@article{Tatem2004,

title = {Measuring urbanization pattern and extent for malaria research: A review of remote sensing approaches},

author = {A. J. Tatem and S. I. Hay},

url = {https://doi.org/10.1093/jurban/jth124},

doi = {10.1093/jurban/jth124},

issn = {1468-2869},

year  = {2004},

date = {2004-09-01},

journal = {Journal of Urban Health},

volume = {81},

number = {3},

pages = {363-376},

abstract = {Within the next 30 years, the proportion of urban dwellers will rise from under half to two thirds of the world's population. Such a shift will entail massive public health consequences, and most of this urban transition will occur in low-income regions of the world. Urban populations face very different health risks compared to those in rural areas, particularly in terms of malaria. To target effective and relevant public health interventions, the need for clear, consistent definitions of what determines urban areas and urban communities is paramount. Decision makers are increasingly seeing remote sensing as a cost-effective solution to monitoring urbanization at a range of spatial scales. This review focuses on the progress made within the field of remote sensing on mapping, monitoring, and modeling urban environments and examines existing challenges, drawbacks, and future prospects. We conclude by exploring' some of the particular relevance of these issues to malaria and note that they are of more general relevance to all those interested in urban public health.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@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}

}