Monitoring and evaluating land use changes using remote sensing techniques and satellite images (case study: Bam plain)

Safavi, Maryam; Galdavi, Somayeh; Dehghan, Hadi

doi:10.22034/jelsa.2024.459150.1067

Monitoring and evaluating land use changes using remote sensing techniques and satellite images (case study: Bam plain)

Document Type : Original research article

Authors

Maryam Safavi ¹

Somayeh Galdavi ²

Hadi Dehghan ²

¹ Ph.D Student of Water Resources, Birjand University, Birjand, Iran

² Department of Water Sciences and Engineering, Kashmar Higher Education Institute, Kashmar, Iran

10.22034/jelsa.2024.459150.1067

Abstract

One way to effectively manage geographical space, natural resources, and the environment is through the use of land use maps. Understanding the quantitative and qualitative characteristics of changes in land use is crucial for environmental planning, land use, and sustainable development. The study aims to assess the potential of Landsat satellite data in identifying, detecting, and monitoring changes in land use. This involves using various digital processing techniques on satellite images to produce maps. The focus is on evaluating both the quantitative and qualitative changes in land use in the Bam Plain in Kerman province. To conduct research using Landsat satellite images from 2003 to 2018, a land use map for the year 2018 was prepared using the maximum likelihood algorithm, neural network, and support vector machine. The accuracy of the algorithms for this year was then discussed. The evaluation of the classification results shows that maximum likelihood classification has an overall accuracy of 95% and a kappa coefficient of 94%, which is higher than the accuracy of 93% and kappa of 91% for neural network classification, as well as the accuracy of 88% and kappa of 85% for support vector machine classification. Then, Using the maximum likelihood algorithm, which had high accuracy, the map of other years was also prepared. then the map of changes for each period was also obtained, which showed the changes in land use during the 5-year periods of 2003-2008, 2008-2013, and 2013-2018. although these maps revealed fluctuations in land area over the mentioned periods, during the last 15 years (2003-2018) significant changes were observed in the extent of barren and Salty lands in the study area. In 2003, these lands covered approximately 6811.91 Km², which accounted for about 38.52% of the study area. This area expanded to 6877.17 Km²in 2018, covering approximately 38.91% of the study area. During this period, agricultural lands and pastures diminished due to overuse. The results of this research assist managers and decision-makers in making more informed decisions regarding changes in land use, as well as the control, protection, and sustainable use of land.

Highlights

The potential of Landsat satellite data in identifying, detecting, and monitoring changes in land use was investigated.
The focus is on evaluating the quantitative and qualitative changes in land use in the Bam Plain in Kerman province.
land use maps were prepared using the maximum likelihood algorithm, neural network, and support vector machine.
The result of land use change detection showed significant changes in the extent of barren and Salty lands.
During this period, agricultural lands and pastures diminished due to overuse.

Keywords

Bam plain

Change detection

Land use

MLC

Remote sensing techniques

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