@article{TATEM200442,

title = {Defining approaches to settlement mapping for public health management in Kenya using medium spatial resolution satellite imagery},

author = {Andrew J. Tatem and Abdisalan M. Noor and Simon I. Hay},

url = {https://www.sciencedirect.com/science/article/pii/S0034425704001944},

doi = {https://doi.org/10.1016/j.rse.2004.06.014},

issn = {0034-4257},

year  = {2004},

date = {2004-01-01},

journal = {Remote Sensing of Environment},

volume = {93},

number = {1},

pages = {42-52},

abstract = {This paper presents an appraisal of satellite imagery types and texture measures for identifying and delineating settlements in four Districts of Kenya chosen to represent the variation in human ecology across the country. Landsat Thematic Mapper (TM) and Japanese Earth Resources Satellite-1 (JERS-1) synthetic aperture radar (SAR) imagery of the four districts were obtained and supervised per-pixel classifications of image combinations tested for their efficacy at settlement delineation. Additional data layers including human population census data, land cover, and locations of medical facilities, villages, schools and market centres were used for training site identification and validation. For each district, the most accurate approach was determined through the best correspondence with known settlement and non-settlement pixels. The resulting settlement maps will be used in combination with census data to produce medium spatial resolution population maps for improved public health planning in Kenya.},

keywords = {JERS-1 SAR, Kenya, Landsat TM, Neural network, Population, Public health, Settlement mapping, Texture},

pubstate = {published},

tppubtype = {article}

}