ABSTRACT
The Qinghai-Tibet Plateau (QTP) holds significance for investigating Earth's surface processes. However, due to rugged terrain, forest canopy, and snow accumulation, open-access Digital Elevation Models (DEMs) exhibit considerable noise, resulting in low accuracy and pronounced data inconsistency. Furthermore, the glacier regions within the QTP undergo substantial changes, necessitating updates. This study employs a fusion of open-access DEMs and high-accuracy photons from the Ice, Cloud, and land Elevation Satellite-2 (ICESat-2). Additionally, snow cover and canopy heights are considered, and an ensemble learning fusion model is presented to harness the complementary information in the multi-sensor elevation observations. This innovative approach results in the creation of HQTP30, the most accurate representation of the 2021 QTP terrain. Comparative analysis with high-resolution imagery, UAV-derived DEMs, control points, and ICESat-2 highlights the advantages of HQTP30. Notably, in non-glacier regions, HQTP30 achieved a Mean Absolute Error (MAE) of 0.71 m, while in glacier regions, it reduced the MAE by 4.35 m compared to the state-of-the-art Copernicus DEM (COPDEM), demonstrating its versatile applicability.
ABSTRACT
Human activities have placed significant pressure on the terrestrial biosphere, leading to ecosystem degradation and carbon losses. However, the full impact of these activities on terrestrial biomass carbon remains unexplored. In this study, we examined changes in global human footprint (HFP) and human-induced aboveground biomass carbon (AGBC) losses from 2000 to 2018. Our findings show an increasing trend in HFP globally, resulting in the conversion of wilderness areas to highly modified regions. These changes have altered global biomes' habitats, particularly in tropical and subtropical regions. We also found accelerated AGBC loss driven by HFP expansion, with a total loss of 19.99 ± 0.196 PgC from 2000 to 2018, especially in tropical regions. Additionally, AGBC is more vulnerable in the Global South than in the Global North. Human activities threaten natural habitats, resulting in increasing AGBC loss even in strictly protected areas. Therefore, scientifically guided planning of future human activities is crucial to protect half of Earth through mitigation and adaptation under future risks of climate change and global urbanization.
Subject(s)
Carbon , Ecosystem , Humans , Biomass , Carbon/metabolism , Climate ChangeABSTRACT
Human Footprint, the pressure imposed on the eco-environment by changing ecological processes and natural landscapes, is raising worldwide concerns on biodiversity and ecological conservation. Due to the lack of spatiotemporally consistent datasets of Human Footprint over a long temporal span, many relevant studies on this topic have been limited. Here, we mapped the annual dynamics of the global Human Footprint from 2000 to 2018 using eight variables that reflect different aspects of human pressures. The accuracy assessment revealed a good agreement between our mapped results and the previously developed datasets in different years. We found more than two million km2 of wilderness (i.e., regions with Human Footprint values below one) were lost over the past two decades. The biome dominated by mangroves experienced the most significant loss (i.e., above 5%) of wilderness, likely attributed to intensified human activities in coastal areas. The derived annual and spatiotemporally consistent global Human Footprint can be a fundamental dataset for many relevant studies about human activities and natural resources.
ABSTRACT
Deduction of urban green space (UGS) and the multidimensional growth of building have exacerbated the urban heat island (UHI). Yet thorough investigations into how 3D building features and UGS combinedly influence urban land surface temperature (LST) are limited, especially at the road-based blocks scale. Therefore, the study uses the boosted regression tree (BRT) model to explore the relative contribution and marginal effects of the influential factors on LST, and quantify the warming/cooling effects of buildings and UGS. Results show that, (1) building coverage ratio (BCR) is the most influential factor among seven building metrics with a relative contribution of 44.6%. Besides, high-rise buildings tend to alleviate LST while low- and mid-rise buildings heat the surroundings. (2) Green coverage ratio (GCR), edge density (ED), and patch density (PD) are the most influential factors among six UGS metrics, with the relative contribution of 21.0%, 20.9%, and 20.4%, respectively. (3) Comprehensively considering 13 metrics, we find that the dominant influential factor is BCR with a relative contribution of 28.3%, while the regulation amplitudes to LST of aggregation index (AI) and GCR dramatically reduced. These findings indicate that the cooling effect of UGS will be obscured when the buildings coverage is large. Hence, only relying on UGS to alleviate the heat island effect seems inadequate, the keys are the reasonable planning and optimization of 3D built environment.
Subject(s)
Hot Temperature , Parks, Recreational , Cities , Environmental Monitoring , TemperatureABSTRACT
Urban air pollution with PM2.5 as the main pollutant has become increasingly prominent in China since 2010. Scholars have conducted many studies on how urbanization affects PM2.5, but few concerns about the relationship between construction land (CL) expansion and PM2.5 at different scales from the perspective of expansion rate. Therefore, this study takes CL and PM2.5 data in China to describe the spatiotemporal progress of atmospheric environmental pollution and then adopts the overall and spatial coupling models to quantitatively reveal the dynamic relationship between them. The results indicate that the growth rate of PM2.5-polluted area in China was found to increase rapidly for 2000-2010 time period, followed by a continuous decline afterward. The annual average growth rates of CL area and PM2.5-polluted area within 15 years were 4.43% and 2.46%, respectively. Moreover, the barycenter distance between PM2.5 concentration and CL decreased gradually, and the two barycenters approached closer. Also, the spatial coupling coordination of CL and PM2.5 enhanced in Central, West, and East China but weakened in Northeast. Cities with a "very strong" coupling type are mainly located in the "Chongqing-Beijing" belt and the lower-middle reaches of the Yangtze River. Finally, the spatial coupling model results show that a low PM2.5 concentration is closely related to CL expansion. This study will provide a basis for cross-regional joint air pollution control and the management of heavily polluted areas in China.
ABSTRACT
Rapid urbanisation causes large urban conversions of natural and agricultural land to non-agricultural use. Research on urban expansion has typically disregarded gradient characteristics. The current study uses slope data calculated based on the Shuttle Radar Topography Mission Digital Elevation Model data set and multi-period land cover data derived from China's Multi-Period Land Use Land Cover Remote Sensing Monitoring data set to reveal the evolution of spatiotemporal patterns of vertical urban expansion in China from 1990 to 2015. A built-up land climbing index is specifically defined to measure the increasing use of land with slopes. A slope-climbing phenomenon has become increasingly apparent over time. Although built-up land with slopes below 5° accounts for over 85% of the total, this proportion has declined steadily from 89.53% in 1990 to 86.61% in 2015. The number of cities where built-up land was developed on high slopes (over 5°) increased from 150 to 238. Slope-climbing intensity spatially increased from north to south, and showed a "low-high-low" pattern from west to east. In addition, built-up land showed evident slope-climbing trend in areas with high variation in slope. Slope-climbing intensity was high for cities located in mountains and ethnic autonomous prefectures. Lastly, cities going uphill are subjected to the combined effects of natural environmental conditions and social factors. The average slope and population growth have significantly positive impact on slope-climbing intensity.
ABSTRACT
The rapid urbanization has greatly changed the spatial pattern and function of regional habitats, profoundly affected the material flow and energy flow between habitats, and also posed a serious threat to habitats and biodiversity. Here, we used InVEST model, landscape index and multiple linear regression to systematically analyze the spatial and temporal variation and influencing factors for the impacts of urbanization on habitat quality in the Loess Plateau and the densely populated areas from 1990 to 2018. The results showed that the urban expansion of Loess Plateau significantly affected habitat quality. Between 1990 and 2018, the area of construction land increased by 49.6%, resulting in a 5.2% reduction in the total area of habitat patch. After 2010, the urban patch area increased, but the patch density and fragmentation decreased, resulting in a spatial pattern of "high outside and low inside" for urban habitat quality. The rate of urban expansion in densely populated areas was significantly negatively correlated with the habitat quality. The average value of habitat quality in the region dropped by 2.7%, whereas the level of habitat degradation increased by 33.4%. The level of habitat quality was unstable, and patches with high-level habitats were easily converted to lower level. The conversion rates of Lanzhou, Xi'an-Xianyang and Taiyuan were 12.9%, 2.9% and 1.7%, respectively. There were eight influencing factors that could effectively explain the spatial variation of habitat quality (R2=68.7%). Among those factors, population density and distance to roads were the main factors for the fragmentation of habitats, while slope, GDP and precipitation had positive effects on the optimization of habitat spatial patterns.
