Application of remote sensing and geographical information system in mapping land cover of the national park

  • سال انتشار: 1399
  • محل انتشار: فصلنامه بین المللی سرمایه انسانی در مدیریت شهری، دوره: 5، شماره: 2
  • کد COI اختصاصی: JR_IJHCUM-5-2_005
  • زبان مقاله: انگلیسی
  • تعداد مشاهده: 249
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نویسندگان

A. Lemma Tadesse

Department of Geography and Environmental Studies, College of Social Science and Humanities, Arbaminch University, Arbaminch, Ethiopia

چکیده

The study was conducted with the objective of mapping landscape cover of Nechsar National park in Ethiopia to produce spatially accurate and timely information on land use and changing pattern. Monitoring provides the planners and decision-makers with required information about the current state of its development and the nature of changes that have occurred. Remote sensing and Geographical Information System have gained importance as powerful and efficient tools for land cover mapping of inaccessible area. Digital image classification is generally performed to produce land cover maps from remote sensing data, particularly for large areas. In this project, LANDSAT 7 ETM+ 2000 data was prepared for producing land cover map of study area, Nechisar National Park. Digital image processing techniques were conducted for the processes of radiometric and geometric correction and classification for land cover analysis. Additionally, training data for supervised classification were collected in the study area. Signature development was carried out and evaluated. Training sites were re-defined such that significant separability was obtained for all six bands of LANDSAT 7 EMT+. Finally, Supervised Classification was applied to classify the satellite image using Maximum Likelihood Classifier and five major land class cover were identified and mapped for the Nechsar National park. These are:  grassland, forest land, deciduous bush land, thickets, and water bodies.

کلیدواژه ها

geographic information system (GIS), Land cover, Nechisar National Park (NNP), Remote Sensing, Satellite images

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