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1.
利用雷达干涉数据进行城市不透水层百分比估算 总被引：2，自引：0，他引：2
人工不透水层是城市地区的重要特征.作为城市生态环境的关键指数,不透水层百分比(Impervious Surfaces Percentage, ISP)常用于城市水文过程模拟、水质面源污染及城市专题制图等研究中.本文利用ERS-1/2 重复轨道雷达干涉数据,采用分类与回归树(CART)算法探究了雷达遥感在城市ISP估算中的可行性和潜力,并与SPOT5 HRG光学遥感图像的估算结果进行了分析比较.香港九龙港岛实验区的初步研究结果表明,雷达干涉数据在城市不透水层研究中具有一定的应用潜力,特别是裸土和稀疏植被的ISP估算结果要好于光学遥感,这主要得益于雷达干涉数据(特别是长时间相干图像)在人工建筑物和裸土或稀疏植被之间具有很强的区分能力,另外,雷达干涉数据和光学遥感数据间的融合能够提高ISP估算精度. 相似文献
2.
Quantifying impervious surfaces in urban and suburban areas is a key step toward a sustainable urban planning and management strategy. With the availability of fine-scale remote sensing imagery, automated mapping of impervious surfaces has attracted growing attention. However, the vast majority of existing studies have selected pixel-based and object-based methods for impervious surface mapping, with few adopting sub-pixel analysis of high spatial resolution imagery. This research makes use of a vegetation-bright impervious-dark impervious linear spectral mixture model to characterize urban and suburban surface components. A WorldView-3 image acquired on May 9th, 2015 is analyzed for its potential in automated unmixing of meaningful surface materials for two urban subsets and one suburban subset in Toronto, ON, Canada. Given the wide distribution of shadows in urban areas, the linear spectral unmixing is implemented in non-shadowed and shadowed areas separately for the two urban subsets. The results indicate that the accuracy of impervious surface mapping in suburban areas reaches up to 86.99%, much higher than the accuracies in urban areas (80.03% and 79.67%). Despite its merits in mapping accuracy and automation, the application of our proposed vegetation-bright impervious-dark impervious model to map impervious surfaces is limited due to the absence of soil component. To further extend the operational transferability of our proposed method, especially for the areas where plenty of bare soils exist during urbanization or reclamation, it is still of great necessity to mask out bare soils by automated classification prior to the implementation of linear spectral unmixing. 相似文献
3.
This paper aims at developing a methodology for assessing urban dynamics in urban catchments and the related impact on hydrology. Using a multi-temporal remote sensing supported hydrological modelling approach an improved simulation of runoff for urban areas is targeted. A time-series of five medium resolution urban masks and corresponding sub-pixel sealed surface proportions maps was generated from Landsat and SPOT imagery. The consistency of the urban mask and sealed surface proportion time-series was imposed through an urban change trajectory analysis. The physically based rainfall-runoff model WetSpa was successfully adapted for integration of remote sensing derived information of detailed urban land use and sealed surface characteristics.A first scenario compares the original land-use class based approach for hydrological parameterisation with a remote sensing sub-pixel based approach. A second scenario assesses the impact of urban growth on hydrology. Study area is the Tolka River basin in Dublin, Ireland.The grid-based approach of WetSpa enables an optimal use of the spatially distributed properties of remote sensing derived input.Though change trajectory analysis remains little used in urban studies it is shown to be of utmost importance in case of time series analysis. The analysis enabled to assign a rational trajectory to 99% of all pixels. The study showed that consistent remote sensing derived land-use maps are preferred over alternative sources (such as CORINE) to avoid over-estimation errors, interpretation inconsistencies and assure enough spatial detail for urban studies. Scenario 1 reveals that both the class and remote sensing sub-pixel based approaches are able to simulate discharges at the catchment outlet in an equally satisfactory way, but the sub-pixel approach yields considerably higher peak discharges. The result confirms the importance of detailed information on the sealed surface proportion for hydrological simulations in urbanised catchments. In addition a major advantage with respect to hydrological parameterisation using remote sensing is the fact that it is site- and period-specific. Regarding the assessment of the impact of urbanisation (scenario 2) the hydrological simulations revealed that the steady urban growth in the Tolka basin between 1988 and 2006 had a considerable impact on peak discharges. Additionally, the hydrological response is quicker as a result of urbanisation. Spatially distributed surface runoff maps identify the zones with high runoff production.It is evident that this type of information is important for urban water management and decision makers. The results of the remote sensing supported modelling approach do not only indicate increased volumes due to urbanisation, but also identifies the locations where the most relevant impacts took place. 相似文献
4.
Mining Trajectory Data and Geotagged Data in Social Media for Road Map Inference 总被引：1，自引：0，他引：1 
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下载免费PDF全文 As mapping is costly and labor‐intensive work, government mapping agencies are less and less willing to absorb these costs. In order to reduce the updating cycle and cost, researchers have started to use user generated content (UGC) for updating road maps; however, the existing methods either rely heavily on manual labor or cannot extract enough information for road maps. In view of the above problems, this article proposes a UGC‐based automatic road map inference method. In this method, data mining techniques and natural language processing tools are applied to trajectory data and geotagged data in social media to extract not only spatial information – the location of the road network – but also attribute information – road class and road name – in an effort to create a complete road map. A case study using floating car data, collected by the National Commercial Vehicle Monitoring Platform of China, and geotagged text data from Flickr and Google Maps/Earth, validates the effectiveness of this method in inferring road maps. 相似文献
5.
Youshui Zhang Inakwu O.A. Odeh Chunfeng Han 《International Journal of Applied Earth Observation and Geoinformation》2009
As more than 50% of the human population are situated in cities of the world, urbanization has become an important contributor to global warming due to remarkable urban heat island (UHI) effect. UHI effect has been linked to the regional climate, environment, and socio-economic development. In this study, Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) imagery, respectively acquired in 1989 and 2001, were utilized to assess urban area thermal characteristics in Fuzhou, the capital city of Fujian province in south-eastern China. As a key indicator for the assessment of urban environments, sub-pixel impervious surface area (ISA) was mapped to quantitatively determine urban land-use extents and urban surface thermal patterns. In order to accurately estimate urban surface types, high-resolution imagery was utilized to generate the proportion of impervious surface areas. Urban thermal characteristics was further analysed by investigating the relationships between the land surface temperature (LST), percent impervious surface area, and two indices, the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Built-up Index (NDBI). The results show that correlations between NDVI and LST are rather weak, but there is a strong positive correlation between percent ISA, NDBI and LST. This suggests that percent ISA, combined with LST, and NDBI, can quantitatively describe the spatial distribution and temporal variation of urban thermal patterns and associated land-use/land-cover (LULC) conditions. 相似文献
6.
《制图学和地理信息科学》2013,40(4):369-380
Insufficient research has been done on integrating artificial-neural-network-based cellular automata (CA) models and constrained CA models, even though both types have been studied for several years. In this paper, a constrained CA model based on an artificial neural network (ANN) was developed to simulate and forecast urban growth. Neural networks can learn from available urban land-use geospatial data and thus deal with redundancy, inaccuracy, and noise during the CA parameter calibration. In the ANN-Urban-CA model we used, a two-layer Back-Propagation (BP) neural network has been integrated into a CA model to seek suitable parameter values that match the historical data. Each cell's probability of urban transformation is determined by the neural network during simulation. A macro-scale socio-economic model was run together with the CA model to estimate demand for urban space in each period in the future. The total number of new urban cells generated by the CA model was constrained, taking such exogenous demands as population forecasts into account. Beijing urban growth between 1980 and 2000 was simulated using this model, and long-term (2001–2015) growth was forecast based on multiple socio-economic scenarios. The ANN-Urban-CA model was found capable of simulating and forecasting the complex and non-linear spatial-temporal process of urban growth in a reasonably short time, with less subjective uncertainty. 相似文献
7.
This study developed an impervious surface fraction algorithm (ISFA) for automatic mapping of urban areas from Landsat data. We processed the data for 2001 and 2014 to trace the urbanization of Tegucigalpa, the capital city of Honduras, using a four-step procedure: (1) data pre-processing to perform image reflectance normalization, (2) quantification of impervious surface area (ISA) using ISFA, (3) accuracy assessment of mapping results and (4) change analysis of urban growth. The mapping results compared with the ground reference data confirmed the validity of ISFA for automatic delineation of ISA in the study region. The overall accuracy and Kappa coefficient achieved for 2001 were 92.8% and 0.86, while the values for 2014 were 91.8% and 0.84, respectively. The results of change detection between the classification maps indicated that ISA increased approximately 1956.7 ha from 2001 to 2014, mainly attributing to the increase of the city’s population. 相似文献
8.
10.
《International Journal of Digital Earth》2013,6(2):89-108
Abstract A methodology is presented for estimating percent coverage of impervious surface (IS) and forest cover (FC) within Landsat thematic mapper (TM) pixels of urban areas. High-resolution multi-spectral images from Quickbird (QB) play a key role in the sub-pixel mapping process by providing information on the spatial distributions of ISs and FCs at 2.4 m ground sampling intervals. Thematic classifications, also derived from the Landsat imagery, have then been employed to define relationships between 30 m Landsat-derived greenness values and percent IS and FC. By also utilizing land cover/land use classification derived from Landsat and defining unique relationships for urban sub-classes (i.e. residential, commercial/industrial, open land), confusion between impervious and fallow agricultural lands has been overcome. Test results are presented for Ottawa-Gatineau, an urban area that encompasses many aspects typical of the North American urban landscape. Multiple QB scenes have been acquired for this urban centre, thereby allowing us to undertake an in-depth study of the error budgets associated with the fractional inference process. 相似文献
11.
Sub-pixel mapping is a promising technique for producing a spatial distribution map of different categories at the sub-pixel scale by using the fractional abundance image as the input. The traditional sub-pixel mapping algorithms based on single images often have uncertainty due to insufficient constraint of the sub-pixel land-cover patterns within the low-resolution pixels. To improve the sub-pixel mapping accuracy, sub-pixel mapping algorithms based on auxiliary datasets, e.g., multiple shifted images, have been designed, and the maximum a posteriori (MAP) model has been successfully applied to solve the ill-posed sub-pixel mapping problem. However, the regularization parameter is difficult to set properly. In this paper, to avoid a manually defined regularization parameter, and to utilize the complementary information, a novel adaptive MAP sub-pixel mapping model based on regularization curve, namely AMMSSM, is proposed for hyperspectral remote sensing imagery. In AMMSSM, a regularization curve which includes an L-curve or U-curve method is utilized to adaptively select the regularization parameter. In addition, to take the influence of the sub-pixel spatial information into account, three class determination strategies based on a spatial attraction model, a class determination strategy, and a winner-takes-all method are utilized to obtain the final sub-pixel mapping result. The proposed method was applied to three synthetic images and one real hyperspectral image. The experimental results confirm that the AMMSSM algorithm is an effective option for sub-pixel mapping, compared with the traditional sub-pixel mapping method based on a single image and the latest sub-pixel mapping methods based on multiple shifted images. 相似文献
12.
《The Cartographic journal》2013,50(3):233-241
AbstractThere have been numerous efforts over many years to map or delineate urban locations and features in the Kathmandu Valley of Nepal. This study acquired 27 land useland cover maps for the Valley or the urban portions of the Valley. Those maps vary greatly in their mapping parameters. The objectives of this study were to first conduct a cartographic comparison of the differences in the creation and content of the maps and then do an analysis of the urban changes in the Valley based upon the maps. The maps for the Valley have differed in their source materials, the amount of field work involved, scale and minimum mapping units, classifications used, definitions of classes and coordinate systems. Source materials have included various scales and formats of aerial photography and different satellite systems. The most difficult issue in comparing the maps is the varied classification systems and definitions. The same feature will be classified differently from map to map. This is particularly an issue for institutional features such as temples, palaces, educational facilities, open public space and governmental sites. Definitions of residential areas are also not consistent. Even with the differences in mapping parameters, considerable useful information can be obtained by comparing these maps. These include a simply documentation of the urban extent and the generally resulting loss in agricultural lands. There was an increase in urban extent from 22 to 83km2 between 1955 and 2000. Urban expansion has also changed from occurring on the upland river terraces or tars to the floodplains. Finally, while not directly documented in these maps, the tremendous pace of urban growth has resulted in multiple infrastructure and environmental challenges. 相似文献
13.
This study aims to prepare a detailed GIS-based geomorphological map accompanied with landfill sites of Dhaka city area which can be used for multipurpose functionality. Attainment of the geomorphological map is based upon interpretation of the oldest available aerial photographs (1:40,000) and contemporary topographic maps (1:8000) which reflect almost pre-urban ground of Dhaka. Randomly distributed 160 boreholes have been used to prepare representative soil profiles (RSP) to identify the near-surface lithology of the geomorphological units. The study reveals that 13 out of 18 low-lying geomorphic units, comprising 65% of the total area demand landfill practices for urban development. Landfill sites have been merged with urban growth on each low-lying geomorphic unit using a spatially enhanced fused image of IRS-1D PAN and ETM+ bands 5, 4 and 3, acquired February 2000 and 2002, respectively. We found that 43% area of the total low-lying geomorphic units experience fill practices so far. The fill sites have been differentiated into four classes based on their relative thickness. Integration of fill classes with geomorphological map shows the urban dynamics of Dhaka city area till 2002. Due to GIS integration, this map can be rapidly updated to demonstrate temporal modifications in urban ground. It can be used effectively in different geomorphological hazard mapping and urban land-use practices. 相似文献
14.
目前,地图的扫描数字化已成为GIS领域中获取数据信息的主要手段之一。应用MapGIS6.7软件,以丰富理论知识及大量实践为基础,对原始扫描地图进行校正过程中发现的一些问题及解决方案进行探讨,最后得出一套较为科学准确的地质图校正的方法流程。 相似文献
15.
通过对当前大比例尺地形图更新存在问题的分析,对测绘大数据时代的大比例尺地形图在数据采集手段、加强历史数据的挖掘和利用、建立地图综合缩编系统、开展城市地下空间测绘等4个方面进行了探讨,总结了测绘大数据时代的大比例尺地形图更新机制和技术方法。 相似文献
16.
Impervious surfaces have a significant impact on urban runoff, groundwater, base flow, water quality, and climate. Increase in Anthropogenic Impervious Surfaces (AIS) for a region is a true representation of urban expansion. Monitoring of AIS in an urban region is helpful for better urban planning and resource management. Cost effective and efficient maps of AIS can be obtained for larger areas using remote sensing techniques. In the present study, extraction of AIS has been carried out using Double window Flexible Pace Search (DFPS) from a new index named as Normalized Difference Impervious Surface Index (NDAISI). NDAISI is developed by enhancing Biophysical Composition Index (BCI) in two stages using a new Modified Normalized Difference Soil Index (MNDSI). MNDSI has been developed from Band 7 and Band 8 (PAN) of Landsat 8 data. In comparison to existing impervious surface extraction methods, the new NDAISI approach is able to improve Spectral Discrimination Index (SDI) for bare soil and AIS significantly. Overall accuracy of mapping of AIS, using NDAISI approach has been found to be increased by nearly 23% when compared with existing impervious surface extraction methods. 相似文献
17.
Outputs of soft classification inherently contain uncertainty. As an input for the sub-pixel mapping (SPM) method, the uncertainty is propagated to SPM result especially the boundary region between classes. Therefore, reducing the uncertainty within the outputs of soft classification is worth exploring. This paper firstly utilizes multiple-point simulation (MPS) through training images for characterizing the spatial structural properties of a surface object/class. Consequently, MPS results are used to increase the accuracy of the fraction image of the surface object/class. The improved fraction image then inputs to the SPM method for producing the land cover map with finer spatial resolution. In order to validate the proposed method, a remotely sensed image from Landsat TM 30 m over the Qianyanzhou red earth hill region in China is used. This experimental study not only compares the results from SPM with improved fraction images with MPS and results from SPM with original fraction images, but also investigates the performances of different soft classifiers. It has been demonstrated that this proposed method is an effective way to reduce the uncertainty in outputs of different soft classification, increase the recognition accuracies of boundary regions and thus increase the accuracies of SPM simulated images. 相似文献
18.
Operational flood mitigation and flood modeling activities benefit from a rapid and automated flood mapping procedure. A valuable information source for such a flood mapping procedure can be remote sensing synthetic aperture radar (SAR) data. In order to be reliable, an objective characterization of the uncertainty associated with the flood maps is required.This work focuses on speckle uncertainty associated with the SAR data and introduces the use of a non-parametric bootstrap method to take into account this uncertainty on the resulting flood maps. From several synthetic images, constructed through bootstrapping the original image, flood maps are delineated. The accuracy of these flood maps is also evaluated w.r.t. an independent validation data set, obtaining, in the two test cases analyzed in this paper, F-values (i.e. values of the Jaccard coefficient) comprised between 0.50 and 0.65. This method is further compared to an image segmentation method for speckle analysis, with which similar results are obtained. The uncertainty analysis of the ensemble of bootstrapped synthetic images was found to be representative of image speckle, with the advantage that no segmentation and speckle estimations are required.Furthermore, this work assesses to what extent the bootstrap ensemble size can be reduced while remaining representative of the original ensemble, as operational applications would clearly benefit from such reduced ensemble sizes. 相似文献
19.
In this study, we developed a prior-knowledge-based spectral mixture analysis (PKSMA) to map impervious surfaces by using endmembers derived separately for high- and low-density urban regions. First, an urban area was categorized into high- and low-density urban areas, using a multi-step classification method. Next, in high-density urban areas that were assumed to have only vegetation and impervious surfaces (ISs), the vegetation–impervious model (V–I) was used in a spectral mixture analysis (SMA) with three endmembers: vegetation, high albedo, and low albedo. In low-density urban areas, the vegetation–impervious–soil model (V–I–S) was used in an SMA analysis with four endmembers: high albedo, low albedo, soil, and vegetation. The fraction of IS with high and low albedo in each pixel was combined to produce the final IS map. The root mean-square error (RMSE) of the IS map produced using PKSMA was about 11.0%, compared to 14.52% only using four-endmember SMA. Particularly in high-density urban areas, PKSMA (RMSE = 6.47%) showed better performance than four-endmember (15.91%). The results indicate that PKSMA can improve IS mapping compared to traditional SMA by using appropriately selected endmembers and is particularly strong in high-density urban areas. 相似文献
20.
The mixed pixel problem affects the extraction of land cover information from remotely sensed images. Super-resolution mapping (SRM) can produce land cover maps with a finer spatial resolution than the remotely sensed images, and reduce the mixed pixel problem to some extent. Traditional SRMs solely adopt a single coarse-resolution image as input. Uncertainty always exists in resultant fine-resolution land cover maps, due to the lack of information about detailed land cover spatial patterns. The development of remote sensing technology has enabled the storage of a great amount of fine spatial resolution remotely sensed images. These data can provide fine-resolution land cover spatial information and are promising in reducing the SRM uncertainty. This paper presents a spatial–temporal Hopfield neural network (STHNN) based SRM, by employing both a current coarse-resolution image and a previous fine-resolution land cover map as input. STHNN considers the spatial information, as well as the temporal information of sub-pixel pairs by distinguishing the unchanged, decreased and increased land cover fractions in each coarse-resolution pixel, and uses different rules in labeling these sub-pixels. The proposed STHNN method was tested using synthetic images with different class fraction errors and real Landsat images, by comparing with pixel-based classification method and several popular SRM methods including pixel-swapping algorithm, Hopfield neural network based method and sub-pixel land cover change mapping method. Results show that STHNN outperforms pixel-based classification method, pixel-swapping algorithm and Hopfield neural network based model in most cases. The weight parameters of different STHNN spatial constraints, temporal constraints and fraction constraint have important functions in the STHNN performance. The heterogeneity degree of the previous map and the fraction images errors affect the STHNN accuracy, and can be served as guidances of selecting the optimal STHNN weight parameters. 相似文献