Impact assessment of a super-typhoon on Hong Kong's secondary vegetation and recommendations for restoration of resilience in the forest succession

Abbas, Sawaid; Nichol, Janet Elizabeth; Fischer, Gunter A.; Wong, Man Sing; Irteza, Syed Muhammad

doi:10.1016/j.agrformet.2019.107784

Cited by 52 publications

(50 citation statements)

References 29 publications

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“…For both VIs, less than 9% of the cells of the FEF were hit by all of the five typhoons examined (Table S4), and the small size of the FFDP relative to the FEF certainly limit its ability to capture cells with high typhoon frequencies Figure 6). Effects of topography on the cyclone damage distribution within forested landscapes are widespread across regions affected by tropical cyclones [23,75,76]. In this study, elevation was the only topographical variable that correlated with typhoon damages for three of the five studied typhoons, although relationships were weak (ρ < 0.2).…”

Section: Typhoons Damages Intensity In the Plot And The Reservementioning

confidence: 49%

Landscape Representation by a Permanent Forest Plot and Alternative Plot Designs in a Typhoon Hotspot, Fushan, Taiwan

2020

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Permanent forest dynamics plots have provided valuable insights into many aspects of forest ecology. The evaluation of their representativeness within the landscape is necessary to understanding the limitations of findings from permanent plots at larger spatial scales. Studies on the representativeness of forest plots with respect to landscape heterogeneity and disturbance effect have already been carried out, but knowledge of how multiple disturbances affect plot representativeness is lacking—particularly in sites where several disturbances can occur between forest plot censuses. This study explores the effects of five typhoon disturbances on the Fushan Forest Dynamics Plot (FFDP) and its surrounding landscape, the Fushan Experimental Forest (FEF), in Taiwan where typhoons occur annually. The representativeness of the FFDP for the FEF was studied using four topographical variables derived from a digital elevation model and two vegetation indices (VIs), Normalized Difference Vegetation Index (NDVI) and Normalized Difference Infrared Index (NDII), calculated from Landsat-5 TM, Landsat-7 ETM+, and Landsat-8 OLI data. Representativeness of four alternative plot designs were tested by dividing the FFDP into subplots over wider elevational ranges. Results showed that the FFDP neither represents landscape elevational range (<10%) nor vegetation cover (<7% of the interquartile range, IQR). Although disturbance effects (i.e., ΔVIs) were also different between the FFDP and the FEF, comparisons showed no under- or over-exposure to typhoon damage frequency or intensity within the FFDP. In addition, the ΔVIs were of the same magnitudes in the plots and the reserve, and the plot covered 30% to 75.9% of IQRs of the reserve ΔVIs. Unexpectedly, the alternative plot designs did not lead to increased representation of damage for 3 out of the 4 tested typhoons and they did not suggest higher representativeness of rectangular vs. square plots. Based on the comparison of mean Euclidian distances, two rectangular plots had smaller distances than four square or four rectangular plots of the same area. Therefore, this study suggests that the current FFDP provides a better representation of its landscape disturbances than alternatives, which contained wider topographical variation and would be more difficult to conduct ground surveys. However, upscaling needs to be done with caution as, in the case of the FEF, plot representativeness varied among typhoons.

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Section: Typhoons Damages Intensity In the Plot And The Reservementioning

confidence: 49%

Landscape Representation by a Permanent Forest Plot and Alternative Plot Designs in a Typhoon Hotspot, Fushan, Taiwan

2020

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“…Topographic factors such as elevation, slope and aspect were reported to significantly affect the forest damage caused by typhoons/hurricanes [1,6,23,38,39]. These data can be derived from the digital elevation model (DEM) data.…”

Section: Topographic and Climatic Datamentioning

confidence: 99%

“…In addition, many previous studies have also indicated that climatic factors, such as wind velocity and rainfall, affect the impact of typhoons/hurricanes on forest damages [1,6]. Therefore, we used wind velocity and rainfall as input variables in the RF model to monitor forest damage.…”

Section: Topographic and Climatic Datamentioning

confidence: 99%

“…The available time-series of VIs from 1986 to 2019 for the period 1 June to 8 August and from 12 August to the end of October were used as inputs in the LandTrendr algorithm on the GEE platform. After smoothing, the ∆VI was calculated as: ∆VI = (VI after − VI before )/VI before (1) where VI after denotes the VI obtained from the mosaic images before Lekima (represented by the images from 1 June to 8 August 2019) and after Lekima (represented by the images from 12 August to the end of October 2019).…”

Section: Mapping Forest Damage Using Univariate Image Differencing Of Vismentioning

confidence: 99%

“…Typhoons, also called hurricanes, are a rotating, organized system of clouds and thunderstorms that originates from tropical or subtropical waters. Typhoons/hurricanes are usually accompanied by torrential rain, severe inundation and extremely strong wind velocity, causing damages to both human and natural systems [1]. Typhoons/hurricanes have caused about 2000 people's death and USD 7 billion in losses worldwide every year.…”

Section: Introductionmentioning

confidence: 99%

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Impact Assessments of Typhoon Lekima on Forest Damages in Subtropical China Using Machine Learning Methods and Landsat 8 OLI Imagery

Chen

Cai

et al. 2021

Sustainability

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Wind damage is one of the major factors affecting forest ecosystem sustainability, especially in the coastal region. Typhoon Lekima is among the top five most devastating typhoons in China and caused economic losses totaling over USD 8 billion in Zhejiang Province alone during 9–12 August 2019. However, there still is no assessment of its impacts on forests. Here we detected forest damage and its spatial distribution caused by Typhoon Lekima by classifying Landsat 8 OLI images using the random forest (RF) machine learning algorithm and the univariate image differencing (UID) method on the Google Earth Engine (GEE) platform. The accuracy assessment indicated a high overall accuracy (>87%) and kappa coefficient (>0.75) for forest-damage detection, as evaluated against field-investigated plot data, with better performance using the RF method. The total affected forest area by Lekima was 4598.87 km2, accounting for 8.44% of the total forest area in Zhejiang Province. The light-, moderate- and severe-damage forest areas were 2106.29 km2, 2024.26 km2 and 469.76 km2, respectively. Considering the damage severity, the net forest canopy loss fraction was 2.57%. The affected forest area and damage severity exhibited large spatial variations, which were affected by elevation, slope, precipitation and forest type. Our study indicated a larger uncertainty for affected forest area and a smaller uncertainty for the proportion of damage severity, based on multiple assessment approaches. This is among the first studies on forest damage due to typhoons at a regional scale in China, and the methods can be extended to examine the impacts of other super-strong typhoons on forests. Our study results on damage severity, spatial distribution and controlling factors could help local governments, the forest sector and forest landowners make decision on tree-planting planning and sustainable management after typhoon strikes and could also raise public and governmental awareness of typhoons’ damage on China’s inland forests.

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A framework to model the performance indicators of resilient construction supply chain: An effort toward attaining sustainability and circular practices

Singh,

Dwivedi,

Agrawal

et al. 2023

Bus Strat Env

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In existing dynamic market place, supply chain disruptions have become a common phenomenon. Emergence of new technologies coupled with variable customer demand and uncertain pandemic has fueled the disruptions across the supply chain ecosystem. To cater the unanticipated disruptions, supply chains of every business has to be circular and sustainable and construction industry is no exception to this. The present study concentrates on identifying the major performance indicators of resilient Construction Supply Chain (CSC) and prioritize the most significant ones. Fuzzy–Decision Making Trial And Evaluation Laboratory (DEMATEL) method was used to reveal the influential relationship of performance indicators on the resilience level in CSCs. Further, a strategy map is prepared to highlight the organizational strategy and cause‐effect approach. The findings from study revealed that maintaining appropriate security level, strong collaboration among supply chain partners, efficient supply chain designs, ability to detect discrepancies, bottlenecks, and vulnerabilities, and conservation of resources to facilitate sustainable operations are the top seven performance indicators that are evident in the causal group for sustainable CSC. In the effect group, prominent performance indicators are flexibility, financial strength, and efficient allocation of resources. The study adds on to the existing literature by identifying and analyzing significant performance indicators for establishing resilient, sustainable and circular practices in the construction industry.

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Impact assessment of a super-typhoon on Hong Kong's secondary vegetation and recommendations for restoration of resilience in the forest succession

Abstract: Impact assessment of a super-typhoon on Hong Kong's secondary vegetation and recommendations for restoration of resilience in the forest succession. Agricultural and Forest Meteorology, 280. a107784.

Cited by 52 publications

References 29 publications

Landscape Representation by a Permanent Forest Plot and Alternative Plot Designs in a Typhoon Hotspot, Fushan, Taiwan

Landscape Representation by a Permanent Forest Plot and Alternative Plot Designs in a Typhoon Hotspot, Fushan, Taiwan

Impact Assessments of Typhoon Lekima on Forest Damages in Subtropical China Using Machine Learning Methods and Landsat 8 OLI Imagery

A framework to model the performance indicators of resilient construction supply chain: An effort toward attaining sustainability and circular practices

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