High accuracy Land Use Land Cover (LULC) maps for detecting agricultural drought effects in rainfed agro-ecosystems in central Mexico

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 effec...

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Main Authors: Sierra-Soler Andres, Adamowski Jan, Qi Zhiming, Saadat Hossein, Pingale Santosh
Format: Article
Language:English
Published: Sciendo 2015-09-01
Series:Journal of Water and Land Development
Subjects:
Online Access:http://www.degruyter.com/view/j/jwld.2015.26.issue-1/jwld-2015-0014/jwld-2015-0014.xml?format=INT
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spelling doaj-fa93b6abad234e189387c26399114f052020-11-25T00:54:46ZengSciendoJournal of Water and Land Development2083-45352015-09-01261193510.1515/jwld-2015-0014jwld-2015-0014High accuracy Land Use Land Cover (LULC) maps for detecting agricultural drought effects in rainfed agro-ecosystems in central MexicoSierra-Soler AndresAdamowski JanQi ZhimingSaadat HosseinPingale SantoshSatellite 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.http://www.degruyter.com/view/j/jwld.2015.26.issue-1/jwld-2015-0014/jwld-2015-0014.xml?format=INTdroughtLULC mapsremote sensingspectral indicesmapy LULCsuszateledetekcjawskaźniki spektralne
collection DOAJ
language English
format Article
sources DOAJ
author Sierra-Soler Andres
Adamowski Jan
Qi Zhiming
Saadat Hossein
Pingale Santosh
spellingShingle Sierra-Soler Andres
Adamowski Jan
Qi Zhiming
Saadat Hossein
Pingale Santosh
High accuracy Land Use Land Cover (LULC) maps for detecting agricultural drought effects in rainfed agro-ecosystems in central Mexico
Journal of Water and Land Development
drought
LULC maps
remote sensing
spectral indices
mapy LULC
susza
teledetekcja
wskaźniki spektralne
author_facet Sierra-Soler Andres
Adamowski Jan
Qi Zhiming
Saadat Hossein
Pingale Santosh
author_sort Sierra-Soler Andres
title High accuracy Land Use Land Cover (LULC) maps for detecting agricultural drought effects in rainfed agro-ecosystems in central Mexico
title_short High accuracy Land Use Land Cover (LULC) maps for detecting agricultural drought effects in rainfed agro-ecosystems in central Mexico
title_full High accuracy Land Use Land Cover (LULC) maps for detecting agricultural drought effects in rainfed agro-ecosystems in central Mexico
title_fullStr High accuracy Land Use Land Cover (LULC) maps for detecting agricultural drought effects in rainfed agro-ecosystems in central Mexico
title_full_unstemmed High accuracy Land Use Land Cover (LULC) maps for detecting agricultural drought effects in rainfed agro-ecosystems in central Mexico
title_sort high accuracy land use land cover (lulc) maps for detecting agricultural drought effects in rainfed agro-ecosystems in central mexico
publisher Sciendo
series Journal of Water and Land Development
issn 2083-4535
publishDate 2015-09-01
description 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.
topic drought
LULC maps
remote sensing
spectral indices
mapy LULC
susza
teledetekcja
wskaźniki spektralne
url http://www.degruyter.com/view/j/jwld.2015.26.issue-1/jwld-2015-0014/jwld-2015-0014.xml?format=INT
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