遥感与GIS在准格尔旗土壤侵蚀监测中的应用

以内蒙古准格尔旗为例,利用TM图像及相关辅助数据,通过GIS软件ARC/INFO、遥感软件ERDAS IMAGINE 8.5,对影像进行格式转换、人机交互解译等处理,得到准格尔旗土壤侵蚀的结果数据。结果表明,准格尔旗风力侵蚀,水力侵蚀总体上仍比较严重,且以水力侵蚀为主。水力侵蚀与风力侵蚀强度侵蚀以上所占比例分别为68.39%和48.45%。     

基于遥感数据的流域土壤侵蚀强度快速估测方法

以北京延庆县境内的妫水河流域为例, 提出了一种基于遥感数据的土壤侵蚀强度快速估测方法。首先, 利用遥感数据和植被指数模型提取流域内土地利用类型信息和植被覆盖度信息; 其次, 利用数字高程模型数据生成坡度图; 然后, 结合土壤侵蚀强度分级指标, 将坡度图与土地类型图、植被覆盖度图空间叠加, 判断和计算侵蚀强度等级, 结果获得了流域土壤侵蚀强度等级图; 最后, 计算了流域的年平均侵蚀模数。结果表明, 妫水河流域的土壤侵蚀以微度和轻度为主, 所占面积比例为74.88% , 极度和剧烈侵蚀很少, 不到总面积的2%。整个流域的年侵蚀模数估计为1 74611/ km ²·a。     

遥感和GIS辅助下的祖厉河流域土壤侵蚀空间变化分析

以遥感数据和观测数据为数据源,基于改进的SEMMED土壤侵蚀模型,对祖厉河流域1999年和2001年土壤侵蚀的空间变换进行了模拟和对比。结果表明,流域土壤侵蚀最严重的区域主要集中在葛家岔站点附近、草滩站附近和北部葛家寨和靖远一带,流域中南部的土壤侵蚀通常小于北部。在北部的屈吴山,以及与宁夏交界的月亮山还有华家岭由于植被覆盖度较高,很好的起到了减少径流,抑制土壤侵蚀的作用。降水的年际差异导致本区的土壤侵蚀年际差异较大。     

基于遥感和GIS技术的土壤侵蚀量估算研究——以澄江太阳山地区为例

土壤侵蚀量的估算是土壤侵蚀研究的核心问题之一。本文以云南省I类淡水湖抚仙湖东岸的太阳山地区为研究对象,在GIS和遥感技术的支持下,利用土壤类型分布图、土地利用、遥感影像、DEM等数据,探讨了侵蚀模型的选择过程,最终利用修正后的通用土壤侵蚀方程(RUSLE),建立各因子的数据库,对该区域近100km2的土壤侵蚀现状和潜在土壤侵蚀量进行模拟估算,并分析了主要的影响因子。     

基于RS与GIS的大尺度水土流失分级制图

以长春市双阳区鹿乡镇为例，选用SPOT5的遥感数据、DWG全要素地形图，运用遥感软件提取植被指数并进行密度分割，确定植被覆盖度；用地理信息系统软件提取地形坡度信息，并对地形坡度进行分级。然后根据植被覆盖度、地形坡度和土地利用类型几个水土流失强度因子，确定水土流失强度的分级指标，生成水土流失等级强度图。为水土流失监测、治理提供依据。
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土壤侵蚀调查中的遥感应用综述

土壤侵蚀引起土壤肥力下降、土地退化及荒漠化和生态环境恶化等一系列区域性和世界性的重大环境问题。中国是土壤侵蚀最严重的国家之一。遥感是进行环境和灾害动态监测的有效技术手段。自从20世纪70年代以来．人们就开始应用遥感技术进行土壤侵蚀的调查。对遥感技术在土壤侵蚀调查中的应用方法进行概括和汇总，分别是影像判读法、指数提取法、图像分类法、光谱分解和正射影像DEM提法等方法，分析不同方法之间的优缺点以及它们各自的适用范围，并结合当前研究的热点问题，指出未来研究的重点及趋势。     

麦田土壤水分NOAA/AVHRR遥感监测方法研究

本文立足于河南省农业遥感业务服务实际,在系统研究麦田土壤水分NOAA/AVHRR遥感监测理论、模型、资料处理、指标及应用技术的基础上,针对这一领域中存在的问题,在GIS技术的支持下,重点探讨了不同土壤质地和风速对遥感干旱监测的影响、用遥感表层土壤水分耦合深层土壤水分的方法与模型、用单时相遥感资料反演土壤水分的方法等,并最终建立了河南省冬小麦干旱遥感监测应用服务系统。     

土壤盐碱化遥感应用研究进展

对近年来国内外遥感监测土壤盐碱化的研究进展作了介绍,并从土壤盐碱化遥感信息特性和影响因素、各种遥感数据源、数据处理方法和研究热点等方面做了总结。土壤盐碱化的遥感方法和传统方法可获取多源的数据,包括来自多平台遥感的光谱数据、地面实测和实验室分析数据、其它研究手段得到的地理相关数据以及历史资料等。在GIS技术支持下的多源数据集成方法可对土壤盐碱化进行定量探测,在土壤盐碱化遥感应用中取得了较好的效果。     

Evaluation of sediment yield by using remote sensing and GIS: A case study from the Phulang Vagu watershed,Nizamabad District (AP), India

The primary objective of this paper is to identify soil erosion zones and to suggest appropriate measures for control of soil erosion using remote sensing, GIS and conventional technique in the Phulang Vagu watershed in the Sriramsagar catchment area of Andhra Pradesh. The digital imagery data of the study area is obtained from the IRS-IC (LISS-III) satellite whereas the toposheets and rainfall data of the study area were obtained from the Survey of India. Satellite images were interpreted to prepare land use/land cover maps by using ERDAS image processing system. Out of 725.983 km 2 of the study area, about 301.435 km 2 is wasteland which is identified as susceptible for soil erosion. Toposheets of the study area were used to prepare drainage and slope maps. Drainage pattern is mainly dendritic with a density of 1.26 km -1 and the stream slope is 0.00614. The arithmetric average method is used to find average annual rainfall. The above parameters were used to calculate the amount of soil erosion from the catchment area. It was found that 882.389 m 3 km -2 year -1 of soil is being eroded from the catchment area which is more than the value adopted in the design of Sriramsagar reservoir. Therefore soil conservation measures such as vegetative cover in the waste land are needed and 12 check dam sites have been proposed by superimposing drainage map and slope map in conjunction with land use/land cover map. With these soil conservation measures, the soil erosion could be kept within the design value of Sriramsagar reservoir.     

应用卫星遥感技术监测生态建设工程

生态建设工程监测的主要目的是了解工程的治理面积和工程质量。对下垫面的动态监测,也就是对实施生态建设工程引起的植被、土壤等改变量的监测,是实现该目的的有效途径。基于3S技术的有机结合和常规手段的辅助,通过一系列遥感数据和实测数据的处理分析,建立了解译标志,完成了对生态建设工程实施前后两年遥感图像的解译,利用地理信息系统矢量化解译的图斑,经统计分析,得到了生态建设工程的治理区域和工程质量数据,为有关生态建设的决策提供了科学依据。另外,还分析了气候条件与生态工程树草成活率的关系。     

微机遥感图像处理系统MRSIPS

MRSIPS是面向遥感应用的遥感图像处理系统与地理信息系统的综合系统,该系统具有二个重要功能:(1)用遥感数据更新 GIS 中的数据,(2)将GIS中的信息和遥感信息进行综合分析,提高分类精度     

A Review on Estimating Fractional Cover of Non-photosynthetic Vegetation by Using Remote Sensing

The quantitative estimation of fractional cover of photosynthetic vegetation(f PV),non-photosynthetic vegetation(f NPV),and bare soil(f BS) is critical for grassland ecosystem carbon storage,vegetation productivity,soil erosion and wildfire monitoring.The ecological importance of NPV has driven considerable research on quantitatively estimating NPV in diverse ecosystems including croplands,forests,grasslands savannah,and shrublands using remote sensing.This paper reviews the research progress in estimating f NPV using hyperspectral and multisspcetral remote sensing data,and hightlights discusses the theoretical bases of PV,NPV and BS spectral characteristics.based on the existing methods for estimating f NPV,this article groupd into two categories:empirical relationship between spectral index and NPV cover,and Spectral mixture analysis.Meanwhile,also discuss applications.of hyperspectral and multisspcetral remote sensing data.Finally,the existential problems and research trends for NPV estimation are analyzed.     

Up-scaling methods based on variability-weighting and simulation for inferring spatial information across scales

Appropriate up-scaling methods to infer spatial information from a finer to a coarser spatial resolution are required when remote sensing and geographical information systems (GIS) are used to generate multi-scale maps that are needed for agriculture, forestry, natural resources, environmental systems, and landscape ecology. The existing methods used in commercial GIS and image analysis packages such as Window Averaging (WA) often do not work well because of different limitations. In this study we developed and compared five widely used WA methods including three spatial variability-weighted methods and two simulation methods. These methods were assessed in a case study for aggregating and using Landsat Thematic Mapper (TM) images for mapping vegetation covers and for inferring a topographical factor related to soil erosion from finer to coarser resolutions. The results showed that the Beta Distribution Simulation (BDS) method was better than WA regardless of the distributions of the spatial data, while the Arithmetic Average Variability-Weighted method (AAVW) performed better than WA for normal distributions. BDS is flexible for variable distributions and AAVW is only suitable for normal distributions. Because of their simplicity, efficiency, and flexibility, it is expected that these two methods can be programmed into commercial GIS and image analysis packages.     

遥感图像多维量化关联规则挖掘

数据与数据库的爆炸式增长引发了一个十分突出的问题,就是如何高效、智能地将海量的数据转化为有用的信息和知识?近年来,数据挖掘技术的广泛研究正是基于这个目的。初步研究了卫星遥感数据的关联规则挖掘及其在土壤侵蚀和退耕还林上的应用。根据多维空间数据的特点,将遥感数据的属性值划分为不同的块。同时为了充分利用现有的关联规则挖掘的算法,还将划分好的数据转变为事务数据库形式。最后,利用Apriori算法提取了土壤侵蚀强度与坡度、植被覆盖度以及坡耕地之间有意义的关联,为退耕还林还草决策提供有益的支持。     

空间信息支持下的江西定南稀土矿区泥石流危险性评价

江西省定南县是我国离子型稀土矿的主要产区。在稀土开采的同时,产生了大量水土流失,诱发的多处泥石流淹没林地和耕地。运用QuickBird高分辨率遥感信息与3D可视化技术相结合对定南矿区开采面、固体废弃物及其造成的泥石流进行解译,根据泥石流分布特点选取危险性评价因子,建立了评价模型,依据预测结果划分了泥石流的危险性空间分布。预测结果得到遥感影像和野外实际调查的检验,模型在赣南离子型稀土矿区有一定的推广意义。     

地理信息系统和遥感结合的现状及发展趋势

地理信息系统和遥感是支撑现代地理学的两大空间技术工具，近年来它们的结合越来越引起了人们的兴趣与研究。文章着重论述了地理信息系统和遥感结合的现状及其发展趋势，包括地理信息系统和遥感结合的内在原因、方式和存在的主要问题，并介绍了加拿大遥感中心在此方面的新的研完成果。     

Probabilistic landslide hazard mapping using GIS and remote sensing data at Boun,Korea

The aim of this study is to evaluate the hazard of landslides at Boun, Korea, using a Geographic Information System (GIS) and remote sensing. Landslide locations were identified in the Boun area from interpretation of aerial photographs and field surveys. The topographic, soil, forest, geologic, lineament and land cover data were collected, processed and constructed into a spatial database using GIS and remote sensing data. The factors that influence landslide occurrence, such as slope, aspect and curvature of the topography, were calculated from the topographic database. Texture, material, drainage and effective soil thickness were extracted from the soil database, and type, age, diameter and density of timber were extracted from the forest database. The lithology was extracted from the geological database and lineaments were detected from Indian Remote Sensing (IRS) satellite images. The land cover was classified based on the Landsat Thematic Mapper (TM) satellite image. Landslide hazard areas were analysed and mapped, using the landslide-occurrence factors, by the probability–likelihood ratio method. The results of the analysis were verified using actual landslide location data. The validation results showed satisfactory agreement between the hazard map and the existing data on landslide locations.     

卫星遥感计划精度的定量分析方法研究

从分析影响卫星遥感计划精度的相关因子入手，应用GIS分析方法研究建立了卫星遥感计划精度分析模型，并利用实验区域数据对分析模型进行了应用验证，应用结果表明该模型可应用于卫星遥感计划精度的定量分析。     

基于遥感的两当河上游生态修复工程监测与分析

生态修复水土保持是一项旨在注重依靠大自然的自我修复能力, 在加强预防保护和开展人工辅助治理的前提下, 在较短的时间内实现大面积水土流失初步治理, 区域生态环境逐步恢复, 最终实现人与自然和谐共处的水土保持措施。两当县位于秦岭以南, 属嘉陵江水系, 该县为长江上游实施水土保持生态修复8 个试点县之一。位于该县北部的研究区总面积327. 26 km ², 是水土流失的主要区域, 2001 至2003 实施生态修复工程。为配合项目区评估利用遥感(RS) 和全球定位系统(GPS) 技术对试验区进行监测与分析。通过项目开始(2001) 和两年后(2003) 的遥感监测、对比分析和结合参考常规观测资料, 对试验区生态环境类型的变化状况和退耕还林还草, 坡改梯田和集水灌溉等辅助措施在生态修复中的作用进行评估。研究结果表明自生态修复工程实施后植被状况有明显变化, 植被覆盖率从86. 50% 增加到98. 04% , 增长11. 54% , 说明研究区生态与环境向逆转方向发展。在实践应用当中, 较高分辨率的卫星资料(TM , SPOT 4, SPOT 5) 可以用于生态修复工程的遥感监测和工程执行的效果评价。     

A patch‐based image classification by integrating hyperspectral data with GIS

Hyperspectral remote sensing data provide detailed spectral information and are widely used for pixel‐based image classification. However, without considering spatial correlation among neighbouring pixels, a generated thematic map may have a ‘salt‐and‐pepper’ appearance. With the development of the Geographic Information System (GIS), the spatial relationship between a pixel and its neighbours can be recorded readily and used together with remote sensing data. The objective of this study was to integrate hyperspectral data with the GIS for effective thematic mapping. To date, GIS data have been used mainly in field surveys or training field selection for remote sensing data interpretation. Here we propose a patch‐classification based on integration of the GIS with remote sensing data. The classification results obtained by using this method can be easily saved in a vector format as used for GIS files. Computational cost is decreased compared with a pixel‐by‐pixel classification. The issue of how to identify pure or mixed patches is addressed and a three‐level simple and effective checking method is developed. A case study is presented with a hyperspectral data set recorded by the Pushbroom Hyperspectral Imager (PHI) and related GIS data.