ASSESSMENT OF CROP AREA AND PRODUCTION OF MAJOR CROPS OF SEDAM TALUK OF GULBARGA USING REMOTE SENSING AND GIS
| dc.contributor.advisor | Munirajappa, R | |
| dc.contributor.author | SHALINI, M N | |
| dc.date.accessioned | 2017-08-21T04:06:22Z | |
| dc.date.available | 2017-08-21T04:06:22Z | |
| dc.date.issued | 2015-10-10 | |
| dc.description.abstract | Remote sensing is the art and science of making measurements of the earth using sensors on airplanes or satellites. These sensors collect data in the form of images and provide specialized capabilities for manipulating, analysing, and visualizing those satellite images. Remote sensed imagery is integrated within a Geographic Information System (GIS). Several methods exist for remote sensing image classification. They include supervised and unsupervised approaches. In supervised classification, the classifier is trained to identify the classes using training data set where as in an unsupervised classification, the classifier itself develops the spectral classes. For statistical comparisons of different image classification methods test imagery obtained through IRS (Indian Remote Sensing) P6 LISS-III on 22nd December, 2011 for Sedum Taluk of Gulbarga district of Karnataka state were used. Maximum likelihood classification, Mahalanobis distance classification, Minimum distance to means classification under supervised classification approach were performed for the test imagery using ERDAS imagine 9.1 version software. Accuracy assessment was found important to evaluate the final output of remote sensing. Accuracy of the classification of each data set and their classifiers were expressed as an error matrix from which overall accuracy, users accuracy, producers accuracy, mapping accuracy, F-measures, Kappa coefficients and sample variance of Kappa coefficients were estimated. The test of significance of Kappa coefficients were performed using Z-test. Pairwise comparison of Kappa coefficients of different classification methods were performed. Maximum likelihood classification was found to be the best with highest overall accuracy of 93.38 per cent for Sedum Taluk, Gulbarga district of Karnataka. | en_US |
| dc.identifier.other | Th-11256 | |
| dc.identifier.uri | http://krishikosh.egranth.ac.in/handle/1/5810029159 | |
| dc.language.iso | en | en_US |
| dc.pages | 85 | en_US |
| dc.publisher | UNIVERSITY OF AGRICULTURAL SCIENCES GKVK, BENGALURU | en_US |
| dc.sub | Agricultural Statistics and Informatics | en_US |
| dc.subject | null | en_US |
| dc.theme | ASSESSMENT OF CROP AREA AND PRODUCTION OF MAJOR CROPS OF SEDAM TALUK OF GULBARGA USING REMOTE | en_US |
| dc.these.type | M.Sc | en_US |
| dc.title | ASSESSMENT OF CROP AREA AND PRODUCTION OF MAJOR CROPS OF SEDAM TALUK OF GULBARGA USING REMOTE SENSING AND GIS | en_US |
| dc.type | Thesis | en_US |