Change Analysis of Watersheds using Remote Sensing GIS applications: A Comparative Case Study of Rawal and Simly Watershed, Pakistan (Paperback)
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Von Händler/Antiquariat, AHA-BUCH GmbH [51283250], Einbeck, Germany.
This item is printed on demand - Print on Demand Titel. Neuware - Evaluation of watersheds and development of a management strategy requires accurate measurement of the past and present land cover/land use parameters as changes observed in these parameters determine the hydrological and ecological processes taking place in a watershed. Present study was thus focused on presenting a comparative case study for detecting the change analysis of two watersheds in Islamabad, namely Rawal and Simly Watershed using satellite data obtained from Landsat 5 and SPOT 5 for the years 1992 and 2012 respectively. Land cover and land use change was detected by applying Supervised classification-maximum likelihood algorithm in ERDAS IMAGINE and five land classes were delineated viz., Agriculture, Bare soil/Rocks, Settlements, Vegetation and Water. Furthermore, land cover/land use and overlay maps for both Watersheds were created in ArcGIS. Achieved overall classification accuracies were 95.32% and 95.13%, while Kappa statistics were 0.9237 and 0.9070 for the final land cover/use maps of 1992 and 2012 respectively. 124 pp. Englisch.

Lieferung aus: Deutschland, zzgl. Versandkosten.
Evaluation of watersheds and development of a management strategy requires accurate measurement of the past and present land cover/land use parameters as changes observed in these parameters determine the hydrological and ecological processes taking place in a watershed. Present study was thus focused on presenting a comparative case study for detecting the change analysis of two watersheds in Islamabad, namely Rawal and Simly Watershed using satellite data obtained from Landsat 5 and SPOT 5 for the years 1992 and 2012 respectively. Land cover and land use change was detected by applying Supervised classification-maximum likelihood algorithm in ERDAS IMAGINE and five land classes were delineated viz., Agriculture, Bare soil/Rocks, Settlements, Vegetation and Water. Furthermore, land cover/land use and overlay maps for both Watersheds were created in ArcGIS. Achieved overall classification accuracies were 95.32% and 95.13%, while Kappa statistics were 0.9237 and 0.9070 for the final land cover/use maps of 1992 and 2012 respectively.

Lieferung aus: Deutschland, Lieferzeit: 5 Tage.
Evaluation of watersheds and development of a management strategy requires accurate measurement of the past and present land cover/land use parameters as changes observed in these parameters determine the hydrological and ecological processes taking place in a watershed. Present study was thus focused on presenting a comparative case study for detecting the change analysis of two watersheds in Islamabad, namely Rawal and Simly Watershed using satellite data obtained from Landsat 5 and SPOT 5 for the years 1992 and 2012 respectively. Land cover and land use change was detected by applying Supervised classification-maximum likelihood algorithm in ERDAS IMAGINE and five land classes were delineated viz., Agriculture, Bare soil/Rocks, Settlements, Vegetation and Water. Furthermore, land cover/land use and overlay maps for both Watersheds were created in ArcGIS. Achieved overall classification accuracies were 95.32% and 95.13%, while Kappa statistics were 0.9237 and 0.9070 for the final land cover/use maps of 1992 and 2012 respectively.

Lieferung aus: Deutschland, Versandkostenfrei.
Change Analysis of Watersheds using Remote Sensing & GIS applications: Evaluation of watersheds and development of a management strategy requires accurate measurement of the past and present land cover/land use parameters as changes observed in these parameters determine the hydrological and ecological processes taking place in a watershed. Present study was thus focused on presenting a comparative case study for detecting the change analysis of two watersheds in Islamabad, namely Rawal and Simly Watershed using satellite data obtained from Landsat 5 and SPOT 5 for the years 1992 and 2012 respectively. Land cover and land use change was detected by applying Supervised classification-maximum likelihood algorithm in ERDAS IMAGINE and five land classes were delineated viz., Agriculture, Bare soil/Rocks, Settlements, Vegetation and Water. Furthermore, land cover/land use and overlay maps for both Watersheds were created in ArcGIS. Achieved overall classification accuracies were 95.32% and 95.13%, while Kappa statistics were 0.9237 and 0.9070 for the final land cover/use maps of 1992 and 2012 respectively. Englisch, Taschenbuch.

Von Händler/Antiquariat, The Book Depository EURO [60485773], London, United Kingdom.
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