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1.
There is much interest in using volunteered geographic information (VGI) in formal scientific analyses. This analysis uses VGI describing land cover that was captured using a web-based interface, linked to Google Earth. A number of control points, for which the land cover had been determined by experts allowed measures of the reliability of each volunteer in relation to each land cover class to be calculated. Geographically weighted kernels were used to estimate surfaces of volunteered land cover information accuracy and then to develop spatially distributed correspondences between the volunteer land cover class and land cover from 3 contemporary global datasets (GLC-2000, GlobCover and MODIS v.5). Specifically, a geographically weighted approach calculated local confusion matrices (correspondences) at each location in a central African study area and generated spatial distributions of user's, producer's, portmanteau, and partial portmanteau accuracies. These were used to evaluate the global datasets and to infer which of them was 'best’ at describing Tree cover at each location in the study area. The resulting maps show where specific global datasets are recommended for analyses requiring Tree cover information. The methods presented in this research suggest that some of the concerns about the quality of VGI can be addressed through careful data collection, the use of control points to evaluate volunteer performance and spatially explicit analyses. A research agenda for the use and analysis of VGI about land cover is outlined.  相似文献   

2.
We use a linear unmixing approach to test how land use and forestry maps, in combination with the MODIS BRDF/albedo product, can be used to estimate land cover type albedos in boreal regions. Operational land use maps from three test areas in Finland and Canada were used to test the method. The resulting endmember albedo estimates had low standard errors of the mean and were realistic for the main land cover types. The estimated albedos were fairly consistent with albedo measurements conducted with a telescope mast and pure pixel albedos. Problems with the method are the possible errors in the land cover maps, lack of good quality winter MODIS albedo composites and the mismatch between the MODIS pixels and the true observation area. The results emphasize the role of tree species as determinant of forest albedo. Comprehensive spatial and temporal measurements of land cover albedo are usually not possible with in situ mast measurements, and the spatial resolution of MODIS albedo product is often too low to allow direct comparison of pixel albedos and land cover types in areas with heterogeneous vegetation. Hence, and since local forestry maps exist for most temperate and boreal regions, we believe that the proposed method will be useful in estimating average regional land cover type albedos as well as in tracking changes in them.  相似文献   

3.
Standard false colour composites (Std. FCC) on 1:50,000 scale was visually interpreted in conjunction with soil survey to prepare physiographic-soil map. Thirteen mapping units were delineated indicating soil association at family-level. Soil and land resource was evaluated for their land capability and irrigation suitability for its sustained use under irrigation. Land capability and land irrigability maps were generated as attribute map. These maps were integrated to suggest potential land use map. Current land use/land cover map prepared by visual analysis was spatially analysed in relation to potential land use to study potential changes in land use / land cover using GIS. The study reveals that 14.66% area has no limitation and can be brought to intensive agriculture by double cropping.  相似文献   

4.
The present study describes a procedure for quantitatively analyzing satellite telemetry data to identify interspecific land use differences among four threatened crane species. The inherent inaccuracy of satellite telemetry data points, the temporal autocorrelation of those points, and the resolution of two land‐cover imagery products from the IGBP‐DISCover Global Land‐Cover Characterization Project (derived from AVHRR data) were assessed and integrated in a GIS. Satellite telemetry is a system where animals are tracked using battery‐operated transmitters and locations are calculated using triangulation from satellites. Using the variable spatial inaccuracy of the telemetry locations, each point was buffered using a radius based on the accuracy of the point, and then intersected with the land cover imagery. The research concluded that the methodology is valuable for studies of birds at a regional scale, with interspecific differences clearly evident, but that diurnal and nocturnal differences were not discernable due to the coarse resolution of both satellite telemetry and land‐cover data.  相似文献   

5.
遥感信息不确定性研究   总被引:6,自引:1,他引:6  
葛咏  王劲峰  梁怡  马江洪 《遥感学报》2004,8(4):339-348
近年来遥感技术及遥感信息产业化发展迅猛 ,但遥感信息的不确定性制约着遥感信息的产品化和实用化的进一步发展。虽然 ,这一问题得到了国内外众多学者的关注 ,并提出和采用相关理论和方法进行分析 ,取得了相当的进展 ,但这些方法在分析遥感信息不确定性时忽略了一个重要的研究点 :遥感信息的不确定性传递机理。本文主要目标就是建立一套遥感信息不确定性的处理方法  相似文献   

6.
The classification of satellite imagery into land use/cover maps is a major challenge in the field of remote sensing. This research aimed at improving the classification accuracy while also revealing uncertain areas by employing a geocomputational approach. We computed numerous land use maps by considering both image texture and band ratio information in the classification procedure. For each land use class, those classifications with the highest class-accuracy were selected and combined into class-probability maps. By selecting the land use class with highest probability for each pixel, we created a hard classification. We stored the corresponding class probabilities in a separate map, indicating the spatial uncertainty in the hard classification. By combining the uncertainty map and the hard classification we created a probability-based land use map, containing spatial estimates of the uncertainty. The technique was tested for both ASTER and Landsat 5 satellite imagery of Gorizia, Italy, and resulted in a 34% and 31% increase, respectively, in the kappa coefficient of classification accuracy. We believe that geocomputational classification methods can be used generally to improve land use and land cover classification from imagery, and to help incorporate classification uncertainty into the resultant map themes.  相似文献   

7.
A common method to assess land use/cover change (LUCC) is the comparison of digital maps of an area within a geographic information system (GIS). However, positional errors of the maps involved in the comparison affect this assessment and much of the change shown by means of this comparison may be an artifact due to these errors. This note presents a simple method to improve change estimates by detecting and correcting erroneous changes resulting from positional errors. It allows an important reduction of error in change area estimates and is likely to be useful in LUCC assessment studies.  相似文献   

8.
Human activities have great influence on fragile coastal ecosystem. For sustainable use of coastal resources it is very important to understand land use/land cover changes and its implications on coastal systems. Remote sensing data because of its synoptic, multispectral and multi temporal nature can be a very good source for mapping, monitoring and understanding these changes. IRS LISS III sensor data were used to find out the rate of land use/land cover changes in Hazira area near Surat, Gujarat. Because of major industrial activities it has become a hot spot area which requires regular monitoring. In the present study, land cover information of the period 1970–1972 from the Survey of India topographical maps, and satellite data of the year 1989 and 1999–2002 have been used and visual analysis has been carried out to measure the land use/land cover changes. Erosion and deposition has been observed around the newly constructed jetty. Forest area and agriculture area is found to decreased, whereas built-up area has increased.  相似文献   

9.
Land use/cover classification is a key research field in remote sensing and land change science as thematic maps derived from remotely sensed data have become the basis for analyzing many socio-ecological issues. However, land use/cover classification remains a difficult task and it is especially challenging in heterogeneous tropical landscapes where nonetheless such maps are of great importance. The present study aims at establishing an efficient classification approach to accurately map all broad land use/cover classes in a large, heterogeneous tropical area, as a basis for further studies (e.g., land use/cover change, deforestation and forest degradation). Specifically, we first compare the performance of parametric (maximum likelihood), non-parametric (k-nearest neighbor and four different support vector machines – SVM), and hybrid (unsupervised–supervised) classifiers, using hard and soft (fuzzy) accuracy assessments. We then assess, using the maximum likelihood algorithm, what textural indices from the gray-level co-occurrence matrix lead to greater classification improvements at the spatial resolution of Landsat imagery (30 m), and rank them accordingly. Finally, we use the textural index that provides the most accurate classification results to evaluate whether its usefulness varies significantly with the classifier used. We classified imagery corresponding to dry and wet seasons and found that SVM classifiers outperformed all the rest. We also found that the use of some textural indices, but particularly homogeneity and entropy, can significantly improve classifications. We focused on the use of the homogeneity index, which has so far been neglected in land use/cover classification efforts, and found that this index along with reflectance bands significantly increased the overall accuracy of all the classifiers, but particularly of SVM. We observed that improvements in producer's and user's accuracies through the inclusion of homogeneity were different depending on land use/cover classes. Early-growth/degraded forests, pastures, grasslands and savanna were the classes most improved, especially with the SVM radial basis function and SVM sigmoid classifiers, though with both classifiers all land use/cover classes were mapped with producer's and user's accuracies of ∼90%. Our classification approach seems very well suited to accurately map land use/cover of heterogeneous landscapes, thus having great potential to contribute to climate change mitigation schemes, conservation initiatives, and the design of management plans and rural development policies.  相似文献   

10.
Identification of suitable site for urban development in hilly areas is one of the critical issues of planning. Site suitability analysis has become inevitable for delineating appropriate site for various developmental initiatives, especially in the undulating terrain of the hills. The study illustrates the use of geographic information system (GIS) and multicriteria evaluation (MCE) technique for selection of suitable sites for urban development in Mussoorie municipal area, Dehradun district, Uttarakhand. For this purpose Toposheet and IKONOS satellite data were used to generate various thematic layers using ArcGIS software. Criteria using five parameters, i.e. slope, road proximity, land use/land cover, land values and geological formation were used for site suitability analysis following land evaluation. The generated thematic maps of these criteria were standardized using pairwise comparison matrix known as analytical hierarchy process (AHP). A weight for each criterion was generated by comparing them with each other according to their importance. With the help of these weights and criteria, final site suitability map was prepared.  相似文献   

11.
Monitoring agricultural land cover is highly relevant for global early warning systems such as ASAP (Anomaly hot Spots of Agricultural Production), because it represents the basis for detecting production deficits in food security assessment. Given the significant inconsistencies among existing land cover datasets, there is a need to obtain a more accurate representation of the spatial distribution and extent of agricultural area in Africa. In this research, we explore a fusion approach that combines the strength of individual datasets and minimises their limitations. Specifically, a semi-automatic method is developed, relying on multi-criteria analysis (MCA) complemented with manual fine-tuning using the best-rated datasets, to generate two hybrid and static agricultural masks – one for cropland and another for grassland. Following a comprehensive selection of land cover maps, each dataset is evaluated at country level according to five criteria: timeliness, spatial resolution, comparison with FAO statistics, accuracy assessment and expert evaluation. A sensitivity analysis is performed, based on an evaluation of the impact of weight settings on the resulting land cover. The proposed methodology is capable of improving agricultural characterisation in Africa. As a result, two static masks at 250 m spatial resolution for the nominal year 2016 are provided.  相似文献   

12.
A nationwide multidate GIS database was generated in order to carry out the quantification and spatial characterization of land use/cover changes (LUCC) in Mexico. Existing cartography on land use/cover at a 1:250,000 scale was revised to select compatible inputs regarding the scale, the classification scheme and the mapping method. Digital maps from three different dates (the late 1970s, 1993 and 2000) were revised, evaluated, corrected and integrated into a GIS database. In order to improve the reliability of the database, an attempt was made to assess the accuracy of the digitalisation procedure and to detect and correct unlikely changes due to thematic errors in the maps. Digital maps were overlaid in order to generate LUCC maps, transition matrices and to calculate rates of conversion. Based upon this database, rates of deforestation between 1976 and 2000 were evaluated as 0.25 and 0.76% per year for temperate and tropical forests, respectively.  相似文献   

13.
Pasture land occupies extensive areas and is increasingly of interest for sustainable intensification, land use diversification, greenhouse gas emission mitigation, and bioenergy expansion. Accurate maps of pasture and other managed land covers are needed for monitoring, intercomparison, assessing potential uses, and planning. Yet, land maps can be generated from different types of classification datasets – i.e. as a land use or land cover type – as well as different sources. In this study our aim was to assess and compare land use and land cover definitions for pasture, and examine variability in the resulting pasture land classification maps. First, we conducted a review of pasture definitions in commonly used mapping databases. We then performed a case study involving Brazil, a dominant global producer of pasture-based livestock. Six geospatial databases were harmonized and compared to each other and to MODIS land cover for Brazil including the Cerrado and Amazon biomes, which are internationally recognized for their ecological value. Total pasture area estimates for Brazil ranged by a factor greater than four, from about 430,000 km2 to over 1.7 million km2. Our analysis showed high variability in pasture land maps depending on the definitions, methods and underlying datasets used to generate them. The results are illustrative of a symptomatic problem for all manage land datasets, demonstrating the need for land categories studies and geospatial data resources that fully define land terms and describe measurable management attributes. Additionally, the suitability of individual geospatial datasets for different types of land mapping must be better described and reported. These recommendations would help bring more consistency in the consideration of managed lands in research, reporting, and policy development, as demonstrated here for pasture land using six case study datasets from multiple sources.  相似文献   

14.
Land use/land cover changes over a period of 30 years were studied using remote sensing technology in a part of Gohparu block, Shahdol district of Madhya Pradesh. Land use/ land cover maps were prepared by visual interpretation of two period remotely sensed data. Post-classification comparison technique was adopted for this purpose. The loss of vegetation cover was estimated to be 22 percent and 14 percent of the land was found to have been tranformed into wasteland between 1967 and 1996. Overall rate of change was found to be 1.8 percent per year during this period.  相似文献   

15.
Abstract

Land cover is an important component of the earth system. Human induced surface alteration can affect earth systems directly, through loss or degradation of ecosystems, or indirectly through impact on the climate and biogeochemical cycles necessary to sustain life on earth. The significance of the earth's surface has made land use/land cover change an important issue in global change research. Alteration of land cover occurs at a variety of spatial scales, but as with many environmental change issues, the impacts of surface changes are often conceptualized at the global scale. In this study, we investigate the effects of land cover change on total reflected radiation and the Normalized Difference Vegetation Index (NDVI) in a 10,000 km2 local area in the High Plains of southwestern Kansas. Landsat MSS data from five years of record within the twenty‐year period 1973 to 1992 were classified into cool season crop, warm season crop, and pasture/prairie. Mean values of summer reflectance and NDVI from each cover type and for the study area as a whole were then analyzed for systematic change over the study period. Both reflectivity and vegetation index increased during the study period, although causes for the increase appear to be different. Results suggest that changes in mean surface reflectance in the study site are strongly influenced by land cover change, whereas changes in NDVI are more closely linked to 50‐day antecedent precipitation.  相似文献   

16.
This paper presents novel techniques to estimate the uncertainty in extrapolations of spatially-explicit land-change simulation models. We illustrate the concept by mapping a historic landscape based on: 1) tabular data concerning the quantity in each land cover category at a distant point in time at the stratum level, 2) empirical maps from more recent points in time at the grid cell level, and 3) a simulation model that extrapolates land-cover change at the grid cell level. This paper focuses on the method to show uncertainty explicitly in the map of the simulated landscape at the distant point in time. The method requires that validation of the land-cover change model be quantified at the grid-cell level by Kappa for location (Klocation). The validation statistic is used to estimate the certainty in the extrapolation to a point in time where an empirical map does not exist. As an example, we reconstruct the 1951 landscape of the Ipswich River Watershed in Massachusetts, USA. The technique creates a map of 1951 simulated forest with an overall estimated accuracy of 0.91, with an estimated users accuracy ranging from 0.95 to 0.84. We anticipate that this method will become popular, because tabular information concerning land cover at coarse stratum-level scales is abundant, while digital maps of the specific location of land cover are needed at a finer spatial resolution. The method is a key to link non-spatial models with spatially-explicit models.  相似文献   

17.
The surface fabric of urbanized areas, (i.e. its constituent land covers and land uses) plays an essential role in the generation of the urban/rural temperature differences, i.e. the Urban Heat Island (UHI) effect. Land surface information, derived from satellite imagery, and complementary information such as demographics can be used as the basis for an understanding of the atmospheric and surface thermal variations within cities. The results of comprehensive land surface characterizations of two major Canadian urban areas, the Greater Toronto Area and Ottawa-Gatineau, are described. Spatial information, including land cover fraction maps, land use and its historic changes, population density maps are compared with intra-urban surface temperature variations derived from satellite thermal imagery. Three aspects of the impacts of land cover and land use on urban land thermal characteristics are addressed, namely, (a) the relationships between surface temperature and subpixel land cover and population density (b) intra-city seasonal temperature variations and (c) the intensification of the urban heat island effect due to urban built-up land growth.  相似文献   

18.
Remote sensing and Geographic Information System (GIS) are well suited to landslide studies. The aim of this study is to prepare a landslide susceptibility map of a part of Ooty region, Tamil Nadu, India, where landslides are common. The area of the coverage is approximately 10 × 14 km in a hilly region where planting tea, vegetables and cash crops are in practice. Hence, deforestation, formation of new settlements and changing land use practices are always in progress. Land use and land cover maps are prepared from Indian Remote Sensing Satellite (IRS 1C - LISS III) imagery. Digital Elevation Model (DEM) was developed using 20 m interval contours, available in the topographic map. Field studies such as local enquiry, land use verification, landslide location identification were carried out. Analysis was carried out with GIS software by assigning rank and weights for each input data. The output shows the possible landslide areas, which are grouped for preparation of landslide susceptibility maps.  相似文献   

19.
机载多光谱LiDAR数据的地物分类方法   总被引:2,自引:1,他引:1  
潘锁艳  管海燕 《测绘学报》2018,47(2):198-207
机载多光谱LiDAR系统能够快速地获取大范围地表面上地物光谱和几何数据,并能够保证所获取的光谱与空间几何数据在空间和时间上相对完整和一致性。支持向量机(SVM)是一种基于小样本的学习方法,它避开了从归纳到演绎的传统分类过程。因此,本文提出了基于SVM多光谱LiDAR数据的地物目标分类方法。该方法首先将多个独立波段的LiDAR数据融合为单一的、包含多个波段信息的点云数据,然后将融合后的点云内插为距离影像和多光谱影像,最后利用SVM进行多光谱LiDAR数据的地物覆盖分类。通过对加拿大Optech公司的Titan机载多光谱LiDAR数据的试验证明:相对于传统的单波段LiDAR数据,多光谱LiDAR数据可以获得较好的地物分类精度;比较试验发现SVM分类方法适用于多光谱LiDAR数据的地物分类。  相似文献   

20.
Inputs to various applications and models, current global land cover (GLC) maps are based on different data sources and methods. Therefore, comparing GLC maps is challenging. Statistical comparison of GLC maps is further complicated by the lack of a reference dataset that is suitable for validating multiple maps. This study utilizes the existing Globcover-2005 reference dataset to compare thematic accuracies of three GLC maps for the year 2005 (Globcover, LC-CCI and MODIS). We translated and reinterpreted the LCCS (land cover classification system) classifier information of the reference dataset into the different map legends. The three maps were evaluated for a variety of applications, i.e., general circulation models, dynamic global vegetation models, agriculture assessments, carbon estimation and biodiversity assessments, using weighted accuracy assessment. Based on the impact of land cover confusions on the overall weighted accuracy of the GLC maps, we identified map improvement priorities. Overall accuracies were 70.8 ± 1.4%, 71.4 ± 1.3%, and 61.3 ± 1.5% for LC-CCI, MODIS, and Globcover, respectively. Weighted accuracy assessments produced increased overall accuracies (80–93%) since not all class confusion errors are important for specific applications. As a common denominator for all applications, the classes mixed trees, shrubs, grasses, and cropland were identified as improvement priorities. The results demonstrate the necessity of accounting for dissimilarities in the importance of map classification errors for different user application. To determine the fitness of use of GLC maps, accuracy of GLC maps should be assessed per application; there is no single-figure accuracy estimate expressing map fitness for all purposes.  相似文献   

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