prompting a paradigm shift toward greater on-board autonomy. However, computational constraints limit the migration of all health management components to the habitat. Running high-fidelity fault detection and diagnosis modules on the ground can conserve on-board re


A Comprehensive Review of Cost Overrun Factors in Construction Projects

Dhruv G. Italiya
Prof. (Dr.) J. R. Pitroda
P. C. Raichura

INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT

Abstract:
Abstract

Cost overruns are the common issue encountered in current construction developments and they often lead to cost increase strain, project overrun delays, and poor relationship between the project stakeholders.  This paper discusses the major reasons behind cost overruns as well as ways of enhancing its management.  The findings indicate that issues such as adjustments in design, poor planning, communication, and the unexpected environmental and financial situations often lead to project over-budgeting.    To ensure the projects do not exceed their set budget and program, the study emphasizes the relevance of teamwork, transparency and timely decisions.  Put together, these tactics a


A Distributed Collaborative Data Relay Method: VLEO Earth Observation Constellation Cross-Layer Access to the Mega-LEO Satellite Internet

Kai Han
Marie Siew
Bingbing Xu
Shengjun Guo
Tianxiang Wang
Wenbin Gong

Abstract: With the rapid development of large-scale low-Earth orbit (LEO) satellite Internet, very LEO (VLEO) Earth observation constellations are increasingly using intersatellite links (LISLs) for cross-layer access to Internet satellites. It is an effective means to enhance data return throughput. When both observation and communication satellite constellations use lasers for networking, cross-layer access between the VLEO and LEO satellite networks requires reallocating lasers. This reallocation disrupts the original topology and impacts network performance. To maximize the collaborative operational efficiency of the double-layer network, we fundamentally analyze the relationship between topology


New Earth Observation Results from the NASA TROPICS CubeSat Constellation Mission

2024 4th URSI Atlantic Radio Science Meeting (AT-RASC)

Abstract: New high-resolution observing systems for earth observation are being enabled by rapidly developing CubeSat and SmallSat constellation capabilities that are transforming the way data are collected and communicated in space, and the cost and schedule barriers to the development, launch, and operations of these high-performance systems have been substantially lowered in recent years. Here we present the NASA TROPICS Earth Venture (EVI-3) CubeSat constellation, which is currently providing new microwave observations of tropical cyclones at unprecedented revisit rates. Four satellites were successfully launched into orbit on May 8 and May 25, 2023 (two 3U CubeSats in each of the two launches), a


A cost-benefit analysis of WildFireSat, a wildfire monitoring satellite mission for Canada

Emily S. Hope
Daniel W. McKenney
Lynn M. Johnston
Joshua M. Johnston

Abstract: In anticipation of growing wildfire management challenges, the Canadian government is investing in WildFireSat, an Earth observation satellite mission designed to collect data in support of Canadian wildfire management. Although costs of the mission can be reasonably estimated, the benefits of such an investment are unknown. Here we forecast the possible benefits of WildFireSat via an avoided cost approach. We consider five socio-economic components: suppression costs (fixed and variable), timber losses, property, asset and infrastructure losses, evacuation costs, and smoke related health costs. Using a Monte Carlo analysis, we evaluated a range of possible changes to these components based


SAR SmallSat Constellation: System Trade off Across Multiple Inclinations

Luca Soli
Vanessa Mastroddi
Alice Nervo
Annamaria Nassisi
Carlo Ciancarelli


Design and analysis of flexible multi-layer staged deployment for satellite mega-constellations under demand uncertainty

J. F. Anderson
M.-A. Cardin
P. T. Grogan

Abstract: Brain (ACTA). Tradespace under uncertainty for distributed architectures; staged-deployment value framing.


A Comprehensive Review on Small Satellite Microgrids

Mohammad Yaqoob
Abderezak Lashab
Juan C. Vásquez
Josep M. Guerrero
Marcos E. Orchard
Angelina D. Bintoudi

Abstract: The small satellite (SmallSat) industry has recorded incredible growth recently. Within this class, among mini-, micro-, and nanosatellites, the cube satellite (CubeSat) is primed for an explosion of growth. These satellites are fascinating for remote sensing, Earth observation, and scientific applications. Remarkable attention from the space operators makes it valuable because of its low cost, cubic shape, less manufacturing time, lightweight, and modular structure. Among the various subsystems comprising the SmallSat, the electrical power system (EPS) is the most crucial one because unreliable power supply to the rest is most of the time detrimental to the mission. The EPS is formed by ele


The Value of Near Real-Time Earth Observations for Improved Flood Disaster Response

Abstract: Information is a critical resource in disaster response scenarios. Data regarding the geographic extent, severity, and socioeconomic impacts of a disaster event can help guide emergency responders and relief operations, particularly when delivered within hours of data acquisition. Information from remote observations provides a valuable tool for assessing conditions "on the ground" more quickly and efficiently. Here, we evaluate the social value of a near real-time flood impact system using a disaster response case study, and quantify the Value of Information (VOI) of satellite-based observations for rapid response using a hypothetical flooding disaster in Bangkok, Thailand. MODIS imagery fr


Value of Information (VOI) Concept to Systematically Justify Observation and Appraisal Wells

I. Budi
E. Kusumah
A. Pramana
Jati Arie Wibowo
Agus Rudiyono

2019 AAPG Asia Pacific Region Technical Symposium The Art of Hydrocarbon Prediction: Managing Uncertainties

Abstract: The Oil and gas industry is a world full of uncertainties which covers a wide spectrum, starting from reservoir parameters (static or dynamic) as well as optimal development options and operating conditions. Business decisions, whether to execute the project, determining the size of the development, etc.) often cannot be done amidst uncertainties, so activity to reduce uncertainty is necessary to ensure the success of a project. It was thought previously that exponentially growing computing power and data storage capacity we have in this era would easily tackle the job, but this just adds complexities to the existing problem. We tend to incorporate more data and variables with uncertainties


Space Sustainability: Reframing the Debate

Abstract: Brain (Simon HoS). Socio-technical reframing of space-system value beyond single-attribute optimization; context for portfolio-level value framing.


Dealing with Uncertainty: Expected Values, Sensitivity Analysis, and the Value of Information


Machine-Learning Space Applications on SmallSat Platforms with TensorFlow

Jacob Manning
David Langerman
B. Ramesh
Evan W. Gretok
Christopher D. Wilson
Alan D. George

Digital Commons - USU (Utah State University)

Abstract: Due to their attractive benefits, which include affordability, comparatively low development costs, shorter development cycles, and availability of launch opportunities, SmallSats have secured a growing commercial and educational interest for space development. However, despite these advantages, SmallSats, and especially CubeSats, suffer from high failure rates and (with few exceptions to date) have had low impact in providing entirely novel, market-redefining capabilities. To enable these more complex science and defense opportunities in the future, small-spacecraft computing capabilities must be flexible, robust, and intelligent. To provide more intelligent computing, we propose employing


Towards disruptions in Earth observation? New Earth Observation systems and markets evolution

Abstract: Brain (ACTA). Evolution of EO systems toward distributed architectures and commercial data buys; supports the timing/portfolio motivation.


Agricultural Case Studies for Measuring the Value of Information of Earth Observation and Other Geospatial Information for Decisions


Multi-Attribute Tradespace Exploration for Survivability

Adam M. Ross
David Stein
Daniel E. Hastings

Abstract: Multi-attribute tradespace exploration for survivability is a system design and analysis methodology that incorporates survivability considerations into the tradespace exploration process (i.e., a solution-generating and decision-making framework that applies decision theory to model-based design). During the concept-generation phase of tradespace exploration, the methodology applies 17 empirically validated survivability design principles spanning susceptibility reduction, vulnerability reduction, and resilience enhancement. During subsequent concept evaluation, the methodology adds value-based survivability metrics to traditional architectural evaluation criteria of mission utility and lif


Time Value of Money and Cost-Benefit Analysis

Budgeting and Financial Management for Nonprofit Organizations: Using Money to Drive Mission Success


Assessment and change analyses (1987–2002) for tropical wetland ecosystem using earth observation and socioeconomic data

N. Nagabhatla
C. Finlayson
S. S. Sellamuttu

Abstract: Abstract The two components of the study reflect assessment and change analysis of a tropical wetland in Sri Lanka. The first section explains spatial classification using pixel level-disaggregated image analysis and refined aggregated image analysis and comparison of information extracted by all methods to analyse a better classifier. The second section illustrates change analysis calibrating the land change modeller (LCM) [IDRISI-Andes]. Key observations: a) visual interpretation provides comprehensive blueprint of the wetlandscape compared to supervised and unsupervised classifiers b) change in landscape pattern reflect substantial transition in wetland use. Validation using field coordin