Methods and Approaches of irrigated area mapping using Remote Sensing: Methods and Approaches of irrigated area mapping at various spatial resolutions using AVHRR, MODIS, and LANDSAT ETM+ data - Couverture souple

Gumma, Murali Krishna; S.Thenkabail, Prasad

 
9783844310993: Methods and Approaches of irrigated area mapping using Remote Sensing: Methods and Approaches of irrigated area mapping at various spatial resolutions using AVHRR, MODIS, and LANDSAT ETM+ data
Couverture souple
ISBN 10 : 3844310991 ISBN 13 : 9783844310993
Editeur : LAP LAMBERT Academic Publishing, 2011

Synopsis

Methods and approaches of mapping irrigated areas at different resolutions using remote sensing data. Irrigated areas were mapped using: (a) AVHRR pathfinder 10-km data, (b) MODIS 500-m (c) MODIS 250-m and (d) Landsat 30-m data. The study was conducted in the Krishna River, India using satellite sensor data for nominal year 2000. The methods analyzing multiple sensors data, time-series and consisted of image segmentation approaches using SRTM data, creation of mega-file data cube, spectral matching techniques, ideal spectra data bank creation, class spectral generation, 2 dimensional brightness-greenness wetness (BGW) plot, space time-spiral curves, comprehensive protocols for class identification and labeling, resolving the mixed classes, calculation of sub-pixel areas (SPAs), and fuzzy classification accuracy assessments. The class identification protocols involved matching class spectra with ideal spectra to group classes, use of extensive ground truth data, innovative use of very high resolution Google Earth Data, and secondary data. The results clearly showed that finer the resolution greater was the irrigated areas.

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Présentation de l'éditeur

Methods and approaches of mapping irrigated areas at different resolutions using remote sensing data. Irrigated areas were mapped using: (a) AVHRR pathfinder 10-km data, (b) MODIS 500-m (c) MODIS 250-m and (d) Landsat 30-m data. The study was conducted in the Krishna River, India using satellite sensor data for nominal year 2000. The methods analyzing multiple sensors data, time-series and consisted of image segmentation approaches using SRTM data, creation of mega-file data cube, spectral matching techniques, ideal spectra data bank creation, class spectral generation, 2 dimensional brightness-greenness wetness (BGW) plot, space time-spiral curves, comprehensive protocols for class identification and labeling, resolving the mixed classes, calculation of sub-pixel areas (SPAs), and fuzzy classification accuracy assessments. The class identification protocols involved matching class spectra with ideal spectra to group classes, use of extensive ground truth data, innovative use of very high resolution Google Earth Data, and secondary data. The results clearly showed that finer the resolution greater was the irrigated areas.

Biographie de l'auteur

Murali has 12 yrs experience on internationally and author of 32 scientific papers and book chapters. His current research interests include Global rice mapping; global land remote sensing; Identify the best sites in inland valleys for agriculture, land use and land cover change and characterization of abiotic/biotic stresses in major crop areas.

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Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2011
Langue
anglais
ISBN 10 
3844310991
ISBN 13 
9783844310993
Reliure
Broché
Nombre de pages
156
Coordonnées du fabricant
non disponible
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