Soil erosion prediction based on land cover dynamics at the Semenyih watershed in Malaysia using LTM and USLE models

This study attempts to identify and forecast future land cover (LC) by using the Land Transformation Model (LTM), which considers pixel changes in the past and makes predictions using influential spatial features. LTM applies the Artificial Neural Networks algorithm) in conducting the analysis. In line with these objectives, two satellite images (Spot 5 acquired in 2004 and 2010) were classified using the Maximum Likelihood method for the change detection analysis. Consequently, LC maps from 2004 to 2010 with six classes (forest, agriculture, oil palm cultivations, open area, urban, and water bodies) were generated from the test area. A prediction was made on the actual soil erosion and the soil erosion rate using the Universal Soil Loss Equation (USLE) combined with remote sensing and GIS in the Semenyih watershed for 2004 and 2010 and projected to 2016. Actual and potential soil erosion maps from 2004 to 2010 and projected to 2016 were eventually generated. The results of the LC change detections indicated that three major changes were predicted from 2004 to 2016 (a period of 12 years): (1) forest cover and open area significantly decreased at rates of almost 30 and 8 km², respectively; (2) cultivated land and oil palm have shown an increment in sizes at rates of 25.02 and 5.77 km², respectively; and, (3) settlement and Urbanization has intensified also by almost 5 km². Soil erosion risk analysis results also showed that the Semenyih basin exhibited an average annual soil erosion between 143.35 ton ha^?1 year^?1 in 2004 and 151 in 2010, followed by the expected 162.24 ton ha^?1 year^?1. These results indicated that Semenyih is prone to water erosion by 2016. The wide range of erosion classes were estimated at a very low level (0–1 t/ha/year) and mainly located on steep lands and forest areas. This study has shown that using both LTM and USLE in combination with remote sensing and GIS is a suitable method for forecasting LC and accurately measuring the amount of soil losses in the future.     

Mapping deer habitat suitability using remote sensing and geographic information systems

This paper describes an effort to map the habitat for the Eastern Tehama Deer Herd located in Northern California. The range of this herd encompasses almost 600,000 hectares (1.5 million acres). Knowledge of the spatial distribution of suitable habitat is prerequisite to managing the deer herd. Remote sensing and GIS are appropriate tools for such an assessment. Remotely sensed data were used to map vegetation/land cover. These data along with elevation, aspect, slope, juxtaposition, and various buffer zones were input into a GIS and a model was used to produce a map of habitat suitability. The accuracy of the vegetation/land cover map was assessed and methods for validating the habitat suitability map are presented.     

基于RS和GIS的农作物估产方法研究进展

实时获取农作物长势及产量等信息对于现代农业的发展具有重要意义。近年来,随着遥感技术(remote sensing,RS)和地理信息系统(geographic information system,GIS)广泛应用于农作物估产领域,相继出现了一些较为实用的估产方法,主要有结合辅助数据的估产方法、基于植被指数的估产方法、基于特定模型的估产方法和基于农作物估产平台(软件)的开发等。其中,基于植被指数的估产方法又分为单一和多植被指数估产2类方法。在对近年来该领域大量文献深入研究的基础上,着重就几类热点方法展开论述,并对每类方法的优势和缺陷进行了评述,最后对该领域需要进一步研究的方向进行了探讨和展望,以期为后续研究提供参考。     

Delineation of groundwater potential zone in hard rock terrain of India using remote sensing,geographical information system (GIS) and analytic hierarchy process (AHP) techniques

The present study has been undertaken to delineate the groundwater potential zones in the hard rock terrain of Palamu district, Jharkhand using the advanced applications of remote sensing, geographical information systems and analytic hierarchy process techniques. The integration and analyses of various thematic databases viz., geomorphology, lithology, soil, slope, lineament density, weathered zone thickness, drainage density and rainfall proved useful in the delineation of GWP zones. The study indicates that only 136?km² of the study area exhibit excellent groundwater potential, 248?km² has very good groundwater potential, whereas 36.89 and 38.23% are under poor and very poor groundwater potential zones, respectively. Hence, only a total of 11.6% of the area (490?km²) is classified as high to excellent groundwater potential. The final groundwater prospect map obtained was classified as excellent potential, very good potential, good potential, moderate potential, poor potential and very poor potential zone.     

Urban growth monitoring and projection using remote sensing and geographic information systems: a case study in the Twin Cities Metropolitan Area,Minnesota

This study investigates urban growth dynamics from regional to local scales in the Twin Cities Metropolitan Area and demonstrates how metropolitan growth can be driven by policies. Urban change from 1975 to 2006 was detected using Landsat imagery. Future growth in 2030 was modelled based on two scenarios with or without regional development policies incorporated. City- or township-level growth was examined by a zonal analysis. Results show urban grew 126,700 ha from 1975 to 2006. The Markov-Cellular Automata model projected at least another 67,000 ha of urban growth from 2006 to 2030. When regional development policies were incorporated, homogeneous and compact growth patterns were predicted along the urban periphery; however, actual land supplies within the cities along the urban edge are facing challenges to accommodate the projected growth as large portions of suitable lands are located outside of the 2030 Municipal Urban Service Area boundary.     

An assessment of gully erosion along major armoured roads in south-eastern region of South Africa: a remote sensing and GIS approach

An assessment of gully erosion along road drainage-release sites is critical for understanding the contribution of roads to soil loss and for informed land management practices. Considering that road-related gully erosion has traditionally been measured using field methods that are expensive, tedious and limited spatially as well as temporally, it is important to identify affordable, timely and robust methods that can be used to effectively map and estimate the volume of gullies along the road networks. In this study, gullies along major roads were identified from remotely sensed data sets and their volumes were estimated in a Geographic Information Systems environment. Also, the biophysical and climatic factors such as vegetation cover, the road contributing surface area, the gradient of the discharge hillslope and rainfall were derived from remotely sensed data sets using Geographic Information Systems techniques to find out whether they could explain the morphology of gullies that existed in this area. The results of this study indicate that hillslope gradient (R²?=?0.69, α = 0.00) and road contributing surface area (R²?=?0.63, α = 0.00) have a strong influence on the volume of gullies along the major roads in the south-eastern region of South Africa, as might have been expected. However, other factors such as vegetation cover (R² = 0.52, α = 0.00) and rainfall (R² = 0.41 and α = 0.58) have a moderately weaker influence on the overall volume of gullies. Overall, the findings of this study highlight the importance of using remote sensing and Geographic Information Systems technologies in investigating gully erosion occurrence along major roads where detailed field work remains a challenge.     

RS与GIS技术在库区地质灾害调查中的应用研究

本文以黄河班多一级水电站库区地质灾害调查为例,利用RS与GIS技术进行地质灾害信息提取与分析。在对卫星影像信息进行增强处理的基础上,通过GIS数据管理和空间分析功能对多源数据进行叠加分析,利用可视化工具—虚拟地理信息系统(VirtualGIS)构建研究区三维场景,多方位、多角度挖掘地质灾害信息。结果表明:采用RS与GIS技术可以快速、准确、高效地提取地质灾害信息和与之相关的地表信息,实现地质灾害调查与分析的目的。     

Soil erosion assessment in Rangit catchment,India through a process-based model in the geospatial environment

The accurate assessment of soil erosion in the spatial environment can give valuable input in designing reservoirs and for preparing watershed management action plans. Rangit River in northeastern India is affected by severe soil erosion, causing reduction in its reservoir capacity. The main aim of the paper is to estimate the soil erosion in the Rangit catchment, India through a process-based soil erosion model that integrates remote sensing and field data in the geospatial domain, and also to identify the problem areas for further watershed management action plans. Various topographic parameters that were derived from land use, soil texture and a digital elevation model were used for the estimation of soil erosion. The Morgan, Morgan and Finny model was used to compute soil erosion. Based on the drainage pattern, the catchment was divided into eight sub-catchments for detailed study. Annual soil erosion was estimated for four years from 2002 to 2005 using the corresponding year’s meteorological data. Estimated soil erosion was compared with the field data in each year and found very good correlation.     

Monitoring and modelling of urban sprawl using remote sensing and GIS techniques

The concentration of people in densely populated urban areas, especially in developing countries, calls for the use of monitoring systems like remote sensing. Such systems along with spatial analysis techniques like digital image processing and geographical information system (GIS) can be used for the monitoring and planning purposes as these enable the reporting of overall sprawl at a detailed level.     

Estuarine sediment deposition during wetland restoration: A GIS and remote sensing modeling approach

Restoration is currently underway in the industrial salt flats of San Francisco Bay, California. Remote sensing of suspended sediment concentration and other GIS predictor variables were used to model sediment deposition within recently restored ponds. Suspended sediment concentrations were calibrated to reflectance values from Landsat TM 5 and ASTER satellite image data using three statistical techniques—linear regression, multivariate regression, and Artificial Neural Network (ANN) regression. Multivariate and ANN regressions using ASTER proved to be the most accurate methods, yielding r² values of 0.88 and 0.87, respectively. Predictor variables such as sediment grain size and tidal frequency were used in the Marsh Sedimentation (MARSED) model for predicting deposition rates. MARSED results show a root mean square deviation (RMSD) of 66.8 mm (<1σ) between modeled and field observations. This model was applied to a pond breached in November 2010 and indicated that the pond will reach sediment equilibrium levels after 60 months of tidal inundation.     

高精度轻小型航空遥感集成系统室外检校场建设方案研究

本文分析了室外检校场在高精度轻小型航空遥感集成系统中的作用,根据系统不同集成方式的检校内容和要求,设计了检校场建设的方案。试验证明该检校场能够满足多种集成方式的轻小型航空遥感系统各项参数的检校验证要求。     

Integration of remote sensing and GIS in monitoring the dynamics of land cover in Oroba-Kibos catchment area, Kenya

Land cover in Kenya is in a state of fl ux at different spatial and temporal scales. This compromises environmental integrity and socioeconomic stability of the population hence increasing their vulnerability to the externalities of environmental change. The Oroba-Kibos catchment area in western Kenya is one locality where rapid land use changes have taken place over the last 30 years. The shrubs, swamps, natural forests and other critical ecosystems have been converted on the altar of agriculture, human settlement, fuel wood and timber. This paper presents the results of a study that aimed at providing spatially-explicit information for effective remedial response through (a) Mapping the land cover; (b) Identifying the spatial distribution of land cover changes; (c) Determining the nature, rates and magnitude of the land cover changes, and; (d) Establishing the drivers of land use leading to land cover changes in Oroba-Kibos catchment area. Bi-temporal Landsat TM imagery, fi eld observation, household survey and ancillary data were obtained. Per-fi eld classifi cation of the Landsat TM imagery was performed in a GIS and the resultant land cover maps assessed using the fi eld observation data. Post-classifi cation comparison of the maps was then done to detect changes in land cover that had occurred between 1994 and 2008. SPSS was used to analyze the household survey data and attribute the detected land cover changes to their causes. The fi ndings showed that 9 broad classes characterize the catchment area including the natural forests, swamps, natural water bodies, woodlands, shrublands, built-up lands, grasslands, bare lands and croplands. Croplands are dominant and accounted for about 65% (57122 ha) of the total land in 1994, which increased at the rate of 0.89% to 73% (64772 ha) in 2008, while natural water bodies has the least spatial coverage accounting for about 0.6% (561 ha) of the total land in 1994, which diminished at the rate of 3.57% to 0.3% (260 ha) in 2008. Climate, altitude, access and rights to land, demographic changes, poverty, political governance, market availability and economic returns are the interacting mix of proximate and underlying factors that drive the land cover changes in Oroba-Kibos catchment area.     

太湖蓝藻水华遥感动态监测信息系统设计与实现

对于动态监测太湖蓝藻水华空间分布的业务需求,构建相应遥感动态监测信息系统可以为之提供有力支持。本文从系统总体结构和系统技术流程角度介绍系统的构建思路,并且探讨研发本系统的关键技术。本系统采用系统配置与单体模式技术实现系统架构,并设计良好的数据结构组织影像数据处理过程,同时将当前蓝藻水华遥感信息提取的主要方法应用到系统影像建模中,使得本系统在太湖蓝藻水华遥感监测的业务化运行中取得明显效果。     

遥感影像并行处理的数据划分及其路径优化算法

研究了一种基于数据划分的遥感影像并行处理的路径优化算法,用于解决将并行技术应用于海量遥感影像分布式存储和处理领域时其处理模型所具有的多路可达性所引起的路径动态、最优选择问题。在栅格数据可分解性分析及并行模型数据态、元素、相对信息量和映射等8个基本定义和6个性质的基础上,给出并行处理一般数学模型。以该模型为基础获得在一般并行处理情况下,以平均计算代价变量的比值作为控制横向并行与纵向并行选择方式的标志,并进一步给出四叉树索引并行生成、基于四叉树的目标检测并行处理等具体示例。最后,通过试验验证了算法的有效性,分析了算法的特点及影响因素。     

Sustainable development of land and water resources using geographic information system and remote sensing

Realizing the potential of spaceborne multispectral measurements in providing spatial information on natural resources, and of Geographic Information System (GIS) in integrating such information with the socio-economic data and other collateral information to arrive at derivative information, we report here the results of a study which was taken up in a watershed in Charkhari block of Mahoba district, northern India, to generate the information on natural resources from Indian Remote Sensing Satellite (IRS-1B) Linear Imaging Self-scanning Sensor (LISS-II) images through a systematic visual interpretation, and its subsequent integration with the collateral information in a GIS environment to develop optimal land use plan/action plan for sustainable development of its land resources. Since permanent vegetation cover in the watershed has been dwindling due to population pressure, the need for establishing more vegetation cover has been stressed.     

多源遥感数据管理与远程处理集成实现

针对目前对多源遥感影像数据管理与远程处理的集成应用研究较少的现状,文章基于FTP、关系数据库和空间数据库引擎设计多源遥感影像数据及其元数据与快视图数据的一体化管理方案,基于Web Service与PCI-EASI设计遥感影像远程处理服务,并对多源遥感影像数据管理与远程处理功能进行集成,通过综合运用FTP和Web Service技术,提高了数据管理效率和应用的灵活性。最后以"粤港澳水质遥感监测系统"为例,实现了对多源遥感影像数据的有效管理及水质监测业务的系统化,验证了研究成果的可行性和实用性。     

星地多源数据的区域土壤有机质数字制图

土壤有机质(SOM)是全球碳循环、土壤养分的重要组成部分,精确估算土壤有机质含量具有重要意义。本文以中国东北—华北平原为研究区,收集了1078个土壤样本,以遥感数据(MODIS,TRMM和STRM数据)与土壤地面光谱数据为预测因子,运用基于树形结构的数据挖掘技术构建土壤有机质-环境预测因子模型进行数字土壤制图。通过不同建模样本数建模精度比较,选择300个样本数时的模型为最优模型。建模结果表明土壤光谱和气候因子是研究区SOM变异的主控因子,生物因子次之,而地形因子影响最小。预测结果经检验,RMSE为7.25,R2为0.69,RPD为1.53制图结果与基于第二次全国土壤普查数据的土壤有机质地图具有相似的分布规律,呈现SOM自东北向西南递减的趋势。通过比较分析发现,经过20年左右的土地开发与利用,研究区低SOM和高SOM含量土壤面积减少,而中等SOM含量土壤面积增加。     

航空遥感航线设计系统研究与实现

航线设计是根据所用传感器、任务技术指标、摄区地形等因素,来计算航线和曝光点的坐标,为航空摄影外业提供依据和准则,使摄影成果满足质量要求。本文针对航空遥感任务的需要,开发了航线设计系统,并详细介绍了系统主要功能、航线和曝光点计算算法,以及系统实现的技术和方法。     

EMD与分形相结合的遥感影像水体信息提取方法

提出一种基于经验模态分解(empirical mode decomposition,EMD)和分形理论相结合的遥感影像水体信息提取方法,该方法尝试结合影像的光谱特征和纹理特征以提高分类提取精度。对影像进行主成分分析得到有效信息量最大的第一主分量,计算每个像元的分维数得到分维图,同时将第一主分量EMD分解得到有效信息量较大的前3个经验模态函数,再结合原有的波段信息作为研究数据,利用极大似然法分类器提取水体信息。该方法充分结合了EMD在降噪和区分相似光谱特征中的优势和分形理论在纹理信息提取中的优势。研究表明,该方法可有效提高水体信息的提取精度,Kappa最高到0.932 5。     

多源遥感影像融合技术及其在更新土地利用数据库中的应用

分析了SPOT和TM卫星影像的特点,提出综合利用SPOT和TM卫星影像的方法.对这两种影像进行融合,提取融合后的影像数据,使之与GIS数据库相叠加,达到对GIS矢量数据库更新的目的.以土地利用数据库为例进行实践,取得了较好的效果.