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ＧＩＳ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ＧＩＳ的综合来实现。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。     

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。     

Irrigation Water Requirements and Supply Analysis in Dehradun Region—An Integrated Remote Sensing and GIS Approach

The paper focuses on analysing the irrigation water supply and demand of different crops under three main canals for kharif and rabi seasons in Dehradun region of Uttaranchal state. Crop acreage maps of rabi and kharif seasons have been prepared using LANDSAT TM 5 digital data by applying different image processing and classification techniques. Crop water and irrigation water requirements of different crops have been computed using CROPWAT computer program. Canal discharges have been compared with the irrigation water planning and management and found to be more than the irrigation water requirements in many months, that shows the need of revising the irrigation water management.     

基于GIS的土壤遥感制图及应用研究

通过遥感技术获取土壤资源类型的分布是实现土地资源遥感监测快捷有效途径的关键技术.本论文进行了以下一些内容的研究:     

基于GIS的中国东北植被综合分类研究

ＮＯＡＡ／ＡＶＨＲＲ由于运行周期短、覆盖范围大、成本低、波段宽等特点,目前正越来越广泛地受到人们的普遍关注。在大尺度、中尺度植被遥感上,ＮＯＡＡ／ＡＶＨＲＲ具有陆地卫星无法比拟的优势,但在另一方面,ＮＯＡＡＡＶＨＲＲ也存在分辨率低、数据变形较大和几何畸变较严重等问题。这样,在应用ＮＯＡＡＡＶＨＲＲ数据进行大区域植被制图时,植被分类的精度仍待提高。本文从理论上探讨了将地理信息系统提供的地理数据与遥感数据复合的可行性;尝试在ＧＩＳ环境下,将气温、降水、高程３个影响区域植被覆盖的主要指标,按一定的地面网格系统和数学模式进行量化,生成数字地学影像,并使之与经过优化、压缩处理的ＮＯＡＡＡＶＨＲＲ数据进行复合,对复合后的综合影像进行监督分类。分类结果显示,与传统的应用最大似然分类方法对单一遥感图像分类相比,该综合分类方法分类精度提高了１８．３％,该研究方法改变了遥感影像的单一信息结构;丰富了图像的信息含量;完成了地理数据的数字传输、处理、存储及影像化显示。     

Assessment of Land use/land cover Change in the North-West District of Delhi Using Remote Sensing and GIS Techniques

Land is one of the prime natural resources. A city grows not only by population but also by changes in spatial dimensions. Urban population growth and urban sprawl induced land use changes and land transformation. The land transformation is a natural process and cannot be stopped but it can be regulated. Many geographical changes at the urban periphery are associated with the transfer of land from rural to urban purpose. There is an urgent need for fast growing areas like Delhi, which can be easily done by high-resolution remote sensing data. Land use/land cover of North West of Delhi has been analyzed for the time period of 1972?C2003. The remote sensing data used in study is Aster image of 2003 with a spatial resolution of 15?m and other data of 1972 Survey of India (SOI) toposheet at the scale of 1:50,000. Supervised digital classification using maximum likelihood classifier was applied for preparing land use/land cover. A change detection model was applied in ERDAS Imagine to find out the land use/land cover during 1972 to 2003. Eight land use classes was identified but main dominated classes were built up and agricultural land. A drastic change has been recorded during 30 years of time i. e. (1972-2003). In 1972, 92.06% of the land was under agricultural practice, which reduced to 64.71% in 2003. This shows 27.35% decrease in agricultural land in three decades. On the other hand built up area was 6.31% in 1972, which increased to 34% in 2003. One of the main cause of this land use change is the population growth due to the migration in the district from small cities and rural areas of Delhi.     

Land Use/Cover Change Detection of Tiruchirapalli City, India, Using Integrated Remote Sensing and GIS Tools

The rapid growth of urban population in India is a cause of concern among country??s urban and town planners for efficient urban planning. The drastic growth of urban areas has resulted in sharp land use and land cover changes. In recent years, the significance of spatial data technologies, especially the application of remotely sensed data and geographical information systems (GIS) has been widely used. The present study investigates the urban growth of Tiruchirapalli city, Tamilnadu using IRS satellite data for the years 1989, 1992, 1995, 1998, 2001, 2004, 2007, and 2010. The eight satellite images are enhanced using convolution spatial enhancement method with Kernel (7?×?7) edge enhance function. Supervised classification method is used to classify the urban land use and land cover. The GIS is used to prepare the different layers belonging to various land uses identified from remotely sensed data. The analysis of the results show the drastic increase of built up area and reduced green cover within the city boundary limit.     

老挝Phonxay区土地利用/土地覆盖遥感调查

老挝是一个发展中国家,境内的大多数地方没有开展过土地利用/土地覆盖调查。本文选择老挝琅勃拉邦省的Phonxay区为研究区域,利用Landsat OLI数据进行土地利用/土地覆盖遥感调查与分析。研究过程中,利用ArcGIS Desktop选择训练样本和验证样本,通过Python和ArcPy编程开发了图像分类、精度评价以及面积统计的工作流程序,实现了快速得到分类结果和精度评价信息,分类结果的总精度为89.53%,Kappa系数为0.81。     

土地覆盖制图：基于最优化遥感数据的支撑向量机分类

遥感数据具有在不同空间、光谱和时间尺度上获取地表测量信息的能力,使其成为获取土地覆盖信息的一个主要数据源。影像分类即把卫星影像上的相关像元划分给某类已知的土地覆盖类型的过程。支撑向量机（SVMs）是一种土地覆盖分类的新技术。三种常用的SVMs是：基于线性和多项式的SVM以及具有高斯核函数的SVM分类器,分类能否成功地应用有赖于其各自选择的最佳参数。但是海量的遥感数据使得这些参数的确定速度十分缓慢。本文研究了一种新的基于最优化遥感数据压缩技术的SVM分类方法。研究显示用于获取SVM参数的数据量能够在不影响土地覆盖的分类精度的前提下进行压缩。数据压缩成功的应用于多项式和高斯核函数的SVM分类,而线性SVM的分类精度却非常低。     

Application of Earth Remote Sensing and GIS in Mapping Land Cover Patterns in Kinangop Division, Kenya

<正>Land cover is a fundamental variable that links many facets of the natural environment and a key driver of global environmental change.Alterations in its status can have significant ramifications at local,regional and global levels.Hence,it is imperative to map land cover at a range of spatial and temporal scales with a view to understanding the inherent patterns for effective characterization,prediction and management of the potential environmental impacts.This paper presents the results of an effort to map land cover patterns in Kinangop division,Kenya,using geospatial tools.This is a geographic locality that has experienced rapid land use transformations since Kenya's independence culminating in uncontrolled land cover changes and loss of biodiversity.The changes in land use/cover constrain the natural resource base and presuppose availability of quantitative and spatially explicit land cover data for understanding the inherent patterns and facilitating specific and multi-purpose land use planning and management.As such,the study had two objectives viz.(i) mapping the spatial patterns of land cover in Kinangop using remote sensing and GIS and;(ii) evaluating the quality of the resultant land cover map.ASTER satellite imagery acquired in January 23,2007 was procured and field data gathered between September l0 and October 16,2007.The latter were used for training the maximum likelihood classifier and validating the resultant land cover map.The land cover classification yielded 5 classes,overall accuracy of 83.5%and kappa statistic of 0.79,which conforms to the acceptable standards of land cover mapping. This qualifies its application in environmental decision-making and manifests the utility of geospatial techniques in mapping land resources.     

Assessment and Management Flash Flood in Najran Wady Using GIS and Remote Sensing

Flash flood assessment and management are necessary for municipal, urban growth planning and emergency action plans. By using the Hydrologic Engineering Centers River Analysis System software, we can model flash flood events and calculate water surface profiles over the length of the modeled stream. After collecting elevation points by using GPS method, the digital elevation model can be calculated for the study area. Najran city has main flood stream passes beside King Abdullah Road based on facts and previous works. A small study area including the mainstream of Wady Najran and King Abdullah Road has chosen as test site. The used methodology has also been proved efficiently for identifying flood inundation maps. Water extent area overlapped by 52–86% for both used methods. At discharge Q = 15 m³/s, the road needs to be protected from the flood.     

Assessment of Post-fire Soil Erosion Risk in Fire-Affected Watersheds Using Remote Sensing and GIS

Soil erosion is a prominent cause of land degradation and desertification in Mediterranean countries. The detrimental effects of soil erosion are exemplified in climate (in particular climate change), topography, human activities, and natural disasters. Forest fires, which are an integral part of Mediterranean ecosystems, are responsible for the destruction of above-and below-ground vegetation that protects against soil erosion. Under this perspective, the estimation of potential soil erosion, especially after fire events, is critical for identifying watersheds that require management to prevent sediment loss, flooding, and increased ecosystem degradation. The objective of this study was to model the potential post-fire soil erosion risk following a large and intensive wildland fire, in order to prioritize protection and management actions at the watershed level in a Mediterranean landscape. Burn severity and preand post-fire land cover/uses were mapped using an ASTER image acquired two years before the fire, air photos acquired shortly after the fire, and a Landsat TM image acquired within one month after-fire. We estimated pre-and post-fire sediment loss using an integrated GIS-based approach, and additionally we analyzed landscape erosion patterns. The overall accuracy of the severity map reached 83%. Severe and heavy potential erosion classes covered approximately 90% of the total area following the fire, compared to 55% before. The fire had a profound effect on the spatial erosion pattern by altering the distribution of the potential erosion classes in 21 out of 24 watersheds, and seven watersheds were identified as being the most vulnerable to post-fire soil erosion. The spatial pattern of the erosion process is important because landscape cover heterogeneity induced especially by fire is a dominant factor controlling runoff generation and erosion rate, and should be considered in post-fire erosion risk assessment.     

遥感测绘在土地确权中的应用

在土地确权中,应用遥感测绘技术,能够提供清晰准确的图片和数据,确保相关部门能够通过对数据信息的识别和判读,结合地块调查确认,明确土地权属和界限,保证土地确权工作的质量要求。本文结合土地确权的内涵和意义,对遥感测绘在土地确权中的应用情况进行了分析和探讨。     

发展中国遥感与地理信息系统的战略

当我们走向世界时 ,迎面扑来的高新科技 :遥感、地理信息系统、全球定位系统、信息高速公路、可持续发展、知识经济、数字地球等一浪一浪接踵而来 ,使得我们应接不暇。大多数科技人员都在考虑追踪国际前沿 ,而对于我国的国情了解不足。在急于求成的心态下 ,重视了应用 ,忽视了基础研究与基础建设 ,缺乏自己的创造性。本文就遥感信息源、遥测基础建设、定位系统、地理信息系统软件、网络基础建设、数据源建设、科学研究方法、人才培养等方面提出系统的建设设想。     

基于遥感和GIS的中国土地潜力资源的研究

在对中国土地资源综合研究基础上,利用已有研究成果,借助ＧＩＳ工具,利用层次分析法,对中国土地地潜力资源进行了综合分析和评价,在评价基础上,对中国土地资源的耕地潜力、生产潜力、生产潜力总量、人口容量潜力及综合潜力的大小和空间展布特征进行分析。结论为：中国土地资源潜力很力,但时空分布不均,在开发利用中,应因地制宜,采取不同的开发、利用的战略方针,在保护好现有土地资源和合理科学利用的基础上,谨慎开发,以     

基于遥感和GIS的宣化县水土流失定量空间特征分析

以遥感和GIS技术为支撑,利用通用的土壤流失方程(USLE)的修正模型(RUSLE)定量评估宣化县2000年的水土流失量和土壤侵蚀强度,并对宣化县水土流失空间分布特征进行了分析。结果表明,宣化县2000年土壤侵蚀(轻度侵蚀以上)面积为982.85 km2,占宣化县总面积的39.25%,平均土壤侵蚀模数为13.92 t/hm2.a,属于轻度侵蚀;坡度越大,极强度及剧烈侵蚀越有可能发生,从整体来看,15°~25°是侵蚀比例最大的坡度带。宣化县土壤侵蚀主要集中于灌草地和旱地两种土地类型,两者土壤侵蚀面积占宣化县2000年总土壤侵蚀面积的93.897%。     

Quantitative Determination of Soil Erosion and Prioritization of Micro-Watersheds Using Remote Sensing and GIS

Soil erosion which occurs at spatially varying rate is a widespread threat to sustainable resource management at watershed scale. Thus estimation of soil loss and identification of critical area for implementation of best management practice is central to success of soil conservation programme. The present study focuses application of most widely used Universal Soil Loss Equation (USLE) to determine soil erosion and prioritization of micro-watersheds of Upper Damodar Valley Catchment (UDVC) of India. Annual average soil loss for the entire basin is 23.17 t/ha/yr; for micro-watersheds. High soil loss is observed in 345 micro-watersheds, medium in 159 micro-watersheds and low soil loss is observed in 201 micro-watersheds. It is found that, out of 705 micro-watersheds of UDVC, 453 micro-watersheds are in agreement with AISLUS suggested priority which is based on observed sediment yield, 116 micro-watersheds under predict and 136 micro-watersheds over predict the priority. Geographic Information System (GIS) is applied to prepare various layers of USLE parameters which interactively estimate soil erosion at micro-watershed level. The main advantage of the GIS methodology is in providing quick information on the estimated value of soil loss for any part of the investigated area.     

土壤盐渍化量化的遥感与GIS实验

为对土壤盐渍化程度做更为科学的定量分析，该文重点研究了地下水埋深，地下水矿化度和地貌因子对土壤盐渍化影响以及这种影响的定量化，研究区为吉林省长岭县实验区。利用地理信息系统作为支持工具，结合遥感数据和专家经验，建立数学模型，进行综合分析，获得了较好的结果，这种方法为分析土壤盐渍化问题的有效途径之一。     

Estimation of Heavy-Metal Contamination in Soil Using Remote Sensing Spectroscopy and a Statistical Approach

Heavy-metal-contaminated soil is a critical environmental issue in suburban regions. This paper focuses on utilizing field spectroscopy to predict the heavy metal contents in soil for two suburban areas in the Jiangning District (JN) and the Baguazhou District (BGZ) in China. The relationship between the surface soil heavy metal contents and spectral features was investigated through statistical modeling. Spectral features of several spectral techniques, including reflectance spectra (RF), the logarithm of reciprocal spectra (LG) and continuum-removal spectra (CR), were employed to establish and calibrate models regarding to Cd, Hg and Pb contents. The optimal bands for each spectral feature were first selected based on the spectra of soil samples with artificially added heavy metals using stepwise multiple linear regressions. With the chosen bands, the average predictive accuracies of the cross-validation, using the coefficient of determination R², for estimating the heavy metal contents in the two field regions were 0.816, 0.796 and 0.652 for Cd; 0.787, 0.888 and 0.832 for Pb; and 0.906 and 0.867 for Hg based on partial least squares regression. Results show that better prediction accuracies were obtained for Cd and Hg, while the poorest prediction was obtained for Pb. Moreover, the performances of the LG and CR models were better than that of the RF model for Pb and Hg, indicating that LG and CR can provide alternative features in determining heavy metal contents. Overall, it’s concluded that Cd, Hg and Pb contents can be assessed using remote-sensing spectroscopy with reasonable accuracy, especially when combined with library and field-collected spectra.