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- Title
Mapping and Attributing Normalized Difference Vegetation Index Trends for Nepal.
- Authors
Krakauer, Nir Y.; Lakhankar, Tarendra; Anadón, José D.
- Abstract
Global change affects vegetation cover and processes through multiple pathways. Long time series of surface land surface properties derived from satellite remote sensing give unique abilities to observe these changes, particularly in areas with complex topography and limited research infrastructure. Here, we focus on Nepal, a biodiversity hotspot where vegetation productivity is limited by moisture availability (dominated by a summer monsoon) at lower elevations and by temperature at high elevations. We analyze the normalized difference vegetation index (NDVI) from 1981 to 2015 semimonthly, at an 8 km spatial resolution. We use a random forest (RF) of regression trees to generate a statistical model of the NDVI as a function of elevation, land use, CO2 level, temperature, and precipitation. We find that the NDVI increased over the studied period, particularly at low and middle elevations and during the fall (post-monsoon). We infer from the fitted RF model that the NDVI linear trend is primarily due to CO2 level (or another environmental parameter that is changing quasi-linearly), and not primarily due to temperature or precipitation trends. On the other hand, interannual fluctuation in the NDVI is more correlated with temperature and precipitation. The RF accurately fits the available data and shows promise for estimating trends and testing hypotheses about their causes.
- Subjects
NEPAL; GLOBAL environmental change; REMOTE sensing; LAND surface temperature; FLUCTUATIONS (Physics); PRECIPITATION (Chemistry); LAND use; RADIO frequency
- Publication
Remote Sensing, 2017, Vol 9, Issue 10, p986
- ISSN
2072-4292
- Publication type
Article
- DOI
10.3390/rs9100986