Spatiotemporal Analysis of Urban Heat Islands in Kisangani City Using MODIS Imagery: Exploring Interactions with Urban–Rural Gradient, Building Volume Density, and Vegetation Effects

Climate, Journal Year: 2025, Volume and Issue: 13(5), P. 89 - 89

Published: April 29, 2025

The urban heat island (UHI) effect has emerged in the literature as a major challenge to well-being, primarily driven by increasing urbanization. To address this challenge, study investigates spatiotemporal pattern of UHI fast-growing city Kisangani and within its urban–rural gradient from 2000 2024 using land surface temperature (LST) data MODIS 11A2 V6.1 product. Inferential descriptive statistics were applied examine patterns relationships between LST, building volume density (BVD), vegetation expressed Normalized Difference Vegetation Index (NDVI). results showed that spatial extent moderate gradually increased 16 km2 38 km2, while high 9 19 km2. Furthermore, although values (0.2 < ≤ 0.3) are observed areas significant differences variations detected across urban, peri-urban, rural zones, indicate mean Kisangani’s remains below 0.2. Therefore, based on average variations, zones exhibit disparities LST compared areas. Moreover, significantly correlate with densities. However, influence predictor decreases increases over time, suggesting need implement synergistic development pathway manage interactions urbanization, landscape change, ecosystem service provision. This integrated approach may represent crucial solution for mitigating regions categorized high-temperature zones.

Language: Английский

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Forest Resilience and Vegetation Dynamics in Southwest Nigeria: Spatiotemporal Analysis and Assessment of Influencing Factors Using Geographical Detectors and Trend Models

Forests, Journal Year: 2025, Volume and Issue: 16(5), P. 811 - 811

Published: May 13, 2025

The Southwest Region (SWR) is one of Nigeria’s six geo-political zones and comprises distinct states. It holds considerable significance due to its unique geographical features, economic vibrancy, pastoral heritage, fragile natural ecosystems. These ecosystems are becoming increasingly susceptible human activities the adverse impacts climate change. This study analyzed temporal spatial variations Normalized Difference Vegetation Index (NDVI) in relation key influencing factors SWR from 2001 2020. analytical methods included Sen’s slope estimator, Mann–Kendall trend test, Geographical Detector Model (GDM). analysis revealed significant variability vegetation cover, with dense concentrated eastern part region low coverage overall, reflected by an average NDVI value 0.45, indicating persistent stress. Human activities, particularly land use cover (LULC) changes, were identified as major drivers loss some states such Ekiti, Lagos, Ogun, Ondo. Conversely, Osun Oyo exhibited signs recovery, suggesting potential for restoration. found that topographic factors, including elevation, well climatic variables like precipitation, influenced patterns. However, impact these was secondary LULC dynamics. interaction detection further highlighted cumulative effect combined anthropogenic environmental on distribution, between topography being significant. findings provide essential insights into biological condition contribute advancing understanding patterns critical implications sustainable management conservation tropical forest

Language: Английский

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Assessing the Sustainability Impact of Land-Use Changes and Carbon Emission Intensity in the Loess Plateau

Sustainability, Journal Year: 2024, Volume and Issue: 16(19), P. 8618 - 8618

Published: Oct. 4, 2024

Regional socioeconomic development is intricately tied to reasonable land-use resources. Although many studies have analyzed carbon emissions, there a lack of analysis the concept intensity. Studying emission intensity (LUCEI) crucial for shaping effective land management strategies that support integrated sustainable society, economy, and environment. This study examines changes on Loess Plateau (LP) from 2000 2020. The coefficient method, spatial autocorrelation analysis, optimal parameters-based geographical detector model are used identify analyze clustering patterns influencing factors affecting LUCEI, which provides more in-depth insights LUCEI. results indicate: (1) Urban Grassland areas showed most significant growth, with expanding by 10,845.21 km2 Grasslands 7848.91 km2, respectively. expansion was mainly caused conversion Cropland, while primarily attributed decline in Barren. (2) average LUCEI LP climbed 0.38 0.73 2020, indicating 190.70% growth rate. (3) pattern remained stable but unevenly distributed, extensive High-High Low-Low clusters. (4) Socioeconomic had greater explanatory power than natural factors. not driven single factor, combined influence multiple interaction between nighttime light population density explained distribution strongly, q-value 0.928. findings underscore critical role dynamics LP. By linking changes, this offers concrete scientific guidance policymakers seeking balance practices. Based these results, we recommend developing appropriate urban plans optimize structures, enhance regional sequestration capacities, fully implement green transition requirements.

Language: Английский

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Impacts of Intensified Human Activity on Vegetation Dynamics in the Qinba Mountains, China

Forests, Journal Year: 2024, Volume and Issue: 15(9), P. 1561 - 1561

Published: Sept. 5, 2024

The Qinba Mountain range is a typical climate-sensitive and ecologically fragile region. Monitoring of vegetation dynamics crucial for ecological protection achieving sustainable development goals. Various mutation-detection methods, along with slope analysis, hot-spot residual were used to examine changes in the Normalized Difference Vegetation Index (NDVI) during growing non-growing seasons over 41 years distinguish relative effects drivers. This revealed four key findings. (1) NDVI increased at 0.02 decade−1, mutation points 2006 growing-season 2007 non-growing-season NDVI. (2) trend changed markedly point. After point, was impacted more by human activity than climate change. hot cold spots rate change location season; season, it shows an obvious north–south distribution. (3) spatial patterns drivers this In before collectively enhanced ca. 81.3% region; after value declined 59.9% area, became dominant driver area formerly dominated both factors combination. areas where promoted growth decreased 12.6% those alone 11.1%, whereas affected only 11.6%. (4) Before contributed >60% western Qinling region, contributing other areas. exerted stronger influence change, enhancing >80% reducing it. These findings provide scientific basis protecting ecosystem are essential

Language: Английский

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