Land Use/Land Cover Classification Using Remote Sensing Techniques . A Case Study AL Mazraa Sub-District .

Authors

  • Safieh Eid
  • Manna Isaa

Abstract

 

Studying of land use changing Detection needs to the speed of implementation to convoy the changes on the ground.  the traditional ways in the analysis and visual interpretation of the images and field studying need a lot of time and effort.  So The objective of this search is to classify group images (Landsat TM , ETM+) taken in different dates automatically, and then to calculate the area of each land use/land cover, during the years studied (1990 -2000- 2010) and comparison areas to identify the most important changes occurring during that period.

The search also sought to analysis the spectral reflectance values for different targets for each wavelength used in classification to determine the wavelengths in the separation of objectives.Supervised classification accuracy (79%) is good accuracy which can be improved by using images with accuracy of spatial and spectral resolution It is higher reliable public studies that do not require detailed information.

The studying found that the band 5 and 7 of the Landsat data can be successfully used in the separation between  pure basalt, basalt mixed with soil and urban uses, can also use the fourth band in irrigated crops, selected with great accuracy.

As for the change of land use studying showed continued increase in irrigated agricultural land area is generally at the expense of the home office space down the Rocky basalt and basalt mixed with soil, and increased space for built-up uses clearly during the period studied.

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Published

2016-12-21

How to Cite

Eid, S. ., & Isaa, M. . . (2016). Land Use/Land Cover Classification Using Remote Sensing Techniques . A Case Study AL Mazraa Sub-District . Tishreen University Journal- Arts and Humanities Sciences Series, 38(1). Retrieved from https://journal.tishreen.edu.sy/index.php/humlitr/article/view/2311

Issue

Vol. 38 No. 1 (2016): الآداب والعلوم الانسانية

Section

Articles

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