Volume 5, Issue 4 (3-2019)
Journal of Spatial Analysis Environmental Hazards 2019, 5(4): 21-48 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Nikpour N, negaresh H, Fotoohi S, Hosseini S Z, Bahrami S. Monitoring the trend of vegetation changes one of the most important indicators of land degradation (in Ilam province). Journal of Spatial Analysis Environmental Hazards 2019; 5 (4) :21-48
URL: http://jsaeh.khu.ac.ir/article-1-2846-en.html
URL: http://jsaeh.khu.ac.ir/article-1-2846-en.html
Noorallah Nikpour1 
, Hossein Negaresh1 , Samad Fotoohi 2, Seyed Zeynalabedin Hosseini3 , Shahram Bahrami4
, Hossein Negaresh1 , Samad Fotoohi 2, Seyed Zeynalabedin Hosseini3 , Shahram Bahrami4
1- Department of Physical Geography, Faculty of Geography and Environmental Planning, University of Sistan and Baluchestan, Zahedan, Iran
2- Department of Physical Geography, Faculty of Geography and Environmental Planning, University of Sistan and Baluchestan, Zahedan, Iran ,fotohi@gep.usb.ac.ir
3- Faculty of Natural Resources and Desert Studies,,Yazd university
4- Shahid Beheshti University
2- Department of Physical Geography, Faculty of Geography and Environmental Planning, University of Sistan and Baluchestan, Zahedan, Iran ,
3- Faculty of Natural Resources and Desert Studies,,Yazd university
4- Shahid Beheshti University
Abstract: (6163 Views)
Deforestation or vegetation degradation is one of the main drivers of global earth changes, which has significant consequences in terms of ecosystem performance and biodiversity conservation. One of the ways for studying vegetation changes as the most important indicator of land degradation is remote sensing. In this study, in order to monitor the vegetation degradation trend in Ilam Province.After obtaining and preparing the required data (410 downloaded images) in the ArcGIS and Surfer software, the multiplication, mosaic and georeferencing operations are made. Converting format of images into ASCII is the next stage of the study. By converting this format, the total number of 953552 pixels is studied within the range; after removing the lost and negative values, 328042 pixels are analyzed. Besides, using parametric statistical method of the classical linear regression and programming in R software, the trend of slope variations and significance of slope variations of vegetations are obtained for the 17-year period (2000-2016). Results of this study show that the focus of the highest trend of declining slope variations (trend of negative slop variations) is in the NDVI index across the western half of the studied area and the focus of the highest trend of increasing slope variations (trend of positive slop variations) is in the NDVI index in the center and east. Significance of the trend of slope variations also approves this claim. Thus, the focus of the highest trend of slope variations (negative) in the west and southwest of the studied area along with the highest trend of slope variations (positive) in the center and east is significant at the probable level of 0.05
Type of Study: Research |
Subject:
Special
Received: 2018/10/7 | Accepted: 2018/12/25 | Published: 2019/03/12
Received: 2018/10/7 | Accepted: 2018/12/25 | Published: 2019/03/12
Send email to the article author
| Rights and permissions | |
 | This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
