• P-ISSN 0974-6846 E-ISSN 0974-5645

Indian Journal of Science and Technology


Indian Journal of Science and Technology

Year: 2019, Volume: 12, Issue: 46, Pages: 1-9

Original Article

A Time Series Analysis of Satellite Imageries for Land Use & Land Cover (LULC) Change Detection of Gujranwala City, Pakistan from 1999–2019


Objectives: Information on land use and land cover changes are very valuable for the viable expansion of the city. LULC are interrelated attributes in which LC means which type of land is covered with cropland, farmland and grassland and LU means which type of land is used for residential, commercial, Agriculture or Marshland. Methods: This study is an effort to monitor land use/ land cover change by using remote sensing and GIS from 1999 to 2019. The use of remote sensing data has proved to be very helpful in LULC change detection. Accuracy assessment is a vital part of image classification and accuracy assessment is an important technique that defines the quality of the information obtained from the remotely sensed data and is considered an important tool for classification image. Maximum Likelihood supervised classification which was used to create a signature class for land cover. Findings: During the last 20 years our results indicate water, agriculture and mix vegetation decrease 0.1%, 7.2% and 4.1% but there is more increase in the other two classes barren land increase 2.9% and built-up increase 7.4%. Mostly agriculture land has been converted into barren and urban land. For the accuracy assessment, overall accuracy assessment was performed. Accuracy assessment was calculated through the Kappa co-efficient index. Applications: For calculating accuracy, we use accuracy statistics, overall accuracy. Temporal changes are time to time changes, in this perspective the change/increase in built-up land is 174.71 sq km. The results of this study would be helpful for decision making, urban development and future planning. 
Keywords: Land Use, Land Cover, Change Detection, Accuracy Assessment, Temporal


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