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991.
Abstract

Urban growth boundary (UGB) is a regulatory measure of local government for delineating limits of urban growth over a period of time. Land within the UGB allows urban development, while the land outside of this boundary remains primarily non-urban. The increasing popularity of UGB demands an easy and effective method to design this boundary. This article introduces a new concept, Ideal Urban Radial Proximity (IURP), to designate a spatial UGB using geoinformatics in the digital environment. The Kolkata urban agglomeration was considered to demonstrate this model. Remotely sensed imageries of three temporal instants (years 1975, 1990 and 2005) were considered to determine the information on urban extent and growth of the city. These data were then used as inputs to model the UGB for the years 2020 and 2035. The proposed model discourages scattered development and increase in urban growth rate. It preserves urban vegetation, water bodies and any other important non-urban areas within the inner city space. The IURP concept will also be useful to make the cities circular and polycentric urban blobs into a monocentric tract. Apart from the proposed model and derived results, this research also proves the potential of geoinformatics in modelling a UGB.  相似文献   
992.
Abstract

It is widely accepted that natural resources should only be sustainably exploited and utilized to effectively preserve our planet for future generations. To better manage the natural resources, and to better understand the closely linked Earth systems, the concept of Digital Earth has been strongly promoted since US Vice President Al Gore's speech in 1998. One core element of Digital Earth is the use and integration of remote sensing data. Only satellite imagery can cover the entire globe repeatedly at a sufficient high-spatial resolution to map changes in land cover and land use, but also to detect more subtle changes related for instance to climate change. To uncover global change effects on vegetation activity and phenology, it is important to establish high quality time series characterizing the past situation against which the current state can be compared. With the present study we describe a time series of vegetation activity at 10-daily time steps between 1998 and 2008 covering large parts of South America at 1 km spatial resolution. Particular emphasis was put on noise removal. Only carefully filtered time series of vegetation indices can be used as a benchmark and for studying vegetation dynamics at a continental scale. Without temporal smoothing, subtle spatio-temporal patterns in vegetation composition, density and phenology would be hidden by atmospheric noise and undetected clouds. Such noise is immanent in data that have undergone solely a maximum value compositing. Within the present study, the Whittaker smoother (WS) was applied to a SPOT VGT time series. The WS balances the fidelity to the observations with the roughness of the smoothed curve. The algorithm is extremely fast, gives continuous control over smoothness with only one parameter, and interpolates automatically. The filtering efficiently removed the negatively biased noise present in the original data, while preserving the overall shape of the curves showing vegetation growth and development. Geostatistical variogram analysis revealed a significantly increased signal-to-noise ratio compared to the raw data. Analysis of the data also revealed spatially consistent key phenological markers. Extracted seasonality parameters followed a clear meridional trend. Compared to the unfiltered data, the filtered time series increased the separability of various land cover classes. It is thus expected that the data set holds great potential for environmental and vegetation related studies within the frame of Digital Earth.  相似文献   
993.
The creation of a quality Digital Terrain Model (DTM) is essential for representing and analyzing the Earth in a digital form. The continuous improvements in the acquisition and the potential of airborne Light Detection and Ranging (LiDAR) data are increasing the range of applications of this technique to the study of the Earth surface. The aim of this study was to determine the optimal parameters for calculating a DTM by using an iterative algorithm to select minimum elevations from LiDAR data in a steep mountain area with shrub vegetation. The parameters were: input data type, analysis window size, and height thresholds. The effects of slope, point density, and vegetation on DTM accuracy were also analyzed. The results showed that the lowest root mean square error (RMSE) was obtained with an analysis window size of 10 m, 5 m, and 2.5 m, rasterized data as input data, and height thresholds equal to or greater than 1.5 m. These parameters showed a RMSE of 0.19 m. When terrain slope varied from 0–10% to 50–60%, the RMSE increased by 0.11 m. The RMSE decreased by 0.06 m when point density was increased from 4 to 8 points/m2, and increased by 0.05 m in dense vegetation areas.  相似文献   
994.
This paper is an attempt to introduce the role of earth observation technology and a type of digital earth processing in mineral resources exploration and assessment. The sub-pixel distribution and quantity of alteration minerals were mapped using linear spectral unmixing (LSU) and mixture tuned matched filtering (MTMF) algorithms in the Sarduiyeh area, SE Kerman, Iran, using the visible-near infrared (VNIR) and short wave infrared (SWIR) bands of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument and the results were compared to evaluate the efficiency of methods. Three groups of alteration minerals were identified: (1) pyrophylite-alunite (2) sericite-kaolinite, and (3) chlorite-calcite-epidote. Results showed that high abundances within pixels were successfully corresponded to the alteration zones. In addition, a number of unreported altered areas were identified. Field observations and X-ray diffraction (XRD) analysis of field samples confirmed the dominant mineral phases identified remotely. Results of LSU and MTMF were generally similar with overall accuracy of 82.9 and 90.24%, respectively. It is concluded that LSU and MTMF are suitable for sub-pixel mapping of alteration minerals and when the purpose is identification of particular targets, rather than all the elements in the scene, the MTMF algorithm could be proposed.  相似文献   
995.
Abstract

This study employs visible-near infrared and short wave infrared datasets of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) to map salt diapirs and salt diapir-affected areas using Multi-Layer Perceptron (MLP) in the Zagros Folded Belt, Iran, and introduces the role of earth observation technology and a type of digital earth processing in lithological mapping and geo-environmental impact assessment. MLP neural network model with several learning rates between 0.01 and 0.1 was carried out on ASTER L1B data, and the results were compared using confusion matrices. The most appropriate classification image for L1B input to MLP was produced by learning rate of 0.01 with Kappa coefficient of 0.90 and overall accuracy of 92.54%. The MLP result of input data set mapped lithological units of salt diapirs and demonstrated affected areas at the southern and western parts of the Konarsiah and Jahani diapirs, respectively. Field observations and X-ray diffraction analyses of field samples confirmed the dominant mineral phases identified remotely. It is concluded that MLP is an efficient approach for mapping salt diapirs and salt-affected areas.  相似文献   
996.
Abstract

The geospatial sciences face grand information technology (IT) challenges in the twenty-first century: data intensity, computing intensity, concurrent access intensity and spatiotemporal intensity. These challenges require the readiness of a computing infrastructure that can: (1) better support discovery, access and utilization of data and data processing so as to relieve scientists and engineers of IT tasks and focus on scientific discoveries; (2) provide real-time IT resources to enable real-time applications, such as emergency response; (3) deal with access spikes; and (4) provide more reliable and scalable service for massive numbers of concurrent users to advance public knowledge. The emergence of cloud computing provides a potential solution with an elastic, on-demand computing platform to integrate – observation systems, parameter extracting algorithms, phenomena simulations, analytical visualization and decision support, and to provide social impact and user feedback – the essential elements of the geospatial sciences. We discuss the utilization of cloud computing to support the intensities of geospatial sciences by reporting from our investigations on how cloud computing could enable the geospatial sciences and how spatiotemporal principles, the kernel of the geospatial sciences, could be utilized to ensure the benefits of cloud computing. Four research examples are presented to analyze how to: (1) search, access and utilize geospatial data; (2) configure computing infrastructure to enable the computability of intensive simulation models; (3) disseminate and utilize research results for massive numbers of concurrent users; and (4) adopt spatiotemporal principles to support spatiotemporal intensive applications. The paper concludes with a discussion of opportunities and challenges for spatial cloud computing (SCC).  相似文献   
997.
Abstract

Changing environmental and socio-economic conditions make land degradation, a major concern in Central and East Asia. Globally satellite imagery, particularly Normalized Difference Vegetation Index (NDVI) data, has proved an effective tool for monitoring land cover change. This study examines 33 grassland water points using vegetation field studies and remote sensing techniques to track desertification on the Mongolian plateau. Findings established a significant correlation between same-year field observation (line transects) and NDVI data, enabling an historical land cover perspective to be developed from 1998 to 2006. Results show variable land cover patterns in Mongolia with a 16% decrease in plant density over the time period. Decline in cover identified by NDVI suggests degradation; however, continued annual fluctuation indicates desertification – irreversible land cover change – has not occurred. Further, in situ data documenting greater cover near water points implies livestock overgrazing is not causing degradation at water sources. In combination of the two research methods – remote sensing and field surveys – strengthen findings and provide an effective way to track desertification in dryland regions.  相似文献   
998.
Abstract

The vision of a Digital Earth calls for more dynamic information systems, new sources of information, and stronger capabilities for their integration. Sensor networks have been identified as a major information source for the Digital Earth, while Semantic Web technologies have been proposed to facilitate integration. So far, sensor data are stored and published using the Observations & Measurements standard of the Open Geospatial Consortium (OGC) as data model. With the advent of Volunteered Geographic Information and the Semantic Sensor Web, work on an ontological model gained importance within Sensor Web Enablement (SWE). In contrast to data models, an ontological approach abstracts from implementation details by focusing on modeling the physical world from the perspective of a particular domain. Ontologies restrict the interpretation of vocabularies toward their intended meaning. The ongoing paradigm shift to Linked Sensor Data complements this attempt. Two questions have to be addressed: (1) how to refer to changing and frequently updated data sets using Uniform Resource Identifiers, and (2) how to establish meaningful links between those data sets, that is, observations, sensors, features of interest, and observed properties? In this paper, we present a Linked Data model and a RESTful proxy for OGC's Sensor Observation Service to improve integration and inter-linkage of observation data for the Digital Earth.  相似文献   
999.
In this article, an extensive inventory in the literature of water erosion modelling from a geospatial point of view is conducted. Concepts of scale, spatiality and complexity are explored and clarified in a theoretical background. Use of Geographic Information Systems (GIS) is pointed out as facilitating data mixing and model rescaling and thus increasing complexity in data-method relations. Spatial scale, temporal scale and spatial methodologies are addressed as the most determining geospatial properties underlying water erosion modelling. Setting these properties as classification criteria, 82 water erosion models are identified and classified into eight categories. As a result, a complete overview of water erosion models becomes available in a single table. The biggest share of the models is found in the category of the mechanistic pathway-type event-based models for watershed to landscape scales. In parallel, geospatial innovations that could be considered as milestones in water erosion modelling are highlighted and discussed. An alphabetical list of all models is also listed in the Appendix. For manipulating scale efficiently, two promising spatial theories are suggested for further exploitation in the future such as hierarchy theory and fractals theory. Regarding erosion applications, uncertainty analysis within GIS is considered to be necessary for further improving performance of erosion models.  相似文献   
1000.
With the increased use of locational information, spatial location referencing and coding methods have become much more important to the mining of both geographical and nongeographical data in digital earth system. Unfortunately, current methods of geocoding, based on reverse lookup of coordinates for a given address, have proven too lossy with respect to administrative and socioeconomic data. This paper proposes a spatial subdivision and geocoding model based on spatial address regional tessellation (SART). Given a hierarchical address object definition, and based on the ‘region of influence’ characteristics of an address, SART creates multiresolution spatial subdivisions by irregular and continuous address regions. This model reflects most of the geographical features and many of the social and economic implications for a given address. It also better reflects the way people understand addresses and spatial locations. We also propose an appropriate method of geocoding for standard addresses (SART-GC). The codes generated by this method can record address footprints, hierarchical relationships, and spatial scales in a single data structure. Finally, by applying our methods to the Shibei District of Qingdao, we demonstrate the suitability of SART-GC for multi-scale spatial information representation in digital earth systems.  相似文献   
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