Although there is a substantive literature concerned with the geopolitics of space and the ethical issues raised by the use of remote sensing in warfare and counterinsurgency, little study has been made of the critical role played by satellites in public health crises. Satellite technologies are increasingly being deployed to manage infectious disease outbreaks. A WebGIS platform was designed for the visualization of the produced water maps along with other data related to mosquito-larvae presence. The presence of vegetation, built-up areas, floating algae in rice-paddies, salt-crust formations in wetlands, and water depth, were found to affect the performance of the algorithm. Results using this method were further assessed during the main larvicide application period. The accuracy is higher at the beginning of the summer (0.948) than at the end of the rice-growing season due to higher density of vegetation.

The Otsu valley-emphasis technique provides the highest overall accuracy (0.835). The results were assessed using field data collected during the mosquito breeding periods of 20 in the region of Central Macedonia (Greece). Four methods were adapted and developed for automated application: the Otsu valley-emphasis algorithm, a classification method based on the textural feature of entropy, a method using K-means unsupervised classification, and a method using the Haralick’s textural feature of dissimilarity and fuzzy-rules classification. This study aims to select a method for the automatic and regular mapping of surface-water bodies in rice fields and wetlands using Sentinel-1 synthetic aperture radar data. Download Microsoft Encarta Premium.Surface-water body maps are imperative for effective mosquito larvae control.

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