The vast unexplored lateritic terrain of Kabirdham District, Chhattisgarh has received attention due to the presence of localized bauxite mines. In the present study, the ASTER images are processed to demarcate the ore, based on the spectral features of boehmite, gibbsite, and goethite in the VNIR–SWIR electromagnetic domain. This approach delineates the target and helps us to pinpoint the potential areas of bauxite deposits more easily from laterite. The bauxite ore is mainly enriched in Al₂O₃ (37.30–59.90%), TiO₂ (4.30–13.40%), and Fe₂O₃ (1.75–29.07%), with low amounts of SiO₂ (0.69–9.83%) of metallurgical grade. Boehmite is the predominant mineral in the study area followed by gibbsite. The band ratio, relative band depth images from ASTER data and the sub-pixel classifications of bauxite are mapped by using Adaptive Coherence Estimator (ACE), Matched Filtering (MF) and Linear Spectral Unmixing (LSU) methods. The bauxite-rich pixels derived from density-sliced images are overlaid on the digital elevation model (DEM) to interpret the relationship between the high-level bauxite distributions and the topographical slope/altitude. The results are validated by conducting substantial fieldwork. An integrated approach of spectral analysis with the petrological and colorimetric studies at Bamhantara block has supported the evidence of bauxite deposits and aided to find out the similar type of deposits at another lateritic province.

由于本地铝土矿的存在，恰蒂斯加尔邦 Kabirdham 区广阔的未开发红土地形受到了关注。在本研究中，根据 VNIR-SWIR 电磁域中勃姆石、三水铝矿和针铁矿的光谱特征，处理 ASTER 图像以标定矿石。这种方法划定了目标，并帮助我们更容易地从红土中确定铝土矿的潜在区域。铝土矿主要富含Al ₂ O ₃ (37.30-59.90%)、TiO ₂ (4.30-13.40%)和Fe ₂ O ₃ (1.75-29.07%)，SiO ₂含量低(0.69–9.83%) 冶金级。勃姆石是研究区的主要矿物，其次是三水铝石。使用自适应相干估计器 (ACE)、匹配滤波 (MF) 和线性谱解混合 (LSU) 方法映射来自 ASTER 数据的带比、相对带深度图像和铝土矿的亚像素分类。来自密度切片图像的富含铝土矿的像素叠加在数字高程模型 (DEM) 上，以解释高层铝土矿分布与地形坡度/高度之间的关系。结果通过进行大量实地调查得到验证。