Mapping global tropical wetlands from earth observing satellite imagery

Mapping global tropical wetlands from earth observing satellite imagery

The extent, volume and carbon content of the world’s tropical wetlands are not accurately known. Present estimates are based on disparate sources, of varying quality from different regions. As wetlands are key regulators not only of the global carbon cycle, but also other biogeochemical cycles, better maps of wetlands are urgently needed. This report presents a set of novel approaches for mapping global tropical wetlands from a variety of image data obtained from satellite images of earth. Wetlands only occur under certain topographic positions, and where the climate system provides sufficient water. Combining a global digital elevation model with global climate data, a tropical global map of topographic wetness was created. Using global optical satellite images from a moderate resolution imaging spectroradiometer (MODIS) a second wetness index was developed. In contrast to previous satellite-based wetness indexes, the index attempts to remove the vegetation influence and focus on the soil surface wetness. From an annual time-series of MODIS images, the inundation cycle of the global tropics was captured. As wetlands are characterised by annual variations in inundation, an approach for classifying wetlands from a chrono-sequence of annual MODIS images was developed. In the chrono-sequence, only locations with similar climatic seasonality, and within spatial proximity are classified based on any reference site. The wetness indexes and the chrono-sequence classification scheme are strong candidates for mapping the distribution of global tropical wetlands.

Authors: Gumbricht, T.

Topic: mangroves,wetlands,climatic change

Series: CIFOR Working Paper no. 103

Pages: 47p

Publisher: Center for International Forestry Research (CIFOR), Bogor, Indonesia

Publication Year: 2012


Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.

Download

Export Citation

Related viewing

Top