甘肃省玛曲县沼泽湿地遥感监测与动态变化分析

利用2000年和2006年TM影像数据、地面调查资料和气象台站观测数据,对玛曲县沼泽湿地进行了目视解译分析,对比研究了非监督分类、监督分类和专家分类的精度,初步探讨了玛曲沼泽湿地退化的原因。结果表明,该县沼泽湿地面积从2000年的19598．67hm^2减少到2006年的14080．80hm^2,沼泽湿地面积平均年递减率为4．69％。非监督分类结果由于受山体阴影、坡向、云的阴影等影响,多分误差高,总分类精度仅为31％;监督分类的总精度为54．1％;专家分类的总精度高达84．2％。因此,专家分类可以用于对玛曲县沼泽湿地的监测和自动提取。草场不合理利用和过度放牧是导致玛曲县沼泽湿地退化的主要原因,黄河干流、各支流径流量减少是导致流域内沼泽湿地退化的直接原因,当地气候变暖促进了这一过程的发生。     

Land system mapping using landsat multispectral scanner imagery in the Willandra lakes region of western New South Wales

Satellite imagery provides a cost effective method of mapping distinctive assemblages of landforms, soils and vegetation over large areas, especially where access is poor. This study reports on an evaluation of supervised and unsupervised techniques of classifying Landsat reflectance information in the Wiilandra Lakes World Heritage region. The accuracy of mapping derived from Landsat information compares very favourably with land systems mapping on the ground.     

Land use and land cover change in Greater Dhaka, Bangladesh: Using remote sensing to promote sustainable urbanization

This study evaluates land use/cover changes and urban expansion in Greater Dhaka, Bangladesh, between 1975 and 2003 using satellite images and socio-economic data. Spatial and temporal dynamics of land use/cover changes were quantified using three Landsat images, a supervised classification algorithm and the post-classification change detection technique in GIS. Accuracy of the Landsat-derived land use/cover maps ranged from 85 to 90%. The analysis revealed that substantial growth of built-up areas in Greater Dhaka over the study period resulted significant decrease in the area of water bodies, cultivated land, vegetation and wetlands. Urban land expansion has been largely driven by elevation, population growth and economic development. Rapid urban expansion through infilling of low-lying areas and clearing of vegetation resulted in a wide range of environmental impacts, including habitat quality. As reliable and current data are lacking for Bangladesh, the land use maps produced in this study will contribute to both the development of sustainable urban land use planning decisions and also for forecasting possible future changes in growth patterns.     

An applied research on remote sensing classification in the Loess Plateau

Due to complex terrain of the Loess Plateau, the classification accuracy is unsatisfactory when a single supervised classification is used in the remote sensing investigation of the sloping field. Taking the loess hill and gully area of northern Shaanxi Province as a test area, a research was conducted to extract sloping field and other land use categories by applying an integrated classification. Based on an integration of supervised classification and unsupervised classification, sampling method is remarkably improved. The results show that the classification accuracy is satisfactory by the method and is of critical significance in obtaining up-to-date information of the sloping field, which should be helpful in the state key project of converting farmland to forest and grassland on slope land in this area. This research sought to improve the application accuracy of image classification in complex terrain areas.     

黄土高原遥感分类应用研究

Due to complex terrain of the Loess Plateau, the classification accuracy is unsatisfactory when a single supervised classification is used in the remote sensing investigation of the sloping field. Taking the loess hill and gully area of northern Shaanxi Province as a test area, a research was conducted to extract sloping field and other land use categories by applying an integrated classification. Based on an integration of supervised classification and unsupervised classification, sampling method is remarkably improved. The results show that the classification accuracy is satisfactory by the method and is of critical significance in obtaining up-to-date information of the sloping field, which should be helpful in the state key project of converting fiumland to forest and grassland on slope land in this area. This research sought to improve the appfication accuracy of image classification in complex terrain areas.     

基于影象融合的干旱区城镇居民地信息提取研究

针对TM多波段图象中城镇居民地与裸地光谱特征相似难以准确提取城镇居民地信息的问题,利用雷达图象对居民地信息的敏感性,采用HIS变换方法,融合了2003年西安地区的Landsat TM和Radarsat SAR影象,并对融合影象做二类监督分类提取出城镇居民地信息,结果显示与TM图象监督分类相比,融合后的图象能很好地消除裸地对城镇居民地提取影响,其精度可达到84.21%,大大高于由TM多光谱影象监督分类所得到的精度71.79%,为提取干旱区城镇居民地信息提供一种新方法。     

基于分层策略和模糊推理的北方石质山区土壤厚度制图——以滦平县虎什哈流域为例

土壤厚度信息对土壤碳储量估算、水文-生态过程模拟等有着重要影响,但我国北方石质山区缺乏现势性好、分辨率高的土壤厚度分布数据及其快速获取方法。基于北方石质山区土壤厚度的分布特点,先将地貌信息和植被类型叠加生成制图单元,再根据每类单元的特征,针对性地选取地形参数和地表覆被参数作为指示土壤厚度空间分布的环境变量,结合少量土壤样点,依据模糊推理模型,构建了基于分层制图策略的土壤厚度空间推测方法。以河北省滦平县虎什哈流域为例,利用从ASTER GDEMs提取的地形变量和从我国环境减灾卫星影像(HJ-A)提取的地表覆被信息对土壤厚度进行了推测。结果表明,该方法精度较高,是利用免费地形和遥感数据进行低成本快速土壤制图的实用途径。     

Broad area mapping of monthly soil erosion risk using fuzzy decision tree approach: integration of multi-source data within GIS

Soil erosion poses a serious problem for sustainable agriculture and the environment. There is a need to develop a simple and practical approach for broad area mapping of soil erosion risk that uses the uncertain but available information as input data within the constraints of reasonable cost and time. In this work, a predictive approach for conducting analytical erosion risk assessment across broad areas is developed, which combines a fuzzy decision tree (FDT), remote sensing and Geographic Information System (GIS). This approach is applicable to situations with a limited amount of input data and can easily adjust assessment factors according to actual need. In this study, four dominating factors affecting soil erosion were considered: soil, topography, land cover and climate. GIS thematic layers of these factors were constructed followed by fuzzified analysis through trapezoidal shaped membership functions. Based on subdivided erosion response units (ERUs), an optimal FDT was determined to classify monthly soil erosion risk into five levels. High-risk and very high-risk soil erosion in the study area is mainly concentrated from June to August, with July and August showing the highest risk covering more than 80% of the study area. November to March is dominated by low risk over more than 90% of the study area, while medium risk is dominant in April, May, September and October. Compared with field survey data, the fuzzy decision erosion risk assessment approach was shown to be applicable and economical for rapidly identifying and locating soil erosion risk with limited input data by means of remote sensing and GIS.     

运用RS、GPS和GIS技术进行大比例尺土地利用动态监测的实验研究

土地利用数据的更新是土地管理工作的重要内容之一。依靠常规的手段不仅更新速度慢、难以主动发现变化区域,而且成图周期长、误差大。依靠遥感（RS）手段可以主动快速地发现变化区域,运用差分GPS技术可以精确获取土地利用变化的数量和性质,GIS则是管理土地利用的图形数据和属性数据（如土地利用类型、权属、图斑号等）的有效工具。基于RS、GIS和GPS的集成技术建立面向工程目标的土地利用动态监测新方法是本文研究的内容。     

Geoinformational Mapping of Landscapes in the Northwestern Part of Western Siberia Using the Hansen Mosaic Dataset

Presented are the technique and results of studying the landscape structure of the north-west of Western Siberia on the basis of the Hansen mosaic dataset consisting of elements covering the entire territory of the Earth. To study this area used a synthesis of classical methods of thematic system mapping as described in the doctrine of geosystems of V. B. Sochava, and automated interpretation of remote sensing data and mapping using GIS technologies. The method of geoinformational mapping of the landscape structure with the use of MultiSpec and Quantum GIS software programs for the purpose of drawing up real-time raster landscape maps is shown. In drawing up the map and the legend, the principle of geomic system-hierarchical representation of the territory as a complex multi-level “bottom-up” structure from topological-level geosystems (groups and classes of landscape facies) to regional-level geosystems (geoms, groups and classes of geoms) was used. Compilation of operational raster landscape maps of the north-west of Western Siberia involved multilevel automated interpretation of the Hansen mosaic dataset and mapping of areas (clusters) on images with different brightness characteristics, with the landscape structure of key areas and stationary physical and geographical profiles. A characteristic of this approach also implies using a dynamic classification of geosystems based on the study of their variable states. Such an approach permits a monitoring of changes in landscape structure and its areas and the intensity of anthropogenic impacts on forest and marsh landscapes, and determination of permissible pressure on geosystems in areas with high technogenic pressure of the oil and gas complex represented by the north-west of Siberia. An automated processing of data based on a supervised classification of territorial objects allows for the elimination of inaccuracies arising in visual image interpretation. Raster landscape maps can be used both for a further generation of vector maps and as a real-time information base for purposes of environmental management and protection.     

西安城市扩张及其驱动力分析

随着人口的增长与经济的发展,尤其我国西部城市在西部大开发的背景下,大中城市的扩张十分明显,深刻地影响城市周边的生态环境。如何快速准确地获取城市扩张信息,并分析其驱动力机制,对于指导城市规划,优化西部生态环境与可持续发展都具有十分重要的意义。作者分别采用了监督分类法和归一化裸露指数 (NDBI) 法提取了西安市的城市边界信息,并对二者进行对比分析,认为监督分类法提取的城市边界信息较为准确。在此基础上通过对相关统计资料的分析,认为西安市城区快速扩张与西部大开发以来西安市固定资产投资额的大幅增加以及经济的快速发展有密切的关系,此外人口的增加、交通等基础设施的发展也是重要的驱动因素。     

近二十年福州市建设用地扩展的时空动态分析

以福州市为研究区,采用1988～2008年5个时间点的LandsatTM／ETM遥感影像为数据源,利用遥感信息提取技术,获取福州市建设用地扩展信息。从扩展来源、扩展的规模和强度、分形特征、重心和方位变化等方面分析了福州市建设用地扩展的时空变化,并从自然、经济、社会等方面探讨福州建设用地扩展的驱动力。研究结果表明：（1）福州市建设用地扩展的主要来源一直以耕地为主;（2）福州市建设用地的扩展,经历了一个由“快－慢－快－更快”的阶段性过程,城市形态越来越趋于复杂,遵循着“先东后西再南,北部稳定发展”的时空规律;（3）城市建设用地扩展是多种因素综合作用的结果,在不同的扩展阶段,不同的因素组合占主导。     

基于粗集的知识发现与地理模拟——以深圳市土地利用变化为例

为了更有效地模拟地理现象的复杂演变过程,提出了用粗集理论来确定元胞自动机 (CA)不确定性转换规则的新方法。CA可以通过局部规则来有效地模拟许多地理现象的演变过程。但目前缺乏很好定义CA转换规则的方法。往往采用启发式的方法来定义CA的转换规则,这些转换规则是静态的,而且其参数值多是确定的。在反映诸如城市扩张、疾病扩散等不确定性复杂现象时,具有一定的局限性。利用粗集从GIS和遥感数据中发现知识,自动寻找CA的不确定性转换规则,基于粗集的CA在缩短建模时间的同时,能提取非确定性的转换规则,更好地反映复杂系统的特点。采用所提出的方法模拟了深圳市的城市发展过程,取得了比传统MCE方法更好的模拟效果。     

东莞地区土地利用变化预测的CBR和CA方法对比研究(英文)

Many studies on land use change(LUC),using different approaches and models,have yielded good results.Applications of these methods have revealed both advantages and limitations.However,LUC is a complex problem due to influences of many factors,and variations in policy and natural conditions.Hence,the characteristics and regional suitability of different methods require further research,and comparison of typical approaches is re-quired.Since the late 1980s,CA has been used to simulate urban growth,urban sprawl and land use evolution successfully.Nowadays it is very popular in resolving the LUC estimating problem.Case-based reasoning(CBR),as an artificial intelligence technology,has also been employed to study LUC by some researchers since the 2000s.More and more researchers used the CBR method in the study of LUC.The CA approach is a mathematical system con-structed from many typical simple components,which together are capable of simulating complex behavior,while CBR is a problem-oriented analysis method to solve geographic problems,particularly when the driving mechanisms of geographic processes are not yet understood fully.These two methods were completely different in the LUC research.Thus,in this paper,based on the enhanced CBR model,which is proposed in our previous research(Du et al.2009),a comparison between the CBR and CA approaches to assessing LUC is presented.LUC in Dongguan coastal region,China is investigated.Applications of the im-proved CBR and the cellular automata(CA) to the study area,produce results demonstrating a similarity estimation accuracy of 89% from the improved CBR,and 70.7% accuracy from the CA.From the results,we can see that the accuracies of the CA and CBR approaches are both >70%.Although CA method has the distinct advantage in predicting the urban type,CBR method has the obvious tendency in predicting non-urban type.Considering the entire ana-lytical process,the preprocessing workload in CBR is less than that of the CA approach.As such,it could be concluded that the CBR approach is more flexible and practically useful than the CA approach for estimating land use change.     

三峡库区土地资源的多源信息综合制图法

本方法用来编制1:10万长江三峡库区土地资源评价图,以卫星数据计算机监督分类为基础,配合以野外调查和遥感、非遥感的资料。把这些资料作为多源信息,加以综合后,编制出的土地资源评价图,经实地校核,与SPOT卫星像片、卫星数据计算机监督分类图相套合,准确率分别为88,91,93(％)。     

Mapping badland areas using LANDSAT TM/ETM satellite imagery and morphological data

Soil erosion is the most influential component of land degradation for its strong impacts on both natural and agricultural environments. In order to support effective intervention and recovery policies for eroded areas, monitoring techniques should take into account the space–time variability of the processes involved, and make use of assessed mapping methodologies as baseline criteria for studying the dynamics of landform development. When using multispectral data for mapping eroded areas, low spectral separability is a significant limit in areas with complex features, where soil materials are frequently remixed by surface runoff. Since multispectral satellite images are a valuable data source for multi-temporal analyses of erosion processes at the medium scale, we assessed how accurately a badland area can be identified from LANDSAT TM and ETM data. A protocol for an optimal mapping was built up by testing the performance of different supervised algorithms and input layers (spectral and morphological). Tests were carried out in a well-known badland area of Basilicata, Italy, with an extension of  8000 ha. Results obtained from the use of spectral bands (with and without thermal channel) and principal components returned an overall accuracy ranging from 53% (for classification on first three components) to 72% (for classification on all bands from TM), with low values for the kappa coefficient (0.30–0.50), showing that the spectral information alone are insufficient to accurately identify badland areas. In order to improve mapping, we found that the integration of slopes and aspects derived from a Digital Elevation Model (DEM) can overcome problems inherent to the low separability of spectral signatures. The use of morphological data was tested for different classification algorithms and integration approaches. In discriminating badlands, the better performing algorithm was MLC (Maximum Likelihood Classifier) and the best results were obtained by integrating all seven bands (including TIR) with slope and aspect maps as input within the classifier (A > 0.85 and K  0.75 for both the sensors). We selected such parameters because they play an important role in characterising badlands of study area from a morphological perspective but the proposed approach is also conceptually simple and can be easily exported to other areas. The obtained results support the hypothesis that the combined use of remote sensing imagery and auxiliary morphological data significantly improves the mapping of badlands over large areas with heterogeneous features, thus providing a useful methodology for long-term studies on soil erosion processes.     

Unsupervised Machine Learning for Lithological Mapping Using Geochemical Data in Covered Areas of Jining,China

Natural Resources Research - Application of (supervised and unsupervised) machine learning algorithms to big geoscience data can facilitate intelligent lithological mapping and interpretation in a...     

近18年来杭州城市用地扩展特征及其驱动机制

基于多时相Landsat TM/ETM+数据和GIS技术,采用人机交互的遥感图像监督分类和空间叠加方法提取了1991,1999,2008三个年份杭州市辖区建设用地专题信息,分时段重点分析了从1991~2008年各市辖区城市扩展强度指数、方向及其侵占其他用地情况,揭示了杭州城市扩展的社会经济等多方面的驱动力因子与作用机制。结果表明:18年来,杭州城市用地快速扩展,各市辖区扩展速度和扩展强度表现出明显的阶段性和空间差异性。与1991年相比,2008年城市建设用地规模增加到近3倍,被侵占用地的主要类型是农用地,其次为水域和林地,其中农用地占66.98%,水域占17.71%,林地占15.31%。分析表明:城市人口、经济总量的快速增长、社会和外商投资额大幅增加、快速增加,以及快速的旧城更新和郊区房地产开发、高教园区和科技开发园区的用地组团式开发、跨江大桥和内外绕城公路的建设等因素是近18年杭州城市空间扩展的主要驱动力。政府应该反思在不同城市扩展阶段的得失,思考如何实现未来城市的理性扩展。     

A Review of “Knowledge Externalities,Innovation Clusters and Regional Development”

Land use information over large areas is increasingly important for many studies related to environment in general and global change in particular. Yet there is a dearth of methodological knowledge in this area, especially regarding the practical task of producing land use maps. In this article, a systematic land use mapping approach is developed, based on land cover maps that in turn are produced through remote sensing. The concept is based on the recognition of varying strengths of land cover (LC) – land use (LU) relationships, from the thematic and spatial points of view. Several categories of relationships are identified, ranging from direct (case 1) to multiple/complex (case 4), and appropriate mapping strategies are discussed for these cases. Using a mapping study in Lebanon, it is shown that the principles embodied in this approach correspond to issues and conditions in real mapping situations. Finally, the concepts are translated into a series of steps through which the method can be applied to large areas, taking into consideration the specific requirements and constraints of each case. The final land use map represents an acceptable compromise between accuracy, level of detail, and cost.     

From Land Cover to Land Use: A Methodology for Efficient Land Use Mapping over Large Areas

Land use information over large areas is increasingly important for many studies related to environment in general and global change in particular. Yet there is a dearth of methodological knowledge in this area, especially regarding the practical task of producing land use maps. In this article, a systematic land use mapping approach is developed, based on land cover maps that in turn are produced through remote sensing. The concept is based on the recognition of varying strengths of land cover (LC) – land use (LU) relationships, from the thematic and spatial points of view. Several categories of relationships are identified, ranging from direct (case 1) to multiple/complex (case 4), and appropriate mapping strategies are discussed for these cases. Using a mapping study in Lebanon, it is shown that the principles embodied in this approach correspond to issues and conditions in real mapping situations. Finally, the concepts are translated into a series of steps through which the method can be applied to large areas, taking into consideration the specific requirements and constraints of each case. The final land use map represents an acceptable compromise between accuracy, level of detail, and cost.