Characterizing Vegetation Fire dynamics in Myanmar and South Asian Countries

Reddy, C. Sudhakar; Unnikrishnan, Anjaly; Bird, Natalia Grace; Faseela, V. S.; Asra, Mahbooba; Manikandan, T. Maya; Rao, Preeti

doi:10.1007/s12524-020-01205-5

Cited by 12 publications

(8 citation statements)

References 28 publications

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“…Subsequently, we applied the Emerging Hotspot Analysis (EHA) using ArcGIS Pro software [47] to understand spatiotemporal variations of emergency calls during the study period. The Emerging Hotspot Analysis is among the new methods added to the GIS-based analyses, and its usage in spatiotemporal analysis is growing [48][49][50][51][52][53][54]. This information is used to analyze various zones according to how frequently EHSA occurred in various metropolitan locations throughout the 23-year timeframe.…”

Section: Methodsmentioning

confidence: 99%

Spatiotemporal Analysis of Urban Heat Islands and Vegetation Cover Using Emerging Hotspot Analysis in a Humid Subtropical Climate

Ghanghermeh,

Roshan,

Asadi

et al. 2024

Atmosphere

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Research on the temporal and spatial changes of the urban heat island effect can help us better understand how urbanization, climate change, and the environment are interconnected. This study uses a spatiotemporal analysis method that couples the Emerging Hot Spot Analysis (EHSA) technique with the Mann–Kendall technique. The method is applied to determine the intensity of the heat island effect in humid subtropical climates over time and space. The data used in this research include thermal bands, red band (RED) and near-infrared band (NIR), and Landsat 7 and 8 satellites, which were selected from 2000 to 2022 for the city of Sari, an Iranian city on the Caspian Sea. Pre-processed spectral bands from the ‘Google Earth Engine’ database were used to estimate the land surface temperature. The land surface temperature difference between the urban environment and the outer buffer (1500 m) was modeled and simulated. The results of this paper show the accuracy and novelty of using Emerging Hotspot Analysis to evaluate the effect of vegetation cover on the urban heat island intensity. Based on the Normalized Difference Vegetation Index (NDVI), the city’s land surface temperature increased by approximately 0.30 °C between 2011 and 2022 compared to 2001 to 2010. However, the intensity of the urban heat island decreased during the study period, with r = −0.42, so an average −0.031 °C/decade decrease has been experienced. The methodology can be transferred to other cities to evaluate the role of urban green spaces in reducing heat stress and to estimate the heat budget based on historical observations.

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Section: Methodsmentioning

confidence: 99%

Spatiotemporal Analysis of Urban Heat Islands and Vegetation Cover Using Emerging Hotspot Analysis in a Humid Subtropical Climate

Ghanghermeh,

Roshan,

Asadi

et al. 2024

Atmosphere

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“…Recently, the approach has been used to detect spatiotemporal patterns of COVID-19 cases [ 13 ], landslides [ 14 ], invasive species [ 15 ] and forest loss [ 12 , 16 – 18 ]. A few studies were done in Australia [ 19 ] and southeast Asia [ 5 , 20 ], utilizing the emerging hotspot analysis method to understand the spatiotemporal patterns of fires. In Zimbabwe, limited studies have analyzed the spatial distribution of fire occurrence [ 21 ] and its intensity [ 22 ] at a national scale.…”

Section: Introductionmentioning

confidence: 99%

National-scale spatiotemporal patterns of vegetation fire occurrences using MODIS satellite data

Mupfiga,

Mutanga,

Dube

2024

PLoS ONE

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As the risk of climate change increases, robust fire monitoring methods become critical for fire management purposes. National-scale spatiotemporal patterns of the fires and how they relate to vegetation and environmental conditions are not well understood in Zimbabwe. This paper presents a spatially explicit method combining satellite data and spatial statistics in detecting spatiotemporal patterns of fires in Zimbabwe. The Emerging Hot Spot Analysis method was utilized to detect statistically significant spatiotemporal patterns of fire occurrence between the years 2002 and 2021. Statistical analysis was done to determine the association between the spatiotemporal patterns and some environmental variables such as topography, land cover, land use, ecoregions and precipitation. The highest number of fires occurred in September, coinciding with Zimbabwe’s observed fire season. The number of fires significantly varied among seasons, with the hot and dry season (August to October) recording the highest fire counts. Additionally, although June, July and November are not part of the official fire season in Zimbabwe, the fire counts recorded for these months were relatively high. This new information has therefore shown the need for revision of the fire season in Zimbabwe. The northern regions were characterized by persistent, oscillating, diminishing and historical spatiotemporal fire hotspots. Agroecological regions IIa and IIb and the Southern Miombo bushveld ecoregion were the most fire-prone areas. The research findings also revealed new critical information about the spatiotemporal fire patterns in various terrestrial ecoregions, land cover, land use, precipitation and topography and highlighted potential areas for effective fire management strategies.

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“…Spatiotemporal modelling methodologies are rapidly developing and evolving. The emerging hotspot analysis is among the new methods added to the GIS-based analyses and its usage in a spatiotemporal analysis is growing [1][2][3][4][5][6][7]. Gudes et al [1] used spatial modelling and spatiotemporal methods to identify emerging hotspots of heavy-vehicle crashes on specific roads in Western Australia.…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Analysis of Emergency Calls during the COVID-19 Pandemic: Case of the City of Vaughan

et al. 2023

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Cities have experienced different realities during the COVID-19 pandemic due to its impacts and public health measures undertaken to respond to and manage the pandemic. These measures revealed significant implications for municipal functions, particularly emergency services. The aim of this study is to examine the spatiotemporal distribution of emergency calls during different stages/periods of the pandemic in the City of Vaughan, Canada, using spatial density and the emerging hotspot analysis. The Vaughan Fire and Rescue Service (VFRS) provided the dataset of all emergency calls responded to within the City of Vaughan for the period of 1 January 2017 to 15 July 2021. The dataset was divided according to 11 periods during the pandemic, each period associated with certain levels of public health restrictions. A spatial analysis was carried out by converting the data into shapefiles using geographic coordinates of each call. Study findings show significant spatiotemporal changes in patterns of emergency calls during the pandemic, particularly during more stringent public health measures such as lockdowns and closures of nonessential businesses. The results could provide useful information for both resource management in emergency services as well as understanding the underlying causes of such patterns.

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Characterizing Vegetation Fire dynamics in Myanmar and South Asian Countries

Cited by 12 publications

References 28 publications

Spatiotemporal Analysis of Urban Heat Islands and Vegetation Cover Using Emerging Hotspot Analysis in a Humid Subtropical Climate

Spatiotemporal Analysis of Urban Heat Islands and Vegetation Cover Using Emerging Hotspot Analysis in a Humid Subtropical Climate

National-scale spatiotemporal patterns of vegetation fire occurrences using MODIS satellite data

Spatiotemporal Analysis of Emergency Calls during the COVID-19 Pandemic: Case of the City of Vaughan

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