RASTER DATA PARTITIONING FOR SUPPORTING DISTRIBUTED GIS PROCESSING
نویسندگان
چکیده
منابع مشابه
Raster Data Partitioning for Supporting Distributed Gis Processing
In the geospatial sector big data concept also has already impact. Several studies facing originally computer science techniques applied in GIS processing of huge amount of geospatial data. In other research studies geospatial data is considered as it were always been big data (Lee and Kang, 2015). Nevertheless, we can prove data acquisition methods have been improved substantially not only the...
متن کاملParallel and Distributed GIS for Processing Geo-data: An Overview
Geographic Information System (GIS) is a collection of applications whose tasks include (collaborating with other systems and) gathering geographic data, store and process spatio–temporal data (geo-data) and share the derived geographic knowledge with the users and other applications. Some of the most important routine applications of GIS are spatial analysis, digital elevation model (DEM) anal...
متن کاملData Structures and Algorithms for Raster Data Processing
The digital image raster data structure is proving to be a useful representation for geographic information from the viewpoints of both storage and processing. Several components of this trend can be identified: the development of scanners such as Landsat for remote sensing of the Earth's surface, the development of a raster representation for terrain (elevation) data, the spread of image proce...
متن کاملGIS ─ application to make geomorphometric analysis in raster data
We present an approach to identify some geomorphometrical characteristics of raster geo-images based on a Geographic Information System (GIS). The characteristic identification involves the generation of raster layers, topographic ruggedness and drainage density. In a sense, the topographic ruggedness is used to express the amount of elevation difference between adjacent cells of the Digital El...
متن کاملDistributed Edge Partitioning for Graph Processing
The availability of larger and larger graph datasets, growing exponentially over the years, has created several new algorithmic challenges to be addressed. Sequential approaches have become unfeasible, while interest on parallel and distributed algorithms has greatly increased. Appropriately partitioning the graph as a preprocessing step can improve the degree of parallelism of its analysis. A ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
سال: 2015
ISSN: 2194-9034
DOI: 10.5194/isprsarchives-xl-3-w3-543-2015