Spatial management of data.

Thesis. 1977. M.S.--Massachusetts Institute of Technology. Dept. of Architecture.MICROFICHE COPY AVAILABLE IN ARCHIVES AND ROTCH. VIDEOCASSETTE IN ARCHIVES AND ROTCH VISUAL COLLECTIONS.M.S

Assessing spatial information access, use and sharing for catchment management in Australia

Spatial data plays an important role in many social, environmental, economic and political decisions and is increasingly acknowledged as a national resource essential for sustainable development. One of the potential areas where spatial data can make a positive impact is for improved decision making to support catchment management. Reliable spatial data infrastructure (SDI) is needed to record the environmental, social and economic dimensions of catchment management. By building an appropriate SDI, disparate spatial data can be accessed and utilised to facilitate the exchange and sharing of spatial data between stakeholders across catchment communities. The aim of this paper is to identify the factors/variables contributing to spatial information access, sharing and use across catchment management areas and evaluate the current status of spatial information access, sharing and use among Australian states from a catchment management authority perspective. A survey method was used to collect primary data from 56 regional natural resource management (NRM) bodies responsible for catchment management in Australia. Descriptive statistics method was used to show the similarities and differences among Australian states. The key factors which influence sharing and access to spatial information are also explored. We found there is significant for spatial information access, use and sharing to contribute to SDI development

Interactive Management and Updating of Spatial Data Bases

The decision making process, whether for power plant siting, load forecasting or energy resource planning, invariably involves a blend of analytical methods and judgement. Management decisions can be improved by the implementation of techniques which permit an increased comprehension of results from analytical models. Even where analytical procedures are not required, decisions can be aided by improving the methods used to examine spatially and temporally variant data. How the use of computer aided planning (CAP) programs and the selection of a predominant data structure, can improve the decision making process is discussed

A study of spatial data management and analysis systems

The Earth Resources Laboratory of the NASA Stennis Space Center is a center of space related technology for Earth observations. It has assumed the task, in a joint effort with Jackson State University, to reach out to the science community and acquire information pertaining to characteristics of spatially oriented data processing

An intelligent user interface for browsing satellite data catalogs

A large scale domain-independent spatial data management expert system that serves as a front-end to databases containing spatial data is described. This system is unique for two reasons. First, it uses spatial search techniques to generate a list of all the primary keys that fall within a user's spatial constraints prior to invoking the database management system, thus substantially decreasing the amount of time required to answer a user's query. Second, a domain-independent query expert system uses a domain-specific rule base to preprocess the user's English query, effectively mapping a broad class of queries into a smaller subset that can be handled by a commercial natural language processing system. The methods used by the spatial search module and the query expert system are explained, and the system architecture for the spatial data management expert system is described. The system is applied to data from the International Ultraviolet Explorer (IUE) satellite, and results are given

Geospatial data integration with Semantic Web services: the eMerges approach

Geographic space still lacks the semantics allowing a unified view of spatial data. Indeed, as a unique but all encompassing domain, it presents specificities that geospatial applications are still unable to handle. Moreover, to be useful, new spatial applications need to match human cognitive abilities of spatial representation and reasoning. In this context, eMerges, an approach to geospatial data integration based on Semantic Web Services (SWS), allows the unified representation and manipulation of heterogeneous spatial data sources. eMerges provides this integration by mediating legacy spatial data sources to high-level spatial ontologies through SWS and by presenting for each object context dependent affordances. This generic approach is applied here in the context of an emergency management use case developed in collaboration with emergency planners of public agencies

Mesoscale mapping of sediment source hotspots for dam sediment management in data-sparse semi-arid catchments

Land degradation and water availability in semi-arid regions are interdependent challenges for management that are influenced by climatic and anthropogenic changes. Erosion and high sediment loads in rivers cause reservoir siltation and decrease storage capacity, which pose risk on water security for citizens, agriculture, and industry. In regions where resources for management are limited, identifying spatial-temporal variability of sediment sources is crucial to decrease siltation. Despite widespread availability of rigorous methods, approaches simplifying spatial and temporal variability of erosion are often inappropriately applied to very data sparse semi-arid regions. In this work, we review existing approaches for mapping erosional hotspots, and provide an example of spatial-temporal mapping approach in two case study regions. The barriers limiting data availability and their effects on erosion mapping methods, their validation, and resulting prioritization of leverage management areas are discussed.BMBF, 02WGR1421A-I, GROW - Verbundprojekt SaWaM: Saisonales Wasserressourcen-Management in Trockenregionen: Praxistransfer regionalisierter globaler Informationen, Teilprojekt 1DFG, 414044773, Open Access Publizieren 2019 - 2020 / Technische Universität Berli

Orchestrating the spatial planning process: from Business Process Management to 2nd generation Planning Support Systems

Metaplanning can be considered as a necessary step for improving collaboration, transparency and accountability in sustainable and democratic spatial decision-making process. This paper reports current findings on the operational implementation of the metaplanning concept developed by the authors relying on Business Process Management methods and techniques. Two solutions are presented which implement spatial planning process workflows thanks to the development of original spatial data and processing services connectors to a Business Process Management suite. These results can be considered as a first step towards the development of 2nd generation Planning Support Systems

Economics of Management Zone Delineation in Cotton Precision Agriculture

This paper develops a management zone delineation procedure based on a spatial clustering approach and evaluates its economic impact for the case of Texas cotton production. The results show that there is potential economic value in using a spatial approach to management zone delineation, but its value critically depends on the cost of collecting soil test information needed to delineate those zones.Management Zones, Exploratory Spatial Data Analysis, Site-Specific Nitrogen Management, Cotton Precision Agriculture, Crop Production/Industries, Q12,