@ARTICLE{Sierra-Soler_Andres_High_2015,
 author={Sierra-Soler, Andres and Adamowski, Jan and Qi, Zhiming and Saadat, Hossein and Pingale, Santosh},
 number={No 26},
 pages={19-35},
 journal={Journal of Water and Land Development},
 howpublished={online},
 year={2015},
 publisher={Polish Academy of Sciences; Institute of Technology and Life Sciences - National Research Institute},
 abstract={Satellite remote sensing provides a synoptic view of the land and a spatial context for measuring drought impacts, which have proved to be a valuable source of spatially continuous data with improved information for monitoring vegetation dynamics. Many studies have focused on detecting drought effects over large areas, given the wide availability of low-resolution images. In this study, however, the objective was to focus on a smaller area (1085 km2) using Landsat ETM+ images (multispectral resolution of 30 m and 15 m panchromatic), and to process very accurate Land Use Land Cover (LULC) classification to determine with great precision the effects of drought in specific classes. The study area was the Tortugas-Tepezata sub watershed (Moctezuma River), located in the state of Hidalgo in central Mexico. The LULC classification was processed using a new method based on available ancillary information plus analysis of three single date satellite images. The newly developed LULC methodology developed produced overall accuracies ranging from 87.88% to 92.42%. Spectral indices for vegetation and soil/vegetation moisture were used to detect anomalies in vegetation development caused by drought; furthermore, the area of water bodies was measured and compared to detect changes in water availability for irrigated crops. The proposed methodology has the potential to be used as a tool to identify, in detail, the effects of drought in rainfed agricultural lands in developing regions, and it can also be used as a mechanism to prevent and provide relief in the event of droughts.},
 type={Article},
 title={High accuracy Land Use Land Cover (LULC) maps for detecting agricultural drought effects in rainfed agro-ecosystems in central Mexico},
 URL={http://ochroma.man.poznan.pl/Content/116652/PDF/High%20accuracy%20Land%20Use%20Land%20Cover%20(LULC)%20maps%20for%20detecting%20agricultural%20drought%20effects%20in%20rainfed%20agro-ecosystems%20in%20central%20Mexico.pdf},
 keywords={drought, LULC maps, remote sensing, spectral indices},
}