ISBN: 9783659404658 - lu/lc map and digital elevation model of jharia town using rs-gis: preparation & analysis of landuse/landcover map and digital elevation model of jharia town in jharia coal field region (6 risultati)

Taschenbuch. Condizione: Neu. LU/LC Map and Digital Elevation Model of Jharia Town using RS-GIS | Preparation & analysis of landuse/landcover map and digital elevation model of Jharia town in Jharia coal field region | Sachin Sharma (u. a.) | Taschenbuch | 92 S. | Englisch | 2013 | LAP LAMBERT Academic Publishing | EAN 9783659404658 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.…

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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The purpose of this book is to explore the utility of remotely sensed data acquired for land-use /land-cover (LULC) classifications. The Resourcesat-1 Data is a high resolution (i.e. 5.8-meter), multispectral (3 bands: red, green and near infrared) dataset. Resourcesat-1 imagery has been selected for this study because of its low cost and potential for small scale land use and land cover classifications similar to the success the Landsat (30 meter, multispectral: 7 band) imagery has achieved with large scale classifications. The study has been done using a subdivision in Jharia Coal Field region i.e. Jharia town and the surrounding (rural) property. Supervised (parametric and nonparametric) classification procedures were conducted for the Jharia town area using ERDAS Imagine 9.2. Random sample points were generated for accuracy assessment via a ground based visual assessment of each point's LULC class. By using a 6 class LULC scheme, a supervised classification of the Resourcesat-1 imagery resulted in classification accuracy of 83.07%. 92 pp. Englisch. …

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Sharma SachinSachin Sharma (Professional Environmentalist)did Environmental Science & Engineering in 2010 from ISM, Dhanbad, India. Completed Master of Science in 2007. Author of two more international books on the same study area. C. …

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The purpose of this book is to explore the utility of remotely sensed data acquired for land-use /land-cover (LULC) classifications. The Resourcesat-1 Data is a high resolution (i.e. 5.8-meter), multispectral (3 bands: red, green and near infrared) dataset. Resourcesat-1 imagery has been selected for this study because of its low cost and potential for small scale land use and land cover classifications similar to the success the Landsat (30 meter, multispectral: 7 band) imagery has achieved with large scale classifications. The study has been done using a subdivision in Jharia Coal Field region i.e. Jharia town and the surrounding (rural) property. Supervised (parametric and nonparametric) classification procedures were conducted for the Jharia town area using ERDAS Imagine 9.2. Random sample points were generated for accuracy assessment via a ground based visual assessment of each point's LULC class. By using a 6 class LULC scheme, a supervised classification of the Resourcesat-1 imagery resulted in classification accuracy of 83.07%. …

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The purpose of this book is to explore the utility of remotely sensed data acquired for land-use /land-cover (LULC) classifications. The Resourcesat-1 Data is a high resolution (i.e. 5.8-meter), multispectral (3 bands: red, green and near infrared) dataset. Resourcesat-1 imagery has been selected for this study because of its low cost and potential for small scale land use and land cover classifications similar to the success the Landsat (30 meter, multispectral: 7 band) imagery has achieved with large scale classifications. The study has been done using a subdivision in Jharia Coal Field region i.e. Jharia town and the surrounding (rural) property. Supervised (parametric and nonparametric) classification procedures were conducted for the Jharia town area using ERDAS Imagine 9.2. Random sample points were generated for accuracy assessment via a ground based visual assessment of each point's LULC class. By using a 6 class LULC scheme, a supervised classification of the Resourcesat-1 imagery resulted in classification accuracy of 83.07%.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 92 pp. Englisch. …