Image Data Handling in Spatial Databases
نویسندگان
چکیده
The recent advances in database technology have enabled the development of a new generation of spatial databases, where the DBMS is able to manage spatial and non-spatial data types together. Most spatial databases can deal with vector geometries (e.g., polygons, lines and points), but have limited facilities for handling image data. However, the widespread availability of high-resolution remote sensing images has improved considerably the application of images to environmental monitoring and urban management. Therefore, it is increasingly important to build databases capable of dealing with images together with other spatial and non-spatial data types. With this motivation, this paper describes a solution for efficient handling of large image data sets in a standard object-relational database management system. By means of adequate indexing, compression and retrieval techniques, satisfactory performances can be achieved using a standard DBMS, even for very large satellite images. This work is part of the development of the TerraLib library, which aims to provide a comprehensive environment for the development of GIS applications.
منابع مشابه
Spatial Match Retrieval Using Signature Files for Iconic Image Databases - Multimedia Computing and Systems '97. Proceedings., IEEE International Conference on
In multimedia information retrieval applications, content-based image retrieval is essential for retrieving relevant multimedia documents. The purpose of our paper is to provide effective representation of images when a pixel-level original image is automatically or manually transformed into its iconic image containing meaningful graphic descriptions, called icon objects. For spatial match repr...
متن کاملSpatial SQL: A Query and Presentation Language
query language presentation language Index Terms Max J. Egenhofer National Center for Geographic Information and Analysis and Department of Surveying Engineering University of Maine Orono, ME 04469, USA [email protected] This research was partially funded by grants from NSF under No. IST 86-09123, Digital Equipment Corporation under Sponsored Research Agreement No. 414, and Intergraph Corporati...
متن کاملScalable and Visualization-oriented Clustering for Exploratory Spatial Analysis
Clustering can be applied to many fields including data mining, statistical data analysis, pattern recognition, image processing etc. In the past decade, a lot of efficient and effective new clustering algorithms have been proposed, in which famous algorithms contributed from the database community are CLARANS, BIRCH, DBSCAN, CURE, STING, CLIGUE and WaveCluster. All these algorithms try to chal...
متن کاملTowards a Model forSpatio - Temporal Schema
Schema versioning provides a mechanism for handling change in the structure of database systems and has been investigated widely, both in the context of static and temporal databases. With the growing interest in spatial and spatio-temporal data as well as the mechanisms for holding such data, the spatial context within which data is formatted also becomes an issue. This paper presents a genera...
متن کاملVHR Semantic Labeling by Random Forest Classification and Fusion of Spectral and Spatial Features on Google Earth Engine
Semantic labeling is an active field in remote sensing applications. Although handling high detailed objects in Very High Resolution (VHR) optical image and VHR Digital Surface Model (DSM) is a challenging task, it can improve the accuracy of semantic labeling methods. In this paper, a semantic labeling method is proposed by fusion of optical and normalized DSM data. Spectral and spatial featur...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2003