Long-term vegetation changes in semi-arid regions using remote sensing and spatial statistics functions in order to prepare a road map

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

علی ملایی محمد مهدی; رضایی مرضیه; مهدوی نجف آبادی رسول; غلامی حمید; کاظمی محمد

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: Journal of RS and GIS for Natural Resources Year:2025 | Volume:16 | Issue:1 Page(s): 25-48

Download Full-Text

Persian Verion

View:

Download:

Cites:

Information Journal Paper

Title

Long-term vegetation changes in semi-arid regions using remote sensing and spatial statistics functions in order to prepare a road map

Author(s)

علی ملایی محمد مهدی | رضایی مرضیه | مهدوی نجف آبادی رسول | غلامی حمید | کاظمی محمد

Keywords

پوشش گیاهی

توابع آماری

فارس

سنجش از دور

Abstract

Currently, Remote sensing is a useful technology that can be used to extract different layers such as soil, rainfall, vegetation and so on. The ultimate goal in most remote sensing analysis operations that are used to investigate different factors of vegetation cover is that the data of various spectral bands that can represent data such as percentage of vegetation cover, biomass and leaf area index into a single value in each pixel. Reduce. Over time, environmental and human factors have caused positive and negative changes in the quantity and quality of vegetation; This situation will continue in the future. Temporal changes in vegetation may be in the form of increasing or decreasing trends. Recognizing these changes and determining their trends in the past and future can open the way for decision-making for the image of the land. One of the ways to study vegetation changes as the most important indicator of land degradation is remote sensing. Based on this, in this research, using the NDVI normalized vegetation difference index in HDF format and MODIS sensor with a pixel size of 250 meters in a 16-day period, monitoring the long-term changes in the vegetation cover of Fars province during a 20-year period from 2000 to 2020 and was investigated using spatial statistics functions in order to prepare a road map in the year 1400. For this purpose, using spatial statistics functions to prepare a road map. For this purpose, MADIS data has been used for a period of twenty years. Then the data were analyzed by classical statistics and spatial statistics. The results show the increasing trend of the vegetation level in a period of 20 years, and the distribution of the vegetation over time was clustered. At the end, a roadmap for long-term vegetation monitoring in Fars province was proposed.

Multimedia

No record.

Cites

No record.

References

No record.

Cite

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans