000 03847nam a22003735i 4500
001 311977
003 MX-SnUAN
005 20160429160524.0
007 cr nn 008mamaa
008 150903s2012 ne | o |||| 0|eng d
020 _a9789400740754
_99789400740754
024 7 _a10.1007/9789400740754
_2doi
035 _avtls000367153
039 9 _a201509030658
_bVLOAD
_c201405070437
_dVLOAD
_y201402251609
_zstaff
040 _aMX-SnUAN
_bspa
_cMX-SnUAN
_erda
050 4 _aTA703-705.4
100 1 _aLakshmanan, Valliappa.
_eautor
_9353452
245 1 0 _aAutomating the Analysis of Spatial Grids :
_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 páginas 136 ilustraciones en color.
_brecurso en línea.
336 _atexto
_btxt
_2rdacontent
337 _acomputadora
_bc
_2rdamedia
338 _arecurso en línea
_bcr
_2rdacarrier
347 _aarchivo de texto
_bPDF
_2rda
490 0 _aGeotechnologies and the Environment ;
_v6
500 _aSpringer eBooks
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.
590 _aPara consulta fuera de la UANL se requiere clave de acceso remoto.
710 2 _aSpringerLink (Servicio en línea)
_9299170
776 0 8 _iEdición impresa:
_z9789400740747
856 4 0 _uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-94-007-4075-4
_zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
942 _c14
999 _c311977
_d311977