Journal
REMOTE SENSING OF ENVIRONMENT
Volume 204, Issue -, Pages 1-17Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2017.11.001
Keywords
Flood mapping; Land cover classification; Wetlands; MODIS; Hydrologic modeling; Non-parametric classification; East Africa
Funding
- National Science Foundation [DGE-1650044]
Ask authors/readers for more resources
Hydrologic models of wetlands enable water resources managers to quantify the environmental and societal roles of wetlands and manage them in ways that sustain their valuable services. However, reliable wetland models require data that are not typically available from in-situ measurements. In this article, we use satellite information from MODIS (500-meter, 8-day composite land surface reflectance product) and limited ground data to quantify the seasonal and inter-annual changes of wetland extent. This information is used to calibrate a new, non-parametric land cover classification approach. Extensive tests demonstrate that the new approach performs well in (i) classifying accurately land cover classes and (ii) delineating reliably seasonal and inter-annual wetland area changes. The new approach is applied to the Sudd wetland in South Sudan, a vast wetland of vital socioeconomic and environmental services, toward developing better, policy-relevant information and tools.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available