被动微波土壤水分反演模型研究

在分析现有地表辐射模型的基础上,分析了被动微波遥感的辐射传输方程,并且对辐射传输过程的主要因素进行了分析.最后对地面辐射进行了介绍,并针对被动微波AMSR数据提出了地表土壤水分反演的模型.     

利用主被动微波遥感结合反演土壤水分的理论模型分析

为了更好地进行土壤水分反演,发展了一种基于热带降雨观测计划(TRMM)的主被动微波结合反演裸露地表土壤水分的算法.为了提高反演精度,同时利用TRMM搭载的测雨雷达(PR)和微波成像仪(TMI)进行观测.另外,针对PR/TMI数据,还建立了包含大范围的土壤水分和粗糙度参数的AIEM模型数据库.通过分析AIEM模型对地表后...     

Improved Understanding of Soil Surface Roughness Parameterization for L-Band Passive Microwave Soil Moisture Retrieval

Surface roughness parameterization plays an important role in soil moisture retrieval from passive microwave observations. This letter investigates the parameterization of surface roughness in the retrieval algorithm adopted by the Soil Moisture and Ocean Salinity mission, making use of experimental airborne and ground data from the National Airborne Field Experiment held in Australia in 2005. The surface roughness parameter is retrieved from high-resolution (60 m) airborne data in different soil moisture conditions, using the ground soil moisture as input of the model. The effect of surface roughness on the emitted signal is found to change with the soil moisture conditions with a law different from that proposed in previous studies. The magnitude of this change is found to be related to soil textural properties: in clay soils, the effect of surface roughness is higher in intermediate wetness conditions (0.2–0.3 v/v) and decreases on both the dry and wet ends. Consequently, this letter calls for a rethink of surface roughness parameterization in microwave emission modeling.      

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.     

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.     

Hydromorphogeological Mapping for Groundwater Prospecting Using Landsat-MSS Images — A Case Study of Part of Dhanbad District,Bihar

The Dhanbad district in Bihar, feces acate water scareity and is chronically drought prone. The groundwater resources in the area have not been fully exploited. The present study was undertaken to evaluate the groundwater prospective zones, Landsat-5 MSS data of band-2 and band-4 and false colour composite of band 2, 3, 4 were interpreted visually to differentiate different hydromarphogeological units and to delineate the major trends of lineaments. The different geomorphic features identified are linear ridges, residual hills, pediplain, buried pedtment and dissected pediplain, besides lineaments. The study shows that the pediplain and buried pediments are promising zones for groundwater prospecting.     

Monitoring the Grassland Change in the Qinghai-Tibetan Plateau: A Case Study on Aba County

Located on the southeast edge of the Qinghai-Tibetan plateau, Aba County is the core area of the Returning Grazing Land to Grassland Project (RGLGP) on the plateau. For the purpose of monitoring the grassland change before and after the grassland protection project in Aba County, Landsat images acquired in 1996, 2003 and 2009 were analyzed. Using Spectral Mixture Analysis (SMA) model, sub-pixel fractions of land cover components were obtained: bright vegetation (BV), dark vegetation (DV), bright soil (BS), dark soil (DS) and water. Fraction images present the distribution and proportions of typical land cover components in this study. Fractions BV and BS were chosen as two indicators for grassland degradation. Thereafter, Change Vector Analysis (CVA) model was applied on the two indicators. After the performance of the CVA model, change results which consisted of both grassland degradation and vegetation re-growth were obtained, showing the change patterns of grassland degradation and vegetation re-growing in Aba County between two gaps: from 1996 to 2003 (before the RGLGP) and from 2003 to 2009 (after the RGLGP). The change patterns of grassland degradation and vegetation re-growing can effectively assist in the development of environmental restoration measures and in the RGLGP plans for the Qinghai-Tibetan plateau.     

Introduction to the Special Issue on Airborne Field Campaigns for Soil Moisture

The 52 papers in this special issue make use of airborne and/or ground data to deal with questions such as: 1) the estimation of effective soil temperature and vegetation water content from remote sensing data; 2) the impact of physical parameters such as soil texture, topography, vegetation type. and surface roughness on surface soil moisture retrieval; 3) the transferability of current retrieval equations across scales ranging from tens of kilometers; and 4) issues related to downscaling of low-resolution passive-microwave observations of surface soil moisture.     

测绘资料数字档案馆建设——以北京市为例

本文完整阐述了测绘资料数字档案馆的建设方法及过程。介绍了测绘资料数字档案的内容并分析了其特点,确定了测绘资料数字档案馆建设的主要工作:明确了标准规范建设的主要工作内容,描述了馆藏资料档案扫描和整理的流程和质量控制方法,提出了三库分离的档案数据库物理设计思想和逻辑关系。在北京市进行了典型开发和应用实践,并对该项目进行了总结分析,指出了档案信息化是今后档案工作的重点。     

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.     

Using Building Permits to Monitor Disaster Recovery: A Spatio-Temporal Case Study of Coastal Mississippi Following Hurricane Katrina

The pace of disaster recovery varies considerably from one place to another. Even when places suffer impacts from the same event, recovery studies often lack the spatial and temporal resolution to fully understand such local variability in the recovery process and patterns. This paper discusses the novel use of building permits and a spatial scan statistic to identify the spatial and temporal dimensions of recovery in coastal Mississippi following Hurricane Katrina. Our work identifies significant space-time clusters of recovery activity and indicates that the amount of damage experienced and the amount of pre-event housing strongly influence the timing and location of building permit clusters. This analytical method and the use of publicly available data are valuable for a better understanding of long-term recovery processes.     

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.     

基于遥感和GIS的辅助规划模型--以珠江三角洲可持续土地开发为例

提出利用遥感和 Ｇ Ｉ Ｓ来获得合理的城市发展布局和减少浪费土地资源的新方法。该模型是根据环境经济学资源分配原理和可持续发展理论,通过遥感和 Ｇ Ｉ Ｓ的结合来实现。模型的核心就是保证在时间和空间上合理地安排土地资源。由此评价了珠江三角洲东莞市近年来的土地开发,获得了有意义的结果。并通过模型的运算,给出了规划期内的土地利用的优化方案,以减少浪费土地资源的现象。     

Using Spatially Explicit Simulated Data to Analyze Animal Interactions: A Case Study with Brown Hyenas in Northern Botswana

New developments in global positioning systems (GPS) and related satellite tracking technologies have facilitated the collection of highly accurate data on moving objects, far surpassing the ability to analyze them. Within geographic information science, ‘movement pattern analysis’ (MPA) has developed as a subfield that addresses concepts and theories used to explore the spatio‐temporal structure in data, although the methodological and analytical framework associated with MPA is new and still evolving. Interactions between individuals can be considered a second order property of movement and have been far less studied. The nature of interactions between individuals in a population is a fundamental aspect of a species' behavioral ecology and information on the frequency and duration of these interactions is vital to understanding mating and territorial behavior, resource use, and infectious disease epidemiology. The focus of this work was to explore how spatially explicit simulated data can be used to analyse dynamic interactions between individuals. Five different techniques that have been used to quantify dynamic interactions based on GPS data of pairs of individuals were utilised, and all were compared in the context of spatially explicit simulated data intended to represent biologically realistic null models for individual movement, and subsequently paired interactions.     

Classification of Satellite Images in Assessing Urban Land Use Change Using Scale Optimization in Object-Oriented Processes (A Case Study: Ardabil City,Iran)

By using satellite imagery, the recognition and evaluation of various phenomena and extraction of information necessary for the planning of land resources or other purposes are easily accomplished. The purpose of this study is to compare the efficiency of seven commonly used methods of monitored classification of satellite data to evaluate land use changes using TM and OLI Landsat, IRS, Spot5 and Quick Bird bands as well as different color combinations of these images to detect agricultural land, residential areas and aquatic areas using object-oriented processing. Digital processing of satellite images was carried out in 1998 and 2016 using advanced methods. Training samples were extracted in five user classes by eCognition software using segmentation scale optimization, different color combinations and coefficients of shape and compression. The appropriate segmentation scale for arable land, human complications and the blue areas were, respectively, 50, 8 and 10. Then each image was classified separately using seven methods and extracted samples, and efficiency of each classification method was obtained by calculating two general health and Kappa coefficients. The results show that the accuracy of each classification method and the neural network with a total accuracy of 94.475 and Kappa coefficient of 92.095 were selected as the most accurate classification method. These results show that the sampling of educational samples with proper precision of the classes in the images and dependency probability of each satellite images pixel can be useful in classifying group available in helpful area.     

测绘监理体系构建与实现——以航测数字化成图项目为例

从测绘监理管理体系、测绘监理技术体系、测绘监理装备体系三个方面研究了测绘监理体系的构建,提出了测绘监理的内容、方法及业务流程,并结合航测数字化成图项目对测绘监理的应用实现进行了归纳总结,可为测绘监理的开展提供技术参考。     

基于深度学习的河道提取与变化监测应用——以永定河为例

本文基于2014年、2017年、2018年三期GF1遥感影像,针对北京市石景山永定河河道变化特征,开展基于深度学习算法的河道自动提取与变化图斑自动发现。选择GEOWAY GFLP作为地理要素智能训练平台,采用基于疑似变化区域自动发现与人工交互确认相结合的遥感监测技术路线,选取典型水体样本进行分析、训练,构建深度学习卷积神经网络水体提取模型。通过分析与验证发现,基于深度学习水体提取模型自动提取的河道准确率高于90%,精度高于最小距离、最大似然及SVM分类方法,可用于城市河道的自动提取和变化发现。     

信息化测绘技术在大遗址保护中的应用研究——以神木县石峁遗址为例

以神木县石峁遗址为例,探讨了应用无人机航空摄影测量技术、三维激光扫描技术、数字化测图技术、地理信息系统技术和三维虚拟仿真技术等多种信息化测绘技术手段,获取神木县石峁遗址本体及周边的多种测绘数据,构建展示平台,应用3D打印技术制作文物本体模型,旨在为神木县石峁遗址的保护规划提供技术支撑。     

Model Building to Investigate the Role of Spatial Location in Classifying Satellite Image Using SVM,CART and mBACT: A Case Study

This paper investigates the importance of spatial location of pixels in terms of row-column as an additional explanatory variable in classification along with available spectral bands of remotely sensed data. In view of this, a forward step-wise variable selection algorithm is used to select significant bands/variables and build an optimal model to extract the maximum accuracy. Author performed a case study on the area of town of Wolfville acquired by LANDSAT 5 TM data containing six 30 m resolution spectral bands and pixel location as an additional variable. Data are classified into seven classes using three advanced classifiers i.e. classification and regression trees (CART), support vector machines (SVM) and multi-class Bayesian additive classification tree (mBACT). Traditionally, it is assumed that addition of more explanatory variables always increase the accuracy of classified satellite images. However, results of this study show that adding more variables may sometimes confuse the classifier, that is, if selected carefully, fewer variables can provide the more accurate classification. Importance of row-column information turns out to be more beneficial for mBACT followed by SVM. Interestingly, spatial locations did not turn out to be useful for CART. Based on the findings of this study, mBACT appears to be a slightly better classifier than SVM and a substantially better than CART.     

基于地理国情普查数据的土地利用变化分析——以东莞市为例

地理国情普查成果的应用是地理国情普查的重要任务之一。本文以东莞市1999、2003、2008年以及2013年的地理国情普查数据为基础,利用土地利用动态度、土地利用程度综合指数等模型,对东莞市建成区14年间的土地利用动态变化进行分析。研究结果表明:1999~2013年间东莞市农业生产用地和生态用地面积大量减少,城乡建设用地面积大幅增加,以耕地和构筑物的面积变化最为活跃,研究后期土地利用动态度呈现减缓趋势;1999、2003、2008年以及2013年东莞市建成区内土地利用程度综合指数分别为:309.23、332.39、350.15、357.94。土地利用总体处于发展阶段。