Multi-scale sensitivity of Landsat and MODIS to forest disturbance associated with tropical cyclones

Negrón‐Juárez, Robinson I.; Baker, David B.; Chambers, Jeffrey Q.; Hurtt, George C.; Goosem, Stephen

doi:10.1016/j.rse.2013.09.028

Cited by 38 publications

(42 citation statements)

References 58 publications

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“…From the surface level to about 600 m asl both bands of forests were affected by Yasi's winds, but a clear pattern between disturbance and surface elevation is not observed here (Figure 3d), probably due to the overlap of topographic affects from the sequence forests-land use-forests, tree species, soil types, etc. [18]. From 600 to 1500 m asl a decrease in disturbance severity with surface elevation is clearly observed (Figure 3d).…”

Section: Resultsmentioning

confidence: 82%

Section: Introductionmentioning

confidence: 99%

“…Studies based on field-measured tree mortality have confirmed that spectral reflectance features vary with the level of cyclonic wind disturbance [8,9,17,18]. However, topographic characteristics play an important role in the pattern and severity of disturbance [11,18,19]. Topographic characteristics not only governs the degree of exposure of a forest to tropical cyclonic winds at any point [19] but can also alter both wind speed and direction [11] making the study of the association between terrain features and hurricane disturbance difficult.…”

Section: Introductionmentioning

confidence: 99%

“…A coarse assessment of tree mortality associated with Yasi and a comparison of cyclone related disturbances using multispectral satellite data in tropical and temperate forests are also presented. This work presents the fundamentals of a recent complementary study [18].…”

Section: Introductionmentioning

confidence: 99%

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Remote Sensing Assessment of Forest Disturbance across Complex Mountainous Terrain: The Pattern and Severity of Impacts of Tropical Cyclone Yasi on Australian Rainforests

et al. 2014

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Topography affects the patterns of forest disturbance produced by tropical cyclones. It determines the degree of exposure of a surface and can alter wind characteristics. Whether multispectral remote sensing data can sense the effect of topography on disturbance is a question that deserves attention given the multi-scale spatial coverage of these data and the projected increase in intensity of the strongest cyclones. Here, multispectral satellite data, topographic maps and cyclone surface wind data were used to study the patterns of disturbance in an Australian rainforest with complex mountainous terrain produced by tropical cyclone Yasi (2011). The cyclone surface wind data (H*wind) was produced by the Hurricane Research Division of the National Oceanic and Atmospheric Administration (HRD/NOAA), and this was the first time that this data was produced for a cyclone outside of United States territory. A disturbance map was obtained by applying spectral mixture analyses on satellite data and presented a significant correlation with field-measured tree mortality. Our results showed that, consistent with cyclones in the southern hemisphere, multispectral data revealed that forest disturbance was higher on the left side of the cyclone track. The highest level of forest disturbance occurred in forests along the path of the cyclone track (±30). Levels of forest disturbance decreased with decreasing slope and with an aspect facing off the track of the cyclone or away from the dominant surface winds. An increase in disturbance with surface elevation was also observed. However, areas affected by the same wind intensity presented increased levels of disturbance with increasing elevation suggesting that complex terrain interactions act to speed up wind at higher elevations. Yasi produced an important offset to Australia's forest carbon sink in 2010. We concluded that multispectral data was sensitive to the main effects of complex topography on disturbance patterns. High resolution cyclone wind surface data are needed in order to quantify the effects of topographic accelerations on cyclone related forest disturbances.

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Section: Resultsmentioning

confidence: 82%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Remote Sensing Assessment of Forest Disturbance across Complex Mountainous Terrain: The Pattern and Severity of Impacts of Tropical Cyclone Yasi on Australian Rainforests

et al. 2014

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“…Wind, wind loading, gusts of winds, tree stature, tree species (and associated characteristics such as tree crown shape and density, root architecture and shape, and wood density), topography, soil, cumulative processes, etc. all play a role in the production of windthrows [11,[83][84][85][86][87][88] resulting in tree failure at a lower wind speed than expected [1,3]. Amazonia covers about 5.3 million km 2 , and has many environmental and functional gradients [89,90].…”

Section: Discussionmentioning

confidence: 99%

Windthrow Variability in Central Amazonia

et al. 2017

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Windthrows are a recurrent disturbance in Amazonia and are an important driver of forest dynamics and carbon storage. In this study, we present for the first time the seasonal and interannual variability of windthrows, focusing on Central Amazonia, and discuss the potential meteorological factors associated with this variability. Landsat images over the 1998-2010 time period were used to detect the occurrence of windthrows, which were identified based on their spectral characteristics and shape. Here, we found that windthrows occurred every year but were more frequent between September and February. Organized convective activity associated with multicell storms embedded in mesoscale convective systems, such as northerly squall lines (that move from northeast to southwest) and southerly squall lines (that move from southwest to northeast) can cause windthrows. We also found that southerly squall lines occurred more frequently than their previously reported~50 year interval. At the interannual scale, we did not find an association between El Niño-Southern Oscillation (ENSO) and windthrows.

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Remote sensing of seasonal changes and disturbances in mangrove forest: a case study from South Florida

et al. 2016

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Knowledge of the spatial and temporal changes caused by episodic disturbances and seasonal variability is essential for understanding the dynamics of mangrove forests at the landscape scale, and for building a baseline that allows detection of the effects of future environmental change. In combination with LiDAR data, we calculated four vegetation indices from 150 Landsat TM images from 1985 to 2011 in order to detect seasonal changes and distinguish them from disturbances due to hurricanes and chilling events in a mangrove‐dominated coastal landscape. We found that normalized difference moisture index (NDMI) performed best in identifying both seasonal and event‐driven episodic changes. Mangrove responses to chilling and hurricane events exhibited distinct spatial patterns. Severe damage from intense chilling events was concentrated in the interior dwarf and transition mangrove forests with tree heights less than 4 m, while severe damage from intense hurricanes was limited to the mangrove forest near the coast, where tree heights were more than 4 m. It took 4–7 months for damage from intense chilling events and hurricanes to reach their full extent, and took 2–6 yr for the mangrove forest to recover from these disturbances. There was no significant trend in the vegetation changes represented by NDMI over the 27‐yr period, but seasonal signals from both dwarf and fringe mangrove forests were discernible. Only severe damage from hurricanes and intense chilling events could be detected in Landsat images, while damage from weak chilling events could not be separated from the background seasonal change.

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Multi-scale sensitivity of Landsat and MODIS to forest disturbance associated with tropical cyclones

Cited by 38 publications

References 58 publications

Remote Sensing Assessment of Forest Disturbance across Complex Mountainous Terrain: The Pattern and Severity of Impacts of Tropical Cyclone Yasi on Australian Rainforests

Remote Sensing Assessment of Forest Disturbance across Complex Mountainous Terrain: The Pattern and Severity of Impacts of Tropical Cyclone Yasi on Australian Rainforests

Windthrow Variability in Central Amazonia

Remote sensing of seasonal changes and disturbances in mangrove forest: a case study from South Florida

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