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Deforestation and land use change: sparse data environments
Author(s) -
Nelson Gerald C.,
Geoghegan Jacqueline
Publication year - 2002
Publication title -
agricultural economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.29
H-Index - 82
eISSN - 1574-0862
pISSN - 0169-5150
DOI - 10.1111/j.1574-0862.2002.tb00117.x
Subject(s) - deforestation (computer science) , land use , econometric model , key (lock) , land use, land use change and forestry , computer science , data science , range (aeronautics) , estimation , economics , machine learning , civil engineering , materials science , computer security , management , engineering , composite material , programming language
Understanding determinants of land use in developing countries has become a priority for researchers and policy makers with a wide range of interests. For the vast majority of these land use issues, the location of change is as important as its magnitude. This overview paper highlights new economic approaches to modeling land use determinants that combine non‐traditional data sources with novel economic models and econometric techniques. A key feature is that location is central to the analysis. All data elements include an explicit location attribute, estimation techniques include the potential for complications from spatial effects, and results are location‐specific. The paper reviews the theory underlying these models. Since this paper is intended to provide the potential new researcher with an introduction to the challenges of this analysis, we present an overview of how remotely‐sensed data are collected and processed, describe key GIS concepts and identify sources of data for this type of econometric analysis. Finally, selected papers using these techniques are reviewed.