地理学与可持续性(英文)

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Wind farms increase land surface temperature and reduce vegetation productivity in the Inner Mongolia

Luyao Liu, Pengtao Liu, Jiawei Yu, Gang Feng, Qing Zhang, Jens-Christian Svenning

2024, 5(3): 319-328. https://doi.org/10.1016/j.geosus.2024.01.007

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Wind power has been developing rapidly as a key measure to mitigate human-driven global warming. The understanding of the development and impacts of wind farms on local climate and vegetation is of great importance for their rational use but is still limited. In this study, we combined remote sensing and on-site investigations to identify wind farm locations in Inner Mongolia and performed landscape pattern analyses using Fragstats. We explored the impacts of wind farms on land surface temperature (LST) and vegetation net primary productivity (NPP) between 1990 and 2020 by contrasting these metrics in wind farms with those in non-wind farm areas. The results showed that the area of wind farms increased rapidly from 1.2 km2 in 1990 to 10,755 km2 in 2020. Spatially, wind farms are mainly clustered in three aggregation areas in the center. Further, wind farms increased nighttime LST, with a mean value of 0.23 °C, but had minor impacts on the daytime LST. Moreover, wind farms caused a decline in NPP, especially over forest areas, with an average reduction of 12.37 GC/m². Given the impact of wind farms on LST and NPP, we suggest that the development of wind farms should fully consider their direct and potential impacts. This study provides scientific guidance on the spatial pattern of future wind farms.}

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Measuring urban thermal environment from accessibility-based perspective: A case study in a populous city

Xinyu Dong, Xiaoya Li, Yanmei Ye, Dan Su, Runjia Yang, Angela Lausch

2024, 5(3): 329-342. https://doi.org/10.1016/j.geosus.2024.02.004

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Understanding the spatial interaction among residents, cooling service, and heat risk area in complex urban areas is conducive to developing targeted management. However, traditional urban thermal environment assessments typically relied on simple linear integration of associated indicators, often neglecting the spatial interaction effect. To explore the spatial interaction among the three elements, this study proposes an accessibility-based urban thermal environment assessment framework. Using Zhengzhou, a rapidly urbanizing city, as an example, remotely sensed images from three periods (2010, 2015 and 2020) were applied to extract urban green space (UGS) and hot island area (HIA). An improved two-step floating catchment area (2SFCA) method and bivariate local Moran’s I were employed to explore whether residents’ clustering locations are more likely to access cooling service or to be exposed to heat risk. The results demonstrate that the UGS in the city has been expanding, whereas the HIA shrank within the inner city in 2015 and then increased in 2020. Even though the urban thermal environment may have improved in the last decade, the spatial interaction among the residents, cooling service and heat risk area could be exacerbated. Spatial autocorrelation shows an increase in locations that are disadvantageous for resident congregation. Even when sufficient cooling services were provided, residents in these areas could still be exposed to high heat risk. The developed urban thermal environment framework provides a novel insight into the residents’ heat risk exposure and cooling service accessibility, and the findings could assist urban planners in targeting the improvement of extra heat exposure risk locations.}

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Increased population exposures to extreme precipitation in Central Asia under 1.5 ℃ and 2 ℃ global warming scenarios

Wei Wei, Shan Zou, Weili Duan, Yaning Chen, Shuai Li, Takahiro Sayama, Jianyu Zhu

2024, 5(3): 343-356. https://doi.org/10.1016/j.geosus.2024.02.005

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The increase in extreme precipitation (EP) may pose a serious threat to the health and safety of population in arid and semi-arid regions. The current research on the impact of EP on population in Central Asia (CA) is insufficient and there is an urgent need for a comprehensive assessment. Hence, we opted for precipitation and temperature data under two Shared Socioeconomic Pathways (SSP2–4.5 and SSP5–8.5) from ten Global Climate Models (GCMs), which were obtained from the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP-CMIP6). By integrating population data in 2020 and 2050 (SSP2 and SSP5), we investigated the future changes in EP and population exposure in CA under 1.5 °C and 2 °C global warming scenarios (GWSs). Our analysis indicates that EP in CA is projected to increase with global warming. Under the SSP5–8.5, the maximum daily precipitation (Rx1day) exhibits an average response rate to global warming of 3.58 %/K (1.99–4.06 %/K). With rising temperatures, an increasing number of areas and populations in CA will be impacted by EP, especially in the Fergana valley. Approximately 25% of the population (land area) in CA is exposed to Rx1day with increases of more than 8.31% (9.32%) under 1.5 °C GWS and 14.18% (13.25%) under 2 °C GWS. Controlling temperature rise can be effective in reducing population exposures to EP. For instance, limiting the temperature increase to 1.5 °C instead of 2 °C results in a 2.79% (1.75%–4.59%) reduction in population exposure to Rx1day. Finally, we found that climate change serves as the predominant factor influencing the population exposure to EP, while the role of population redistribution, although relatively minor, should not be disregarded. Particularly for prolonged drought, the role of population redistribution manifests negatively.}

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Urbanity mapping reveals the complexity, diffuseness, diversity, and connectivity of urbanized areas

Dawa Zhaxi, Weiqi Zhou, Steward T. A. Pickett, Chengmeng Guo, Yang Yao

2024, 5(3): 357-369. https://doi.org/10.1016/j.geosus.2024.03.004

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There are urgent calls for new approaches to map the global urban conditions of complexity, diffuseness, diversity, and connectivity. However, existing methods mostly focus on mapping urbanized areas as bio physical entities. Here, based on the continuum of urbanity framework, we developed an approach for cross-scale urbanity mapping from town to city and urban megaregion with different spatial resolutions using the Google Earth Engine. This approach was developed based on multi-source remote sensing data, Points of Interest – Open Street Map (POIs-OSM) big data, and the random forest regression model. This approach is scale-independent and revealed significant spatial variations in urbanity, underscoring differences in urbanization patterns across megaregions and between urban and rural areas. Urbanity was observed transcending traditional urban boundaries, diffusing into rural settlements within non-urban locales. The finding of urbanity in rural communities far from urban areas challenges the gradient theory of urban-rural development and distribution. By mapping livelihoods, lifestyles, and connectivity simultaneously, urbanity maps present a more comprehensive characterization of the complexity, diffuseness, diversity, and connectivity of urbanized areas than that by land cover or population density alone. It helps enhance the understanding of urbanization beyond biophysical form. This approach can provide a multifaceted understanding of urbanization, and thereby insights on urban and regional sustainability.}

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Spatial patterns and driving forces of urban vegetation greenness in China: A case study comprising 289 cities

Yansong Jin, Fei Wang, Quanli Zong, Kai Jin, Chunxia Liu, Peng Qin

2024, 5(3): 370-381. https://doi.org/10.1016/j.geosus.2024.03.001

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Urban vegetation in China has changed substantially in recent decades due to rapid urbanization and dramatic climate change. Nevertheless, the spatial differentiation of greenness among major cities of China and its evolution process and drivers are still poorly understood. This study examined the spatial patterns of vegetation greenness across 289 cities in China in 2000, 2005, 2010, 2015, and 2018 by using spatial autocorrelation analysis on the Normalized Difference Vegetation Index (NDVI); then, the influencing factors were analyzed by using the optimal parameters-based geographical detector (OPGD) model and 18 natural and anthropogenic indicators. The findings demonstrated a noticeable rise in the overall greenness of the selected cities during 2000–2018. The cities in northwest China and east China exhibited the rapidest and slowest greening, respectively, among the six sub-regions. A significant positive spatial correlation was detected between the greenness of the 289 cities in different periods, but the correlation strength weakened over time. The hot and very hot spots in southern and eastern China gradually shifted to the southwest. While the spatial pattern of urban greenness in China is primarily influenced by wind speed (WS) and precipitation (PRE), the interaction between PRE and gross domestic product (GDP) has the highest explanatory power. The explanatory power of most natural factors decreased and, conversely, the influence of anthropogenic factors generally increased. These findings emphasize the variations in the influence strength of multiple factors on urban greenness pattern, which should be taken into account to understand and adapt to the changing urban ecosystem.}

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Sustainable land management in Mali

Karim Nchare, Marcel Vitouley, Richard Mbih

2024, 5(3): 382-391. https://doi.org/10.1016/j.geosus.2024.03.003

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This study uses logistic and Poisson regression models to examine the factors influencing the adoption of sustainable land management (SLM) practices in Mali using two rounds of the nationally representative survey Enquête Agricole de Conjoncture Intégrée aux Conditions de Vie des Ménages. The SLMs considered include the application of organic fertilizers, the application of inorganic fertilizers, the use of improved seeds, and the practice of intercropping. On average the application of organic fertilizers (39.2%), and inorganic fertilizers (28.7%) are the most frequent SLM practices among Malian farmers, and between 2014 and 2017, we observe a decline in the practice of intercropping. The regression results show that farmers’ adoption of different SLMs is significantly associated with biophysical factors (average temperature, climate type, plot size, plot shape, and location), demographic factors (age, gender, education, household size), and socioeconomic factors (number of cultivated plots, livelihood diversification, type of crop grown, market access, credit access, economic shocks, and social capital). Our findings suggest that policymakers and agricultural development agencies in Mali need to adopt a multidimensional policy framework to unlock the untapped potential of SLM practices in promoting sustainable agriculture and food security.}

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Exploring factors of disaster preparedness in UNESCO-designated heritage sites

Emmanuel Eze, Alexander Siegmund

2024, 5(3): 392-404. https://doi.org/10.1016/j.geosus.2024.04.001

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Increased hazards threatening the United Nations Educational, Scientific and Cultural Organization (UNESCO)-designated sites and endangering cultural heritage and community well-being require attention and action. Considering the pivotal role of UNESCO sites in conservation and development, this study assessed their levels of disaster preparedness. The absence of studies assessing disaster awareness, risk perception, and preparedness among UNESCO site actors, as well as the pivotal place of preparedness within the Disaster Risk Management (DRM) cycle justifies this research. Applying the tenets of the Person-Relative-to-Event framework, we hypothesized that a strong positive correlation exists between perceived risks, resources, and disaster preparedness. To collect pertinent data, we employed an embedded mixed-method design and conducted an online questionnaire survey yielding 141 responses from 59 countries. From the results of relevant analyses, wildfires, floods, and droughts are top hazards occurring frequently in UNESCO sites, with significant concerns about pollution and habitat loss during future events. Smartphones emerged as the most available crucial DRM resource, with higher availability of DRM resources correlating positively and significantly with sites’ preparedness. Our findings contribute valuable insights to address missing links for disaster-ready and resilient UNESCO sites, promoting their preservation for future generations.}

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Prevalence of vegetation browning in China’s drylands under climate change

Li Fu, Guolong Zhang, Jianping Huang, Ming Peng, Lei Ding, Dongliang Han

2024, 5(3): 405-414. https://doi.org/10.1016/j.geosus.2024.04.002

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Vegetation greening has long been acknowledged, but recent studies have pointed out that vegetation greening is possibly stalled or even reversed. However, detailed analyses about greening reversal or increased browning of vegetation remain scarce. In this study, we utilized the normalized difference vegetation index (NDVI) as an indicator of vegetation to investigate the trends of vegetation greening and browning (monotonic, interruption, and reversal) through the breaks for the additive season and trend (BFAST) method across China’s drylands from 1982 to 2022. It also reveals the impacts of ecological restoration programs (ERPs) and climate change on these vegetation trends. We find that the vegetation displays an obvious pattern of east-greening and west-browning in China’s drylands. Greening trends mainly exhibits monotonic greening (29.8 %) and greening with setback (36.8 %), whereas browning shows a greening to browning reversal (19.2 %). The increase rate of greening to browning reversal is 0.0342/yr, which is apparently greater than that of greening with setback, 0.0078/yr. This research highlights that, under the background of widespread vegetation greening, vegetation browning is progressively increasing due to the effects of climate change. Furthermore, the ERPs have significantly increased vegetation coverage, with the increase rate in 2000–2022 being twice as much as that of 1982–1999 in revegetation regions. Vegetation browning in southwestern Qingzang Plateau is primarily driven by adverse climatic factors and anthropogenic disturbances, which offset the efforts of ERPs.}

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The carrying capacity for vegetation of forest land across China: Near real-time monitoring and short-term forecasting based on satellite observation

Huiqian Yu, Nan Lu, Bojie Fu, Lu Zhang, Shufen Pan

2024, 5(3): 415-429. https://doi.org/10.1016/j.geosus.2024.04.005

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Ecological restoration projects implemented over the past 20 years have substantially increased forest coverage in China, but the high tree mortality of new afforestation forest remains a challenging but unsolved problem. It is still not clear how much vegetation can be sustained by the forest lands with given water, energy and soil conditions, i.e., the carrying capacity for vegetation (CCV) of forest lands, which is the prerequisite for planning and implementing forest restoration projects. Here, we used a simplified method to evaluate the CCV across forest lands nationwide. Specifically, based on leaf area index (LAI) dataset, we use boosted regression tree and multiple linear regression model to analyze the CCV during 2001–2020 and 2021–2030 and explore the contribution of environmental factors. We find that there are three typical regions with lower CCV located in the Loess Plateau and the southern region of the Inner Mongolia Plateau, the Hengduan Mountain region, and the Tianshan Mountains. More importantly, the vegetation in the regions near the dry-wet climate transition zone show excess local carrying capacity for vegetation over the past two decades and they are more susceptible to potential climatic stress. In comparison, in the Greater Khingan Mountains and Hengduan Mountains, there is high potential to improve the forest growth. Temperature, precipitation and soil affects the CCV by shaping the vegetation in the optimal range. This indicates that more consideration should be given to restrictions of regional environmental constraints when planning afforestation and forest management. This study has important implications for guiding future forest scheme in China.}

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Residents’ perceptions of ecosystem services in an urbanizing basin: A case study in the Guanting Reservoir basin, China

Yansong Bai, Qingxu Huang, Luis Inostroza, Haoran Xu, Dan Yin, Ziwen Liu, Ling Zhang, Fangjin Xu

2024, 5(3): 430-444. https://doi.org/10.1016/j.geosus.2024.04.004

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Understanding stakeholders’ differences in perceptions of ecosystem services (ES) is crucial for guiding ecological conservation and planning. However, the variations of ES perception amongst different types of residents in urbanizing areas along an urban-rural gradient are still poorly understood. Combining a questionnaire-based survey, redundancy analysis, and statistical tests, we delineated the urban-rural gradient according to local residents’ socio-economic characteristics, and investigated the differences in local residents’ perceptions of ES and potential factors affecting them in the Guanting Reservoir basin, a rapidly urbanizing basin in China. The results showed that residents living in urban-rural transitional areas attached great importance to provisioning services of providing food and domestic water, regulating services of carbon sequestration and air purification, and cultural services of providing education and training, which were 0.7%–13.1%, 0.7%–9.1% and 2.5%–21.2% higher than that of residents in other areas, respectively. Age and occupation were major factors affecting residents’ perceptions. In terms of land-use types that deliver ES, the difference in perceptions of ES delivered by grassland was the greatest amongst residents. Our results support recommendations for policymakers to take into account the stakeholders’ diverse perceptions, thus promoting residents’ sense of gain on ES.}

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Unpacking the ‘supply-utilization-demand’ interplay: Keys to multifunctional sustainability in rural China

Yanbo Qu, Lingyun Zhan, Qingqing Zhang, Meijing Wu

2024, 5(3): 445-458. https://doi.org/10.1016/j.geosus.2024.04.006

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Sustainable rural development is predicated on a delicate balance between rural territorial functions and ecological constraints. While various functions can catalyze economic growth in rural settings, aligning them with inherent ecological variables is essential. An exhaustive analysis of Beijing’s Pinggu District elucidated specific supply-demand thresholds and evaluated the adaptability of current utilization within these boundaries, culminating in a novel optimization strategy. Notably, while locals place significant emphasis on production functions, the area’s topography and soil characteristics present palpable challenges to achieving these goals. We discovered that ‘shackle type’ predominantly characterize individual rural territorial functions, while ‘diversified weak function optimization type’ define multifunctional aspects, showcasing varied development paths and uncovering potential strategies for sustainable improvement. This study contributes a groundbreaking perspective to sustainable rural development, offering key insights and strategic recommendations for policy formulation.

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