COMPARISON OF LAND USE LAND COVER CLASSIFICATION METHODS USING THE RANDOM FOREST ALGORITHM WITH NDVI VERSUS A COMBINED INDEX APPROACH (NDVI, DEM, NDWI, AND NDSI) IN DAK GLONG AND KRONG NO DISTRICTS, DAK NONG PROVINCE
DOI:
https://doi.org/10.70169/VJFS.1060Keywords:
Normalized difference soil index, Normalized difference water index, Normalized difference vegetation index, Digital elevation model, Land use and land coverAbstract
ABSTRACT
This study focuses on evaluating and comparing the classification performance of Land use and land cover (LULC) using the Random Forest (RF) algorithm with two approaches: (i) employing only the Normalized difference vegetation index (NDVI), and (ii) integrating a combination of NDVI, Digital elevation model (DEM), Normalized difference water index (NDWI), and Normalized difference soil index (NDSI) derived from Landsat imagery in Dak Glong and Krong No districts, Dak Nong province. The results indicate that the NDVI-only approach yields relatively low overall accuracy (OA), ranging from 35.89% to 59.35%, with a Kappa coefficient (K) between 0.24 and 0.41. In contrast, the integrated index approach significantly enhances model performance, achieving OA between 81.75% and 86.04%, and K ranging from 0.75 to 0.78. The OA improvement reaches up to 45.86%, while the average K increase is approximately 0.40. The inclusion of DEM, NDWI, and NDSI effectively mitigates spectral confusion and improves the discrimination between spectrally similar land cover classes. Based on these findings, the study recommends applying the integrated NDVI, DEM, NDWI, and NDSI approach in LULC classification tasks using remote sensing data, especially in topographically complex regions such as the Central Highlands, to enhance classification accuracy and the reliability of land use maps for sustainable land and forest resource planning and monitoring. The analysis of land cover changes in Dak Glong and Krong No districts reveals a significant decline in natural forest areas, while planted forests have increased markedly, reflecting a shift in land use towards the development of production forests. At the same time, the areas of bare land, agricultural land, and residential zones have also experienced considerable changes due to socio-economic development and the growing demand for land use.
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