Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/40801
Title: The development of the geographic image cognition approach on studying land degradation
Authors: Wang, J
Chen, YQ 
Liu, AX
He, T
Lv, CY
Keywords: Earth sciences
Remote sensing
Issue Date: 2010
Publisher: SPIE-International Society for Optical Engineering
Source: Proceedings of SPIE : the International Society for Optical Engineering, 2010, v. 7676, 76760U How to cite?
Journal: Proceedings of SPIE : the International Society for Optical Engineering 
Abstract: For the extraction of land degradation information we should use not only information on climate, soil, vegetation, physiognomy, land use and its productivities, but also the knowledge and methodologies of geosciences. It is of importance to study some conceptual issues about geographic image cognition (GEOIC) on studying land degradation. The study is to discuss some conceptual issues and the theoretical background of the approach of geographic image cognition (GEOIC) on studying land degradation for building its methodological framework. Some issues concerning the approach of GEOIC on studying land degradation, especially the factors of impacting human's visual cognition, were discussed. The results indicated that the GEOIC is the objectification cognition on remote sensing images and multi-source information using geo-knowledge. As an integrated approach, it is the extension of the methodology of OBIA. The key objective of the GEOIC on studying land degradation is to simulate the function and process of the visual interpretation by experts, and extract spatial features, spatial object and spatial pattern of land degradation under the cognition mode of feature-object-pattern from remote sensing images and multi-source information. The methodology of the GEOIC is realized through the segmentation of geo-objects or meaningful image objects using remote sensing information, geographic information, vegetation, soil, and other ancillary information with geosciences knowledge and intelligence.
Description: Conference on Sensing for Agriculture and Food Quality and Safety II, Orlando, USA, 4 April 2010
URI: http://hdl.handle.net/10397/40801
ISSN: 0277-786X
EISSN: 1996-756X
DOI: 10.1117/12.849780
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