FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2897680743> ?p ?o ?g. }

• W2897680743 endingPage "98" @default.
• W2897680743 startingPage "89" @default.
• W2897680743 abstract "Along the urban-rural gradient in megacities, the extent and material composition of impervious surfaces are different. This leads to variations in the frequently mentioned heat-island property, but possibly also to different spectral signatures and, consequently, different accuracies in remote sensing image classification. This, in turn, creates a challenge when it comes to selecting suitable image processing techniques. In this study, we examine how the accuracy of land-cover classification changes along an urban-rural gradient as a function of spatial resolution and the gradient in landscape structure. RapidEye, Sentinel-2A and Landsat 8 images were used. Land-cover classification was performed using a deep learning model and landscape metrics were used to assess landscape structure. A high degree of landscape heterogeneity and lowest classification accuracy was observed in the transition zone between urban and rural domains, within a stretch of 15–20 km from the urban center. As expected, spatial resolution was found to be influential in classification accuracy. A comparison of classifications indicates that within rural landscapes finer resolution images retain more spatial and thematic details in land-cover, e.g., RapidEye and Sentinel-2A imagery better distinguish built-up areas within the agricultural landscape and discriminate more of the mapped land-cover/use classes than Landsat 8. Overall accuracy increased with increasing spatial resolution (30 m, 10 m, 5 m) within the urban and rural areas, however, the 10 m resolution image (Sentinel-2A) produced better results in the transition zone. The findings from this study provide a basis for more focused, consistent and possibly more accurate time-series analyses of land-use dynamics at the urban-rural interface." @default.
• W2897680743 created "2018-10-26" @default.
• W2897680743 creator A5020413391 @default.
• W2897680743 creator A5023682374 @default.
• W2897680743 creator A5024761567 @default.
• W2897680743 creator A5053413373 @default.
• W2897680743 creator A5068954980 @default.
• W2897680743 creator A5085963216 @default.
• W2897680743 date "2018-11-01" @default.
• W2897680743 modified "2023-09-25" @default.
• W2897680743 title "Spatial resolution and landscape structure along an urban-rural gradient: Do they relate to remote sensing classification accuracy? – A case study in the megacity of Bengaluru, India" @default.
• W2897680743 cites W126936368 @default.
• W2897680743 cites W1965545344 @default.
• W2897680743 cites W1983248868 @default.
• W2897680743 cites W1995345006 @default.
• W2897680743 cites W2000318706 @default.
• W2897680743 cites W2001747857 @default.
• W2897680743 cites W2005347387 @default.
• W2897680743 cites W2011500029 @default.
• W2897680743 cites W2017726567 @default.
• W2897680743 cites W2021524677 @default.
• W2897680743 cites W2045529976 @default.
• W2897680743 cites W2083630421 @default.
• W2897680743 cites W2084120092 @default.
• W2897680743 cites W2088899772 @default.
• W2897680743 cites W2098829158 @default.
• W2897680743 cites W2099577969 @default.
• W2897680743 cites W2108372438 @default.
• W2897680743 cites W2113870108 @default.
• W2897680743 cites W2117092697 @default.
• W2897680743 cites W2125261478 @default.
• W2897680743 cites W2133785052 @default.
• W2897680743 cites W2136258041 @default.
• W2897680743 cites W2138973222 @default.
• W2897680743 cites W2141924908 @default.
• W2897680743 cites W2144362041 @default.
• W2897680743 cites W2168809519 @default.
• W2897680743 cites W2169048824 @default.
• W2897680743 cites W2282484194 @default.
• W2897680743 cites W2484803562 @default.
• W2897680743 cites W2491899631 @default.
• W2897680743 cites W2513566916 @default.
• W2897680743 cites W2576092195 @default.
• W2897680743 cites W2591733388 @default.
• W2897680743 cites W2758754989 @default.
• W2897680743 cites W2765470012 @default.
• W2897680743 cites W4238404964 @default.
• W2897680743 cites W44536460 @default.
• W2897680743 cites W61533110 @default.
• W2897680743 doi "https://doi.org/10.1016/j.rsase.2018.10.003" @default.
• W2897680743 hasPublicationYear "2018" @default.
• W2897680743 type Work @default.
• W2897680743 sameAs 2897680743 @default.
• W2897680743 citedByCount "5" @default.
• W2897680743 countsByYear W28976807432020 @default.
• W2897680743 countsByYear W28976807432021 @default.
• W2897680743 countsByYear W28976807432022 @default.
• W2897680743 countsByYear W28976807432023 @default.
• W2897680743 crossrefType "journal-article" @default.
• W2897680743 hasAuthorship W2897680743A5020413391 @default.
• W2897680743 hasAuthorship W2897680743A5023682374 @default.
• W2897680743 hasAuthorship W2897680743A5024761567 @default.
• W2897680743 hasAuthorship W2897680743A5053413373 @default.
• W2897680743 hasAuthorship W2897680743A5068954980 @default.
• W2897680743 hasAuthorship W2897680743A5085963216 @default.
• W2897680743 hasConcept C100970517 @default.
• W2897680743 hasConcept C127040729 @default.
• W2897680743 hasConcept C154945302 @default.
• W2897680743 hasConcept C18903297 @default.
• W2897680743 hasConcept C205372480 @default.
• W2897680743 hasConcept C205649164 @default.
• W2897680743 hasConcept C2668921 @default.
• W2897680743 hasConcept C2775938548 @default.
• W2897680743 hasConcept C2778102629 @default.
• W2897680743 hasConcept C2780648208 @default.
• W2897680743 hasConcept C41008148 @default.
• W2897680743 hasConcept C4792198 @default.
• W2897680743 hasConcept C58640448 @default.
• W2897680743 hasConcept C62649853 @default.
• W2897680743 hasConcept C86803240 @default.
• W2897680743 hasConcept C93692415 @default.
• W2897680743 hasConceptScore W2897680743C100970517 @default.
• W2897680743 hasConceptScore W2897680743C127040729 @default.
• W2897680743 hasConceptScore W2897680743C154945302 @default.
• W2897680743 hasConceptScore W2897680743C18903297 @default.
• W2897680743 hasConceptScore W2897680743C205372480 @default.
• W2897680743 hasConceptScore W2897680743C205649164 @default.
• W2897680743 hasConceptScore W2897680743C2668921 @default.
• W2897680743 hasConceptScore W2897680743C2775938548 @default.
• W2897680743 hasConceptScore W2897680743C2778102629 @default.
• W2897680743 hasConceptScore W2897680743C2780648208 @default.
• W2897680743 hasConceptScore W2897680743C41008148 @default.
• W2897680743 hasConceptScore W2897680743C4792198 @default.
• W2897680743 hasConceptScore W2897680743C58640448 @default.
• W2897680743 hasConceptScore W2897680743C62649853 @default.
• W2897680743 hasConceptScore W2897680743C86803240 @default.
• W2897680743 hasConceptScore W2897680743C93692415 @default.
• W2897680743 hasFunder F4320320879 @default.

• next