Assessing Land Use/Land Cover Changes and Urban Heat Island Intensification: A Case Study of Kamrup Metropolitan District, Northeast India (2000–2032)

Earth, Journal Year: 2023, Volume and Issue: 4(3), P. 503 - 521

Published: July 10, 2023

Amid global concerns regarding climate change and urbanization, understanding the interplay between land use/land cover (LULC) changes, urban heat island (UHI) effect, surface temperatures (LST) is paramount. This study provides an in-depth exploration of these relationships in context Kamrup Metropolitan District, Northeast India, over a period 22 years (2000–2022) forecasts potential implications up to 2032. Employing high-accuracy supervised machine learning algorithm for LULC analysis, significant transformations are revealed, including considerable growth built-up areas corresponding decline cultivated land. Concurrently, progressive rise LST observed, underlining escalating UHI effect. association further substantiated through correlation studies involving normalized difference index (NDBI) vegetation (NDVI). The leverages cellular automata–artificial neural network (CA-ANN) model project scenario 2032, indicating predicted intensification LST, especially regions undergoing rapid expansion. findings underscore environmental unchecked growth, such as rising effects. Consequently, this research stresses critical need sustainable management planning strategies, well proactive measures mitigate adverse changes. results serve vital resource policymakers, planners, scientists working towards harmonizing with sustainability face change.

Language: Английский

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Unveiling Nature’s Resilience: Exploring Vegetation Dynamics during the COVID-19 Era in Jharkhand, India, with the Google Earth Engine

Climate, Journal Year: 2023, Volume and Issue: 11(9), P. 187 - 187

Published: Sept. 8, 2023

The Severe Acute Respiratory Syndrome Coronavirus Disease 2019 (COVID-19) pandemic has presented unprecedented challenges to global health and economic stability. Intriguingly, the necessary lockdown measures, while disruptive human society, inadvertently led environmental rejuvenation, particularly noticeable in decreased air pollution improved vegetation health. This study investigates lockdown’s impact on Jharkhand, India, employing Google Earth Engine for cloud-based data analysis. MODIS-NDVI were analyzed using spatio-temporal NDVI analyses time-series models. These revealed a notable increase maximum greenery of 19% from April 2020, with subsequent increases 13% 3% observed March May same year, respectively. A longer-term analysis 2000 2020 displayed an overall 16.7% rise greenness. While value remained relatively constant, it demonstrated slight increment during dry season. Landsat Mann–Kendall trend test reinforced these findings, displaying significant shift negative (1984–2019) positive 17.7% (1984–2021) Jharkhand’s north-west region. precipitation (using NASA power Merra2 data) correlation also studied pre- periods. Maximum (350–400 mm) was June, July typically experienced around 300 mm precipitation, covering nearly 85% Jharkhand. Interestingly, August saw up 550 primarily southern region, compared 400 month 2019. Peak changes this period ranged between 0.6–0.76 0.76–1, throughout state. Although decrease health, benefits began diminish post-lockdown. observation underscores need immediate attention intervention scientists researchers. Understanding lockdown-induced their can facilitate development proactive management strategies, paving way towards sustainable resilient future.

Language: Английский

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Active wildfire detection via satellite imagery and machine learning: an empirical investigation of Australian wildfires

Natural Hazards, Journal Year: 2025, Volume and Issue: unknown

Published: March 6, 2025

Language: Английский

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Substantial Changes in Selected Volatile Organic Compounds (VOCs) and Associations with Health Risk Assessments in Industrial Areas during the COVID-19 Pandemic

Toxics, Journal Year: 2023, Volume and Issue: 11(2), P. 165 - 165

Published: Feb. 9, 2023

During the COVID-19 pandemic, governments in many countries worldwide, including India, imposed several restriction measures, lockdowns, to prevent spread of infection. lockdowns led a reduction gaseous and particulate pollutants ambient air. In present study, we investigated substantial changes selected volatile organic compounds (VOCs) after outbreak coronavirus pandemic associations with health risk assessments industrial areas. VOC data from 1 January 2019 31 December 2021 were collected Central Pollution Control Board (CPCB) website, identify percentage levels before, during, COVID-19. The mean TVOC at all monitoring stations 47.22 ± 30.15, 37.19 37.19, 32.81 µg/m3 for 2019, 2020, 2021, respectively. As result, gradually declined consecutive years due India. 9 61% during period as compared pre-pandemic period. current T/B ratio values ranged 2.16 (PG) 26.38 (NL), which indicated that major pollutant contributors traffic non-traffic sources findings had positive but low correlations SR, BP, RF, WD, correlation coefficients (r) 0.034, 0.118, 0.012, 0.007, respectively, whereas negative observed AT WS, −0.168 −0.150, lifetime cancer (LCR) value benzene was reported be higher children, followed by females males, pre-pandemic, post-pandemic periods. A nationwide scale-up this study’s might useful formulating future air pollution policies associated factors. Furthermore, study provides baseline studies on impacts anthropogenic activities quality region.

Language: Английский

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Deep Learning Models for Fine-Scale Climate Change Prediction: Enhancing Spatial and Temporal Resolution Using AI

Advances in geographical and environmental sciences, Journal Year: 2024, Volume and Issue: unknown, P. 81 - 100

Published: Jan. 1, 2024

Language: Английский

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Assessment of nitrogen dioxide concentrations in nonattainment cities during COVID-19 lockdown using GIS technique

Elsevier eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 383 - 398

Published: Jan. 1, 2025

Language: Английский

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Identification of forest fire-prone region in Lamington National Park using GIS-based multicriteria technique: validation using field and Sentinel-2-based observations

Geocarto International, Journal Year: 2025, Volume and Issue: 40(1)

Published: Feb. 10, 2025

Lamington National Park in Queensland, Australia, is increasingly threatened by wildfires, intensified climate change. This study integrates remote sensing, GIS, and the Analytical Hierarchy Process (AHP) to identify fire-prone areas within park. Eight parameters were analyzed, with major fuel type being most significant. Multispectral satellite data provided essential insights into landscape changes vegetation stress, enhancing understanding of wildfire risks. Historical records, field observations, sensing utilized develop validate a Forest Fire Risk Index map, highlighting heightened fire susceptibility northern eastern regions due subtropical humid conditions. The findings emphasise importance advanced spatial analysis for proactive management. Combining GIS multicriteria decision-making equips conservationists policymakers critical tools strengthen response strategies, safeguard vital ecosystems, protect surrounding communities. approach valuable managing similar landscapes globally.

Language: Английский

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A Comprehensive Review of Empirical and Dynamic Wildfire Simulators and Machine Learning Techniques used for the Prediction of Wildfire in Australia

Technology Knowledge and Learning, Journal Year: 2025, Volume and Issue: unknown

Published: April 2, 2025

Language: Английский

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Technology‐Driven Approaches to Enhance Disaster Response and Recovery

Published: Oct. 17, 2024

Language: Английский

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From Firestick to Satellites: Technological Advancement and Indigenous Cultural Practice in Managing Forest Fires in Australia

The Historic Environment Policy & Practice, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 24

Published: Nov. 24, 2024

Language: Английский

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