Automatic Detection of Open and Vegetated Water Bodies Using Sentinel 1 to Map African Malaria Vector Mosquito Breeding Habitats

Remote Sensing

Andy Hardy¹  Georgina Ettritch¹  Pete Bunting¹  ChrisJ. Thomas²  DónallE. Cross²  Douglas Singini³  Andrew Silumesii⁴  Jacob Sakala⁵  Francis Liywalii⁵  Tom Willis⁶  Mark Smith⁶ 

[1] Department of Geography and Earth Sciences, Aberystwyth University, Aberystwyth SY23 3DB, UK;Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth SY23 3DA, UK;Limulunga District Health Office, P.O. Box 910022, Limulunga, Zambia;Ministry of Health, P.O. Box 30205, Lusaka, Zambia;Provincial Health Office, Western Province, P.O. Box 910022, Mongu, Zambia;School of Geography, University of Leeds, Leeds LS2 9JT, UK;

关键词: flood mapping;    water body detection;    malaria;    wetland;    Sentinel-1;    open-source;    sub-Saharan Africa;    hydrology;   

DOI  :  10.3390/rs11050593

来源: DOAJ

【 摘 要 】

Providing timely and accurate maps of surface water is valuable for mapping malaria risk and targeting disease control interventions. Radar satellite remote sensing has the potential to provide this information but current approaches are not suitable for mapping African malarial mosquito aquatic habitats that tend to be highly dynamic, often with emergent vegetation. We present a novel approach for mapping both open and vegetated water bodies using serial Sentinel-1 imagery for Western Zambia. This region is dominated by the seasonally inundated Upper Zambezi floodplain that suffers from a number of public health challenges. The approach uses open source segmentation and machine learning (extra trees classifier), applied to training data that are automatically derived using freely available ancillary data. Refinement is implemented through a consensus approach and Otsu thresholding to eliminate false positives due to dry flat sandy areas. The results indicate a high degree of accuracy (mean overall accuracy 92% st dev 3.6) providing a tractable solution for operationally mapping water bodies in similar large river floodplain unforested environments. For the period studied, 70% of the total water extent mapped was attributed to vegetated water, highlighting the importance of mapping both open and vegetated water bodies for surface water mapping.

【 授权许可】

Unknown