Landscape fragmentation analysis in Riau Province based on Sentinel-2A and SRTM imagery

Fitria Alfani; Projo Danoedoro

doi:10.1117/12.3009775

29 January 2024 Landscape fragmentation analysis in Riau Province based on Sentinel-2A and SRTM imagery

Fitria Alfani, Projo Danoedoro

Proceedings Volume 12977, Eighth Geoinformation Science Symposium 2023: Geoinformation Science for Sustainable Planet; 129770B (2024) https://doi.org/10.1117/12.3009775
Event: 8th Geoinformation Science Symposium 2023: Geoinformation Science for Sustainable Planet, 2023, Yogyakarta, Indonesia

Abstract

This research aimed to map land-use in Riau Province using a landscape ecological approach and to assess the level of landscape fragmentation using fragmentation index, edge density, and landscape metrics at observation window sizes of 3×3, 5×5, and 7×7 pixels. Sentinel-2A imagery was the primary input for land-cover mapping, while SRTM DEM was used as the input for terrain unit mapping. The land-cover and terrain unit maps were overlaid to create a land-use map. This map was then used as an input for spatial analysis of fragmentation by computing the fragmentation index and edge density. Another analysis that has been carried out was landscape metrics calculation. The results of the land-use mapping revealed that the study area is predominantly occupied by plantations and forests, with an overall accuracy of 81.88%. The landscape fragmentation analysis showed that areas with high fragmentation level are scattered in the central part of the region, characterized by dense human activity in heterogeneous land-use types. Meanwhile, low fragmentation levels found in homogeneous land-use areas such as natural and semi-natural forests.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Fitria Alfani and Projo Danoedoro "Landscape fragmentation analysis in Riau Province based on Sentinel-2A and SRTM imagery", Proc. SPIE 12977, Eighth Geoinformation Science Symposium 2023: Geoinformation Science for Sustainable Planet, 129770B (29 January 2024); https://doi.org/10.1117/12.3009775

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