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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Environmental Sustainability and Applications".

Deadline for manuscript submissions: closed (29 February 2024) | Viewed by 22267

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Special Issue Editors

Dr. Bing Guo

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Guest Editor

School of Civil and Architectural Engineering, Shandong University of Technology, Zibo 255000, China
Interests: climate change; land use; remote sensing; land degradation; natural hazards
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Weijun Zhao

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Guest Editor

Department of geography, Taishan University, Taian 271000, China
Interests: climate change; ecological environment assessments; soil erosion and conservation
Special Issues, Collections and Topics in MDPI journals

Dr. Jinxin Zhu

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Guest Editor

School of Geography and Planning, Sun Yat-Sen University, Guangzhou, China
Interests: climate modeling; climate extremes; climate change adaptation
Special Issues, Collections and Topics in MDPI journals

Dr. Jianwan Ji

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Guest Editor

School of Geography Science and Geomatics Engineering, Suzhou University of Science and Technology, Suzhou 215009, China
Interests: eco-environment monitoring and assessment; coordination analysis; spatial analysis; sustainable development
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Climate change refers to long-term shifts in temperature and weather patterns, and these swings may be natural or may be as a result of human activities, such as burning fossil fuels like coal, oil, and gas. Global atmospheric temperature is predicted to rise by approximately 4 °C by 2080, which is consistent with a doubling of atmospheric carbon dioxide (CO₂) concentration. These climate changes have resulted in increased frequency and occurrence of climate-induced environmental disasters (floods, cyclones, mud slides, heat waves, and droughts), which cause great stress to already vulnerable livelihoods, as well as health, food systems and sustainability, structures, and safety. In the recent decades, over 4 billion people have been affected by disasters globally, and over 1,000,000 people have died. In addition, under the rapid urban sprawl, many eco-environment issues have attracted great concern, such as forest area reduction, air quality degradation, land degradation, etc. Hence, it is of great importance to report new methods, new technologies and new theories on climate change, eco-environmental monitoring and assessment, and disaster monitoring.

Based on the above, the Special Issue aims at collecting articles providing approaches, methods, tools, and best practices to reveal the change trend and characteristics of climate and environmental disasters. Moreover, the Special Issue is devoted to promoting advances in understanding and modeling the relationships between climate change and environmental disasters. Studies that to inform climate change adaptation and environmental disaster risk assessments are also welcomed.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but not limited to) the following:

Climate change adaptation and disaster management;
Global and regional climate modelling and monitoring;
Spatial and temporal change patterns of environmental disasters;
Response mechanisms of environmental disasters to climate change;
Detection of environmental disasters based on remote sensing;
Observed and projected climate extremes.

We look forward to receiving your contributions.

You may choose our Joint Special Issue in Urban Science.

Dr. Bing Guo
Prof. Dr. Weijun Zhao
Dr. Jinxin Zhu
Dr. Jianwan Ji
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (13 papers)

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Research

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20 pages, 7494 KiB

Open AccessArticle

Estimating the Past and Future Trajectory of LUCC on Wetland Ecosystem Service Values in the Yellow River Delta Region of China

by Zhiyi Zhang, Liusheng Han, Zhaohui Feng, Jian Zhou, Shengshuai Wang, Xiangyu Wang and Junfu Fan

Sustainability 2024, 16(2), 619; https://doi.org/10.3390/su16020619 - 10 Jan 2024

Cited by 1 | Viewed by 706

Abstract

Land use/cover change (LUCC) can impact the provision of ecosystem service values (ESVs), particularly in wetland regions that are subject to frequent and unsustainable land conversions. Exploring the past and future trajectory of LUCC and its effects on ESV has a great significance for wetland management and habitat stability. This study tried to reveal the patterns and magnitude of LUCC on ESV under varying land development scenarios in the Yellow River Delta region, which is a typical region undergoing serious degradation in China. In this study, a combined approach utilizing equivalent coefficients of ecosystem services was employed to determine the ESV of the wetland in relation to the major land use types (LUTs). The Markov–FLUS model was then used to simulate LUTs across multiple scenarios in 2030 and to clarify the relationship of ESV between wetland and other LUTs. The results indicated that the wetland was severely degraded, with a loss in area of 6679.89 ha between 2000 and 2020. Cropland and water body were the main sources of diversion and turnover for the wetland, respectively. Despite the multiple scenario projections revealed, the wetland area exhibited a similar growth rate and a homogeneity in ESV under the natural development (ND), urban construction and development (UCD), and the ecological development (ED) scenarios. The ED scenario was deemed the optimal development strategy for the wetland ecosystem. Our research will improve the comprehension of land development decisions and promote sustainable development in estuarine wetland areas. Full article

(This article belongs to the Special Issue Climate Change and Enviromental Disaster)

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23 pages, 18497 KiB

Open AccessArticle

Analysis of Spatiotemporal Evolution and Influencing Factors of Vegetation Net Primary Productivity in the Yellow River Basin from 2000 to 2022

by Kunjun Tian, Xing Liu, Bingbing Zhang, Zhengtao Wang, Gong Xu, Kai Chang, Pengfei Xu and Baomin Han

Sustainability 2024, 16(1), 381; https://doi.org/10.3390/su16010381 - 31 Dec 2023

Viewed by 802

Abstract

The Yellow River Basin (YRB) plays a very important role in China’s economic and social development and ecological security, so studying the spatiotemporal variation characteristics of net primary productivity (NPP) and its influencing factors is of great significance for protecting the stable development of its ecological environment. This article takes the YRB as the research area, based on Moderate Resolution Imaging Spectroradiometer (MODIS) data, climate data, terrain data, land data, social data, and the gravity recovery and climate experiment (GRACE) data. The spatiotemporal evolution characteristics of vegetation NPP in the YRB from 2000 to 2022 were explored using methods such as trend analysis, correlation analysis, and geographic detectors, and the correlation characteristics of NPP with meteorological factors, social factors, and total water storage (TWS) were evaluated. The results indicate that the NPP of vegetation in the YRB showed an increasing trend (4.989 gC·m⁻²·a⁻¹) from 2000 to 2022, with the most significant changes occurring in the middle reaches of the YRB. The correlation coefficient indicates that temperature and accumulated temperature have a significant positive impact on the change of NPP, while TWS has a significant negative impact. In the study of the factors affecting vegetation NPP in the YRB, the most influential factors are soil type (0.48), precipitation (0.46), and temperature (0.32). The strong correlation between TWS and vegetation NPP in the YRB is about 39%, with a contribution rate of about 0.12, which is a factor that cannot be ignored in studying vegetation NPP changes in the YRB. Full article

(This article belongs to the Special Issue Climate Change and Enviromental Disaster)

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16 pages, 2787 KiB

Open AccessArticle

Numerical Analysis of the Dynamic Response Law of Counter-Tilt Layered Rock Slopes

by Weiguo Wang, Yanping Wang, Binpeng Lan and Guang Zheng

Sustainability 2023, 15(18), 13525; https://doi.org/10.3390/su151813525 - 10 Sep 2023

Viewed by 754

Abstract

Counter-tilt layered rock slopes are common types of slopes that are susceptible to destabilizing damage under seismic action. Therefore, the dynamic response law of counter-tilt layered rock slopes under seismic action is of great significance for the study of slope stability. This study utilizes UDEC (Universal Distinct Element Code) numerical simulation software to vary slope geometry and seismic wave parameters, such as joint thickness, joint inclination angle, slope angle, seismic wave frequency, amplitude, and duration. The maximum displacements of the monitoring points of a slope were obtained, and the dynamic response law of counter-tilt layered rock slopes under seismic action was investigated. The results yielded the following insights: (1) The thickness of the joints of a slope is an important factor affecting the dynamic response of a slope, and with the increase in the thickness of the joints, the maximum displacement of each monitoring point of the slope will decrease. (2) The maximum displacement of a slope increases with the increase in the joint inclination angle and the slope angle. When the joint inclination angle is less than 50°, the change in the joint inclination angle has less of an effect on the maximum displacement of the slope in the x and y directions. When the joint inclination angle is more than 50°, the maximum displacement of the slope in the x and y directions increases faster with the change in the joint inclination angle, and a similar pattern is observed for the slope angle. (3) Slopes are less susceptible to damage when both the joint inclination angle and the slope angle are less than 50°, and the probability of slope damage increases significantly when both are greater than 50°. (4) The maximum displacement at each monitoring point of a slope increases with the frequency, amplitude, and duration of a seismic wave. (5) Seismic wave amplitude has the greatest effect on the dynamic response of a slope, followed by duration, and frequency has the weakest effect on the dynamic response of a slope. The conclusions drawn in this paper can be useful for the control of counter-tilt layered rock slopes. Full article

(This article belongs to the Special Issue Climate Change and Enviromental Disaster)

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18 pages, 11665 KiB

Open AccessArticle

Temporal and Spatial Changes of Drought Characteristics in Temperate Steppes in China from 1960 to 2020

by Jie Chen, Bo Zhang, Jing Zhou and Feng Guo

Sustainability 2023, 15(17), 12909; https://doi.org/10.3390/su151712909 - 26 Aug 2023

Cited by 4 | Viewed by 738

Abstract

To study the change in drought characteristics, it is helpful to explore the dynamics of drought, analyze the rules of drought, and prevent drought. The annual and seasonal standardized precipitation evapotranspiration index (SPEI) was calculated based on the meteorological data of the temperate steppe region of China from 1960 to 2020, and the spatio-temporal variation of drought characteristics was analyzed by combining the run-course theory to identify drought characteristics. The results show that: (1) During 1960–2020, the SPEI of the temperate steppe region fluctuated in the range of −1.5 to 1.5 and decreased significantly at a rate of −0.02·a⁻¹ (p < 0.01). In general, there is an increasing trend of drought in the temperate steppe region. (2) There is little difference in the duration of drought in the four seasons, and the very low duration of drought is about 2 months. The cumulative drought intensity was higher in the semi-arid and semi-humid zones of the temperate zone. (3) The very low value of drought frequency occurred in summer, and the very high value of drought frequency occurred in winter. From SPEI-3 to SPEI-12, that is, from seasonal scale to interannual scale, with the increase of time scale, the distribution of the extreme value of drought frequency moved to the southwest, semi-arid, and arid areas. The frequency of the four drought levels showed light drought > middle drought > severe drought > extreme drought in all time scales and all zones. Full article

(This article belongs to the Special Issue Climate Change and Enviromental Disaster)

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19 pages, 10061 KiB

Open AccessArticle

The Factors Affecting the Quality of the Temperature Vegetation Dryness Index (TVDI) and the Spatial–Temporal Variations in Drought from 2011 to 2020 in Regions Affected by Climate Change

by Yuchen Guo, Liusheng Han, Dafu Zhang, Guangwei Sun, Junfu Fan and Xiaoyu Ren

Sustainability 2023, 15(14), 11350; https://doi.org/10.3390/su151411350 - 21 Jul 2023

Cited by 3 | Viewed by 2819

Abstract

The temperature vegetation dryness index (TVDI) is widely used for the monitoring of global or regional drought because of its strong drought-monitoring capabilities and ease of implementation. However, the temporal errors in the land surface temperature (LST) and normalized difference vegetation index (NDVI) can affect warm and cold edges, thus determining the quality of the TVDI, especially in regions affected by climate change, such as Shandong Province. This paper explores this issue in the region in 2011, using daily MODIS MOD09GA and MOD11A1 data products. For each image acquisition time, the warm and cold edges of the NDVI–LST were extracted based on the NDVI, derived from red and near-infrared reflectance data, and the LST, derived from the MOD11A1 dataset. Then, the variations in the warm and cold edges with the LST and NDVI were analyzed. Subsequently, the influence of warm and cold edges, based on the daily values of the temperature, NDVI and precipitation during the observed period, was assessed using a linear regression. The soil moisture (SM) data obtained from the Global Land Data Assimilation System (GLDAS) datasets and the crop water stress index (CWSI) obtained from the MOD16A2 products were used for the assessment. The spatial and temporal variations in drought in Shandong Province from 2011 to 2020 were measured based on Theil–Sen median trend analysis and the Mann–Kendall test. The results show that apparently random variations were evident in the temporal evolution of the slope of the warm edge, indicating that daily data were appropriate to determine the boundary of the warm edge. Daily data were also appropriate to determine the boundary of the cold edge in a similar way. Additionally, the temperature, NDVI and precipitation in this region affected by climate change had a negative correlation with the slope and a positive correlation with the intercept. The validation results show that there was a significant negative correlation between the observed TVDI and GLDAS soil moisture values (R² > 0.62) in 12 scatter plots. Therefore, we deduced that the monthly or yearly TVDI product produced by the daily MODIS data has a higher precision than that produced by 8-day or monthly data in regions affected by climate change. The spatial and temporal variations show that the trend of slight and moderate droughts first increased and then decreased, and, in particular, some areas presented severe drought from 2011 to 2015. The results obtained in this study are important for the scheduling of irrigation and drought warnings. Full article

(This article belongs to the Special Issue Climate Change and Enviromental Disaster)

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19 pages, 9329 KiB

Open AccessArticle

Mechanical Properties of Polypropylene Fiber Recycled Brick Aggregate Concrete and Its Influencing Factors by Gray Correlation Analysis

by Shangwei Gong, Lichao Bai, Zhenyu Tan, Lina Xu, Xiaohong Bai and Zhanfang Huang

Sustainability 2023, 15(14), 11135; https://doi.org/10.3390/su151411135 - 17 Jul 2023

Cited by 2 | Viewed by 1361

Abstract

Making construction waste into raw materials for recycled concrete is beneficial for resource conservation and environmental protection. This paper investigated the effects of different recycled brick aggregate (RBA) replacement rates (30%, 50%, 70%, and 100%) and different contents of polypropylene fibers (PPFs) (0.08%, 0.10%, 0.12%, 0.16%, and 0.2%) on the mechanical properties of recycled brick concrete. Gray correlation was also used to analyze the degree of effect factors on the mechanical properties of concrete. The results showed that the mechanical properties decreased when the natural coarse aggregate (NCA) was replaced with RBA, while PPFs could better improve the mechanical properties of RBA concrete. The improvement of compressive and flexural properties was optimal when the PPF content was 0.12%; the improvement of tensile properties was optimal when the PPF content was 0.2%. In addition, PPFs significantly improved the toughness of RBA concrete. The gray correlation degrees between compressive strength (tensile strength, flexural strength) and NCA, RBA, and PPFs were 0.8964 (0.8691, 0.8935), 0.7301 (0.6530, 0.7074), and 0.5873 (0.5870, 0.5840), respectively. Full article

(This article belongs to the Special Issue Climate Change and Enviromental Disaster)

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21 pages, 5022 KiB

Open AccessArticle

Study on Vertical Load Distribution of Pile Group–Liquefied Soil System under Horizontal Seismic Environment

by Zhanfang Huang, Lichao Bai, Tian Su, Xiaohong Bai, Junjie Zheng and Yongqiang Liu

Sustainability 2023, 15(12), 9549; https://doi.org/10.3390/su15129549 - 14 Jun 2023

Viewed by 946

Abstract

The dynamic responses of pile–liquefied composite soils are complex, and the bearing capacities of single piles or pile groups in liquefiable soils remain unclear. For friction piles, the friction resistance determines the vertical bearing capacity of the pile. In a pile–soil system, it is very important to study the friction resistance changes in the pile during vibration. Based on a shaking table test, this study investigated the vertical bearing capacity of a pile foundation–liquefied soil system under simulated horizontal seismic forces, using the MIDAS GTS software. The load borne by the top of the pile was studied under a horizontal earthquake with a certain vertical load, different pile spacings, and different vibration times, along with the cumulative coefficient CCPF of the pile side friction. The distributions of the CCPF along the pile body of a single pile and pile groups with different pile spacings were analyzed at different vibration times. It was found that the CCPF intuitively reflected the distribution law of the pile side friction during vibration. When the CCPF at the bottom of the pile was equal to 1, the load on the top of the pile was equal to the average value of the total load. When the CCPF at the bottom of the pile was less than 1, the load on the top of the pile was less than the average value of the total load. When the CCPF at the bottom of the pile was greater than 1, the load on the top of the pile was greater than the average of the total load. Full article

(This article belongs to the Special Issue Climate Change and Enviromental Disaster)

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16 pages, 5336 KiB

Open AccessArticle

Assessing Land Use and Climate Change Impacts on Soil Erosion Caused by Water in China

by Xuerou Weng, Boen Zhang, Jinxin Zhu, Dagang Wang and Jianxiu Qiu

Sustainability 2023, 15(10), 7865; https://doi.org/10.3390/su15107865 - 11 May 2023

Cited by 8 | Viewed by 2325

Abstract

Soil erosion poses a significant threat to land conservation, freshwater security, and ocean ecology. Climate change, with rainfall as one of its primary drivers, exacerbates this problem. Therefore, reliably predicting future soil erosion rates and taking into account anthropogenic influences are crucial for policymakers and researchers in the earth-system field. To address this challenge, we have developed a novel framework that combines the Bayesian Model Averaging (BMA) method with the Revised Universal Soil Loss Equation (RUSLE) model to estimate erosion rates on a national scale. We used BMA to merge five Regional Climate Models (RCMs), reducing uncertainty in ensemble simulations and improving the plausibility of projected changes in climatic regimes over China under two Representative Concentration Pathway (RCP) scenarios (RCP4.5 and RCP8.5). The RUSLE model was applied to forecast the effects of climate change and land-use change on water erosion in China, using high-resolution climate simulation and prediction inputs. Our findings revealed that under the RCP4.5 and RCP8.5 scenarios, average annual soil loss will increase by 21.20% and 33.06%, respectively, compared to the baseline period. Our analysis also demonstrated a clear distinction between the effects of climate change and land-use change on water erosion. Climate change leads to an increase in precipitation, which exacerbates water erosion rates, with contributions ranging from 59.99% to 78.21%. Furthermore, an increase in radiative forcing will further amplify the effects of climate change. The transformation of land from one that has not been disturbed by humans to one that has been exposed to some soil and water conservation measures will have a mitigating effect on water erosion, with a contribution of −6.96% to −4.68%. Therefore, implementing effective soil and water conservation measures can somewhat mitigate the severity of ongoing soil loss. Our findings have significant implications for policymakers seeking to develop national strategies for soil conservation and model developers working to reduce uncertainty in erosion predictions. Full article

(This article belongs to the Special Issue Climate Change and Enviromental Disaster)

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17 pages, 21215 KiB

Open AccessArticle

Eco-Asset Variations and Their Driving Factors in the Qinghai–Tibet Plateau, China, under the Context of Global Change

by Xingming Yuan, Bing Guo, Miao Lu, Wenqian Zang, Chuan Liu, Baoyu Wang and Xiangzhi Huang

Sustainability 2023, 15(9), 7466; https://doi.org/10.3390/su15097466 - 1 May 2023

Cited by 2 | Viewed by 1279

Abstract

The Qinghai–Tibet plateau (QTP), as the “roof of the world” and the “Asian Water Tower”, provides important ecological resources for China and other Asian countries. The changing trend of ecological assets and their dominant influencing factors in different sub-regions and periods are not yet clear. In order to reveal the differences in driving mechanisms among sub-regions under the context of global changes, this study quantitatively analyzed the ecological assets and their spatial and temporal evolution patterns during 2000–2015 by using the value equivalent method. Then, the Geodetector was introduced to reveal and clarify the dominant factors of ecological asset changes in different ecological sub-regions. The results show the following. (1) From 2000 to 2010, the total value of ecological assets in Nakchu County was the highest, followed by Kangding County, while that in 2015 was the highest in Kangding County, followed by Nakchu County. (2) During 2000–2015, the average value of ecological assets of the Qinghai–Tibet plateau gradually decreased from east to west, while the average ecological asset value in the southern Qinghai–Tibet plateau was lower. (3) The QTP showed the highest value in 2005 with an increasing trend from 2000 to 2005, followed by a subsequent decrease from 2005 to 2015. (4) Between 2000 and 2015, the area of the stable zone (slight or no change) of ecological assets was the largest, followed by that of the decreasing zone. (5) During all the study period, the spatio-temporal evolution of ecological assets in different ecological sub-regions was mainly affected by natural factors, which were the main driving variables rather than human activities. These results could provide important support for decisions regarding the protection of ecosystems and resources in the Qinghai–Tibet plateau. Full article

(This article belongs to the Special Issue Climate Change and Enviromental Disaster)

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20 pages, 9575 KiB

Open AccessArticle

Optimal Scale Selection and an Object-Oriented Method Used for Measuring and Monitoring the Extent of Land Desertification

by Junliang Han, Liusheng Han, Guangwei Sun, Haoxiang Mu, Zhiyi Zhang, Xiangyu Wang and Shengshuai Wang

Sustainability 2023, 15(7), 5619; https://doi.org/10.3390/su15075619 - 23 Mar 2023

Cited by 1 | Viewed by 1198

Abstract

Desertification has become a major problem in the field, affecting both the global ecological environment and economy. The effective monitoring of desertified land is an important prerequisite for land desertification protection and governance. With the aim of addressing the problems of spectral confusion as well as the salt and pepper phenomenon concerning the successful extraction of desertification information by utilizing the pixel-based method in the studies, Landsat remote sensing images obtained from the year 2001 to 2021 were selected in this study as the data source, and then, the object-oriented random forest classification method was improved by using different optimal segmentation scale selection techniques and combining multi-thematic index characteristics for measuring the extent of land desertification. Finally, the improved method was applied to study the dynamic changes in desertification in the Mu Us Sandy Land Ecological Function Reserve. The results show that the optimal scale determined by different optimal segmentation scale selection methods is not entirely consistent, and a minor scale should be selected as the optimal scale. Compared with the pixel-based classification method, the overall accuracy of object-oriented classification based on the optimal segmentation scale was improved by 8.06%, the Kappa coefficient increased by 0.1114, and the salt and pepper phenomenon was significantly reduced. From 2001 to 2021, the area of desertified land decreased by 587.12 km² and the area of severely desertified land decreased by 4115.92 km², indicating that the control effect was remarkable. This study can provide effective decision-making evidence and support for the successful governance of desertification. Full article

(This article belongs to the Special Issue Climate Change and Enviromental Disaster)

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17 pages, 4672 KiB

Open AccessArticle

Investigating Extreme Snowfall Changes in China Based on an Ensemble of High-Resolution Regional Climate Models

by Jinxin Zhu, Xuerou Weng, Bing Guo, Xueting Zeng and Cong Dong

Sustainability 2023, 15(5), 3878; https://doi.org/10.3390/su15053878 - 21 Feb 2023

Viewed by 1310

Abstract

Anthropogenically induced global warming intensifies the water cycle around the world. As a critical sector of the water cycle, snow depth and its related extremes greatly impact agriculture, animal husbandry, and food security, yet lack investigation. In this study, five high-resolution climate models are selected to simulate and project snow depth and its extremes over China. The simulation capabilities of models in reproducing the basic climate variables in winter are gauged in terms of spatial and temporal patterns over nine subregions. It is found that the driving global climate model (GCM) can contribute to similar patterns, while the different regional climate model (RCM) schemes lead to large variations in the snowfall accumulating on the land surface. The warming magnitude is larger under a higher representative concentration pathway (RCP) scenario (2.5 °C greater under RCP8.5 than RCP4.5). The distribution of ensemble mean winter precipitation changes is more fragmented because of the relatively low skill in reproducing water-related content in the climate system. The projected precipitation change is larger under RCP8.5 than under RCP4.5 due to the amplification of the hydrological cycle by temperature warming. The projected changes in the ensemble mean snow depth mainly occur over the Tibetan Plateau with a decreasing trend. Only several grids over the Himalayas Mountains and the upper stream of the Yarlung Zangbo River are projected with a slight increase in snow depth. Both the intensity and frequency of extreme snow events are projected to increase in Northeast China and Inner Mongolia, which are important agricultural and animal husbandry production areas in China. The reason behind this projection can be explained by the fact that the hydrological cycle intensified by temperature warming leads to excessive snowfall stacking up during winter. The changes in extreme snowfall events in the future will have a significant impact on China’s agricultural and animal husbandry production and threaten food security. Full article

(This article belongs to the Special Issue Climate Change and Enviromental Disaster)

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20 pages, 8189 KiB

Open AccessArticle

A Novel Desert Vegetation Extraction and Shadow Separation Method Based on Visible Light Images from Unmanned Aerial Vehicles

by Yuefeng Lu, Zhenqi Song, Yuqing Li, Zhichao An, Lan Zhao, Guosheng Zan and Miao Lu

Sustainability 2023, 15(4), 2954; https://doi.org/10.3390/su15042954 - 6 Feb 2023

Cited by 2 | Viewed by 1409

Abstract

Owing to factors such as climate change and human activities, ecological and environmental problems of land desertification have emerged in many regions around the world, among which the problem of land desertification in northwestern China is particularly serious. To grasp the trend of land desertification and the degree of natural vegetation degradation in northwest China is a basic prerequisite for managing the fragile ecological environment there. Visible light remote sensing images taken by a UAV can monitor the vegetation cover in desert areas on a large scale and with high time efficiency. However, as there are many low shrubs in desert areas, the shadows cast by them are darker, and the traditional RGB color-space-based vegetation index is affected by the shadow texture when extracting vegetation, so it is difficult to achieve high accuracy. For this reason, this paper proposes the Lab color-space-based vegetation index L2AVI (L-a-a vegetation index) to solve this problem. The EXG (excess green index), NGRDI (normalized green-red difference index), VDVI (visible band difference vegetation index), MGRVI (modified green-red vegetation index), and RGBVI (red-green-blue vegetation index) constructed based on RGB color space were used as control experiments in the three selected study areas. The results show that, although the extraction accuracies of the vegetation indices constructed based on RGB color space all reach more than 70%, these vegetation indices are all affected by the shadow texture to different degrees, and there are many problems of misdetection and omission. However, the accuracy of the L2AVI index can reach 99.20%, 99.73%, and 99.69%, respectively, avoiding the problem of omission due to vegetation shading and having a high extraction accuracy. Therefore, the L2AVI index can provide technical support and a decision basis for the protection and control of land desertification in northwest China. Full article

(This article belongs to the Special Issue Climate Change and Enviromental Disaster)

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24 pages, 1712 KiB

Open AccessReview

Review on Urban Flood Risk Assessment

by Cailin Li, Na Sun, Yihui Lu, Baoyun Guo, Yue Wang, Xiaokai Sun and Yukai Yao

Sustainability 2023, 15(1), 765; https://doi.org/10.3390/su15010765 - 31 Dec 2022

Cited by 13 | Viewed by 4948

Abstract

Under the background of rapid urban development and continuous climate change, frequent floods around the world have caused serious economic losses and social problems, which has become the main reason for the sustainable development of cities. Flood disaster risk assessment is an important non-engineering measure in urban disaster prevention and mitigation, and scientific flood disaster risk assessment is the premise and foundation of flood disaster risk management. This paper summarizes the current situation of flood risk assessment by analyzing the international literature in recent 20 years. The mechanism of flood disaster is mainly discussed. The flood disaster assessment methods are summarized, including historical disaster statistics method, multi-criteria index system method, remote sensing and GIS (Geographic Information System) coupling method, scenario simulation evaluation method and machine learning method. Furthermore, the development status of flood risk analysis and forecasting is summarized. Finally, the development trend and direction of flood risk assessment are put forward. Full article

(This article belongs to the Special Issue Climate Change and Enviromental Disaster)

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