Dynamic Monitoring and Analysis of Ecological Quality of Pingtan Comprehensive Experimental Zone, a New Type of Sea Island City, Based on RSEI

Analysis of Ecological Environment in the Shanxi Section of the Yellow River Basin and Coal Mining Area Based on Improved Remote Sensing Ecological Index

As a major coal-producing area, the Shanxi section of the Yellow River Basin has been significantly affected by coal mining activities in the local ecological environment. Therefore, an in-depth study of the ecological evolution in this region holds great scientific significance and practical value. In this study, the Shanxi section of the Yellow River Basin, including its planned coal mining area, was selected as the research subject. An improved remotely sensed ecological index model (NRSEI) integrating the remotely sensed ecological index (RSEI) and net primary productivity (NPP) of vegetation was constructed utilizing the Google Earth Engine platform. The NRSEI time series data from 2003 to 2022 were calculated, and the Sen + Mann-Kendall analysis method was employed to comprehensively assess the ecological environment quality and its evolutionary trends in the study area. The findings in this paper indicate the following data: (1) The contribution of the first principal component of the NRSEI model is more than 70%, and the average correlation coefficient is higher than 0.79. The model effectively integrates the information of multiple ecological indicators and enhances the applicability of regional ecological environment evaluation. (2) Between 2003 and 2022, the ecological environment quality in the Shanxi section of the Yellow River Basin showed an overall upward trend, with the average NRSEI value experiencing phases of fluctuation, increase, decline, and stabilization. The NRSEI values in non-coal mining areas consistently remained higher than those in coal mining areas. (3) Over 60% of the areas have improved ecological conditions, especially in coal mining areas. (4) The impact of coal mining on the ecological environment is significant within a 6 km radius, while the effects gradually diminish in the 6 to 10 km range. This study not only offers a reliable methodology for evaluating ecological environment quality on a large scale and over a long time series but also holds significant guiding value for the ecological restoration and sustainable development of the Shanxi section of the Yellow River Basin and its coal mining area.

Coupling eco-environmental quality and ecosystem services to delineate priority ecological reserves-A case study in the Yellow River Basin

Priority ecological reserves (PER) aim to protect areas with significant ecological value and crucial ecological functions, optimizing resource allocation to maximize the benefits of ecological conservation. However, most previous studies have considered only ecosystem services (ESs) in delineating PER, neglecting eco-environmental quality (EEQ). This study used the Remote Sensing-based Ecological Index (RSEI) to represent EEQ and combined it with ESs to delineate PER at the county scale in the Yellow River Basin (YRB). Additionally, it employed Multiscale Geographically Weighted Regression to identify the driving factors influencing the ESs and EEQ of PER. The results showed that: (1) From 2000 to 2020, both RSEI and the Comprehensive ESs (CES) in the YRB exhibited a fluctuating upward trend; (2) Three types of PER were extracted, with ESs reserve mainly distributed in the upstream region, EEQ reserve primarily in the middle and lower reaches, and integrated ecological reserve mainly in the midstream region, all dominated by vegetation land-use types; (3) Within the extracted PER, RSEI was mainly influenced by soil, aspect, population (pop), PM2.5, temperature (tmp), and potential evapotranspiration (pet), while CES was affected by soil, pop, PM2.5, slope, tmp, precipitation, and pet. To enhance the EEQ and ESs of the YRB, it was recommended to incorporate at least 105,379 km2 into the existing protected areas in the YRB. These areas should be subdivided based on their ecological status, with specific management measures for different types of PER. This study provides recommendations for environmental protection and land planning in the YRB, actively responding to current policies on high-quality development and ecological environmental protection in the YRB.

Eco-environmental changes due to human activities in the Erhai Lake Basin from 1990 to 2020

Human activities have increased with urbanisation in the Erhai Lake Basin, considerably impacting its eco-environmental quality (EEQ). This study aims to reveal the evolution and driving forces of the EEQ using water benefit-based ecological index (WBEI) in response to human activities and policy variations in the Erhai Lake Basin from 1990 to 2020. Results show that (1) the EEQ exhibited a pattern of initial degradation, subsequent improvement, further degradation and a rebound from 1990 to 2020, and the areas with poor and fair EEQ levels mainly concentrated around the Erhai Lake Basin with a high level of urbanisation and relatively flat terrain; (2) the EEQ levels were not optimistic in 1990, 1995 and 2015, and areas with poor and fair EEQ levels accounted for 43.41%, 47.01% and 40.05% of the total area, respectively; and (3) an overall improvement in the EEQ was observed in 1995-2000, 2000-2005, 2005-2009 and 2015-2020, and the improvement was most significant in 1995-2000, covering an area of 823.95 km2 and accounting for 31.79% of the total area. Results also confirmed that the EEQ changes in the Erhai Lake Basin were primarily influenced by human activities and policy variations. Moreover, these results can provide a scientific basis for the formulation and planning of sustainable development policy in the Erhai Lake Basin.

The dynamics of red Noctiluca scintillans in the coastal aquaculture areas of Southeast China

Noctiluca scintillans (NS) adds an aesthetic appeal to many coastal areas because of their bioluminescence. An intense bloom of the red NS frequently occurs in the coastal aquaculture region of Pingtan Island in Southeastern China. However, when NS exceeds in abundance, it causes hypoxia which has devastating impacts on the aquaculture. This study was conducted in the Southeastern part of China with an aim to examine the relationship between the profusion of NS and its impacts on marine environment. Samples from four stations on Pingtan Island were collected for 12 months (January to December 2018) and were later analyzed in laboratory against five parameters, namely temperature, salinity, wind speed, dissolved oxygen, and chlorophyll a. Results showed that the NS blooms were particularly active during the months of May and June in the Pingtan Island area. The seawater temperatures during that time were recorded between 20 and 28.8 °C indicating the optimum survival temperature for NS. The NS bloom activity ceased above 28.8 °C. A principal component analysis (PCA) indicated that the richness of NS was positively associated with temperature and salinity, whereas there was a significant reverse correlation between NS accumulation and wind speed. NS is a heterotrophic dinoflagellate and relies on the predation of algae for reproduction; therefore, a significant correlation was observed between NS abundance and chlorophyll a concentration, and an inverse correlation was observed between NS and phytoplankton abundance. Additionally, red NS growth was observed immediately following the diatom bloom, suggesting that phytoplankton, temperature, and salinity are the essential factors in the evolution, progression, and termination of NS growth.

Urban Ecological Environment Quality Evaluation and Territorial Spatial Planning Response: Application to Changsha, Central China

Scientific territorial spatial planning is of great significance in the realization of the sustainable development goals in China, especially in the context of China's ecological civilization construction and territorial spatial planning. However, limited research has been carried out to understand the spatio-temporal change in EEQ and territorial spatial planning. In this study, Changsha County and six districts of Changsha City were selected as the research objects. Based on the remote sensing ecological index (RSEI) model, the spatio-temporal changes in the EEQ and spatial planning response in the study area during 2003-2018 were analyzed. The results reveal that (1) the EEQ of Changsha declined and then rose between 2003 and 2018, showing an overall decreasing trend. The average RSEI declined from 0.532 in 2003 to 0.500 in 2014 and then increased to 0.523 in 2018, with an overall decrease of 1.7%. (2) In terms of spatial pattern changes, the Xingma Group, the Airport Group and the Huangli Group in the east of the Xiangjiang River had the most serious EEQ degradation. The EEQ degradation of Changsha showed an expanding and polycentric decentralized grouping pattern. (3) Massive construction land expansion during rapid urbanization caused significant EEQ degradation in Changsha. Particularly, the areas with low EEQ were concentrated in the areas with concentrated industrial land. Scientific territorial spatial planning and strict control were conducive to regional EEQ improvement. (4) The prediction using the urban ecological model demonstrates that every 0.549 unit increase in NDVI or 0.2 unit decrease in NDBSI can improve the RSEI of the study area by 0.1 unit, thus improving EEQ. In the future territorial spatial planning and construction of Changsha, it is necessary to promote the transformation and upgrading of low-end industries into high-end manufacturing industries and control the scale of inefficient industrial land. The EEQ degradation caused by industrial land expansion needs to be noted. All of these findings can provide valuable information for relevant decision-makers to formulate ecological environment protection strategies and conduct future territorial spatial planning.

Monitoring Multi-Scale Ecological Change and Its Potential Drivers in the Economic Zone of the Tianshan Mountains' Northern Slopes, Xinjiang, China

Accurately capturing the changing patterns of ecological quality in the urban agglomeration on the northern slopes of the Tianshan Mountains (UANSTM) and researching its significant impacts responds to the requirements of high-quality sustainable urban development. In this study, the spatial and temporal distribution patterns of remote sensing ecological index (RSEI) were obtained by normalization and PCA transformation of four basic indicators based on Landsat images. It then employed geographic detectors to analyze the factors that influence ecological change. The result demonstrates that: (1) In the distribution of land use conversions and degrees of human disturbance, built-up land, principally urban land, and agricultural land, represented by dry land, are rising, while the shrinkage of grassland is the most substantial. The degree of human disturbance is increasing overall for glaciers. (2) The overall ecological environment of the northern slopes of Tianshan is relatively poor. Temporally, the ecological quality changes and fluctuates, with an overall rising trend. Spatially, ecological quality is low in the north and south and high in the center, with high values concentrated in the mountains and agriculture and low values in the Gobi and desert. However, on a large scale, the ecological quality of the Urumqi-Changji-Shihezi metropolitan area has worsened dramatically compared to other regions. (3) Driving factor detection showed that LST and NDVI were the most critical influencing factors, with an upward trend in the influence of WET. Typically, LST has the biggest influence on RSEI when interacting with NDVI. In terms of the broader region, the influence of social factors is smaller, but the role of human interference in the built-up area of the oasis city can be found to be more significant at large scales. The study shows that it is necessary to strengthen ecological conservation efforts in the UANSTM region, focusing on the impact of urban and agricultural land expansion on surface temperature and vegetation.

Spatiotemporal Changes in Ecological Quality and Its Associated Driving Factors in Central Asia

Maintaining the ecological security of arid Central Asia (CA) is essential for the sustainable development of arid CA. Based on the moderate-resolution imaging spectroradiometer (MODIS) data stored on the Google Earth Engine (GEE), this paper investigated the spatiotemporal changes and factors related to ecological environment quality (EEQ) in CA from 2000 to 2020 using the remote sensing ecological index (RSEI). The RSEI values in CA during 2000, 2005, 2010, 2015, and 2020 were 0.379, 0.376, 0.349, 0.360, and 0.327, respectively; the unchanged/improved/deteriorated areas during 2000–2005, 2005–2010, 2010–2015, and 2015–2020 were about 83.21/7.66%/9.13%, 77.28/6.68%/16.04%, 79.03/11.99%/8.98%, and 81.29/2.16%/16.55%, respectively, which indicated that the EEQ of CA was poor and presented a trend of gradual deterioration. Consistent with the RSEI trend, Moran’s I index values in 2000, 2005, 2010, 2015, and 2020 were 0.905, 0.893, 0.901, 0.898, and 0.884, respectively, revealing that the spatial distribution of the EEQ was clustered rather than random. The high–high (H-H) areas were mainly located in mountainous areas, and the low–low (L-L) areas were mainly distributed in deserts. Significant regions were mainly located in H-H and L-L, and most reached the significance level of 0.01, indicating that EEQ exhibited strong correlation. The EEQ in CA is affected by both natural and human factors. Among the natural factors, greenness and wetness promoted the EEQ, while heat and dryness reduced the EEQ, and heat had greater effects than the other three indexes. Human factors such as population growth, overgrazing, and hydropower development are important factors affecting the EEQ. This study provides important data for environmental protection and regional planning in arid and semi-arid regions.

Land Use and Climate Change Altered the Ecological Quality in the Luanhe River Basin

Monitoring and assessing ecological quality (EQ) can help to understand the status and dynamics of the local ecosystem. Moreover, land use and climate change increase uncertainty in the ecosystem. The Luanhe River Basin (LHRB) is critical to the ecological security of the Beijing–Tianjin–Hebei region. To support ecosystem protection in the LHRB, we evaluated the EQ from 2001 to 2020 based on the Remote Sensing Ecological Index (RSEI) with the Google Earth Engine (GEE). Then, we introduced the coefficient of variation, Theil–Sen analysis, and Mann–Kendall test to quantify the variation and trend of the EQ. The results showed that the EQ in LHRB was relatively good, with 61.08% of the basin rated as ‘good’ or ‘excellent’. The spatial distribution of EQ was low in the north and high in the middle, with strong improvement in the north and serious degradation in the south. The average EQ ranged from 0.58 to 0.64, showing a significant increasing trend. Furthermore, we found that the expansion of construction land has caused degradation of the EQ, whereas climate change likely improved the EQ in the upper and middle reaches of the LHRB. The results could help in understanding the state and trend of the eco-environment in the LHRB and support decision-making in land-use management and climate change.

Quality Assessment of Ecological Environment Based on Google Earth Engine: A Case Study of the Zhoushan Islands

With the development of society, the impact of human activities on the ecological environment is becoming increasingly intense, so the dynamic monitoring of the status of the ecological environment is of great significance to the management and protection of urban ecology. As an objective and rapid ecological quality monitoring and evaluation technique, the remote sensing based ecological index (RSEI) has been widely used in the field of ecological research. Free available Landsat series data has the character of a long time series and high spatial resolution provides the possibility to conduct large-scale and long-term monitoring of ecological environment quality. Compared with traditional methods, the Google Earth Engine (GEE) platform can save a lot of time and energy in the data acquisition and preprocessing steps. To monitor the quality of the ecological environment in Zhoushan from 2000 to 2020, the GEE platform was used for cloud computing to obtain the RSEI, which can reflect the quality of the ecological environment. The results show that (1) from 2000 to 2020, the average RSEI value in Zhoushan Islands decreased from 0.748 to 0.681, indicating that the overall ecological environment exhibited a degradation trend. (2) From 2000 to 2020, the change in the area of each ecological environment level indicates that the quality of the ecological environment in Zhoushan Islands exhibited a degradation trend. The proportion of the area with an excellent eco-environment grade decreased by 13.54%, and the proportion of the area with poor and fair eco-environment grades increased by 3.43%.

Monitoring and Evaluation of Eco-Environment Quality Based on Remote Sensing-Based Ecological Index (RSEI) in Taihu Lake Basin, China

Rapid and effective access to the spatiotemporal patterns and evolutionary trends of the regional eco-environment is key to regional environment protection and planning. Based on the Google Earth Engine platform, we use 165 Landsat images from the summer and autumn seasons (May–November) of 2000, 2010, and 2018 as data sources to calculate the RSEI, which represents the quality of the eco-environment, and then analyze the factors influencing the spatial heterogeneity of the eco-environment and the relationship between eco-environment and land-use changes based on RSEI. The results showed the following: (1) From 2000 to 2018, the overall ecological environment quality of the Taihu Lake Basin showed a stage of rapid decline (2000–2010) and a stage of slow decline (2010–2018). (2) The factors were ranked in order of their explanatory power for the spatial heterogeneity of the RSEI: land-use (0.594) > population density (0.418) > slope (0.309) > elevation (0.308) > GDP (0.304) > temperature (0.233) > precipitation (0.208). An interactive effect was found for each factor of the RSEI, which is mainly represented by a mutual enhancement. (3) From 2000 to 2010, the rapid urban expansion was the main reason for the deterioration of ecological quality. From 2010 to 2018, urban expansion slowed down, and the trend of ecological quality deterioration was effectively curbed. Therefore, promoting the intensive use of land and reducing construction land expansion are key to ensuring sustainable regional socio-economic development.

Invasive Alien Plants and Invasion Risk Assessment on Pingtan Island

Pingtan Island is the largest island in Fujian Province and the fifth largest island in China. The invasion of a large number of alien plants has had a profound impact on the local ecological environment. Because the harm caused by alien invasive plants varies greatly between different ecosystems and even in different habitats, the risk assessment index system suitable for one region may not be suitable for other regions. Therefore, it is necessary to establish a risk assessment index system for invasive alien plants on Pingtan Island. Alien plant communities in different habitats were studied by means of quadrat investigation and professional literature review. Some invasive alien species were selected and compiled into a list of invasive alien plants on Pingtan Island, and their species composition, origin, flora, life forms, and habitats were statistically grouped. There were 104 species in 80 genera and 37 families of alien invasive plants. Asteraceae, Fabaceae, Amaranthaceae, and Poaceae were the main families, accounting for 26.7%, 6.7%, 6.7% and 5.8% of the total species, respectively. The geographical components of families and genera have obvious tropical properties, accounting for 51.3% and 66.6% of the total species, respectively. These originated mainly from South America and North America, accounting for 45.5% and 30.1% of the total frequency, respectively. Annual herbs, biennial herbs, and perennial herbs accounted for 84.6% of the total species. Based on a DPSIR conceptual model and an AHP method, an invasion risk assessment of 104 invasive alien plants was conducted. The ecological adaptability, habitat distribution and landscape impact of species were considered in the selection of indicators and the formulation of standards. A total of 23 high-risk invasive species were identified at level I, 37 medium-risk invasive species at level II, and 44 low-risk invasive species at level III. Lantana camara L. had the highest risk score (49), followed by Cenchrus echinatus L. (45), Spartina alterniflora Loisel. (45), and Panicum repens L. (43.5). Suggestions are put forward to prevent the invasion of alien plants on Pingtan Island and to provide a theoretical basis for promoting the healthy and stable development of the ecological environment on the island.

Research and Analysis of Ecological Environment Quality in the Middle Reaches of the Yangtze River Basin between 2000 and 2019

Ecological environment quality is a long-term continuous concept that is affected by various environmental factors. Its assessment has important implications for implementing the planning and protection of dynamic regional ecosystems. Therefore, this study attempted to obtain these indicators (green, dry, wet, heat) through the Google Earth Engine (GEE) platform, and then coupled the ecological environment quality index in the middle reaches of the Yangtze River Basin (MYRB) between 2000 and 2019, based on the remote sensing ecological index (RSEI). The major results show that: (1) changes in the four indicators in summer were more obvious than those in winter, and the changes were concentrated in the central and northern regions of the MYRB; (2) both the modified normalized difference water index (MNDWI) and normalized differential build-up and bare soil index (NDBI) in summer and winter have higher weighting ratios, implying that water body changes and human activities had a greater impact on the ecological environment; and (3) ecological environment quality in the MYRB between 2000 and 2019 was relatively flat. The ecological conditions began to deteriorate in 2008, and substantial ecological degradation was noted in some areas between 2008 and 2019 (18.7% in the central region, 16.0% in the eastern region). The MYRB has an important position in the Yangtze River economic belt and is an important part of the Yangtze River protection. This research could provide a theoretical basis and decision support for the development and protection of the Yangtze River Basin (YRB) green economy.

Assessing the Urban Eco-Environmental Quality by the Remote-Sensing Ecological Index: Application to Tianjin, North China

The remote-sensing ecological index (RSEI), which is built with greenness, moisture, dryness, and heat, has become increasingly recognized for its use in urban eco-environment quality assessment. To improve the reliability of such assessment, we propose a new RSEI-based urban eco-environment quality assessment method where the impact of RSEI indicators on the eco-environment quality and the seasonal change of RSEI are examined and considered. The northern Chinese municipal city of Tianjin was selected as a case study to test the proposed method. Landsat images acquired in spring, summer, autumn, and winter were obtained and processed for three different years (1992, 2005, and 2018) for a multitemporal analysis. Results from the case study show that both the contributions of RSEI indicators to eco-environment quality and RSEI values vary with the season and that such seasonal variability should be considered by normalizing indicator measures differently and using more representative remote-sensing images, respectively. The assessed eco-environment quality of Tianjin was, overall, improving owing to governmental environmental protection measures, but the damage caused by rapid urban expansion and sea reclamation in the Binhai New Area still needs to be noted. It is concluded that our proposed urban eco-environment quality assessment method is viable and can provide a reliable assessment result that helps gain a more accurate understanding of the evolution of the urban eco-environment quality over seasons and years.

Assessment of Spatio-Temporal Variation and Driving Mechanism of Ecological Environment Quality in the Arid Regions of Central Asia, Xinjiang

Grassland ecosystems are increasingly threatened by pressures from climate change and intensified human activity, especially in the arid region of Central Asia. A comprehensive understanding of the ecological environment changes is crucial for humans to implement environmental protection measures to adapt to climate change and alleviate the contradiction between humans and land. In this study, fractional vegetation coverage (FVC), leaf area index (LAI), gross primary productivity of vegetation (GPP), land surface temperature (LST), and wetness (WET) were retrieved from Moderate-Resolution Imaging Spectroradiometer (MODIS) satellite remote sensing products in 2008 and 2018. Principal component analysis (PCA) was used to establish the MODIS data-based ecological index (MODEI) in the study area, and the spatial differentiation characteristics and driving mechanism of ecological quality in the last ten years were explored. The results showed that: (1) FVC, GPP, LAI, and WET had positive effects on the ecological environment, while LST had a negative impact on the ecological environment. FVC and GPP were more significant than other indicators. (2) The MODEI showed a spatial pattern of “excellent in the north and poor in the south” and changed from north to south in the study area. (3) From 2008 to 2018, the average MODEI of Fuyun County increased from 0.292 to 0.303, indicating that the ecological quality in Fuyun County became better overall. The improved areas were mainly located in the summer pastures at higher elevations. In comparison, the deteriorated areas were concentrated in the spring and autumn pastures and winter pastures at lower elevations. The areas where the ecological environment had obviously improved and degraded were distributed along the banks of the Irtysh River and the Ulungur River. (4) With the increase in precipitation and the decrease in grazing pressure, the MODEI of summer pasture was improved. The deterioration of ecological environment quality in spring and autumn pastures and winter pastures was related to the excessive grazing pressure. The more significant changes in the MODEI on both sides of the river were associated with implementing the herdsmen settlement project. On the one hand, the implementation of newly settled villages increased the area of construction land on both sides of the river, which led to the deterioration of ecological quality; on the other hand, due to the increase in cropland land and the planting of artificial grasses along the river, the ecological quality was improved. The study offers significant information for managers to make more targeted ecological restoration efforts in ecologically fragile areas.

Spatiotemporal ecological quality assessment of metropolitan cities: a case study of central Iran

The present study used the recently developed Remote Sensing-Based Ecological Index (RSEI) to assess the temporal-spatial variation of ecological quality in the metropolitan city of Isfahan (Iran) as a member of the UNESCO Creative Cities Network. This study was conducted from the Landsat TM/OLI satellite images of 2004, 2009, 2014 and 2019. The RSEI was synthesized by principal component analysis for four indices of Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST), Land Surface Moisture (LSM) and Normalized Differential Build-up, and Bare Soil Index (NDBSI) based on the framework of the Pressure-State-Response (PSR) in the aforementioned years. The ecological quality of the city was assessed by RSEI over a 15-year period. The index has a value range of 0 (completely poor ecological quality) to 1 (completely desirable). In addition, the spatial heterogeneity of RSEIs at different intervals was assessed by the Moran index. The results showed that the RSEI value was always less than 0.4, which indicated the unfavourable ecological quality of the city. This index was 0.34, 0.37, 0.26 and 0.30 in 2004, 2009, 2014 and 2019, respectively. Therefore, the ecological quality of the city did not have a constant trend during the studied period and had several fluctuations, which could be attributed to the natural and anthropogenic changes in the studied period. Additionally, the results of the Moran index showed a steady decline, which indicated a declining homogeneity during this period. Matching the calculated RSEIs with the realities of the region at each time interval suggested that the index could be a useful tool for assessing urban ecological quality.

Spatiotemporal Evolution of Lakes under Rapid Urbanization: A Case Study in Wuhan, China

The impact of urbanization on lakes in the urban context has aroused continuous attention from the public. However, the long-term evolution of lakes in a certain megacity and the heterogeneity of the spatial relationship between related influencing factors and lake changes are rarely discussed. The evolution of 58 lakes in Wuhan, China from 1990 to 2019 was analyzed from three aspects of lake area, lake landscape, and lakefront ecology, respectively. The Multi-Scale Geographic Weighted Regression model (MGWR) was then used to analyze the impact of related influencing factors on lake area change. The investigation found that the total area of 58 lakes decreased by 15.3%. A worsening trend was found regarding lake landscape with the five landscape indexes of lakes dropping; in contrast, lakefront ecology saw a gradual recovery with variations in the remote sensing ecological index (RSEI) in the lakefront area. The MGWR regression results showed that, on the whole, the increase in Gross Domestic Product (GDP), RSEI in the lakefront area, precipitation, and humidity contributed to lake restoration. The growth of population and the proportion of impervious surface (IS) in the lakefront area had different effects on different lakes. Specifically, the increase in GDP and population in all downtown districts and two suburb districts promoted lake restoration (e.g., Wu Lake), while the increase in population in Jiangxia led to lake loss. The growth of RSEI in lakefront area promoted the restoration of most lakes. A higher proportion of IS in lakefront area normally resulted in more lake loss. However, in some cases, the growth of IS was caused by lake conservation, which contributed to lake restoration (e.g., Tangxun Lake). The study reveals the spatiotemporal evolution of multiple lakes in Wuhan and provides a useful reference for the government to formulate differentiated protection policies.

Spatiotemporal Analysis of Urbanization Using GIS and Remote Sensing in Developing Countries

The international statistics show that the global urban population will increase by up to 68% by 2050 [...]