Using Remote Sensing Technologies to Monitor Aid's Impact
Remote sensing can help social and environmental scientists better understand aid's role as a possible driver of land use and land cover change
Global climate change, deforestation, the growth of ethanol-based agricultural systems, and aquaculture expansion are all issues that are closely related to land use and land cover (LULC) change. LULC scientists study all aspects of land use and land cover change, including its determinants, its short-term and long-term consequences, and the process of change itself. Increasingly, LULC scientists also recognize that social science data can help shed light on many of these research questions. For example, the International Council for Science (ICSU) has established the Belmont Challenge, which seeks to integrate social science and LULC research in order to improve human adaptation to regional environmental change.
How can AidData contribute to future LULC research? It can help social and environmental scientists better understand aid's role as a possible driver of LULC change, and it can also help researchers assess the effects of assistance geared towards environmental protection and remediation.
It is widely accepted that developing countries demonstrate the highest level, rate, and intensity of land cover change. Many of these countries are of course also large aid recipients, with some countries relying on aid for as much as half of their total gross domestic income (GNI). Correlation should never be confused with causation, but the fact that a substantial amount of aid supports the agriculture, forestry, and fishery sectors (see Graph 1) raises several important questions: Does aid have a discernible effect on LULC change? If so, which types of aid have the greatest impact? Is there any evidence that environmental assistance has reduced deforestation? If so, which types of environmental aid are most effective?
Graph 1: Total aid commitments to the agriculture, forestry, and fishing sectors from 1975 to 2007. Source: AidData
At the moment, there is little research on the relationship between LULC change and aid flows. One exception is an article I recently published in the Journal of Land Use Science. In the article, I provide some tentative evidence of a relationship between international aid, shrimp farm expansion, and mangrove deforestation in coastal Ecuador. (See Figure 1 for an illustration of the conversion of an Ecuadorian mangrove estuary since the arrival of shrimp aquaculture.) Making a strong causal argument will ultimately depend upon the existence of foreign assistance data that is sub-nationally geo-referenced over a significant period of time.
Figure 1: The conversion of a mangrove estuary since the arrival of shrimp aquaculture. Chone Estuary, Ecuador. 1968 to 1991.
With time-varying, geo-coded information from AidData and LULC data, I believe that social and environmental scientists can tackle some of these previously unanswerable questions. The landsat program is widely agreed to be the first Earth Observing System (EOS) that allows for robust LULC analysis. AidData, with its similar temporal scale as landsat and considerable collection of sub-national data, makes aid information increasingly compatible with EOS. I expect that the integration of AidData and EOS will feature prominently in aid research over the next decade.
Stuart Hamilton is the Director of the Center for Geospatial Analysis at the College of William & Mary.