UAVs improve detection of seasonal growth responses during post-fire shrubland recovery

LANDSCAPE ECOLOGY(2022)

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摘要
(1) We monitored post-fire shrubland recovery responses to changes in rainfall seasonality using a multi-year field experiment in the Cape Floristic Region (CFR) of South Africa. A primary objective was to test the utility of UAVs for monitoring ultra-fine-scale vegetation changes in the early post-fire context. (2) By comparison with detailed ground-based measurements, we showed that UAVs improved detection of integrated community growth responses, given that the appropriate relative radiometric normalisation techniques were applied to repeated imagery data. UAVs supported ground-based findings and, moreover, helped to identify previously undetected growth form responses. However, due to the limitations in detecting species-specific demographic changes, UAVs could not completely replace ground-based measurements. (3) Our combined UAV-based and ground-based monitoring approaches indicated strong coupling between post-fire shrubland recovery and seasonal rainfall patterns in the CFR but also demonstrated that sensitivity to rainfall seasonality could differ between neighbouring shrubland communities occurring on different soil types. (4) The careful integration of UAV-based and ground-based monitoring approaches provided the fullest understanding of early post-fire shrubland recovery patterns.
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关键词
UAV, Pseudo-invariant features, NDVI, Multispectral, Radiometric normalisation, Remote sensing, Post-fire, Shrubland, Rainfall, Seasonality
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