高寒干旱地区环境遥感信息提取方法研究

根据高寒干旱地区环境研究的特点,研究了适合于遥感信息提取的区域环境综合分类系统,提出了利用现有成熟的图像分类和专题信息提取的技术方法,在ＧＩＳ的支持下实现了多种遥感信息与非遥感信息的复合。利用多重判据在ＧＩＳ环境下,通过基于知识的识别和修改,对初分类结果中相混淆异类进行了有效分离,达到类型纯化     

Seasonal vegetation cover changes as indicators of soil types along a climatological gradient: a mutual study of environmental patterns and controls using remote sensing

A remote sensing analysis of the temporal changes of vegetation cover in the arid and semi-arid regions of the Judean Desert and Judean Mountains was carried out in order to reveal the controlling factor of the environmental system. Assessment of ditTerent combinations of temperal changes in the region using GIS techniques indicated that it is possible to differentiate between two major patterns of vegetation cover change. The classification of the region according to these patterns has produced a map that is highly correlated to the soil map of the region, thus suggesting that the soil is an important environmental controlling factor in the region. From the remote sensing point of view, the patterns of vegetation cover change may serve as indicators of soil types in similar arid and semi-arid environments.     

Estimation of forest Leaf Area Index using remote sensing and GIS data for modelling net primary production

Ecosystem models can be used to estimate potential net primary production (pNPP) using GIS data, and remote sensing input of actual forest leaf area to such models can provide estimates of current actual net primary production (aNPP) . Comparisons of pNPP and aNPP for a given site or regional landscape can be used to identify forest stands for different management treatments, and may provide new information on wildlife habitat, forest diversity and growth characteristics. Leaf area estimates may be obtained from satellite imagery through correlation with physiologically-based vegetation indices such as the Normalized Difference Vegetation Index (NDVI). However, in areas with high Leaf Area Index (LAI), vegetation indices usually saturate at leaf areas greater than about 4. In predominantly deciduous (hardwood) and mixedwood stands remote sensing estimates may be influenced by understory and other factors. We examined digital Landsat TM imagery and GIS data in the Fundy Model Forest of southeastern New Brunswick to determine relations to forest leaf area index within different stand structures or covertypes. The image data were stratified using GIS covertype information prior to development of LAI predictive equations using spectral reflectance, and the prediction of LAI from Landsat TM imagery was improved with reference to estimates of stem density which are standard forest inventory information contained in GIS databases. Actual stand LAI was compared to assumed maximum LAI values for several species and sites using an ecosystem process model (BIOME-BGC) which relies on climate, soils and topographic information also obtained from the GIS. Subsequent comparison of pNPP and aNPP revealed that even disturbed sites in this environment can reach close to maximum site potential. Specific sites with suboptimal species composition were identified. A future refinement of this approach is to classify the imagery independently of the GIS, which assumes a homogeneous covertype for each polygon in the system, and thus improve still further the aNPP estimates through higher covertype and LAI estimation accuracy.     

基于QuickBird影像的滩涂资源监测研究

利用QuickBird卫星遥感影像结合水下地形图对上海市宝山区长兴岛滩涂资源进行了监测，并将遥感(RS)及地理信息系统(GIS)技术结合起来作为监测手段来计算和分析冲淤演变过程，这一方法的先进性、科学性，计算的精确性和结果显示的直观性，都是以往传统方法所无法比拟的。同时，还利用植被的光谱特性结合专家系统知识，运用遥感图像处理软件ERDAS8．5，采取监督分类方法对滩涂植被覆盖情况进行了分析，为更好地规划和利用滩涂资源提供了新的方法和思路。     

L波段多角度微波植被指数研究

植被指数是卫星遥感领域中用来表征地表植被覆盖,生长状况的一个简单有效的度量参数。通常由于植被光谱受到植被本身、环境条件、大气状况等多种因素的影响,植被指数往往具有明显的区域性和时效性。微波遥感具有全天时、全天候的工作能力,利用被动微波遥感观测数据建立植被指数,将能够弥补现有植被指数的局限性。2009年发射的土壤水分和海洋盐度(SMOS)卫星首次采用L波段多角度微波观测。通过双极化多角度微波辐射信号组合,可以最小化地表辐射的影响,从而发展了仅与植被参数有关的微波植被指数。这种方法为SMOS监测全球植被信息提供新的机会。     

水源保护区划界的遥感与GIS技术研究

科学合理地划定水源地的保护范围是一项技术含量较高的工作。以厦门市饮用水源中的北溪引水渠(管道)和坂头水库为例,根据饮用水源保护区划分原则,研究基于数字化的地形图建立数字高程模型并自动生成汇水区盆地和流域范围的GIS技术、获取相关自然环境专题信息的遥感技术、以及综合利用社会和自然等多种数据源进行保护区范围界定的方法。重点探讨数字高程模型的建立以及汇水区盆地和流域边界自动生成的GIS方法。     

矿产违法开采信息的快速提取

采用HIS彩色变换并利用遥感数据提取矿区变化区域,将变化区域与土地利用现状矢量数据和采矿权登记矢量数据相叠加,利用地理信息系统快速提取叠加分析功能剔除干扰区域,实现违法采矿信息的自动提取。该方法充分利用遥感数据和矢量数据,避免了单独使用遥感影像数据时必须进行人工监督分类的繁琐操作,其提取违法信息的速度快、费用低廉,有利于及时发现并制止矿产违法开采行为。     

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     

Strategic environmental assessment as an approach to assess waste management systems. Experiences from an Austrian case study

Waste management has evolved from the simple transportation of waste to landfills to complex systems, including waste prevention and waste recycling as well as several waste treatment and landfill technologies. To assess the environmental, economical and social effects of waste management systems, several tools have been developed. Strategic Environmental Assessment (SEA) is an approach for integrated assessment enhancing involvement in the planning of a decision supporting process. The aim of this paper is to show how SEA can be applied in a waste management context. For this purpose a case study is described where a SEA process was undertaken to develop a regional waste management plan. The approach from this case study is compared to other methods.     

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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基于遥感GIS信息融合的测绘机器人滑动模跟踪控制系统

测绘机器人是实现测绘自动化的执行设备,测绘机器人的工作空间更为复杂,给机器人的跟踪控制工作带来较大挑战。为提高测绘机器人跟踪控制效果,设计了基于遥感GIS信息融合的测绘机器人滑动模跟踪控制系统。加设遥感信息采集器和GIS信息采集器,改装遥感GIS信息处理器以及滑动模跟踪控制器,完成硬件系统的优化设计。考虑信息结构以及信息之间的逻辑关系,构建系统数据库,为遥感GIS信息提供充足的存储空间。根据测绘任务生成机器人滑动模移动轨迹,作为机器人的控制目标。采集测绘机器人实时遥感与GIS信息,利用遥感GIS信息融合技术跟踪机器人实时位姿,比对位姿跟踪结果与生成的控制目标,计算滑动模跟踪控制量,完成系统的测绘机器人滑动模跟踪控制软件功能优化。系统测试结果表明:设计系统的控制误差平均值为1.9 m,抖振幅值为0.8 dB,具有较好的控制效果。     

浅析遥感光谱特征参量的原理及基本方法

概述了导数光谱、红边参数、光谱吸收特征以及光谱反射特征等遥感光谱特征参量的原理及基本方法,总结和分析了这些参量在植被领域中的应用动态,提出了遥感技术存在的问题及其应用展望,遥感光谱特征参量能够为植被理化信息的提取提供强有力的工具。     

Integrated use of satellite remote sensing,GIS, and ground spectroscopy techniques for monitoring olive oil mill waste disposal areas on the island of Crete,Greece

Olive oil mill wastes (OOMW) constitute a major pollution factor in olive-growing regions and an important problem to be solved for the agricultural industry. Olive oil mill wastes are normally deposited in tanks, or directly into the soil or even on adjacent torrents, rivers, and lakes, posing a high risk of environmental pollution in regard to public health. This study aims to develop integrated satellite remote sensing, geographical information systems (GIS), and ground spectroscopy methodologies to detect and monitor OOMW disposal areas on the island of Crete, Greece in the Southeastern Mediterranean. More than 1000 disposal tanks were mapped through an extended global positioning system (GPS) survey that took place throughout the island. Satellite images of both high (IKONOS) and medium (Landsat 8 OLI (Operational Land Imager)) resolution were preprocessed and analysed by applying geometric, radiometric, and atmospheric corrections. A library with a spectral signature of OOMW including both different time periods and satellite sensors was developed. At the same time, ground spectroscopy campaigns were carried out and a complementary spectral signature library was developed. The narrow band reflectance of ground measurements was recalculated using the relative response filters of the corresponding satellite sensors. Both libraries were compared for their accuracy through statistical approaches and the optimum spectral range for detecting OOMW areas was estimated. Subsequently, further auxiliary image-processing techniques such as image fusion, linear spectral unmixing (LSU), false-colour composites (FCCs), image classification, and principal component analysis (PCA) were applied to satellite images to enhance OOMW patterns, and an innovative OOMW detection index for Landsat 8 was developed. In addition, several vegetation indices were applied and compared in regard to their efficiency in detecting waste ponds. Finally an integrated, semi-automatic methodology was developed in the GIS environment employing classification algorithms for the detection of waste ponds. This study highlights the potential of satellite remote sensing, GIS, and ground spectroscopy in the semi–automatic detection of OOMW disposal areas in the context of the Mediterranean landscape.     

基于RS与GIS的夏尔希里自然保护区植被NPP估测研究

以植被净第一性生产力NPP遥感估测为研究内容,以地学和生态学知识为基础,利用RS、GIS 技术手段,综合遥感光谱数据、DEM数据、统计数据、定位点的实测数据等多源信息,构建了 NPP 遥感地形模型,计算出夏尔希里自然保护区7 月份的植被 NPP。最终完成夏尔希里自然保护区植被生产力的定量化。     

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。     

Remote sensing and GIS for detecting changes in the aquatic vegetation of a rehabilitated lake

Remote sensing and geographical information system (GIS) methods combined with ground estimations were used to assess the effects of rehabilitation on the aquatic vegetation of a shallow, eutrophic lake in Finland. Aerial photograph interpretation was used to study the distribution of aquatic vegetation before (1953, 1996) and after (2001) rehabilitation in 1997. A digital elevation model was derived to relate the change in the aquatic vegetation to water depth. In addition, changes in the biomass of the most abundant species of the lake, Common Club-rush (Schoenoplectus lacustris), were studied by means of a regression analysis relating the ground estimations to the reflectance values (R ²=0.889, p@lt;0.001). The results indicated that the objective of the rehabilitation--to stop the overgrowth process--has at least temporarily been achieved. After rehabilitation the most noticeable change had taken place in the area covered by floating-leaved vegetation. Greater proportional changes in the aquatic vegetation areas had occurred in the deep rather than in the shallow areas. A decrease in biomass of Common Club-rush was estimated to be 30% due to rehabilitation. The use of remote sensing and GIS provided valuable information on temporal and spatial changes in the aquatic vegetation, and the methods could be applied more extensively for lake monitoring purposes.     

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。     

黑岱沟煤矿生态修复遥感监测及效果评价

随着社会经济的发展,对煤碳的过度掘取,导致的生态环境问题日益突出,因此对煤矿开采区进行生态修复就变得越来越重要。矿区生态修复的关键是植被恢复,以黑岱沟煤矿为研究区,进行植被修复监测和效果评价。选择1999~2011年6~10月的Landsat遥感影像数据,采用遥感与GIS相结合的技术手段,绘制了1999~2011年的典型地物类型解译图,进行了数据分析。结果表明:黑岱沟煤矿区排土场的总面积逐年增加,即煤矿开采的力度逐年加大;植被修复区的面积逐年增加,表明黑岱沟煤矿区生态修复的范围增大力度加强。     

全球典型植被叶片光谱特征及其对LAI反演的影响分析

在全球范围长时间序列LAI遥感产品反演算法中,植被冠层反射率模型仅使用少量叶片光谱特征代表全球植被全年的典型植被光谱特征,叶片光谱的不确定性导致LAI遥感产品存在一定的误差。目前全球已经构建了多个典型植被叶片波谱数据集,这些数据集包含多个植被物种、不同空间地域及多时相叶片光谱数据,为定量分析叶片光谱特征提供了数据支持。主要利用LOPEX’93、ANGERS’03、中国典型地物波谱数据库和野外实测的叶片光谱数据,以黄边参数、红边参数和叶片光谱指数作为分析指标,探讨不同植被物种、不同气候区和不同物候期的叶片光谱特征差异,及其对植被冠层反射率、LAI反演的影响,为发展考虑现实叶片光谱差异的LAI反演算法提供研究基础。结果表明:植被叶片光谱存在多样性,叶片光谱特征差异主要影响MODIS传感器近红外波段和绿波段反射率值,其中,绿波段反射率值对叶片光谱变化最为敏感;在LAI反演算法中,如果只考虑植被类型而不考虑物种叶片光谱差异,可能会给LAI反演带来大于3的误差。