Optimising forest rehabilitation and restoration through remote sensing and machine learning: Mapping natural forests in the eThekwini Municipality DOI Creative Commons
Mthokozisi Ndumiso Mzuzuwentokozo Buthelezi, Romano Lottering, Kabir Peerbhay

et al.

Remote Sensing Applications Society and Environment, Journal Year: 2024, Volume and Issue: 36, P. 101335 - 101335

Published: Aug. 28, 2024

Forests are crucial in delivering ecosystem services that underpin human well-being and biodiversity conservation. However, these vital ecosystems threatened by forest degradation rapid urbanisation. This study addresses this challenge proposing a comprehensive framework for mapping natural forests at the municipal scale. The integrates remote sensing techniques with machine learning algorithms to provide valuable insights into extent of within eThekwini Municipality. utilised Landsat 7, 8, 9 satellite imagery analyse map historical current distribution forests. Five spectral indices, namely, Normalized Differential Vegetation Index (NDVI), Green Difference (GNDVI), Chlorophyll (CIG), Enhanced (EVI), Index-2 (EVI-2), which were calculated from bands, employed analysis. Light Gradient Boosting Machine (LightGBM), Categorical (CatBoost), Extreme (XGBoost) used model distribution. Accuracy was assessed through confusion matrices, Receiver Operating Characteristic (ROC) Curves, area under ROC curve (AUC), F1 scores. LightGBM achieved highest overall accuracy (90.76%), followed CatBoost (89.56%) XGBoost (84.34%). also obtained best score (90.76%). These findings highlight LightGBM's effectiveness classifying forests, making it preferred classifications based on 7 significantly underestimated area, whereas 8 data revealed an increase 2015 2023. will guide effective targeted rehabilitation restoration efforts, ensuring preservation enhancement services.

Language: Английский

Prediction of potentially toxic elements in water resources using MLP-NN, RBF-NN, and ANFIS: a comprehensive review DOI
Johnson C. Agbasi, Johnbosco C. Egbueri

Environmental Science and Pollution Research, Journal Year: 2024, Volume and Issue: 31(21), P. 30370 - 30398

Published: April 20, 2024

Language: Английский

Citations

21
Geospatial modelling of seasonal water and electricity consumption in Doha's residential buildings using multiscale geographically weighted regression (MGWR) and Bootstrap analysis DOI Creative Commons
Rana N. Jawarneh, Ammar Abulibdeh

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: 113, P. 105654 - 105654

Published: July 9, 2024

Ensuring sustainable water and electricity consumption in urban residential buildings is a growing challenge worldwide, particularly rapidly developing regions with harsh climates. This study examines the seasonal variation of Doha, Qatar, exploring interconnectedness land use/land cover (LULC) socio-demographic characteristics household consumption. For this purpose, we employed statistical analysis (i.e. Pearson correlation Bootstrap analysis) advanced geostatistical models, including Geographically Weighted Regression (GWR) Multiscale (MGWR), to analyze monitor spatial variations The methods involved assessing relationship between surface temperature (LST), water-electricity consumption, analyzing impact demographic variables. Key findings indicate significant spatiotemporal influenced by changes LULC such as size structure. highlight need for integrated planning energy policies that consider impacts enhance efficiency sustainability settings. Furthermore, results underscore importance addressing complex interplay development resource policy-making.

Language: Английский

Citations

9
Analyzing trade-offs, synergies, and driving factors of ecosystem services in Anhui Province using spatial analysis and XG-boost modeling DOI

Jianshen Qu,

Zhili Xu,

Bin Dong

et al.

Ecological Indicators, Journal Year: 2025, Volume and Issue: 171, P. 113098 - 113098

Published: Jan. 24, 2025

Language: Английский

Citations

1
High-resolution remote sensing data-based urban heat island study in Chongqing and Changde City, China DOI
Tao Hai, Zaher Mundher Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬, Mou Leong Tan

et al.

Theoretical and Applied Climatology, Journal Year: 2024, Volume and Issue: 155(7), P. 7049 - 7076

Published: June 11, 2024

Language: Английский

Citations

5
Spatio-temporal Analysis of LST, NDVI and SUHI in a Coastal Temperate City using Local Climate Zone DOI Creative Commons
Tania Sharmin, Adrian Chappell, Simon Lannon

et al.

Energy and Built Environment, Journal Year: 2024, Volume and Issue: unknown

Published: June 1, 2024

Extreme heat due to changing climate poses a new challenge for temperate climates. The is further aggravated by inadequate research, policy, or preparedness effectively respond and recover from its impacts. While urban morphology plays crucial role in mitigating heat, it has received limited attention planning, highlighting the need exploration, particularly regions. To illustrate potential mitigations, we use example of coastal city Cardiff. establish interrelations between island patterns, explored spatiotemporal variations land surface temperature (LST), normalised difference vegetation index (NDVI), (SUHI) local zone (LCZ) classification Results showed significant variation SUHI LCZ zones. Both LST NDVI were found vary significantly across zones demonstrating their association with form locality. For built-up areas, more compact built-environment smaller cover larger building density was 2.0°C warmer than open when comparing mean summer LSTs. On average, natural classes exhibit that 8.0°C lower 6.0°C built-environment. Consequently, high-density, LCZs have greater effect compared classes. Therefore, cities will benefit incorporating an sufficient greenery spaces. These findings help determine optimal climates develop mitigation strategies while designing, improving existing areas. In addition, map applied this study Cardiff enable international comparison testing proven change adaptation techniques similar

Language: Английский

Citations

5
Hourly impact of urban features on the spatial distribution of land surface temperature: A study across 30 cities DOI
Qi Wang, Haitao Wang,

Lanhong Ren

et al.

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: 113, P. 105701 - 105701

Published: July 27, 2024

Language: Английский

Citations

5
Robust drivers of urban land surface temperature dynamics across diverse landscape characters: An augmented systematic literature review DOI Creative Commons
P Eneche, Funda Atún, Yijian Zeng

et al.

Ecological Indicators, Journal Year: 2024, Volume and Issue: 163, P. 112056 - 112056

Published: May 11, 2024

To effectively develop strategies that address the escalating surface temperatures of cities in diverse landscape characters, various and sometimes contradicting drivers are presented literature. A synthesis findings observations this aspect is lacking. Therefore, main tenet our study was to identify robust metrics (LMs) drive dynamics urban land temperature (ULST) analyse extent which character influences their impact. We adopted a systematic literature review protocol, augmented with different geospatial datasets (at global scale) applied mixed approaches for analyses. total 101 relevant articles were identified, although skewed towards Asia; methods utilised analysing LMs – ULST relationship; about 432 unique revealed only 11 % these confirmed be robust. Landscape elements found exert slight moderate significant influence on − relationship reported This further strengthened proposition need consider understanding environments. end, we developed an interactive scheme synthesize reveal characters. Our FAIRly-open serves as call scientific community stakeholders engage interact may help rethink (current) mitigation strategies. Also, combining expert local spatial knowledge can offer practical foundation addressing ULSTs across landscapes.

Language: Английский

Citations

4
Rock Slope Stability Analysis Using Ensemble Decision Tree Approaches and Feature Importance Along an Economic Corridor in Central India DOI
Nikhil Kumar Pandey, Kunal Gupta, Neelima Satyam

et al.

Physics and Chemistry of the Earth Parts A/B/C, Journal Year: 2025, Volume and Issue: unknown, P. 103868 - 103868

Published: Jan. 1, 2025

Language: Английский

Citations

0
High-Resolution Insights into Nighttime Urban Heat Island Detection: a comparative temporal analysis of 1988 and 2015 in Greater Cairo DOI

Faten Nahas

GeoJournal, Journal Year: 2025, Volume and Issue: 90(1)

Published: Jan. 23, 2025

Language: Английский

Citations

0
Exploring the impact of urban spatial morphology on land surface temperature: A case study in Linyi City, China DOI Creative Commons

Yongyu Feng,

Huimin Wang, Jing Wu

et al.

PLoS ONE, Journal Year: 2025, Volume and Issue: 20(1), P. e0317659 - e0317659

Published: Jan. 27, 2025

The increasing population density and impervious surface area have exacerbated the urban heat island effect, posing significant challenges to environments sustainable development. Urban spatial morphology is crucial in mitigating effect. This study investigated impact of on land temperature (LST) at township scale. We proposed a six-dimensional factor system describe morphology, comprising Atmospheric Quality, Remote Sensing Indicators, Terrain, Land Use/Land Cover, Building Scale, Socioeconomic Factors. Spatial autocorrelation regression methods were used analyze impact. To this end, township-scale data Linyi City from 2013 2022 collected. results showed that LST are significantly influenced by with strongest correlations found factors use types, landscape metrics, remote sensing indices. global Moran’s I value exceeds 0.7, indicating strong positive correlation. High-High LISA values distributed central western areas, Low-Low northern regions some scattered counties. Geographically Weighted Regression (GWR) model outperforms Error Model (SEM) Ordinary Least Squares (OLS) model, making it more suitable for exploring these relationships. findings aim provide valuable references town planning, resource allocation,

Language: Английский

Citations

0