基于多源遥感数据的石漠化信息提取研究

Research on the Information Extraction of Rocky Desertification Based on Multi-Source Remote Sensing Image Data

利用撒拉溪示范区和花江示范区2016年的12个月份的SAR数据后向散射系数,构建时间序列,进行石漠化信息的提取,同时利用雷达遥感影像和光学遥感影像融合的方法进行喀斯特地区石漠化等级的确定,并选取野外实地验证的方法进行精度验证.结果表明:多源遥感数据支持下的石漠化信息提取方法相比较于传统的光学遥感提取方法,在石漠化地物界定和石漠化强度定级上更加准确和有效.在喀斯特高原山地轻—中度石漠化区,其精度分别提高7.69%和5.99%;在喀斯特高原山地中—强度石漠化区,其精度分别提高9.41%和5.39%.

The twelve months＇ radar data＇s backscattering coefficients was used to construct the time series for information extraction of rocky desertification in the year of 2016 in Salaxi and Huajiang demonstration areas,then ranked the karst rocky desertification information by fusing the SAR remote sensing image and optical remote sensing image,and verified the accuracy by field surveying.The result showed that the method of information extraction of rocky desertification based on multi-source remote sensing image data was more accurate and effective than traditional optical method in translating and ranking of rocky desertification.Their accuracy rates were improved by 7.69% and 5.99%,respectively,in mild and moderate rocky desertification region of karst plateau-mountain region,and their accuracy rates were improved by 9.41% and 5.39%,respectively,in moderate and severe rocky desertification region of karst plateau-mountain region.