Modeling Deforestation and Land Use Change: Sparse Data Environments

Land use change in developing countries is of great interest to policymakers and researchers from many backgrounds. Concerns about consequences of deforestation for global climate change and biodiversity have received the most publicity, but loss of wetlands, declining land productivity, and watershed management are also problems facing developing countries. In developing countries, analysis is especially constrained by lack of data. This paper reviews modeling approaches for data-constrained environments that involve methods such as neural nets and dynamic programming and research results that link individual household survey data with satellite images using geographic positioning systems.

Issue Date:
Publication Type:
Conference Paper/ Presentation
Record Identifier:
PURL Identifier:
Total Pages:
JEL Codes:
Q15; Q23; R14
Series Statement:
Invited Paper

 Record created 2017-04-01, last modified 2018-01-22

Download fulltext

Rate this document:

Rate this document:
(Not yet reviewed)