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Classification of Limestone Mining Site using Multi-Sensor Remote Sensing Data and OBIA Approach a Case Study: Biak Island, Papua

机译:使用多传感器遥感数据和OBIA方法对石灰石矿山进行分类的案例研究:巴布亚比亚克岛

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摘要

Most of Soil Type in Biak Island, Papua is Coral Limestone. This limestone is used as building material. Limestone mining is one of the income sources for local people. This study tries to map limestone mining sites using multi-sensor remote sensing data fusion and Object-Based Image Analysis (OBIA) classification approach. 1.5 meters resolution SPOT-6 data acquired in 2015 and 2017 used as spectral and geometric parameters in OBIA classification process. Surface deformation points obtained from the PS-InSAR technique on Sentinel-IA SLC SAR data acquired from November 2017 to May 2018 is used as the structural variable for OBIA classification process to determine whether mining site is active or inactive. The overall accuracy of classification result is 84.7% for 2015 SPOT-6 data and 74.9% for 2017 SPOT-6 data.
机译:巴布亚比亚克岛的大部分土壤类型是珊瑚石灰石。该石灰石用作建筑材料。石灰石开采是当地人的收入来源之一。本研究尝试使用多传感器遥感数据融合和基于对象的图像分析(OBIA)分类方法来绘制石灰石采矿场的地图。 2015年和2017年获得的1.5米分辨率SPOT-6数据在OBIA分类过程中用作光谱和几何参数。从2017年11月至2018年5月获取的Sentinel-IA SLC SAR数据的PS-InSAR技术获得的表面形变点用作OBIA分类过程的结构变量,以确定采矿地点是活跃的还是非活跃的。对于2015 SPOT-6数据,分类结果的总体准确性为84.7%,对于2017 SPOT-6数据,为74.9%。

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