<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Over the last decades, north of Iran underwent remarkable land use/cover changes due to socio-economic and environmental factors. This study, focused on agricultural land changes for the period of 1990–2020 at Shanderman, Iran, employed Landsat 5 TM, and Landsat 8 OLI/TIRS images. A supervised maximum likelihood classification technique was utilized for the purposes of satellite data classification to four classes: agricultural land, forest, grassland, and built-up area. Results of land change modeller showed that, during the last three decades, agricultural land, grassland and forest decreased by 42.81%, 35.50%, and 4.05%, respectively, while built-up area increased by 361.23%. Most of the losses in agriculture areas occurred in 1990–2011 (44.64%). The predominant losses in 2011–2020 belonged to the forestland (12.47%), making them approx. 3.44 times higher than in 1990–2011. The results highlight the need for serious attention to the deforestation phenomenon, which leads to the conversion of forest into agricultural and built-up areas.</p>
</abstract>

Over the last decades, north of Iran underwent remarkable land use/cover changes due to socio-economic and environmental factors. This study, focused on agricultural land changes for the period of 1990–2020 at Shanderman, Iran, employed Landsat 5 TM, and Landsat 8 OLI/TIRS images. A supervised maximum likelihood classification technique was utilized for the purposes of satellite data classification to four classes: agricultural land, forest, grassland, and built-up area. Results of land change modeller showed that, during the last three decades, agricultural land, grassland and forest decreased by 42.81%, 35.50%, and 4.05%, respectively, while built-up area increased by 361.23%. Most of the losses in agriculture areas occurred in 1990–2011 (44.64%). The predominant losses in 2011–2020 belonged to the forestland (12.47%), making them approx. 3.44 times higher than in 1990–2011. The results highlight the need for serious attention to the deforestation phenomenon, which leads to the conversion of forest into agricultural and built-up areas.

Multi-Temporal Detection of Agricultural Land Losses Using Remote Sensing and Gis Techniques, Shanderman, Iran

Acta Technologica Agriculturae

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Over the last decades, north of Iran underwent remarkable land use/cover changes due to socio-economic and environmental factors. This study, focused on...

Multi-Temporal Detection of Agricultural Land Losses Using Remote Sensing and Gis Techniques, Shanderman, Iran

Online veröffentlicht: 18. Juni 2022

Seitenbereich: 67 - 72

DOI: https://doi.org/10.2478/ata-2022-0011

Schlüsselwörter
deforestation, Landsat, supervised classification, urbanization

© 2022 Fatemeh Rahimi-Ajdadi et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Multi-Temporal Detection of Agricultural Land Losses Using Remote Sensing and Gis Techniques, Shanderman, Iran

Online veröffentlicht: 18. Juni 2022

Seitenbereich: 67 - 72

DOI: https://doi.org/10.2478/ata-2022-0011

Schlüsselwörterdeforestation, Landsat, supervised classification, urbanization

© 2022 Fatemeh Rahimi-Ajdadi et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
deforestation, Landsat, supervised classification, urbanization