Volume XLII-4/W18
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W18, 1159–1162, 2019
https://doi.org/10.5194/isprs-archives-XLII-4-W18-1159-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W18, 1159–1162, 2019
https://doi.org/10.5194/isprs-archives-XLII-4-W18-1159-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  19 Oct 2019

19 Oct 2019

INVESTIGATING OF FOREST CHANGE IN GOLESTAN PROVINCE USING LANDSAT IMAGE

M. Zoraghi, R. Saadi, and M. Hasanlou M. Zoraghi et al.
  • School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Iran

Keywords: Change detection, Post classification comparison, Golestan province, Land use, Remote sensing

Abstract. In recent years, forests in the north of the country have been attacked due to human interference. Increasing population and development of residential and agricultural areas have led to deforestation. Change detection is one of the most common methods for evaluating natural resources. The aim of this study is to monitor changes in forests of Golestan province in two period times from 1990 to 2019, using Landsat images. Accordingly, by incorporating those data sets land use maps are produced. Also, the SVM algorithm is used with six different classes including forest (F), urban area (U), agriculture (A), uncultivated land (UL), water (w) and bare soil (BS). The achieved overall accuracies are 85.48% and 89.86%. Then the map and matrix changes were obtained by post-classification comparison method. The results showed that the Golestan province's forests were reduced and converted to agricultural and urban land uses.