Linda Moser

Monitoring of the Lac Bam Wetland Extent Using Dual-Polarized X-Band SAR Data

Wetlands in semi-arid Africa are vital as water resource for local inhabitants and for biodiversity, but they are prone to strong seasonal fluctuations. Lac Bam is the largest natural freshwater lake in Burkina Faso, its water is mixed with patches of floating or flooded vegetation, and very turbid and sediment-rich. These characteristics as well as the usual cloud cover during the rainy season can limit the suitability of optical remote sensing data for monitoring purposes. This study demonstrates the applicability of weather-independent dual-polarimetric Synthetic Aperture Radar (SAR) data for the analysis of spatio-temporal wetland dynamics. A TerraSAR-X repeat-pass time series of dual-co-polarized HH-VV StripMap data—with intervals of 11 days, covering two years (2013–2015) from the rainy to the dry season—was processed to normalized Kennaugh elements and classified mono-temporally and multi-temporally. Land cover time series and seasonal duration maps were generated for the following four classes: open water, flooded/floating vegetation, irrigated cultivation, and land (non-wetland). The added value of dual-polarimetric SAR data is demonstrated by significantly higher multitemporal classification accuracies, where the overall accuracy (88.5%) exceeds the classification accuracy using single-polarimetric SAR intensity data (82.2%). For relevant change classes involving flooded vegetation and irrigated fields dual-polarimetric data (accuracies: 75%–97%) are favored to single-polarimetric data (42%–87%). This study contributes to a better understanding of the dynamics of semi-arid African wetlands in terms of water areas including water with flooded vegetation, and the location and timing of irrigated cultivations.

Multitemporal Wetland Monitoring in Sub-Saharan West-Africa Using Medium Resolution Optical Satellite Data

Surface water is a critical resource in semiarid West-African regions that are frequently exposed to droughts. Natural and artificial wetlands are of high importance for different livelihoods, particularly during the dry season, from October/November until May. However, wetlands largely go unmonitored. In this work, remote sensing is used to monitor wetlands in semiarid Burkina Faso over large areal extents along a gradient of different rainfall and land use characteristics. Time series of data from the Moderate Resolution Imaging Spectrometer (MODIS) from 2000 to 2012 is used for near-infrared (NIR)-based water monitoring using a latitudinal threshold gradient approach. The occurrence of 21 new water bodies with a size larger than 0.5 km2 over the 13-year analysis period results from a postclassification change detection. Yearly cumulative spatiotemporal analysis shows lower water extents in the drought seasons of 2000-2001, 2004-2005, and 2011-2012. Multiple wetlands indicate a positive trend toward a larger yearly maximum area, but a negative trend toward shorter flooding duration. Such a negative trend is observed particularly for natural wetlands. The temporal behavior of five selected case studies demonstrates that monthly negative anomalies of watercovered areas coincide with the occurrence of drought seasons. The successful application of remote sensing time series as a tool to monitor wetlands in semiarid regions is presented, and the potential of novel early warning indicators of drought from remote sensing is demonstrated.

Monitoring of critical water and vegetation anomalies of sub-Saharan West-African Wetlands

Surface water is a critical resource in semi-arid west-African regions that are frequently exposed to droughts. The application of time series from the Moderate Resolution Imaging Spectrometer (MODIS) to derive spatio-temporal changes of water and vegetation in and around West-African wetlands is demonstrated for the years 2000-2012. A near infrared (NIR) based gradient threshold and calculation of the Normalized Difference Vegetation Index (NDVI) is applied on the time series using the MOD09Q1 surface reflectance product. Surface water dynamics and vegetation anomalies of surrounding regions were found to coincide with the occurrence of drought seasons. This study demonstrates the successful application of remote sensing time series for wetland monitoring.