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The Defense Meteorological Satetlite Program (DMSP) is described and information is provided about the spacecraft, its environment, ground data system, global visible and infrared cloud data, The Third precipitation Intercomparison Project (PIP-3) objectives, principles of operation, serisof specifications and calibration ittformation of the SSM/I are discussed. Finally, some results of the Third Precipitation Intercornparison Project are presented. 相似文献
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The Minimum Step Linkage Algorithm and Cumulative Cost Model for Time‐Dependent Shortest Paths 
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下载免费PDF全文 Real‐word road networks are typically time‐dependent, but research on time‐dependent shortest paths (TDSPs) is not as rich as that on static shortest paths (SSPs). For large networks, some speed‐up techniques are usually applied to compute SSPs. Unfortunately, many of these techniques are impractical for TDSPs, especially the techniques requiring a precomputation because the number of time instances may be incredibly large or even infinite. Therefore, this study introduced a new TDSP technique that is able to overcome the issue of infinite time instances by utilizing network geometry alone for the pre‐computation, namely the Minimum Step Linkage (MSL) algorithm. It works with a data model called Cumulative Cost Model (CCM). The theoretical concepts of the new data model and algorithm are described, and its performances were tested and compared with existing algorithms through a series of simulations. 相似文献
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Mileva Samardžić‐Petrović Suzana Dragićević Miloš Kovačević Branislav Bajat 《Transactions in GIS》2016,20(5):718-734
Support Vector Machines (SVM) is a machine learning (ML) algorithm commonly applied to the classification of remotely sensing data and more recently for modeling land use changes. However, in most geospatial applications the current literature does not elaborate on specifications of the SVM method with respect to data sampling, attribute selection and optimal parameters choices. Therefore the main objective of this study is to present and investigate the SVM technique for modeling urban land use change. The SVM model building procedure is presented together with the detailed evaluation of the output results with respect to the choice of datasets, attributes and the change of SVM parameters. Geospatial datasets containing nine land use classes and spatial attributes for the Municipality of Zemun, Republic of Serbia were used for years 2001, 2003, 2007 and 2011. The Correlation‐based Feature Subset method, kappa coefficient, Area Under Receiver Operating Characteristic Curve (AUC) and kappa simulation were used to perform the model evaluation and compare the model outputs with the real land use datasets. The obtained results indicate that the SVM‐based models perform better when implementing balanced data sampling, reduced data sets to informative subsets of attributes and properly identify the optimal learning parameters. 相似文献
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Minna Ma Jie Dong Fawei Zhang Wenwen Cai Hongqin Li 《International Journal of Digital Earth》2018,11(11):1166-1183
Vegetation gross primary production (GPP) is an important variable for the carbon cycle on the Qinghai-Tibetan Plateau (QTP). Based on the measurements from 12 eddy covariance flux sites, we validated a light use efficiency model (i.e. EC-LUE) to evaluate the spatial-temporal patterns of GPP and the effect of environmental variables on QTP. In general, EC-LUE model performed well in predicting GPP at different time scale over QTP. Annual GPP over the entire QTP ranged from 575 to 703 Tg C, and showed a significantly increasing trend from 1982 to 2013. However, there were large spatial heterogeneities in long-term trends of GPP. Throughout the entire QTP, air temperature increase had a greater influence than solar radiation and precipitation (PREC) changes on productivity. Moreover, our results highlight the large uncertainties of previous GPP estimates due to insufficient parameterization and validations. When compared with GPP estimates of the EC-LUE model, most Coupled Model Intercomparison Project (CMIP5) GPP products overestimate the magnitude and increasing trends of regional GPP, which potentially impact the feedback of ecosystems to regional climate changes. 相似文献
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We introduce a novel scheme for automatically deriving synthetic walking (locomotion) and movement (steering and avoidance) behavior in simulation from simple trajectory samples. We use a combination of observed and recorded real‐world movement trajectory samples in conjunction with synthetic, agent‐generated, movement as inputs to a machine‐learning scheme. This scheme produces movement behavior for non‐sampled scenarios in simulation, for applications that can differ widely from the original collection settings. It does this by benchmarking a simulated pedestrian's relative behavioral geography, local physical environment, and neighboring agent‐pedestrians; using spatial analysis, spatial data access, classification, and clustering. The scheme then weights, trains, and tunes likely synthetic movement behavior, per‐agent, per‐location, per‐time‐step, and per‐scenario. To prove its usefulness, we demonstrate the task of generating synthetic, non‐sampled, agent‐based pedestrian movement in simulated urban environments, where the scheme proves to be a useful substitute for traditional transition‐driven methods for determining agent behavior. The potential broader applications of the scheme are numerous and include the design and delivery of location‐based services, evaluation of architectures for mobile communications technologies, what‐if experimentation in agent‐based models with hypotheses that are informed or translated from data, and the construction of algorithms for extracting and annotating space‐time paths in massive data‐sets. 相似文献
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Audrey Hohmann Gilles Grandjean Vincent Mardhel Gilles Schaefer Nicolas Desramaut 《Transactions in GIS》2013,17(1):78-95
A vehicle mobility estimator has been developed to produce decision aid maps for projecting civil or military forces on operational theatres. Based on the exploitation of classical geographical sources (e.g. digital elevation models, optical images, and vector databases) and thematic sources (e.g. climate, meteorological, pedological and land cover databases), the system computes speed maps for different kinds of vehicles moving both on‐road and off‐road. Such computations are realized through a ground‐vehicle interaction module that estimates the vehicle performance from experimental results, numerical simulations and empirical relationships. The system's architecture is built using a GIS interface that manages the data, the computation and the presentation layers. An operational version of this tool has been tested and validated on several operational theatres in France and in northern Africa. The results show good agreement between the predicted mobility performance of various vehicles and those observed on the field. A case study is presented to illustrate the mobility maps and demonstrate their relevance in the decision‐making chain depending on different climate contexts. A short application to itinerary optimization is presented as a promising future application. 相似文献
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Light Detection and Ranging (LiDAR) collects dense 3D topographic information in the form of points. LiDAR data can be displayed either through direct rendering of the point cloud or by generalizing features extracted through classification or segmentation. We are working in the domain of visualizing LiDAR data sets and have developed certain pipelines for visualization. These pipelines have been presented elsewhere. We present a technique for the evaluation of visualization schemes for LiDAR data, by conducting a visualization experience survey for 13 pre-processing and visualization schemes where 60 participants rated these schemes on a 10 point scale on a questionnaire. The paper establishes a ranking for the different visualization schemes described herein. Finally, this paper establishes that our heuristic-based algorithm (presented elsewhere) performs almost equal to a classification-based visualization pipeline made using professional software. We believe that the presented technique can be used to assess other geospatial visualization schemes. 相似文献
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Background
Coupled climate-carbon cycle simulations generally show that climate feedbacks amplify the buildup of CO2 under respective anthropogenic emission. The effect of climate-carbon cycle feedback is characterised by the feedback gain: the relative increase in CO2 increment as compared to uncoupled simulations. According to the results of the recent Coupled Climate-Carbon Cycle Model Intercomparison Project (C4MIP), the gain is expected to increase during the 21st century. This conclusion is not supported by the climate model developed at the A.M. Obukhov Institute of Atmospheric Physics at the Russian Academy of Sciences (IAP RAS CM). The latter model shows an eventual transient saturation of the feedback gain. This saturation is manifested in a change of climate-carbon cycle feedback gain which grows initially, attains a maximum, and then decreases, eventually tending to unity.Results
Numerical experiments with the IAP RAS CM as well as an analysis of the conceptual framework demonstrate that this eventual transient saturation results from the fact that transient climate sensitivity decreases with time.Conclusion
One may conclude that the eventual transient saturation of the climate-carbon cycle feedback is a fundamental property of the coupled climate-carbon system that manifests itself on a relevant time scale. 相似文献11.
Runoff and soil moisture are two key components of the global hydrologic cycle that should be validated at local to global scales in Earth System Models (ESMs) used for climate projection. We have evaluated the runoff and surface soil moisture output by the Community Climate System Model (CCSM) along with 8 other models from the Coupled Model Intercomparison Project (CMIP5) repository using satellite soil moisture observations and stream gauge corrected runoff products. A series of Community Land Model (CLM) runs forced by reanalysis and coupled model outputs was also performed to identify atmospheric drivers of biases and uncertainties in the CCSM. Results indicate that surface soil moisture simulations tend to be positively biased in high latitude areas by most selected CMIP5 models except CCSM, FGOALS, and BCC, which share similar land surface model code. With the exception of GISS, runoff simulations by all selected CMIP5 models were overestimated in mountain ranges and in most of the Arctic region. In general, positive biases in CCSM soil moisture and runoff due to precipitation input error were offset by negative biases induced by temperature input error. Excluding the impact from atmosphere modeling, the global mean of seasonal surface moisture oscillation was out of phase compared to observations in many years during 1985–2004. The CLM also underestimated runoff in the Amazon, central Africa, and south Asia, where soils all have high clay content. We hypothesize that lack of a macropore flow mechanism is partially responsible for this underestimation. However, runoff was overestimated in the areas covered by volcanic ash soils (i.e., Andisols), which might be associated with poor soil porosity representation in CLM. Our results indicate that CCSM predictability of hydrology could be improved by addressing the compensating errors associated with precipitation and temperature and updating the CLM soil representation. 相似文献
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面向对象的无人机遥感影像岩溶湿地植被遥感识别 总被引：1，自引：0，他引：1
以广西桂林会仙喀斯特国家湿地公园为研究区，以无人机航摄影像为数据源，综合利用面向对象的影像分析技术、随机森林算法、阈值分类方法和Boruta全相关特征变量选择算法进行岩溶湿地植被的遥感识别。结果表明：针对不同特征变量对岩溶湿地遥感识别的贡献率而言，光谱特征（DOM > DSM） > 纹理特征（DOM > DSM） > 几何特征 > 上下文变量；两个航摄影像数据集的总体分类精度都在85%以上，Kappa系数也高于0.85。本文研究结果对基于高空间分辨率无人机可见光影像的岩溶湿地植被遥感识别在特征变量选择、分割参数选择及方法选择方面具有一定的借鉴意义。 相似文献
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Mining Association Rules in Spatio-Temporal Data: An Analysis of Urban Socioeconomic and Land Cover Change 总被引：8，自引：0，他引：8
This research demonstrates the application of association rule mining to spatio‐temporal data. Association rule mining seeks to discover associations among transactions encoded in a database. An association rule takes the form A→B where A (the antecedent) and B (the consequent) are sets of predicates. A spatio‐temporal association rule occurs when there is a spatio‐temporal relationship in the antecedent or consequent of the rule. As a case study, association rule mining is used to explore the spatial and temporal relationships among a set of variables that characterize socioeconomic and land cover change in the Denver, Colorado, USA region from 1970–1990. Geographic Information Systems (GIS)‐based data pre‐processing is used to integrate diverse data sets, extract spatio‐temporal relationships, classify numeric data into ordinal categories, and encode spatio‐temporal relationship data in tabular format for use by conventional (non‐spatio‐temporal) association rule mining software. Multiple level association rule mining is supported by the development of a hierarchical classification scheme (concept hierarchy) for each variable. Further research in spatio‐temporal association rule mining should address issues of data integration, data classification, the representation and calculation of spatial relationships, and strategies for finding ‘interesting’ rules. 相似文献
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Krzysztof Stereńczak Rafal Zapłata Maciej Sztampke Radomir Bałazy 《Transactions in GIS》2017,21(2):300-316
This article presents the results and potential of using volunteered geographic information (VGI) in heritage detection. Research was completed under the project entitled “Laser Discoverers – non‐invasive examination and documentation of archeological and historical objects in the ?wi?tokrzyskie Voivodeship”, carried out as a part of the Ministry of Science and Higher Education program entitled “The Paths of Copernicus”. Within the project, strong emphasis was placed on promotional and awareness‐raising activities, to involve as many voluntary users as possible. Project participants had at their disposal a web application, which provided access to a digital terrain model (DTM) where they identified possible heritage objects. All samples of data were additionally available in eight variants of sunshine, based on the simulation of sunlight from eight directions and at a constant angle. In total, 5,989 elementary areas with dimensions of 100 × 100 m were used for the project. After conducting a field inventory, Internet users together with specialists were able to recognize several thousands of potential archaeological and historic objects. During the project, approximately 10% of those features were verified through non‐invasive (field survey) work, with 75% success. 相似文献
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Davood Akbari 《Journal of the Indian Society of Remote Sensing》2017,45(6):927-937
This paper aims to improve the accuracy and the efficiency of high resolution land cover mapping in urban area. To this end, an improved approach for classification of hyperspectral imagery is proposed and evaluated. This approach benefits from both inherent spectral and spatial information of an image. The weighted genetic (WG) algorithm is first used to obtain the subspace of hyperspectral data. The obtained features are then fed into the enhanced marker-based minimum spanning forest (EMSF) classification algorithm. In this algorithm, the markers are extracted from the classification maps obtained by both support vector machine and watershed segmentation algorithm classifiers. For this purpose, the class’s pixels with the largest population in the classification map are kept for each region of the segmentation map. Then, the most reliable classified pixels are chosen from among the exiting pixels as markers. To evaluate the efficiency of the proposed approach, three hyperspectral data sets acquired by ROSIS-03, Hymap and Hyper-Cam LWIR are used. Experimental results showed that the proposed WG–EMSF approach achieves approximately 9, 8 and 6% better overall accuracy than the original MSF-based algorithm for these data sets respectively. 相似文献
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T. Ch. Malleswara Rao G. Jai Sankar T. Roopesh Kumar 《Journal of the Indian Society of Remote Sensing》2012,40(2):191-200
The focus of this work is on developing a new hierarchical hybrid Support Vector Machine (SVM) method to address the problems
of classification of multi or hyper spectral remotely sensed images and provide a working technique that increases the classification
accuracy while lowering the computational cost and complexity of the process. The paper presents issues in analyzing large
multi/hyper spectral image data sets for dimensionality reduction, coping with intra pixel spectral variations, and selection
of a flexible classifier with robust learning process. Experiments conducted revealed that a computationally cheap algorithm
that uses Hamming distance between the pixel vectors of different bands to eliminate redundant bands was quite effective in
helping reduce the dimensionality. The paper also presents the concept of extended mathematical morphological profiles for
segregating the input pixel vectors into pure or mixed categories which will enable further computational cost reductions.
The proposed method’s overall classification accuracy is tested with IRS data sets and the Airborne Visible Infrared Imaging
Spectroradiometer Indian Pines hyperspectral benchmark data set and presented. 相似文献
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本文提出了一种新的结合多光谱和变化检测技术的多时相卫星数据集分类方法。该方法以数理统计中的最近邻法为基础,其目标函数是使得正确分类的平均概率得到最优化,即把每个分类类别看成同等重要。该新算法被应用于一个农业作物分类的研究区域,并利用覆盖该区的不同季节的SPOT和LANDSAT TM多时像影像。结果表明,与单时像影像相比,使用五个不同季节的多时像影像可以充分地提高分类精度。为了说明该方法在大尺度范围内的效果,本文选取瑞典道拉河流域作为研究区。由于不同地物的分布高度重叠,不可能得到像元水平上满意的分类精度。这就需要引进一种新的概念：像元概率分类法。基于像元的概率向量可用于判别传统分类法的可靠性并测量单个像元的不确定性（熵）。概率分类法同时提供了不同地物的面积的无偏估计,无论所感兴趣的区域的大小。这已经在不同特性的耕地试验点进行了检验。 相似文献
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Crowdsourcing the character of a place: Character‐level convolutional networks for multilingual geographic text classification 下载免费PDF全文
下载免费PDF全文 This article presents a new character‐level convolutional neural network model that can classify multilingual text written using any character set that can be encoded with UTF‐8, a standard and widely used 8‐bit character encoding. For geographic classification of text, we demonstrate that this approach is competitive with state‐of‐the‐art word‐based text classification methods. The model was tested on four crowdsourced data sets made up of Wikipedia articles, online travel blogs, Geonames toponyms, and Twitter posts. Unlike word‐based methods, which require data cleaning and pre‐processing, the proposed model works for any language without modification and with classification accuracy comparable to existing methods. Using a synthetic data set with introduced character‐level errors, we show it is more robust to noise than word‐level classification algorithms. The results indicate that UTF‐8 character‐level convolutional neural networks are a promising technique for georeferencing noisy text, such as found in colloquial social media posts and texts scanned with optical character recognition. However, word‐based methods currently require less computation time to train, so currently are preferable for classifying well‐formatted and cleaned texts in single languages. 相似文献
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Sandra G García 《Transactions in GIS》2004,8(2):245-254
This study presents a spatiotemporal analysis tool, called Shyska. This tool allows the simulation and prediction of flash floods in semiarid basins. Shyska has been developed by Geographical Information System (GIS)‐embedded functions, allowing the integration of hydrometeorological information from modern technologies of data acquisition in real time. A Digital Elevation Model (DEM) is used in order to obtain the relevant parameters from the integrated rainfall‐runoff models. Some of its most relevant modules and methodology employed for its development are described. Case studies in basins of south‐east Spain illustrate the applicability of the proposed techniques. 相似文献