利用单窗算法反演Landsat 8 TIRS数据地表温度

以Landsat 8为数据源,并结合地表发射率、大气透过率等参数遥感估算方法,提出了针对TIRS 10数据的单窗算法TIRS10_SC,并开展了研究区的地表温度反演3种单窗算法的对比研究。结果表明,TIRS10_SC算法紧密结合Landsat8 TIRS传感器的特性,通过遥感估算城区下垫面的地表发射率、大气透过率等特征,可以较为准确地估算出地表不同覆被类型的温度;裸土与水泥下垫面等相对均质的下垫面的温度反演效果稍好,TIRS10_SC算法和Q_SC算法其平均误差为0.60℃,JM_SC算法其平均误差为1.01℃;对于植被下垫面,TIRS10_SC算法和Q_SC算法其平均误差为1.48℃,JM_SC算法其平均误差为1.26℃,为了提升城区植被下垫面温度反演精度,应该进一步准确地量化其发射率特性。     

利用ASTER GDEM提取瓯江流域水系及精度评价

采用Arc Hydro Tools软件以及GIS空间分析功能,以浙江省瓯江流域为例,基于ASTER GDEM开展水系自动提取研究,并分河流等级、分地貌、多指标地评价水系精度,探索1∶25万水系自动更新的可行性.     

基于ASTER影像的蚀变异常提取方法研究——以赞比亚谦比希铜矿床地区为例

基于赞比亚谦比希(Chambishi)铜矿带中的多种蚀变矿物及其在ASTER影像VNIR - SWIR谱带的特征光谱分析,采用相对波段吸收深度(Relative absorption- Band Depth,RBD)和波段比值的方法对蚀变信息进行增强处理.用波段比值ASTER 2/ASTER 1和ASTER 3的RBD...     

A Case Study on Forewarning of Yellow Rust Affected Areas on Wheat Crop Using Satellite Data

Objective of this study was to identify stripe rust affected areas of wheat crop as well as evaluation of remote sensing (RS) derived indices. Moderately low temperature and high humidity favour the growth of yellow rust. Most affected areas of Punjab are the foothill districts such as Gurdaspur, Hoshiarpur and Ropar. Occurrence of yellow rust is possible when maximum temperature for day is below 15 °C and Temperature difference of day’s maximum and minimum temperature is less than 5 °C during the early growth of wheat. Forecast of the infestation was done using 3 days forecast of weather data obtained from Weather Research and Forecasting (WRF) model at 5 km resolution. Weather forecast used was obtained from Meteorological and Oceanographic Satellite Data Archival System (MOSDAC) site and post infestation, identification of specific locations were done using multi-date IRS AWiFS data. It is an attempt for early detection through 3 days advance forewarning of weather which will be handy tool for planners to expedite relief measures in case of epidemic with a more focused zones of infestation as well as for crop insurers to know the location and extent of damage affected areas.     

Mapping Wetland Areas Using Landsat-Derived NDVI and LSWI: A Case Study of West Songnen Plain,Northeast China

Increasing interest in wetlands for environmental management requires an understanding of the location, spatial extent, and configuration of the resource. The National Wetlands Inventory is the most commonly used data source for this information. However, its accuracy is limited in some contexts, such as agricultural and forested wetlands. An large number of studies have mapped wetlands worldwide from the perspective of land use and land cover change. However, information on the actual wetland planting areas annually is limited, which greatly impacts ongoing research. In this case study of the West Songnen Plain, we developed a simple algorithm for the quick mapping of wetlands by utilizing their unique physical features, such as annual display of phenological land-cover change of exposed soils, shallow flooding water, and plants from multi-temporal Landsat images. Temporal variations of the Normalized Difference Vegetation Index (NDVI) and Land Surface Water Index (LSWI) derived from Landsat images in 2010 for wetlands at different growth stages were analyzed. Results show that during the ante-tillering phase, the NDVI value (above zero) is lower than the LSWI value of paddies because of flooding of shallow water; during the reproductive and ripening phases, the NDVI value is higher than the LSWI value (above zero); and during the post-harvest wetland planting phase, the NDVI value is still higher than the LSWI value, but the LSWI value is negative. Wetland areas can be detected using one or two images in the optimum time window. The algorithm based on the difference of NDVI and LSWI values derived from Landsat images was used to extract the actual wetland planting area. Validated alongside statistical data, the algorithm showed high accuracy. Therefore, this algorithm highlights the unique features of wetlands and can help in mapping the actual wetland area annually on a regional scale. Results further indicate that the new method has a classification accuracy of 92 %. In comparison, two traditional methods based on Landsat-7/ETM registered accuracy rates of only 83 % and 87 % respectively.     

ASTER数据在北方铝土矿预普查中的应用——以豫西渑池地区为例

ASTER数据的光谱和空间分辨率均具有一定优势,适合于中等比例尺的矿产预普查。为了探讨ASTER数据应用于铝土矿预普查的效果,通过对ASTER图像彩色合成、地质解译及异常信息提取,对豫西渑池地区的铝土矿进行了预普查试验。结果表明,在北方基岩裸露地区,应用ASTER数据圈定"赋矿影像单元"和提取铝土矿遥感找矿信息能获得较好的效果。     

基于矿物光谱指数的蚀变信息提取——以西藏多龙铜金矿集区ASTER数据为例

矿物光谱指数是利用比值的方法增强Fe和含OH矿物在可见光、短波红外区间的吸收特征,进而提取蚀变矿物信息的一种方法。由于斑岩型矿床的蚀变分带特征明显,西藏多龙矿集区中集中了斑岩型、浅成低温热液型等铜、金矿床,通过矿物光谱指数的计算提取相关蚀变信息,对该区域的下一步找矿具有指导意义。本文采用矿物光谱指数(5+7)/6、(6+9)/8等方法提取了镁、铝两类羟基及铝羟基类下的高岭石等蚀变信息,采用5/4、2/1的方法提取了二价铁、三价铁的蚀变信息。经过与OLI影像采用PCA方法及野外实地勘查采样,证实了利用本文方法所提取的蚀变信息有效。     

基于ASTER数据的蚀变矿物信息提取——以哈密黄山铜镍矿区为例

在分析哈密黄山铜镍矿区典型地物波谱特征的基础上,设计了基于ASTER数据的蚀变信息提取流程,详细论述了对4组含不同离子或基团的常见蚀变矿物应用主成分分析(PCA)进行蚀变信息提取、采用光谱角制图法(spectral angle mapper,SAM)进行干扰异常筛选的“SAM去干扰异常主分量门限技术”.4组(9种)蚀变矿物包括:含Fe离子的矿物(针铁矿、赤铁矿)、含CO23-基团的矿物(方解石、白云石)、含Al - OH基团的矿物(白云母、蒙脱石、高岭石)以及含Mg - OH基团的矿物(绿泥石、绿帘石).蚀变矿物信息提取结果表明,“SAM去干扰异常主分量门限技术”方法可行,对ASTER数据的应用效果与实际情况比较吻合,充分证明ASTER在短波红外范围内具有很强的矿物刻画能力.     

Using GIS in Areawide Pest Management: A Case Study in South Dakota

Infestations of corn rootworms (Coleoptera: Chrysomelidae) create economic and environmental concerns in the Corn Belt region of the United States. To supplement the population control tactics of areawide pest management programs, we believe that a better understanding of the spatial relationships between biotic and abiotic or physical factors at the landscape scale is needed. Our research used several geographical information systems (GIS) and spatial analytical techniques to examine relationships between corn rootworm metapopulation dynamics, soil texture, and elevation. Within GIS, several spatially explicit procedures were used that include an interpolation technique, spatial autocorrelation analysis, and contingency analysis. Corn rootworm metapopulation distributions were found to be aggregated and related to soil texture and elevation. We review techniques and discuss our preferences for using particular spatially explicit procedures. The information derived from the spatial analyses demonstrates how GIS can be used in areawide pest management to provide inputs for spatially explicit models to predict future pest populations and formulate more well‐informed pest management decisions. The techniques described in this paper could easily be extended to study the spatial dynamics between other pest populations in agricultural landscapes.     

农牧交错带湿地信息提取技术研究——以多伦县大仓乡为例

农牧交错地带地类复杂,混合像元现象严重,湿地信息的自动提取难度较大.针对该区湿地遥感信息提取的特点和难点,选取多伦县大仓乡地区的TM遥感数据,先采用NDVI阈值提取出水体,并利用水体形状特征(如面积s、周长p、形状指数k等)对水体类型进行提取;再尝试应用线性光谱混合模型( LSMM)提取去除水体后的湿地信息,并以SPO...     

LIDAR Validation Using GIS: A Case Study Comparison between Two LIDAR Collection Methods

Abstract

In the summer of 2000, the Annapolis Valley of Nova Scotia, Canada was selected for a high‐resolution elevation survey utilizing LIDAR (Light Detection And Ranging). Two different LIDAR systems were used to acquire data for the area. The vertical accuracy specification for the survey called for heights to be within an average of 15 cm of measured GPS heights and 95% of the data to be within 30 cm. Prior to the application of these data to geoscientific problems, extensive validation procedures were employed. High precision GPS and traditional surveys were conducted to collect height validation checkpoints. Two validation methods were developed in a GIS environment that involved comparing the checkpoints to the original LIDAR points and to an interpolated “bald earth” DEM. A systematic height error between flight lines for one of the LIDAR methods was detected that related to the calibration procedures used in the survey. This study highlights the differences between laser systems, calibration and deployment methodologies and emphasizes the necessity for independent validation data.     

Terrain Characterization for Soil Resource Mapping Using IRS-P6 Data and GIS - A Case Study From Basaltic Terrain of Central India

In the present study, landforms and soils have been characterized in Borgaon Manju watershed of basaltic terrain located in Akola district, Maharashtra, Central India. Terrain characterization using Shuttle Radar Topography Mission (SRTM) elevation data (90 m) and IRS-P6 LISS IV data in conjunction with adequate field surveys shows nine distinct landforms. Soil resource inventory shows fourteen soil series in the study area. Soils formed on gently sloping (3–8 %) subdued plateau are very shallow (23 cm), moderately well drained, moderate (15–40 %) surface stoniness, severely eroded, clayey and slightly alkaline in reaction, whereas, the soils formed on level to nearly level (0–1 %) slope in the main valley are very deep (>150 cm), well drained, very slight (<3 %) surface stoniness, moderately eroded with clayey surface and moderately alkaline in reaction. Soils in the watershed are grouped into Lithic Ustorthents, Vertic Haplustepts, Calcic Haplustepts, Typic Haplustepts, Typic Haplusterts and Sodic Calciusterts. The study demonstrates that the analysis of SRTM elevation data and IRS P6–IV data in Geographic Information System (GIS) with adequate field surveys helps in characterization of landforms and soils in analysis of landscape-soil relationship.     

基于GIS的湖南农业大学土地利用景观格局变化分析

以湖南农业大学为研究区,对2005年和2010年的遥感影像进行土地利用景观分类,选取并计算具有代表性的景观指数,结合GIS的空间分析技术,从景观的总体和单元特征、空间构型和景观异质性等方面对景观变化情况进行分析。结果表明,经过五年的建设,研究区大量其他景观转变为绿地景观、道路景观、生活设施景观、娱乐场地景观及教学设施景观。尽管土地利用程度加大,但景观格局日趋合理,功能分区进一步明确,且生态环境得到较好的保护。     

应用ASTER数据提取矽卡岩型锡矿蚀变遥感异常信息——以滇东南马关都龙锡矿为例

运用多光谱遥感数据进行矿化蚀变信息提取,对圈定找矿预测区具有重要意义.采用ASTER数据及其矿化蚀变信息提取原理,对滇东南马关都龙锡矿含矿岩体分布区分别提取了方解石化、白云岩化、绿泥石化等3类蚀变遥感异常信息.所提取的蚀变异常与野外调查发现的矿化点吻合性好,蚀变信息可靠,对指导找矿有较好的效果,为该地区矿产资源潜力评价...     

高度城市化地区土地利用变化分析及效益评价——以深圳市为例

为研究全国第二次土地调查以后高度城市化地区的土地利用变化及效益,本文以深圳市为例,利用其2009—2014年土地变更调查数据,从土地利用结构、土地利用程度、土地利用空间格局以及动态度等多个方面进行分析,并通过熵值法从社会、经济、生态和环境4个角度选取23个指标评估深圳市的土地利用效益及各效益的调度发展状况。研究结果表明:1)深圳市土地利用率已达93%,建设用地率达48.49%,土地综合利用程度逐年提高,土地利用空间格局趋向单一,各指数年变化率均逐渐降低;2)社会效益、经济效益和环境效益提高,生态效益降低,综合效益逐年提高;3)各分项效益子系统从基本协调上升到高度协调。深圳市的土地利用变化分析及效益评价,为深圳市的土地利用总体规划及可持续土地利用提供了一定的参考依据,并对其他高度城市化地区的土地利用具有借鉴价值。     

基于POI数据的广场功能研究——以兰州市城关区为例

基于ArcGIS中的网络分析法,选取兰州市城关区东方红广场、五泉下广场和万达广场构建沿不同等级交通线的1 min、1.5 min、3 min 3个缓冲区圈层,同时统计不同缓冲区内居住设施、公共管理与公共服务设施和商业设施三大类兴趣点(point of interest,POI)数据的数量与占比.结果显示,东方红广场的交...     

基于DEM的6种坡度提取算法的比较分析——以山东省青岛市为例

坡度是描述地形特征信息的一个重要指标,对于制订土地利用规划和防御地质灾害具有重要意义。本文基于山东省青岛市的ASTER GDEM数据,利用MATLAB进行矩阵运算,采用6种坡度提取算法分别获取坡度矩阵、最大值和中误差等统计指标,对比分析6种算法的提取精度。结果表明:简单差分算法出现极端和偏差情况的概率较高,可信度不高;三阶不带权差分和三阶反距离平方权差分算法比较稳定,偏差较小且精度较高,对沿海地区坡度提取具有借鉴意义。     

高分辨率遥感影像中的土地利用分类研究——以西南大学为例

大学校园是城市用地中的一个特殊群体,作为公共设施用地的一个重要部分,在城市土地利用日益紧张的条件下,对其进行土地利用分类研究有着重要的意义.本研究以西南大学为例,将最大似然监督分类法和决策树分类法相结合对其进行分类研究.研究表明:1)最大似然监督分类法和决策树法相结合对西南大学土地利用进行分类,取得了较好的效果,总分类精度达到了91.51%,Kappa系数达到了0.8831;2)分析出西南大学建筑分布特点:①校园内部建筑物趋于密集布局,提高了土地利用效率;②校园建筑物高层化,提高了建筑容积率.     

基于时间序列InSAR分析的西部山区滑坡灾害隐患早期识别——以四川丹巴为例

滑坡是仅次于地震、发生最频繁、造成损失最严重的一种地质灾害,中国西部山区则是世界上滑坡灾害分布最密集的地区之一。广域范围内滑坡灾害隐患的早期识别是地质灾害防治工作中的一项关键任务,基于星载合成孔径雷达重复轨道观测的时间序列雷达干涉测量（interferometric synthetic aperture radar,InSAR）技术在此领域具有巨大的应用潜力,但以永久散射体干涉测量为代表的传统时序InSAR方法在西部山区应用中往往受到植被覆盖等不利因素的影响,滑坡探测识别的可靠性较差。针对这一问题,以大渡河上游丹巴县为例,采用自主研发的相干散射体时序InSAR（coherent scatterer InSAR,CSI）方法,从历史存档的ALOS PALSAR和ENVISAT ASAR数据集中成功识别出了17处持续变形中的不稳定坡体,通过与外部观测数据比对和实地调查核实等手段验证了CSI方法探测结果的有效性和优势,并探讨了影响时序InSAR方法滑坡监测应用效果的主要因素及未来的优先研究方向。