2018
DOI: 10.3390/rs10020306
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Combined Landsat and L-Band SAR Data Improves Land Cover Classification and Change Detection in Dynamic Tropical Landscapes

Abstract: Robust quantitative estimates of land use and land cover change are necessary to develop policy solutions and interventions aimed towards sustainable land management. Here, we evaluated the combination of Landsat and L-band Synthetic Aperture Radar (SAR) data to estimate land use/cover change in the dynamic tropical landscape of Tanintharyi, southern Myanmar. We classified Landsat and L-band SAR data, specifically Japan Earth Resources Satellite (JERS-1) and Advanced Land Observing Satellite-2 Phased Array L-b… Show more

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Cited by 105 publications
(119 citation statements)
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References 112 publications
(170 reference statements)
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“…Our results match the findings of other studies that use optical data [15][16][17][18][19]. In the case of SAR data, the situation is less clear.…”
Section: Discussionsupporting
confidence: 85%
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“…Our results match the findings of other studies that use optical data [15][16][17][18][19]. In the case of SAR data, the situation is less clear.…”
Section: Discussionsupporting
confidence: 85%
“…Results with L-band SAR data have been close to the results of optical data particularly in forest and non-forest classification [17,[26][27][28] and L-band data have also been shown to be applicable for producing forest cover maps at global scales [29]. However, the results in land cover classification using SAR data are not consistent [17,18,30,31]. In [30] the overall accuracy in forest and non-forest classification was 92.1% for ALOS PALSAR L-band data and 81.2% for Radarsat-2 C-band data.…”
Section: Introductionmentioning
confidence: 68%
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“…For instance, while our 2014 mangrove forest cover estimate for Tanintharyi (0.24 million ha) and the estimate of Gaw, Linkie, and Friess () for the same state and year were relatively close (0.25 million ha), this was not necessarily the case for the year 2000 (0.28 and 0.26 million ha, respectively). For the years 2015 and 2016, De Alban, Connette, Oswald, and Webb () and Connette, Oswald, Songer, and Leimgruber () estimated the state's mangrove area to be 0.34 and 0.24 million ha, respectively. Furthermore, Weber, Keddell, and Kemal () estimated a 0.03 million ha net mangrove forest cover loss from 2000 to 2013 in Rakhine state, whereas in this study, we detected a 0.08 million ha net mangrove forest cover loss from 2000 to 2014 (Table ).…”
Section: Discussionmentioning
confidence: 99%