By Peter Atkinson, Giles M. Foody, Steven E. Darby, Fulong Wu
Papers from a September 2003 convention, offered right here, tackle distant sensing, spatially disbursed dynamic modeling of land floor strategies, and concrete dynamics. individuals in geocomputation, spatial research, GIS, and environmental modeling learn contemporary advancements in assembling geographical details, and speak about the administration, merits, and demanding situations of modeling dynamic methods in 3 dimensions. Papers are in sections on distant sensing, actual techniques, and human tactics. The paintings accrued right here illustrates the significance of incorporating interdisciplinary sciences to hone GIS features, percentage information and representations, and speak successfully via visualization.
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Additional info for GeoDynamics (2004)(en)(440s)
1 11 13 14 17 21 24 24 25 INTRODUCTION The value of any geodata set depends on its fitness for use. A critical measure of the fitness is the data quality, knowledge of which may significantly increase the confidence of the user in explaining and defending the results derived from analyses with the map (LMIC, 1999). Therefore, extensive information about the quality of geodata input to a GeoDynamics analysis and modeling process (refer chapters in Section II) is essential.
1 29 31 31 33 35 36 37 38 INTRODUCTION Thematic raster maps are digital images where each pixel is assigned to one of a k discrete classes. This type of maps is ubiquitous, and numerous remote sensing applications yield products such as maps of land cover, vegetation, or soil, all in the format of thematic raster maps. In remote sensing applications, aggregation is a process of laying a grid of cells on the image or raster map (cell size > pixel size), and defining the larger cells as the basic units of the new map.
2002. Status of land cover classification accuracy assessment. Remote Sensing of Environment, 80, 185–201. M. , 1996. Incorporating mixed pixel in the training, allocation and testing stages of supervised classification. Pattern Recognition Letters, 17, 1389–1398. M. , 1994. Sub-pixel land cover composition estimation using a linear mixture model and fuzzy membership functions. International Journal of Remote Sensing, 15, 619–631. , 1992. Derivation and applications of probabilistic measures of class membership from maximum likelihood classification.
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