Earth Science Informatics, Journal Year: 2024, Volume and Issue: 18(1)
Published: Dec. 14, 2024
Language: Английский
One Earth, Journal Year: 2024, Volume and Issue: 7(8), P. 1387 - 1401
Published: June 13, 2024
Urbanization is usually ignored when estimating past changes in large-scale climate and for future projections since cities historically covered a small fraction of the Earth's surface. Here, by combining global land surface temperature observations with historical estimates urban area, we demonstrate that contribution to continental- regional-scale warming has become non-negligible, especially rapidly urbanizing regions countries Asia. Consequently, expected expansion over next century suggests further increased influence on (approximately 0.16 K North America Europe high-emission scenario 2100). Based these results, also seen air temperature, argue that, line other forms use/land cover change, urbanization should be explicitly included change assessments. This requires incorporation dynamic extent biophysics current-generation Earth system models quantify potential feedback across scales.
Language: Английский
Citations
13
Earth system science data, Journal Year: 2024, Volume and Issue: 16(11), P. 5357 - 5374
Published: Nov. 25, 2024
Abstract. Understanding urban vertical structures, particularly building heights, is essential for examining the intricate interaction between humans and their environment. Such datasets are indispensable a variety of applications, including climate modeling, energy consumption analysis, socioeconomic activities. Despite importance this information, previous studies have primarily focused on estimating heights regionally at grid scale, often resulting in with limited coverage or spatial resolution. This limitation hampers comprehensive global analysis ability to generate actionable insights finer scales. In study, we developed height map footprint scale by leveraging Earth Observation (EO) advanced machine learning techniques. Our approach integrated multisource remote-sensing features morphology develop estimation models using extreme gradient boosting (XGBoost) regression method across diverse regions. methodology allowed us estimate individual buildings worldwide, culminating creation three-dimensional (3D) Global Building Footprints (3D-GloBFP) dataset year 2020. evaluation results show that perform exceptionally well R2 values ranging from 0.66 0.96 root-mean-square errors (RMSEs) 1.9 14.6 m 33 subregions. Comparisons other demonstrate 3D-GloBFP closely matches distribution pattern reference heights. derived 3D shows distinct regions, countries, cities, gradually decreasing city center surrounding rural areas. Furthermore, our findings indicate disparities built-up infrastructure (i.e., volume) different countries cities. China country most intensive total (5.28×1011 m3, accounting 23.9 % total), followed USA (3.90×1011 17.6 total). Shanghai has largest volume (2.1×1010 m3) all representative The building-footprint-scale reveals significant heterogeneity environments, providing valuable dynamics climatology. available https://doi.org/10.5281/zenodo.11319912 (Building Americas, Africa, Oceania 3D-GloBFP; Che et al., 2024c), https://doi.org/10.5281/zenodo.11397014 Asia 2024a), https://doi.org/10.5281/zenodo.11391076 Europe 2024b).
Language: Английский
Citations
10
Published: June 24, 2024
Abstract. Understanding urban vertical structures, particularly building heights, is essential for examining the intricate interaction between humans and their environment. Such datasets are indispensable a variety of applications, including climate modeling, energy consumption analysis, socioeconomic activities. Despite importance this information, previous studies have primarily focused on estimating heights regionally grid scale, often resulting in with limited coverage or spatial resolution. This limitation hampers comprehensive global analyses ability to generate actionable insights finer scales. In study, we developed height map (3D-GloBFP) at footprint scale by leveraging Earth Observation (EO) advanced machine learning techniques. Our approach integrated multisource remote sensing features morphology develop estimation models using eXtreme Gradient Boosting (XGBoost) regression method across diverse regions. methodology allowed us estimate individual buildings worldwide, culminating creation first three-dimensional (3-D) footprints (3D-GloBFP). evaluation results show that perform exceptionally well worldwide R2 ranging from 0.66 0.96 root mean square errors (RMSEs) 1.9 m 14.6 33 subregions. Comparisons other demonstrate our 3D-GloBFP closely matches distribution pattern reference heights. derived 3-D shows distinct regions, countries, cities, gradually decreasing city center surrounding rural areas. Furthermore, findings indicate disparities built-up infrastructure (i.e., volume) different countries cities. China country most intensive total (5.28×1011 m3, accounting 23.9 % total), followed United States (3.90×1011 17.6 total). Shanghai has largest volume (2.1×1010 m3) all representative The building-footprint reveals significant heterogeneity environments, providing valuable dynamics climatology. dataset available https://doi.org/10.5281/zenodo.11319913 (Building Americas, Africa, Oceania 3D-GloBFP) (Che et al., 2024a), https://doi.org/10.5281/zenodo.11397015 Asia 2024b), https://doi.org/10.5281/zenodo.11391077 Europe 2024c).
Language: Английский
Citations
9
The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 954, P. 176638 - 176638
Published: Oct. 2, 2024
Language: Английский
Citations
8
Heliyon, Journal Year: 2024, Volume and Issue: 10(13), P. e33708 - e33708
Published: June 28, 2024
Urban heat island (UHI) and thermal comfort conditions are among the impacts of urbanization, which have been extensively studied in most cities around world. However, comprehensive studies Indonesia context urbanization is still lacking. This study aimed to classify land use cover (LULC) analyse urban growth its effects on surface islands (SUHIs) as well contributing factors SUHI intensity (SUHII) using remote sensing western part Java Island three focused areas: Jakarta metropolitan area (JMA), Bandung Cimahi Municipalities (BC), Sukabumi Municipality (SKB). Landsat imagery from years was used: 2000, 2009, 2019. Three types daytime SUHII were quantified, namely central two SUHIIs sprawl area. In last decades, areas grown by more than twice JMA SKB nearly 1.5 times BC. Along with cities, has almost reached a magnitude 6 °C decade. Rates temperature change unchanged pixels magnitudes 0.25, 0.15, 0.14 °C/year JMA, SKB, BC, respectively. The field variance index (UTFVI) discomfort (DI) showed that strongest effect prevalent regions mostly very hot categories. Anthropogenic flux ratio positive contributions variation, while vegetation water ratios negative contributors variation. For each city, unique can be used evaluate mitigation options.
Language: Английский
Citations
4
IEEE Transactions on Geoscience and Remote Sensing, Journal Year: 2024, Volume and Issue: 62, P. 1 - 14
Published: Jan. 1, 2024
Language: Английский
Citations
4
Journal of Building Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 112357 - 112357
Published: March 1, 2025
Language: Английский
Citations
0
Remote Sensing, Journal Year: 2025, Volume and Issue: 17(6), P. 1044 - 1044
Published: March 16, 2025
This paper addresses the challenge of small object detection in remote sensing image recognition by proposing an improved YOLOv8-based lightweight attention cross-scale feature fusion model named LACF-YOLO. Prior to backbone network outputting maps, this introduces a module, Triplet Attention, and replaces Concatenation with Fusion (C2f) more convenient higher-performing dilated inverted convolution layer acquire richer contextual information during extraction phase. Additionally, it employs convolutional blocks composed partial pointwise as main body integrate from different levels. The also utilizes faster-converging Focal EIOU loss function enhance accuracy efficiency. Experimental results on DOTA VisDrone2019 datasets demonstrate effectiveness model. Compared original YOLOv8 model, LACF-YOLO achieves 2.9% increase mAP 4.6% mAPS dataset 3.5% 3.8% dataset, 34.9% reduction number parameters 26.2% decrease floating-point operations. exhibits superior performance aerial detection.
Language: Английский
Citations
0
Urban Science, Journal Year: 2025, Volume and Issue: 9(4), P. 95 - 95
Published: March 25, 2025
Urbanization promotes urban infrastructure development and increases artificial impervious surfaces, leading to rising temperatures climate alterations, contributing the appearance intensification of Urban Heat Island (UHI). In this study, a 40-year time series Landsat images city Oran was used generate two biophysical indices. The Normalized Difference Built-up Index (NDBI) distinguished built-up areas from non-built-up areas, while semi-automatic classification produced Land Use/Land Cover (LULC) maps, for precise analysis sprawl. results revealed significant expansion with an increase 65.28 km2 between 1984 2024. Vegetation (NDVI) estimate Surface Temperature (LST) by applying “Mono Window” algorithm Thematic Mapper (TM) “Split Enhanced (ETM+) Operational Imager–Thermal Infrared Sensor (OLI–TIRS) images. surface temperature difference rural increased 0.36 °C in 4.5 2024, highlighting UHI (SUHI) effect. LST maps also helped identify most vulnerable UHI, as well those where effect is persistent, corresponding Permanent (PUHI).
Language: Английский
Citations
0
Springer proceedings in physics, Journal Year: 2025, Volume and Issue: unknown, P. 57 - 76
Published: Jan. 1, 2025
Language: Английский
Citations
0