The feasibility of Sentinel-2A and Landsat 8 imagery in rock outcrop extraction using object-based oriented classification
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Abstract
The presence of exposed rocks in the mountainous areas of the Thua Thien Hue province in Vietnam has affected the expansion of agroforestry farming areas. A novel classification approach is proposed to extract rock outcrops in the mountainous region by integrating the object-based oriented classification (OBOC) method and multiple ratio image indices. The default index (mean Near-infrared - NIR, mean Blue, Brightness) and calculated index (normalized difference built-up index - NDBI, normalized difference vegetation index - NDVI, topsoil grain size index - TGSI) ratio images effectively integrate delineating rock outcrops through the determination of the threshold of image index values. The main findings are that Sentinel-2A and Landsat 8 provided an acceptable extraction of exposed rocks in the mountainous area with an overall accuracy of over 80% based on the OBOC technique. Sentinel-2A extracted the revealed rocks with higher accuracy than Landsat 8 in two test sites of the mountainous region of the Thua Thien Hue province. The results were verified in the field, demonstrating that rock outcrops were better detected by Sentinel-2A (93%) than Landsat 8 (86%), in agreement with existing map soil data published in the geographic information system of the Thua Thien Hue province (GISHue data). Furthermore, Sentinel-2A data revealed specific sites with outcropping rocks which were not included, yet yielded reliable field results confirming its potential for mapping and monitoring exposed rocks for environmental protection and agroforestry development in mountainous areas.
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