Submit to Remote Sensing Review for Remote Sensing Propose a Special Issue

Journal Browser

► Journal Browser

Observation for Resilient Cities and Human Settlements: Theory, Algorithms and Applications

Print Special Issue Flyer
Special Issue Editors
Special Issue Information
Keywords
Published Papers

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Urban Remote Sensing".

Deadline for manuscript submissions: closed (31 May 2023) | Viewed by 25725

Share This Special Issue

Special Issue Editors

Prof. Dr. Wenhui Kuang

E-Mail Website
Guest Editor

Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Interests: urban land-system dynamic and ecological remote sensing
Special Issues, Collections and Topics in MDPI journals

Dr. Rafiq Hamdi

E-Mail Website
Guest Editor

Royal Meteorological Institute of Belgium, B1180 Brussels, Belgium
Interests: NWP; urban parametrization; urban meteorology; interaction climate change and urban climate; land atmosphere interactions; surface data assimilation
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Yuhai Bao

E-Mail Website
Guest Editor

College of Geographical Science, Inner Mongolia Normal University, Hohhot 010022, China
Interests: remote sensing of resources and environment; physical geography

Dr. Yinyin Dou

E-Mail Website
Guest Editor

Dr. Tao Pan

E-Mail Website
Guest Editor

School of Geography and Tourism, Qufu Normal University, Rizhao 276826, China
Interests: remote sensing and ecological process in cities
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Dengsheng Lu

E-Mail Website
Guest Editor

School of Geographic Sciences, Fujian Normal University, No. 8 Shangsan Road, Cangshan District, Fuzhou 350007, China
Interests: forest remote sensing; classification; change detection; biomass modeling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Humanity is moving into a new era of sustainable, inclusive, and resilient cities. However, cities and settlements worldwide are suffering from serious consequences due to both rapid urbanization and climate change, including accelerating urban sprawl, increasing flood threat, intensifying heat island effect, and rising disaster risk. Therefore, it is essential to address the state-of-the-art research issues on interactions among urbanization, land system change, ecosystem services, and climate systems within and beyond cities as a cross-discipline. Resilient cities and human settlements were recognized as a fourth engagement priority in the Group on Earth Observations (GEO) WEEK 2021, and have become a key research topic for both achieving Sustainable Development Goals (SDGs) and the UN New Urban Agenda (NUA). The latest Intergovernmental Panel on Climate Change (IPCC) report AR6 from the Working Group I states that the combination of future urbanization and increasingly frequent extreme climate events such as heatwaves, with more hot days and warm nights, will have significant implications for heat stress in cities. In this situation, how to achieve the grand goals for sustainable, comfortable, and resilient cities, and how to provide solutions for climate adaptation are pivotal in future urban construction and development.

The synthesized observation, modelling, and assessment of multi-elements or dimensions with the interaction among urbanization, land, ecosystems, and climate systems, and their sustainable and resilient solutions or regulating pathways should be engaged as soon as possible from local to regional and global scales toward 2035/2050 or 2100. This Special Issue encourages submissions associated with the theories, algorithms, and applications in the observation of resilient cities and human settlements. We welcome manuscripts from the global research community actively involved in this session, wishing to improve urban resilience and promote urban sustainability. The potential topics include but are not limited to:

Scientific theory and knowledge mining for resilient cities and human settlements and their assessment indicator systems.
Novel models and synthesized algorithms for satellite observation, both ecosystem and climate simulation for resilient cities building from local to regional and global scales.
Solutions for resilient cities or strategies for climate adaptation associated with Nature-based solutions (NBSs), urban green infrastructure (UGI), and others.
Practical and application cases as pioneers from megacities, cities, or towns guided by resilient cities or climate adaptation globally.

The fifth Asia-Oceania Group on Earth Observations (AOGEO) Workshop (https://aogeo-workshop-2022.casconf.cn/page/1531810927035420672) will be held on 15-17 June 2022 in online format. The Workshop will focus on the development of IPS activities, cases and technical advances for addressing "Urban Resilience and Human Settlements", emerging technical exchange and practice from youth, efforts of capacity building.

Prof. Dr. Wenhui Kuang
Dr. Rafiq Hamdi
Prof. Dr. Yuhai Bao
Dr. Yinyin Dou
Dr. Tao Pan
Prof. Dr. Dengsheng Lu
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. Remote Sensing 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 2700 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.

Keywords

urban remote sensing
resilient cities
human settlements
urban heat island
climate adaptation
urban land system
ecosystem services
urban governance
urban sustainable solutions
urban eco-regulation

Published Papers (12 papers)

Download All Papers

Research

21 pages, 10487 KiB

Open AccessArticle

Analyzing Changes in Urban Green Spaces and Their Effect on Land Temperature from the Perspective of Surface Radiation Energy Balance in Rizhao City, the Central Coast of China

by Tao Pan, Shanfeng He, Zhaoyu Liu, Liming Jiang, Qinglei Zhao and Rafiq Hamdi

Remote Sens. 2023, 15(19), 4785; https://0-doi-org.brum.beds.ac.uk/10.3390/rs15194785 - 30 Sep 2023

Viewed by 866

Abstract

The greening of land plays a meaningful role in improving human settlements by regulating ecosystem functions in the central coast region of China. However, research on the spatiotemporal heterogeneity of green land changes in different urbanized regions and the cooling temperature effect of the different green land densities are still lacking in this region, which limits the understanding of the effect of greening of land on land thermal properties. To address this issue, we integrated several approaches to establish a comprehensive way of ‘human–computer interactive interpretation method—urban interior mixed pixel model—surface radiation energy balance model’ using data from remote sensing images and the national land use/cover database of China, focusing on Rizhao city. The conclusions are as follows: The total greening of land from 2000 to 2022 was monitored, and it was found that its cover improved within the built-up area of the city, with the proportion of green land increasing from 25.34% in 2000 to 42.98% in 2022. Differences in the amount of green spaces in different urbanized regions were first observed, namely, the urban greening rate was 37.78% in the old urban area in 2022, while it was as high as 46.43% in the newly expanded urban area in 2022, showing that more attention should be given to the construction of urban green spaces during urban expansion. Thermal comfort indicators in the study area were evaluated in terms of latent heat flux (0–457.83 W/m²), sensible heat flux (0–645.09 W/m²), and total available energy (254.07–659.42 W/m²). We also found that the cooling temperature effect in the middle- and high-density green land regions were 1.05 °C and 2.12 °C higher than those in the low-density region, and the established comfort/discomfort zones in terms of land surface temperature were depicted. These results provide a new practical reference for exploring the spatiotemporal heterogeneity change in green land and its impact on land-surface thermal properties in coastal regions. Full article

(This article belongs to the Special Issue Observation for Resilient Cities and Human Settlements: Theory, Algorithms and Applications)

► Show Figures

Figure 1

17 pages, 5727 KiB

Open AccessArticle

The Transport Path and Vertical Structure of Dust Storms in East Asia and the Impacts on Cities in Northern China

by Tana Bao, Guilin Xi, Yanling Hao, I-Shin Chang, Jing Wu, Zhichao Xue, Erdemtu Jin, Wenxing Zhang and Yuhai Bao

Remote Sens. 2023, 15(12), 3183; https://0-doi-org.brum.beds.ac.uk/10.3390/rs15123183 - 19 Jun 2023

Viewed by 1284

Abstract

Dust storm disasters have emerged as a significant environmental challenge in East Asia. However, relying on a single monitoring method to track dust storms presents limitations and can be variable. Therefore, it is necessary to use a combination of ground and remote sensing monitoring methods to explore the source and impact range of dust storms in order to fully characterize them. To achieve this, we examined the sources and impact ranges of dust storms in East Asia from 1980 to 2020 using both ground station data and remote sensing data. In addition, we focused on three specific dust storm events in the region. Our results indicate that the central source areas of dust storms are located in southern Mongolia and the Taklamakan Desert in China. Dust storms are mainly transported and spread in the northwestern region, while they are relatively rare in the southeastern region. The HYSPLIT model simulations reveal that the primary source directions of dust storms in East Asia are northwest, west, and north, the region involved includes Kazakhstan, southern Mongolia, and the Taklimakan Desert in China. The vertical structure of the dust storm layer depends on the source of the dust storm and the intensity of the dust storm event. Dust grain stratification probably occurs due to differences in dust storm sources, grain size, and regularity. These findings demonstrate that a combination of ground-based and remote sensing monitoring methods is an effective approach to fully characterize dust storms and can provide more comprehensive information for dust storm studies. Full article

(This article belongs to the Special Issue Observation for Resilient Cities and Human Settlements: Theory, Algorithms and Applications)

► Show Figures

Graphical abstract

24 pages, 19011 KiB

Open AccessArticle

A Method for Assessing Urban Ecological Resilience and Identifying Its Critical Distance Belt Based on the “Source-Sink” Theory: A Case Study of Beijing

by Xiaogang Ning, Xiaoyuan Zhang, Xiaoyu Zhang, Hao Wang and Weiwei Zhang

Remote Sens. 2023, 15(10), 2502; https://0-doi-org.brum.beds.ac.uk/10.3390/rs15102502 - 10 May 2023

Cited by 1 | Viewed by 1287

Abstract

A reasonable assessment of urban ecological resilience (UER), as well as quantitative identification of critical thresholds of UER, is an important theoretical basis for the formulation of scientific urban development planning. The existing UER assessment methods ignore the dynamic relationship between protection factors and disturbance factors in urban systems and do not address the question of where UER starts to become unstable. Therefore, based on the “source-sink” landscape theory, we constructed a UER assessment model and a method to quantitatively identify the UER’s critical distance belt (UER-CDB) using the transect gradient analysis. Additionally, we combined scenario simulation to analyze the change characteristics of UER and its critical distance belt in different urban development directions over past and future periods. The results show that: (1) Based on the “source-sink” theory and transect gradient method, the UER can be effectively assessed and the UER-CDB can be quantitatively identified. (2) The UER in Beijing shows a distribution pattern of high in the northwest and low in the southeast, and the High resilience area accounts for more than 40%. (3) The changes in UER-CDB in Beijing in different development directions have obvious variability, which is mainly influenced by topography and policy planning. (4) Compared with the natural development scenario (NDS), the ecological protection scenario (EPS) is more consistent with Beijing’s future urban development plan and more conducive to achieving sustainable development. The methodology of this paper provides a fresh perspective for the study of urban ecological resilience and the critical threshold of ecosystems. Full article

(This article belongs to the Special Issue Observation for Resilient Cities and Human Settlements: Theory, Algorithms and Applications)

► Show Figures

Figure 1

21 pages, 193592 KiB

Open AccessArticle

Seg-Road: A Segmentation Network for Road Extraction Based on Transformer and CNN with Connectivity Structures

by Jingjing Tao, Zhe Chen, Zhongchang Sun, Huadong Guo, Bo Leng, Zhengbo Yu, Yanli Wang, Ziqiong He, Xiangqi Lei and Jinpei Yang

Remote Sens. 2023, 15(6), 1602; https://0-doi-org.brum.beds.ac.uk/10.3390/rs15061602 - 15 Mar 2023

Cited by 11 | Viewed by 4207

Abstract

Acquiring road information is important for smart cities and sustainable urban development. In recent years, significant progress has been made in the extraction of urban road information from remote sensing images using deep learning (DL) algorithms. However, due to the complex shape, narrowness, and high span of roads in the images, the results are often unsatisfactory. This article proposes a Seg-Road model to improve road connectivity. The Seg-Road uses a transformer structure to extract the long-range dependency and global contextual information to improve the fragmentation of road segmentation and uses a convolutional neural network (CNN) structure to extract local contextual information to improve the segmentation of road details. Furthermore, a novel pixel connectivity structure (PCS) is proposed to improve the connectivity of road segmentation and the robustness of prediction results. To verify the effectiveness of Seg-Road for road segmentation, the DeepGlobe and Massachusetts datasets were used for training and testing. The experimental results show that Seg-Road achieves state-of-the-art (SOTA) performance, with an intersection over union (IoU) of 67.20%, mean intersection over union (MIoU) of 82.06%, F1 of 91.43%, precision of 90.05%, and recall of 92.85% in the DeepGlobe dataset, and achieves an IoU of 68.38%, MIoU of 83.89%, F1 of 90.01%, precision of 87.34%, and recall of 92.86% in the Massachusetts dataset, which is better than the values for CoANet. Further, it has higher application value for achieving sustainable urban development. Full article

(This article belongs to the Special Issue Observation for Resilient Cities and Human Settlements: Theory, Algorithms and Applications)

► Show Figures

Graphical abstract

19 pages, 3516 KiB

Open AccessArticle

Spatiotemporal Changes in Supply–Demand Patterns of Carbon Sequestration Services in an Urban Agglomeration under China’s Rapid Urbanization

by Wenhai Hong, Guangdao Bao, Yunxia Du, Yujie Guo, Chengcong Wang, Guodong Wang and Zhibin Ren

Remote Sens. 2023, 15(3), 811; https://0-doi-org.brum.beds.ac.uk/10.3390/rs15030811 - 31 Jan 2023

Cited by 7 | Viewed by 1507

Abstract

Quantifying the urban supply and demand of carbon sequestration services is an important prerequisite for achieving global carbon neutrality goals. However, the spatiotemporal patterns for balancing the supply and demand of carbon sequestration services in urban agglomerations remain unclear. In this study, NPP/VIIRS nighttime light data were used to identify the carbon sequestration service demand and were then combined with the carbon sequestration service supply to analyze the spatiotemporal patterns of supply and demand for carbon sequestration services in the Harbin-Changchun urban agglomeration (HCUA) in Northeast China. Our results indicate that both the supply and demand of carbon sequestration services showed increasing trends from 2012 to 2020 in the HCUA. The regions with increasing supply and demand trends were mainly located in the eastern mountainous and western urban areas, respectively. The total supply and demand of carbon sequestration services in the HCUA were 2080.3 Mt·C yr⁻¹ and 433.6 Mt·C yr⁻¹, respectively. Carbon surpluses (supply > demand) were found in most areas (98%), although particularly in the southeastern mountainous region. However, with rapid urbanization, in most cities, the supply–demand ratio decreased from 2012 to 2020, and the proportion of carbon deficit regions showed a continuous increase, which was mainly distributed in newly developed urban areas. The low supply–high demand (L-H) pattern showed significant spatial mismatching for supply and demand in the HCUA. The proportion of regions with the L-H pattern also showed a rapidly increasing trend from 2012 to 2020, indicating a more obvious carbon deficit trend in the future. This study provides important guidelines for formulating effective policies for energy consumption and carbon sequestration to combat global warming under China’s rapid urbanization. Full article

(This article belongs to the Special Issue Observation for Resilient Cities and Human Settlements: Theory, Algorithms and Applications)

► Show Figures

Graphical abstract

22 pages, 19747 KiB

Open AccessArticle

Mapping Population Distribution with High Spatiotemporal Resolution in Beijing Using Baidu Heat Map Data

by Wenxuan Bao, Adu Gong, Tong Zhang, Yiran Zhao, Boyi Li and Shuaiqiang Chen

Remote Sens. 2023, 15(2), 458; https://0-doi-org.brum.beds.ac.uk/10.3390/rs15020458 - 12 Jan 2023

Cited by 12 | Viewed by 3143

Abstract

Population distribution data with high spatiotemporal resolution are of significant value and fundamental to many application areas, such as public health, urban planning, environmental change, and disaster management. However, such data are still not widely available due to the limited knowledge of complex human activity patterns. The emergence of location-based service big data provides additional opportunities to solve this problem. In this study, we integrated ambient population data, nighttime light data, and building volume data; innovatively proposed a spatial downscaling framework for Baidu heat map data during work time and sleep time; and mapped the population distribution with high spatiotemporal resolution (i.e., hourly, 100 m) in Beijing. Finally, we validated the generated population distribution maps with high spatiotemporal resolution using the highest-quality validation data (i.e., mobile signaling data). The relevant results indicate that our proposed spatial downscaling framework for both work time and sleep time has high accuracy, that the distribution of the population in Beijing on a regular weekday shows “centripetal centralization at daytime, centrifugal dispersion at night” spatiotemporal variation characteristics, that the interaction between the purpose of residents’ activities and the spatial functional differences leads to the spatiotemporal evolution of the population distribution, and that China’s “surgical control and dynamic zero COVID-19” epidemic policy was strongly implemented. In addition, our proposed spatial downscaling framework can be transferred to other regions, which is of value for governmental emergency measures and for studies about human risks to environmental issues. Full article

(This article belongs to the Special Issue Observation for Resilient Cities and Human Settlements: Theory, Algorithms and Applications)

► Show Figures

Figure 1

17 pages, 4372 KiB

Open AccessArticle

Examining Spatio-Temporal Dynamics of Ecological Quality in the Pan-Third Pole Region in the Past 20 Years

by Geer Hong, Wenfeng Chi, Tao Pan, Yinyin Dou, Wenhui Kuang, Changqing Guo, Runmei Hao and Yuhai Bao

Remote Sens. 2022, 14(21), 5473; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14215473 - 31 Oct 2022

Cited by 2 | Viewed by 1397

Abstract

Examining the ecology quality of the Pan-Third Pole region has implications for global environmental change and sustainable development. However, spatio-temporal evolution of ecological quality in this region is still lacking. In this study, 65 countries of the Pan-Third Pole region were selected. A comprehensive evaluation index system of ecological quality was constructed using a dataset containing remote sensing, ecological environment and socio-economic data to spatially quantify the ecological quality, as well as its change from 2000 to 2020. The results displayed that the average ecological quality of the Pan-Third Pole region was at a moderate level of 0.53. Spatially, the excellent ecological quality regions were mainly concentrated in East Asian countries, while the severe quality regions were located in the Middle East. From 2000–2020, areas with improved ecological changes accounted for 38.48% of the total area, and 10.66% of the total area experienced a decline; specifically, European countries had a large proportion of improved ecological quality areas, while East Asian countries had a significantly larger proportion of declining ecological quality areas. We also found that ecosystem changes and human activities had an influence on ecological quality in the Pan-Third Pole region. This study provides an important empirical study on ecosystem services in the region. Full article

(This article belongs to the Special Issue Observation for Resilient Cities and Human Settlements: Theory, Algorithms and Applications)

► Show Figures

Figure 1

14 pages, 6652 KiB

Open AccessArticle

Assessment of the Combined Risk of Drought and High-Temperature Heat Wave Events in the North China Plain during Summer

by Tianxiao Wu, Baofu Li, Lishu Lian, Yanbing Zhu and Yanfeng Chen

Remote Sens. 2022, 14(18), 4588; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14184588 - 14 Sep 2022

Cited by 9 | Viewed by 1902

Abstract

Drought-induced risk has attracted the attention of many scholars, but the risk of combined events caused by drought and high-temperature heat waves still needs further study. Based on MODIS products and meteorological data, the spatiotemporal variation characteristics of summer drought and high-temperature heat waves in the North China Plain from 2000 to 2018 were analyzed by the standardized precipitation evapotranspiration index (SPEI), crop water stress index (CWSI) and high-temperature threshold, and their combined-events risk was evaluated. The results showed that (1) from 2000 to 2018, summer drought in the North China Plain became more severe. Especially in Henan, Anhui and Jiangsu Provinces, drought increased significantly. (2) From 2000 to 2018, the frequency and intensity of high-temperature heat wave events in the North China Plain gradually increased at rates of 0.28 times/10 year and 1.6 °C/10 year, respectively. (3) The slightly high risk and high risk caused by summer drought were mainly distributed in Hebei Province and Tianjin Municipality in the north, and the risk change was characterized by a decrease in the north and an increase in the south. (4) The combined-events risk of summer drought and high-temperature heat waves did not increase significantly, with an increase rate of approximately 0.01/10 year. Among them, the increase rate of combined-events risk in Henan Province was the largest (0.14/10 year), followed by the obvious increase in northern Anhui, Jiangsu and southern Shandong, while the risk in Beijing showed a decreasing trend. The research results have scientific guiding significance for formulating disaster prevention and reduction strategies. Full article

(This article belongs to the Special Issue Observation for Resilient Cities and Human Settlements: Theory, Algorithms and Applications)

► Show Figures

Figure 1

18 pages, 19347 KiB

Open AccessArticle

Assessing the Impact of Urbanization and Eco-Environmental Quality on Regional Carbon Storage: A Multiscale Spatio-Temporal Analysis Framework

by Lu Niu, Zhengfeng Zhang, Yingzi Liang and Yanfen Huang

Remote Sens. 2022, 14(16), 4007; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14164007 - 17 Aug 2022

Cited by 9 | Viewed by 2129

Abstract

Understanding the mechanisms, intensity, and spatio-temporal heterogeneity of the impacts of urbanization and eco-environmental quality on carbon storage is crucial for achieving carbon neutrality goals. This study constructed a multiscale spatio-temporal analysis framework using multi-source remote sensing data, the InVEST model, and the multiscale geographically weighted regression (MGWR) model. Then, the effects of multiple factors on regional carbon storage were assessed in an empirical study involving 199 counties in Beijing-Tianjin-Hebei. The results showed that the carbon storage loss in the Beijing-Tianjin-Hebei region from 2010 to 2018 was 58.87 Tg C, with an annual relative loss rate of 0.16%. The MGWR model used in this study explained more than 98% of the spatial variation in regional carbon storage. In contrast, the impacts of various urbanization and eco-environmental indicators on regional carbon storage varied with the spatial and temporal variation. Overall, urban land structure and vegetation growth strongly influenced regional carbon storage resulting from urbanization and eco-environmental quality, respectively. In addition, based on an analysis of spatial context, MGWR suggests that the northwestern mountains in the Beijing-Tianjin-Hebei region have a greater potential to store more carbon than the other regions. This study also details the impact of future sustainable land use on regional carbon storage. Our findings can provide a scientific reference for formulating relevant carbon storage conservation policies. Full article

(This article belongs to the Special Issue Observation for Resilient Cities and Human Settlements: Theory, Algorithms and Applications)

► Show Figures

Figure 1

19 pages, 7820 KiB

Open AccessArticle

Spatiotemporal Variation in Compound Dry and Hot Events and Its Effects on NDVI in Inner Mongolia, China

by Yao Kang, Enliang Guo, Yongfang Wang, Yuhai Bao, Shuixia Zhao and Runa A

Remote Sens. 2022, 14(16), 3977; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14163977 - 16 Aug 2022

Cited by 3 | Viewed by 1677

Abstract

In recent decades, frequent compound dry and hot events have posed a great threat to humans and the ecological environment, especially in Inner Mongolia, which has arid and semi-arid characteristics. In this study, monthly temperature and precipitation data from 115 meteorological stations in Inner Mongolia from 1982 to 2020 were used to establish a standardized dry and hot index (SDHI). Theil–Sen median trend analysis, Mann–Kendall test, partial correlation analysis, and stepwise multiple regression models were used to characterize the changes in compound dry and hot events and the normalized difference vegetation index (NDVI) from 1982 to 2020, and the relationship between the SDHI and NDVI was quantitatively evaluated. The results showed that the overall SDHI values in Inner Mongolia showed a significant decrease at a rate of 0.03/year from 1982 to 2020, indicating an increase in the severity of compound dry and hot events. NDVI values showed a significant increasing trend and NDVI showed mutated 2001. Among the grassland vegetation types, SDHI and NDVI trends were more significant in forests, and meadow steppe, desert steppe, and desert were more susceptible to compound dry and hot events, and forests had the greatest severity of compound dry and hot events. The results of the partial correlation analysis showed that the average value of the partial correlation coefficient between the SDHI and NDVI was 0.68, and the area of positive correlation was 84.13%. Spatially, it showed strong response characteristics in the middle and gradual weakening towards the east and west sides. The correlation between NDVI and climatic conditions varied greatly in different vegetation areas. The forest area is most sensitive to the influence of temperature, and the desert steppe area is most affected by compound dry and hot events. The overall vegetation growth in Inner Mongolia was most affected by temperature conditions, followed by compound dry and hot conditions, and the influence of drought conditions was the least significant. The results of the relative importance analysis confirmed this. The research results provide a more detailed understanding of compound dry and hot events in arid and semi-arid regions and useful insights and support for ecological protection. Full article

(This article belongs to the Special Issue Observation for Resilient Cities and Human Settlements: Theory, Algorithms and Applications)

► Show Figures

Graphical abstract

26 pages, 25783 KiB

Open AccessArticle

High-Precision Population Spatialization in Metropolises Based on Ensemble Learning: A Case Study of Beijing, China

by Wenxuan Bao, Adu Gong, Yiran Zhao, Shuaiqiang Chen, Wanru Ba and Yuan He

Remote Sens. 2022, 14(15), 3654; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14153654 - 29 Jul 2022

Cited by 7 | Viewed by 2098

Abstract

Accurate spatial population distribution information, especially for metropolises, is of significant value and is fundamental to many application areas such as public health, urban development planning and disaster assessment management. Random forest is the most widely used model in population spatialization studies. However, a reliable model for accurately mapping the spatial distribution of metropolitan populations is still lacking due to the inherent limitations of the random forest model and the complexity of the population spatialization problem. In this study, we integrate gradient boosting decision tree (GBDT), extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM) and support vector regression (SVR) through ensemble learning algorithm stacking to construct a novel population spatialization model we name GXLS-Stacking. We integrate socioeconomic data that enhance the characterization of the population’s spatial distribution (e.g., point-of-interest data, building outline data with height, artificial impervious surface data, etc.) and natural environmental data with a combination of census data to train the model to generate a high-precision gridded population density map with a 100 m spatial resolution for Beijing in 2020. Finally, the generated gridded population density map is validated at the pixel level using the highest resolution validation data (i.e., community household registration data) in the current study. The results show that the GXLS-Stacking model can predict the population’s spatial distribution with high precision (R² = 0.8004, MAE = 34.67 persons/hectare, RMSE = 54.92 persons/hectare), and its overall performance is not only better than the four individual models but also better than the random forest model. Compared to the natural environmental features, a city’s socioeconomic features are more capable in characterizing the spatial distribution of the population and the intensity of human activities. In addition, the gridded population density map obtained by the GXLS-Stacking model can provide highly accurate information on the population’s spatial distribution and can be used to analyze the spatial patterns of metropolitan population density. Moreover, the GXLS-Stacking model has the ability to be generalized to metropolises with comprehensive and high-quality data, whether in China or in other countries. Furthermore, for small and medium-sized cities, our modeling process can still provide an effective reference for their population spatialization methods. Full article

(This article belongs to the Special Issue Observation for Resilient Cities and Human Settlements: Theory, Algorithms and Applications)

► Show Figures

Graphical abstract

19 pages, 5996 KiB

Open AccessArticle

Contributions of Climatic and Anthropogenic Drivers to Net Primary Productivity of Vegetation in the Mongolian Plateau

by Chaohua Yin, Min Luo, Fanhao Meng, Chula Sa, Zhihui Yuan and Yuhai Bao

Remote Sens. 2022, 14(14), 3383; https://0-doi-org.brum.beds.ac.uk/10.3390/rs14143383 - 14 Jul 2022

Cited by 13 | Viewed by 1918

Abstract

Global warming and intense human activity are altering the net primary productivity (NPP) of vegetation in arid and semi-arid regions where vegetation ecosystems are sensitive to climate change, including the Mongolian Plateau (MP). To deepen the understanding of the dynamics of vegetation and its driving factors on the MP, the actual NPP (ANPP) of the MP from 2000 to 2019 was estimated based on a modified Carnegie–Ames–Stanford Approach (CASA) model. The Thornthwaite Memorial and Guangsheng Zhou models were applied concurrently to estimate the potential NPP of the vegetation, and different scenarios were constructed to evaluate quantitatively the impact of climate change and human activity on the vegetation productivity of our study area. The results showed that the carbon sequestration capacities of various vegetation types in the MP differ, with forest > cropland > grassland > wetland. The NPP increased significantly during 2000–2019. Most areas showed a continuous and stable change in vegetation ANPP, with the current trend in variation mainly reflected in the continuous improvement of vegetation. In general, restoration of vegetation was prominent in the MP, and human activities affected more than 30% of vegetation restoration. The ANPP was positively correlated with temperature and precipitation, the latter of which had a more significant effect. Desertification management, restoration of cropland to forest and grassland, afforestation and reasonable grazing activities were the main human activities performed to restore vegetation. This study is expected to advance the theoretical understanding of ecological protection and sustainable development in the MP. Full article

(This article belongs to the Special Issue Observation for Resilient Cities and Human Settlements: Theory, Algorithms and Applications)

► Show Figures

Graphical abstract

Journal Menu

Journal Browser

Observation for Resilient Cities and Human Settlements: Theory, Algorithms and Applications

Share This Special Issue

Special Issue Editors

Special Issue Information

Keywords

Published Papers (12 papers)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI