基于谐波分析和线性混合模型的河北平原区土地覆被分类研究

土地覆被分类是研究土地利用/覆被变化的基础数据和关键环节。以16d合成MODIS-EVI时间序列数据为主要数据源,采用谐波分析方法分析不同土地覆被类型的季节性变化规律和物候特征差异,引入谐波特征值构建线性混合模型,提取不同端元的丰度值。从土地覆被类型较齐全、谐波特征具有代表性的石家庄地区高空间分辨率影像上选择训练样本,确定MODIS纯净像元和混合像元的划分阈值,对河北平原区进行土地覆被分类制图。结果表明,与河北省县级土地调查统计数据对比,一年两熟耕地、一年一熟耕地、园地及有林地、自然陆地表面的总量精度分别为90.19%、86.17%、85.96%和77.82%,平均总量精度为85.03%;与石家庄地区9个县(市)一年两熟耕地和一年一熟耕地基于TM的分类结果对比,平均面积相对误差分别为10.25%、13.98%。受粗空间分辨率和合成周期、水热条件以及种植模式破碎化限制,混合像元主要集中在河北平原中东部地区,一年两熟耕地、一年一熟耕地、园地及有林地混合面积比重较大。     

极端干旱区荒漠稀疏河岸林遥感分类研究

研究以位于极端干旱区的塔里木河干流中下游地区为例,基于Landsat TM影像,结合决策树分类、几何光学模型与光谱角匹配,解决混合像元信息分解,实现干旱区稀疏荒漠河岸林类别识别。首先从遥感视角的角度,将地物分解为目标和背景,提出塔里木河干流荒漠河岸林植被分类系统;其次以多变量决策树法将非荒漠植被信息剔除,采用几何光学模型模拟各类荒漠植被的像元光谱,最后以光谱角匹配的方法将荒漠植被进一步进行分解,得到塔里木河干流中下游地区典型研究区的植被分类专题图,分类精度结果表明:基于混合像元分解与几何光学模型的分类方法总精度达到了79.43%,Kappa系数为0.718,表明分类质量良好。     

基于支撑向量回归的二端元混合像元分解

针对遥感影像混合像元光谱复杂,其非线性特征,传统LSMM分解模型难以进行有效的混合像元分解的不足。通过基于SVR的二端元混合像元分解的研究,从真实遥感影像上获取典型的植被、非植被光谱信息,构造二端元混合光谱库,进行SVR模型的混合像元分解。当样本量为6%时,交叉验证获得最佳模型参数（C=1024.0和g=4.0）,进一步对全部混合像元进行混合像元分解。实验结果表明：SVR分解结果RMSE为5.95,R²为0.958,优于LSMM方法（RMSE=7.71,R²=0.932）,且在各个不同真值丰度下具有更好的稳定性,证明该方法对于非线性混合光谱具有很好的学习和推广能力。此外,该方法的精度不随训练样本量的增加呈明显变化,体现出SVR在有限样本情况下能够保证高效率的训练能力。     

松嫩平原西部土地退化的遥感动态监测研究——以吉林省通榆县为例

以松嫩平原西部土地退化典型地区－吉林省通榆县为例，在RS和GIS集成技术支持下，利用不同时相的TM数据，采用线性光谱混合模型方法，选用植被、盐碱地、裸沙地、沼泽地、苇地作为最终光谱单元进行线性光谱分解，依据盐碱地和裸沙地加权和分量，将试点区的土地退化划分为未退化、轻度退化、中度退化和重度退化四个等级进行动态监测，并分析土地退化的数量、空间分布与动态过程。     

基于混合像元分解和知识规则的人工刺槐林健康分类

提出一种基于精度较高的Landsat TM数据检测刺槐林枯梢状况的方法,整个过程分为:1)利用监督分类提取出林地分布范围,制作刺槐林地掩膜;2)对刺槐林地利用线性光谱混合模型进行混合像元分解,得到健康刺槐、非光合作用绿色植被(NPV)、土壤的丰度图,定义刺槐林的健康分类等级:健康或轻度枯梢、中度枯梢、重度枯梢或死亡;3)利用决策树分类器对丰度图像、归一化植被指数(NDVI)以及经缨帽变换获取的亮度和绿度成分定义一组规则,进行刺槐林生长健康状况分类,分类结果与实地样方数据具有较好的一致性,利用林冠分级向导进行精度分析,精度达82.2%,Kappa系数为0.752。     

基于混合像元分类的城市地表覆盖时空演变格局研究

基于可能性理论和中心点聚类方法的原理,提出可能性C中心点(PCRMDD)聚类方法.运用该法对上海市中心城区Landsat ETM+遥感影像进行混合像元分类,并自动获取地物端元盖度分布图及影像端元光谱,解混精度的检验结果表明该方法能在噪声环境下获得精度较高的分类结果和端元光谱信息.根据各时期研究区域的地表覆盖分类结果,应用GIS空间分析功能,进一步探讨在城市化过程中上海中心城区土地利用时空演变格局,揭示城市用地空间扩展模式.     

基于混合像元分解的辽河口滨海湿地分类

滨海湿地高精度的地物分类可以为湿地监测与保护提供数据支持和决策依据。以辽河口湿地为研究对象,以Landsat8 OLI多光谱影像为数据源,结合研究区域实际地物情况,采用像元纯度指数和均值波谱法确定端元光谱,并利用全约束最小二乘混合像元技术和决策树技术制定分类规则,最后将研究区域分为芦苇、翅碱蓬、水稻、滩涂、水体(海水、虾池水、河水等)和人工建筑(包括路面、人工设施、房屋等)六大类。结果表明:该算法分类精度高于90%,结合目视判读与野外实地调查,发现分类结果符合实际地物情况。     

ALOS融合影像质量评价及其土地盐渍化应用研究

将经过配准的同一地区不同空间分辨率和光谱分辨率的遥感影像进行融合是提高土地覆盖/土地利用分析精度的有效途径。采用PCA、IHS、HPF和小波变换融合法对内蒙古杭锦后旗中部地区的ALOS全色和多光谱影像进行融合,并对融合结果进行了定性和定量评价。基于地物光谱特征、解译标志和监督分类法提取试验区土地盐渍化信息,比较多光谱影像和融合影像的土地盐渍化信息提取精度。结果显示,PCA、IHS和HPF融合影像的空间细节表现能力得到提升,而PCA和小波变换融合影像的光谱保真度优于IHS和HPF融合影像;PCA融合影像的盐渍化分类精度、总分类精度和Kappa系数均为最高,是最适于试验区土地盐渍化分类研究的融合方法。     

训练样本对遥感影像分类精度影响研究

以大理SPOT-5 HRG影像和Landsat TM影像作为数据源,在构建标准训练样本数据集的基础上,探索训练样本对遥感影像分类的影响。选取不同训练样本数量组合,分别对监督分类中的平行六面体、最小距离、马氏距离、最大似然法、神经网络和支持向量机6种分类方法进行多次实验,并采用Kappa系数和总体分类精度对实验分类结果的精度进行评价。结果表明:以多次分类结果的平均值作为最终的分类结果能减小随机误差;增加训练样本数量可以减小单次分类引起的随机误差;在不同的训练样本量下,支持向量机的分类精度最高。     

基于MODIS数据的松辽平原土地退化宏观评估

该文利用植被指数、最小噪声化变换、纯净像元指数和匹配滤波等遥感信息定量分析方法,从MDDIS陆地观测数据中提取反映松辽平原土地退化状况的植被覆盖、盐碱化和沙漠化信息,实现土地退化制图及土地退化格局分析。MODIS数据及其定量分析技术,对干旱区与半干旱区土地退化的宏观监测具有重要作用。     

西南地区山地不同土地退化类型特征及调控途径

土地退化不仅是目前全还需性的重大环境问题之一，而且也是重大的社会和经济问题之一，西南地区的土地退化是以水力侵蚀为主要动力形成的，文中简述了西南地区的土地退化状况，选择了4个（楚雄市、遂宁市，毕节地区及元谋县）山地不同土地退化类型进行分析，讨论了土 退化过程，提出了土地退化调控途径。     

基于机载成像光谱数据的宜兴市土地利用/土地覆盖分类方法对比研究

对宜兴市机载成像光谱数据辐进行射畸变纠正、几何精确纠正和辐射定标等预处理,获得高光谱反射率图像。利用相关系数、均方差、离散度等统计特征进行面向土地利用/土地覆盖目的的波段优选,采用高光谱像元提纯分析工具获得分类所需的终端单元,并利用终端单元进行了研究区土地利用/土地覆盖分类对比研究。研究发现:最大似然法分类精度低,整体精度为84.89%,而二进制编码、神经网络分类和光谱角分类方法精度较高,整体精度分别为87.12%,88.75%,90.41%。这说明光谱角分类是最有效的高光谱影像土地利用/土地覆盖分类方法,文章研究采用的高光谱预处理以及波段选择方法是正确的。     

金衢盆地丘陵荒山土地退化评价及其时空分异特征——以兰溪市上华试验区为例

本文根据联合国土地退化和土地荒漠化定义，结合研究区特点，提出以植被覆盖度、侵蚀地貌形态和地面组成物质作为丘陵荒山土地退化程度的评价指标，既反映了植被的退化和土地表面形态的退化，又反映了土壤的退化。以此为基础，进而通过两期航空相片的解译，完成了研究区５０年代和８０年代丘陵荒山土地退化程度的模糊数学半定量评价和制图。分析表明，不同等级退化土地约占全区土地总面积的３６％，其中严重和剧烈退化的土地约占５％；退化土地的分布具有明显的坡位分异性和地域分异性；区内严重和剧烈退化的“劣地”早在解放以前即已存在，其形成历史可以追溯至明清时期，５０年代到８０年代土地退化的发展主要表现为微度退化土地的明显减少及中度和轻度退化土地的增加。     

Soil and plant responses to degradation of alpine grassland in source region of the Yellow River

Land degradation has been rapidly taking place in source region of the Yellow River in China. This study was conducted during 2008 in Maduo County to investigate soil and plant changes in relation to land degradation. Several results were derived from this work. First, the soil organic carbon (SOC) and total nitrogen (TN) decreased significantly on the extremely degraded land comparing with the natural grassland. Second, soil bulk density increased as land degradation worsened. Soil bulk density of the extremely degraded land was significantly greater than that of the grassland. Third, pH showed no obvious variation pattern. Finally, aboveground biomass decreased from grassland to the moderately degraded land. But aboveground biomass increased on the extremely degraded land and very extremely degraded land with most aboveground biomass inedible for livestock.     

基于全球土地退化零增长监测体系构建的中国沙化土地监测体系及效果评估

土地荒漠化是非常重要的生态环境问题,而科学评价荒漠化治理和零增长目标是否实现的必要前提是具有完善统一的评价体系。为此,联合国防治荒漠化公约（UNCCD）提出了土地退化零增长（LDN）的概念和监测指标。防治土地退化是中国的重要生态目标,中国已开展了多次全国土地荒漠化和沙化监测工作。但是,如何将这些监测结果用于土地退化的评估实践,尚未见报道。因此,本研究针对中国四大沙地,利用3期全国荒漠化和沙化监测数据,与基于UNCCD框架体系下的土地退化零增长（LDN）指标进行对比分析,并基于土地沙化程度变化趋势提出了中国沙化土地退化指标体系（CSLDN）。结果表明：UNCCD所提出的LDN监测指标与中国的荒漠化监测数据总体精度为0.51,中国沙化土地监测指标与LDN指标具有宏观一致性。此外,经本地优化后的CSLDN指标克服了低植被盖度区域LDN对土地退化和恢复的评价不准确的问题,更准确刻画了精细尺度空间内的土地动态变化状况,对土地退化防治意义重大。     

Land use/land cover (LULC) classification with MODIS time series data and validation in the Amur River Basin

There is a need for improved and up-to-date land use/land cover (LULC) data sets over an intensively changing area in the Amur River Basin (ARB) in support of science and policy applications focused on understanding of the role and response of the LULC to environmental change issues. The main goal of this study was to map LULC in the ARB using MODIS 250-m Normalized Difference Vegetation Index (NDVI), Land Surface Vegetation Index (LSWI), and reflectance time series data for 2001 and 2007. Another goal was to test the consistency of the classification results using relatively coarse resolution MODIS imagery data in order to develop a methodology for rapid production of an up-to-date LULC data set. The results on MODIS land cover were evaluated using existing land use/cover data as derived from Landsat TM data. It was found that the MODIS 250-m NDVI data sets featured sufficient spatial, spectral and temporal resolution to detect unique multi-temporal signatures for the region’s major land cover types. It turned out that MODIS 250 NDVI time series data have high potential for large-basin land use/land cover monitoring and information updating for purposes of environmental basin research and management.     

Changes in intensity of wind erosion at different stages of degradation development in grasslands of Inner Mongolia, China

Overgrazing by increasing numbers of livestock in the Horqin Sandy Land of Inner Mongolia, China, has led to extensive degradation of the region's sandy steppes. Degraded grasslands are generally classified into four main types: fixed (least degradation), semi-fixed (light degradation), semi-shifting (moderate degradation) and shifting (severe degradation) sandy lands, representing four stages of degradation development. An experiment was conducted in the Horqin Sandy Land to investigate changes in intensity of wind erosion at different stages of degradation development in sandy grasslands and determine the extent to which surface wind erosion was affected by surface-related soil and vegetation factors through their effects on surface roughness length and wind regimes. Daily wind erosion rate was monitored at four sites of degraded grassland over an erosive period from 1 April to 10 June in 2001. Soil and vegetation properties for these sites were also measured twice: one in mid-April prior to the establishment of vegetation and again in mid-June after the establishment of vegetation. Relationships between surface roughness length and soil and vegetation variables were examined at each of the two stages of vegetation development. This study shows striking differences in the intensity of surface wind erosion among sites. The daily wind erosion rate in the fixed sandy land was, on average, only about 1/5 of the rate in the semi-fixed sandy land, 1/14 of the rate in the semi-shifting sandy land and 1/47 of the rate in the shifting sandy land suggesting a much higher resistance of the fixed sandy land to wind erosion compared to other sites. Differences in rate of wind erosion between sites were attributed to between-site differences in soil and vegetation properties that exerted significant effects on wind regimes by altering surface roughness length. At the pre-establishment stage of vegetation, surface roughness length was determined by a combination of litter amount on the ground, soil surface hardness and soil moisture content, with litter amount explaining the greatest proportion of the variation. At the post-establishment stage of vegetation, the development of the surface roughness effects was mainly governed by vegetation characteristics (vegetation cover in particular), while the effects of soil surface hardness and soil moisture on surface roughness length are likely to be masked by vegetation effects. The findings suggest that better management practices of restoring vegetation in degraded grasslands are required to reduce soil erosion losses and achieve a sustainable livestock production in the Horqin Sandy Land, an ecologically fragile sandy land ecosystem.     

Urban mapping,accuracy, & image classification: A comparison of multiple approaches in Tsukuba City,Japan

The rapid growth of urban space and its environmental challenges require precise mapping techniques to represent complex earth surface features more accurately. In this study, we examined four mapping approaches (unsupervised, supervised, fuzzy supervised and GIS post-processing) using Advanced Land Observing Satellite images to predict urban land use and land cover of Tsukuba city in Japan. Intensive fieldwork was conducted to collect ground truth data. A random stratified sampling method was chosen to generate geographic reference data for each map to assess the accuracy. The accuracies of the maps were measured, producing error matrices and Kappa indices. The GIS post-processing approach proposed in this research improved the mapping results, showing the highest overall accuracy of 89.33% as compared to other approaches. The fuzzy supervised approach yielded a better accuracy (87.67%) than the supervised and unsupervised approaches. The fuzzy supervised approach effectively dealt with the heterogeneous surface features in residential areas. This paper presents the strengths of the mapping approaches and the potentials of the sensor for mapping urban areas, which may help urban planners monitor and interpret complex urban characteristics.     

基于光谱和纹理特征的ALOS影像土地利用信息提取

针对高分辨率遥感影像易于反映地物纹理特征的特点,综合利用地物的光谱和纹理特征进行分类,探讨适用于ALOS影像的土地利用信息提取方法。以川东丘陵地区影像为例,基于GLCM提取纹理信息,将提取的纹理特征向量采用赋权值法融合为一个综合纹理信息波段,然后采用面向对象法将其与光谱特征信息共同参与分类。与最大似然法的提取结果对比表明,考虑了纹理特征的面向对象分类方法能明显提高分类精度,Kappa精度提高了0.12;避免了椒盐现象,分割的地类边界具有更好的语义表达,更贴合地物实际分布特征;建筑用地和林地具有明显的纹理特征,而旱地纹理特征不明显。该方法不仅分出了6个基本地物类型,而且对于林地、建筑用地等类型还能进一步细分。     

从若干典型地区的研究对近十余年来中国土地沙漠化演变趋势的分析

土地沙漠化是当前世界上一个重要的生态环境问题,在我国也存在着严重的土地沙漠化问题。50年代末至70年代中期,我国沙漠化土地以每年1560km~2的速度扩大。近10余年来其总的趋势仍在发展,平均每年以2100km~2的速度蔓延。目前,全国已经沙漠化了的土地面积达19.70×10~4km~2以上,其中以沙质草原农垦区和能源基地附近的情况最为严重。实例说明,沙漠化土地在采取必要的措施之后,不仅可以防止其蔓延,而且还可以重新恢复其生产潜力成为农牧业用地。