Matches in SemOpenAlex for { <https://semopenalex.org/work/W2085872383> ?p ?o ?g. }
Showing items 1 to 72 of
72
with 100 items per page.
- W2085872383 abstract "The development of high spatial resolution remote sensing, such as IKONOS and QuickBird, makes it possible to describe the landscape pattern in the smaller scales. However, the level of landscape pattern detail represented by high spatial resolution images is different from middle and low resolution images. The image process and image analysis methods are also different as well. New techniques including image segmentation and object-based analysis are widely used in the high spatial resolution imagery analysis. So the landscape models and analysis methods set up by middle and low spatial resolution remote sensing are not suitable for the high spatial resolution remote sensing. In this study, focusing on the method for landscape pattern analysis for high spatial resolution remote sensing, we try to achieve the following goals: 1) set up a hybrid landscape model to describe the landscape patch mosaic, continuum and connectivity characteristics based on a unified data structure; 2) set up a landscape scaling method based on high spatial resolution image object-oriented analysis. The result shows that Delaunay-Voronoi data structure based on image object-oriented analysis is proper to set up the hybrid landscape model. Multi-scale image segmentation is better than aggregation method for multi-scale landscape pattern analysis." @default.
- W2085872383 created "2016-06-24" @default.
- W2085872383 creator A5012072530 @default.
- W2085872383 creator A5064708195 @default.
- W2085872383 date "2013-06-01" @default.
- W2085872383 modified "2023-09-22" @default.
- W2085872383 title "Multi-scale landscape pattern analysis based on high spatial resolution imagery segmentation" @default.
- W2085872383 cites W1983186335 @default.
- W2085872383 cites W1984792953 @default.
- W2085872383 cites W2042741439 @default.
- W2085872383 cites W2096414113 @default.
- W2085872383 cites W2153633422 @default.
- W2085872383 cites W2166109934 @default.
- W2085872383 cites W2175013224 @default.
- W2085872383 cites W2402602297 @default.
- W2085872383 doi "https://doi.org/10.1109/geoinformatics.2013.6626170" @default.
- W2085872383 hasPublicationYear "2013" @default.
- W2085872383 type Work @default.
- W2085872383 sameAs 2085872383 @default.
- W2085872383 citedByCount "0" @default.
- W2085872383 crossrefType "proceedings-article" @default.
- W2085872383 hasAuthorship W2085872383A5012072530 @default.
- W2085872383 hasAuthorship W2085872383A5064708195 @default.
- W2085872383 hasConcept C124504099 @default.
- W2085872383 hasConcept C154945302 @default.
- W2085872383 hasConcept C159620131 @default.
- W2085872383 hasConcept C205372480 @default.
- W2085872383 hasConcept C205649164 @default.
- W2085872383 hasConcept C2778755073 @default.
- W2085872383 hasConcept C31972630 @default.
- W2085872383 hasConcept C41008148 @default.
- W2085872383 hasConcept C58640448 @default.
- W2085872383 hasConcept C62649853 @default.
- W2085872383 hasConcept C89600930 @default.
- W2085872383 hasConceptScore W2085872383C124504099 @default.
- W2085872383 hasConceptScore W2085872383C154945302 @default.
- W2085872383 hasConceptScore W2085872383C159620131 @default.
- W2085872383 hasConceptScore W2085872383C205372480 @default.
- W2085872383 hasConceptScore W2085872383C205649164 @default.
- W2085872383 hasConceptScore W2085872383C2778755073 @default.
- W2085872383 hasConceptScore W2085872383C31972630 @default.
- W2085872383 hasConceptScore W2085872383C41008148 @default.
- W2085872383 hasConceptScore W2085872383C58640448 @default.
- W2085872383 hasConceptScore W2085872383C62649853 @default.
- W2085872383 hasConceptScore W2085872383C89600930 @default.
- W2085872383 hasLocation W20858723831 @default.
- W2085872383 hasOpenAccess W2085872383 @default.
- W2085872383 hasPrimaryLocation W20858723831 @default.
- W2085872383 hasRelatedWork W1265977266 @default.
- W2085872383 hasRelatedWork W1926395863 @default.
- W2085872383 hasRelatedWork W1967698997 @default.
- W2085872383 hasRelatedWork W1971060690 @default.
- W2085872383 hasRelatedWork W1974912395 @default.
- W2085872383 hasRelatedWork W2003224325 @default.
- W2085872383 hasRelatedWork W2026086052 @default.
- W2085872383 hasRelatedWork W2044623981 @default.
- W2085872383 hasRelatedWork W2062436213 @default.
- W2085872383 hasRelatedWork W2087050005 @default.
- W2085872383 hasRelatedWork W2128440476 @default.
- W2085872383 hasRelatedWork W2133407861 @default.
- W2085872383 hasRelatedWork W2150702635 @default.
- W2085872383 hasRelatedWork W2524266365 @default.
- W2085872383 hasRelatedWork W2972593789 @default.
- W2085872383 hasRelatedWork W2991599706 @default.
- W2085872383 hasRelatedWork W2999869172 @default.
- W2085872383 hasRelatedWork W3038549548 @default.
- W2085872383 hasRelatedWork W2188146623 @default.
- W2085872383 hasRelatedWork W3110305193 @default.
- W2085872383 isParatext "false" @default.
- W2085872383 isRetracted "false" @default.
- W2085872383 magId "2085872383" @default.
- W2085872383 workType "article" @default.