The application of remote sensing and geographic information system techniques for the analysis of land use and land cover changes in Wayanad district of Kerala
| Autor: | M. G. Bijosh, John Abraham |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2024 |
| Předmět: | |
| Zdroj: | Journal of Veterinary and Animal Sciences, Vol 55, Iss 3, Pp 516-523 (2024) |
| Druh dokumentu: | article |
| ISSN: | 0971-0701 2582-0605 |
| DOI: | 10.51966/jvas.2024.55.3.516-523 |
| Popis: | Mapping Land Use and Land cover Changes (LULC) and detecting changes using remote sensing and Geographic Information System (GIS) techniques is a cost-effective way of gaining a good understanding of the land cover alteration processes caused by land use change and their effects. This study assessed the transformation of the Wayanad district landscape over a period of 23 years. LANDSAT satellite images (of 30 m resolution) encompassing the area at three epochs were classified into nine classes (coffee dominated mixed crop, built-up, evergreen forest, deciduous forest, grassland, mixed crop with built-up, paddy, tea plantation, and waterbody) using the maximum likelihood algorithm, resulting in classes for each land use. The results showed that over the past 23 years, coffee-dominated mixed crops have increased by 0.84% in 2014 and 11.84% in 2022 compared to 1999; deciduous forest area decreased 3.6% and increased 0.6% in 2014 and 2022, respectively. Tea plantations increased by 0.9% in 2014 and by 0.49% in 2022, which decreased by 0.41% compared to 2014. Built-up has increased by 6.42% and 6.02% in 2014 and 2022 respectively, and slightly decreased by 0.4% compared to 2014. Evergreen forest areas increased in 2014 by 6.68% and 2.28% in 2022 and decreased by 4.44% compared to the previous time period. Grass land areas have decreased by 6.25% and 5.33%, respectively, and mixed crops with built-up areas has decreased by 0.74% and remained the same in the last two epochs, while paddy and waterbodies have decreased by 3.4%, 15.79%, and 0.07 and 0.19%, respectively, in 2014 and 2022 of the total geographical area Keywords: Remote sensing, GIS techniques, LULC, forest cover |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
|