000 04004nam a22004815i 4500
001 978-94-007-4075-4
003 DE-He213
005 20140220083345.0
007 cr nn 008mamaa
008 120613s2012 ne | s |||| 0|eng d
020 _a9789400740754
_9978-94-007-4075-4
024 7 _a10.1007/978-94-007-4075-4
_2doi
050 4 _aTA703-705.4
072 7 _aRB
_2bicssc
072 7 _aSCI019000
_2bisacsh
082 0 4 _a624.151
_223
100 1 _aLakshmanan, Valliappa.
_eauthor.
245 1 0 _aAutomating the Analysis of Spatial Grids
_h[electronic resource] :
_bA Practical Guide to Data Mining Geospatial Images for Human & Environmental Applications /
_cby Valliappa Lakshmanan.
264 1 _aDordrecht :
_bSpringer Netherlands :
_bImprint: Springer,
_c2012.
300 _aX, 320 p. 136 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aGeotechnologies and the Environment ;
_v6
505 0 _aAutomated Analysis of Spatial Grids: Motivation and Challenges -- -Geographic Information Systems -- -GIS Operations -- -Need for Automation -- -Spatial Grids -- -Challenges in Automated Analysis -- -Spatial Data Mining Algorithms -- Geospatial grids -- -Representation -- -Linearity of data values -- -Instrument geometry -- -Gridding point observations -- -Rasterization -- -Example Applications -- Data Structures for Spatial Grids -- -Array -- -Pixels -- -Level set -- -Topographical surface -- -Markov chain -- -Matrix -- -Parametric approximation -- -Relational structure -- -Applications -- Global and Local Image Statistics -- -Types of statistics -- -Distances -- -Distance transform -- -Probability Functions -- -Local measures -- -Example Applications -- Neighborhood and Window Operations -- -Preprocessing -- -Window operations -- -Median filter -- -Morphological operations -- -Skeletonization -- -Frequency Domain Convolution -- -Example Applications -- Identifying Objects -- -Object identification -- -Region growing -- -Region properties -- -Hysteresis -- -Active contours -- -Watershed Transform -- -Enhanced watershed -- -Contiguity-enhanced Clustering -- -Choosing an object-identification technique -- -Example Applications -- Change and Motion Estimation -- -Estimating change -- -Optical Flow -- -Object-tracking -- -Choosing a change or motion estimation technique -- -Example Applications -- Data Mining Attributes from Spatial Grids -- -Data Mining -- -A Fuzzy Logic Application -- -Supervised learning models -- -Clustering -- -Example Applications.
520 _aThe ability to create automated algorithms to process gridded spatial data is increasingly important as remotely sensed datasets increase in volume and frequency. Whether in business, social science, ecology, meteorology or urban planning, the ability to create automated applications to analyze and detect patterns in geospatial data is increasingly important. This book provides students with a foundation in topics of digital image processing and data mining as applied to geospatial datasets. The aim is for readers to be able to devise and implement automated techniques to extract information from spatial grids such as radar, satellite or high-resolution survey imagery.
650 0 _aGeography.
650 0 _aData mining.
650 0 _aGeographical information systems.
650 1 4 _aEarth Sciences.
650 2 4 _aGeotechnical Engineering & Applied Earth Sciences.
650 2 4 _aGeographical Information Systems/Cartography.
650 2 4 _aData Mining and Knowledge Discovery.
650 2 4 _aEarth Sciences, general.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9789400740747
830 0 _aGeotechnologies and the Environment ;
_v6
856 4 0 _uhttp://dx.doi.org/10.1007/978-94-007-4075-4
912 _aZDB-2-ENG
999 _c104704
_d104704