Satellite Data in Agricultural and Environmental Economics: Theory and Practice

ABSTRACT Agricultural and environmental economists are in the fortunate position that a lot of what is happening on the ground is observable from space. Most agricultural production happens in the open and one can see from space when and where innovations are adopted, crop yields change, or forests are converted to pastures, to name just a few examples. However, converting remotely sensed images into measurements of a particular variable is not trivial, as there are more pitfalls and nuances than “meet the eye”. Overall, however, research benefits tremendously from advances in available satellite data as well as complementary tools, such as cloud‐based platforms, machine learning algorithms, and econometric approaches. Our goal here is to provide agricultural and environmental economists with an accessible introduction to working with satellite data, show‐case applications, discuss pitfalls and available solutions, and emphasize the best practices. This is supported by extensive supporting information, where we describe how to create different variables, common workflows, and a discussion of required resources and skills. Last but not least, example data and reproducible codes are made available online.

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Institutions

Publication Details

Journal
Agricultural Economics
Published
2025-03-16
DOI
https://doi.org/10.1111/agec.70006
Citations
10
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
17.16

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article

Satellite Data in Agricultural and Environmental Economics: Theory and Practice

David Wuepper, Hadi Hadi, Wyclife Agumba Oluoch
10 citations
Agricultural Economics
Remote Sensing in Agriculture
17.16
article

Satellite Data in Agricultural and Environmental Economics: Theory and Practice

David Wuepper, Hadi Hadi, Wyclife Agumba Oluoch
article en
10 citations

Abstract

ABSTRACT Agricultural and environmental economists are in the fortunate position that a lot of what is happening on the ground is observable from space. Most agricultural production happens in the open and one can see from space when and where innovations are adopted, crop yields change, or forests are converted to pastures, to name just a few examples. However, converting remotely sensed images into measurements of a particular variable is not trivial, as there are more pitfalls and nuances than “meet the eye”. Overall, however, research benefits tremendously from advances in available satellite data as well as complementary tools, such as cloud‐based platforms, machine learning algorithms, and econometric approaches. Our goal here is to provide agricultural and environmental economists with an accessible introduction to working with satellite data, show‐case applications, discuss pitfalls and available solutions, and emphasize the best practices. This is supported by extensive supporting information, where we describe how to create different variables, common workflows, and a discussion of required resources and skills. Last but not least, example data and reproducible codes are made available online.

Agricultural EconomicsVol. 56(3)
University of Bonn (DE)
Deutsche Forschungsgemeinschaft
Openalex Percentile: Top 1%
Remote Sensing in Agriculture
17.16
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