江西省都昌县山地与平原植被界线提取

发布时间：2018-02-11 00:43

本文关键词： GF_高分遥感影像绝对高程地形起伏度地形部位指数地貌位置类型　出处：《地球信息科学学报》2017年04期 　论文类型：期刊论文

【摘要】：由于生长环境、地带性分布规律和垂直差异,山地与平原地区的不同植被类型在遥感影像上存在"同物异谱"及"异物同谱"现象,易导致土地类型的误分。为避免此类错分,在进行土地覆被类型解译之前,应首先确定平原、山地植被的边界。本文在遥感影像聚类分析、GIS空间分析及数理统计分析技术的支持下,以江西省都昌县北部地区为研究区域,基于高分一号(GF-1)遥感卫星影像及地形要素,完成了山地植被与平原植被的界线提取。实验结果显示,本研究得到的植被界线精度高达99.47%和96.28%。与单纯基于遥感影像分类得到的植被边界成果相比,精度提高了近25%和23%。研究证明,高分辨率遥感影像与地形因子结合后,计算得到的山地平原划分界线精度有明显提高,可以满足高分辨率遥感影像土地覆被类型解译研究的需要。
[Abstract]:Because of the growth environment, zonal distribution law and vertical difference, the different vegetation types in mountainous and plain areas have the phenomenon of "same material difference spectrum" and "foreign body same spectrum" in remote sensing image, which is liable to lead to the wrong division of land type. Before the interpretation of land cover types, the boundary of plain and mountain vegetation should be determined first. With the support of GIS spatial analysis and mathematical statistics analysis of remote sensing image clustering analysis, this paper takes the northern region of Duchang County, Jiangxi Province, as the research area. Based on GF-1) remote sensing satellite images and terrain elements, the boundary between vegetation in mountainous areas and plain vegetation has been extracted. The experimental results show that, The accuracy of vegetation boundary obtained in this study is as high as 99.47% and 96.28. Compared with the results of vegetation boundary classification based solely on remote sensing images, the accuracy is improved by nearly 25% and 23.3. The research proves that the combination of high-resolution remote sensing images and terrain factors, The precision of dividing line of mountain plain is improved obviously, which can meet the need of land cover type interpretation of high resolution remote sensing image.
【作者单位】：中国科学院地理资源与科学研究所资源与环境信息系统国家重点实验室;中国科学院大学;
【基金】：国家重点研发计划项目“基于国产遥感卫星的典型要素提取技术”(2016YFB0501404) 江西省科技计划项目(2015ACF60025)
【分类号】：Q948;TP79

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