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  • 软件名称:基于航空高光谱影像的额济纳绿洲土地覆被提取
  • 软件大小: 0.00 B
  • 软件评级: ★★★
  • 开 发 商: 苏阳,祁元,王建华,徐菲楠,张金龙
  • 软件来源: 《遥感技术与应用》
  • 解压密码:www.gissky.net

资源简介

摘要: 土地覆被分类是生态环境评价、植被变化分析以及区域生态水文过程研究的基础。航空高光谱遥感具有高机动、高空间分辨率和高光谱分辨率等特点,在土地覆被提取方面极具优势。以黑河下游机载高光谱遥感数据为基础,针对额济纳旗胡杨林国家级自然保护区植被单一、景观破碎和异质性强的景观特点,以及高光谱数据量大、冗余度高等数据特点,对比分析最小噪声变换与主成分分析两种降维方法,最大似然法、支持向量机与面向对象3种监督分类方法。依据研究结果,首先利用NDVI区分高光谱遥感数据中的植被与非植被类别,然后采用最小噪声变换分别进行降维处理,最后利用最大似然法对研究区内土地覆被类型进行分类提取,提取结果聚类处理。依据随机验证点结合地面调查数据和正射影像,对土地覆被分类结果进行精度验证,总体精度和Kappa系数分别为87.95%和0.855,表明分类结果精度高,能够为生态研究等提供有效数据。 关键词: 高光谱;  干旱区;  降维方法;  监督分类;  土地覆被     Abstract: The extraction of land surface coverage is the basis of ecological environment evaluation,vegetation change analysis and regional ecological and hydrological processes.Aerial hyperspectral remote sensing has great advantage in land surface coverage extraction,such as flexible,wide coverage,high spatial resolution and high spectral resolution.Research area has landscape characteristics of vegetation,landscape fragmentation and heterogeneity in Ejina Poplar Forest National Nature Reserve.Comparison and analysis of two methods of dimension reduction based on minimum noise transform and principal component analysis,three supervised classification methods based on maximum likelihood method,support vector machine and object\|oriented classification.Land surface coverage is extracted by NDVI threshold segmentation,minimum noise transform dimensionality reduction method and maximum likelihood classification method according to the characteristics of landscape fragmentation,heterogeneity and high redundancy of hyperspectral data based on the Airborne Hyperspectral Data of Ejina oasis in the lower reaches of Heihe.The land surface coverage results overall accuracy and Kappa coefficient are 87.95% and 0.885 by random sampling based on airborne remote sensing data.The results show that the classification results of high accuracy can provide effective parameters for ecological research.

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