Remote Sensing Data For Monitoring Research Articles

Correlations between ecosystem service value and landscape ecological risk and its spatial heterogeneity in Jilin Province, China.

Exploring the correlations between ecosystem service value (ESV) and landscape ecological risk and the driving factors of their spatial variations is crucial for maintaining regional ecological security and promoting sustainable human well-being. We carried out a grid resampling size of 5 km×5 km assessment units of Jilin Pro-vince based on the remote sensing monitoring data of land use in 2000, 2005, 2010, 2015, and 2020. We quantitatively evaluated the landscape ecological risk and ESV, and analyzed their spatial-temporal variations. Employing bivariate spatial autocorrelation analysis and the geographical detector models, we examined the correlation between the landscape ecological risk and ESV and explored the driving factors for their spatial variations. The results showed that ESV in Jilin Province decreased from 385.895 billion yuan to 378.211 billion yuan during 2000-2020. The eastern region was dominated by extremely low risk, medium risk, and low risk areas. In contrast, the western region was mainly composed of extremely high risk and high risk areas. There was a significant negative correlation and spatial negative correlation between landscape ecological risk and ESV in Jilin Province. Human activity and land use type were the important driving factors for spatial differentiation in both landscape ecological risk and ESV. Our findings suggested that scientific land use regulation and appropriate control of human activities are critically needed to optimize Jilin Province's ecological environment.

Dynamic variation and driving mechanisms of land use change from 1980 to 2020 in the lower reaches of the Yangtze River, China

To systematically explore land use/cover change (LUCC) trends and driving mechanisms at the large watershed scale under the background of climate change and rapid urbanization. Taking the lower reaches of the Yangtze River (LRYR) as the research object, based on the land use remote sensing monitoring data from 1980 to 2020, the spatial and temporal evolution characteristics of LUCC in LRYR were analyzed by adopting the methods of land use dynamics degree (LUDD) and hotspot analysis and used geospatial detectors to quantitatively assess the intensity of the role of the land use change drivers in the LRYR. The results show that: 1) The land-use types in LRYR were dominated by arable land and woodland, accounting for more than 70% of the total area. During the study period, the construction land area increased by 11,835 km2, and became the third largest land-use type in LRYR after 2010 and formed a typical urban contiguous zone along the route from Nanjing to Shanghai. 2) The land use degree comprehensive index (LUDCI) in LRYR at each stage is 270.91, 270.88, 272.22, 272.72, 274.00, 275.57, 276.93 and 280.37, respectively. LUCC in LRYR has become more dramatic, and there is significant spatial heterogeneity. Shanghai has always been a hot area of LUCC and Huangshan and Chizhou are cold spots of LUCC. 3) The driving mechanism of LUCC in LRYR can be divided into three stages. In these three stages, secondary industry output value, precipitation, and elevation are always important factors affecting LUCC. The interaction between driving factors is significant. The strongest interaction is the output value of the secondary industry ∩ precipitation, the interaction reaches above 0.6. The research results are of great significance for promoting the sustainable development of land use in this region.

Analysis of Land Use Type Changes in Yulin City in the 21st Century

Using remote sensing monitoring data of land use/land cover in China in 2000 and 2020, this study explores the changes in land use types in Yulin City through the land use transfer matrix. The results indicate that the main types of land use in Yulin City are grassland, cultivated land, and unused land. From 2000 to 2020, the order of absolute changes in the area of land use types in the study area is: unused land>grassland>construction land>cultivated land>forest land>water area, and its changes are closely related to national ecological policies; The area of construction land has significantly increased after 2000, which is consistent with the process of urbanization development; The continuous decrease in water area is mainly influenced by natural factors. The changes in land use types in Yulin City are influenced by both natural and social factors, with ecological policies and urbanization development dominating.

Spatiotemporal Distribution and Driving Force Analysis of the Ecosystem Service Value: A Typical Case Study of the Coastal Zone, Eastern China

Identifying and assessing the drivers of change in ecosystem service value (ESV) is critical for integrated management and human well-being in coastal zone areas. This paper took a typical coastal zone in eastern China as the research object. Based on five periods of remote sensing monitoring data of land use status from 2000 to 2020, the ESV of Yancheng was estimated by adopting the equivalence factor method. Spatial statistical analysis and GeoDetector were applied to reveal the heterogeneous features of ESV and its driving mechanism. The results suggested that: (1) From 2000–2020, each land use type in the study area changed to different degrees, among which the most drastic change was in the construction land, which increased continuously by 962.69 km2, the cultivated land area decreased continuously by 784.1 km2, and the area of water body decreased by 163.34 km2. (2) ESV experienced a process of increasing and then decreasing, from 547.84 × 108 yuan to 570.86 × 108 yuan and then decreasing to 507.62 × 108 yuan, with farmland ecosystems having the largest ESV, accounting for more than 60%. Regulatory services were the core function of ecosystem services, accounting for more than 60%. (3) There was significant spatial-temporal differentiation in ESV, with extremely low ESV expanding in rapidly developing urbanized areas. The ESV distribution exhibited significant spatial autocorrelation and local spatial clustering, with the gravity center showing a general trend from north to southwest. (4) The ESV spatial and temporal evolutionary characteristics were the result of a multifactorial integration of land use, topography, socio-economics, and climate factors. The explanatory power of each factor in descending order was LDI > DEM > POP > GDP > RAI > TEM, and any two-factor interaction had higher explanatory power than the single factor.

Spatiotemporal Changes and Influencing Factors of Rural Settlements in the Middle Reaches of the Yangtze River Region, 1990–2020

China has experienced rapid urbanization, causing dramatic changes to the patterns of urban and rural land use relationships. This paper analyzes the spatiotemporal characteristics of rural settlements in the middle reaches of the Yangtze River region (MRYRR) using remote sensing monitoring data from 1990 to 2020 and reveals the influencing factors of spatiotemporal changes. The research found that (1) the overall increase in the quantity of rural settlements in the MRYRR between 1990 and 2020 was 504.70 km2. The area of transfer of other land use types to rural settlement was 1382.57 km2, of which 78.55% came from arable land and 16.62% came from forests; the area of rural settlement transfer to other land use types was 867.24 km2, of which 66.27% was reclaimed as arable land and 8.48% was transferred into urban built-ups. Changes in different stages and regions are diversified. (2) The spatial layout of rural settlements showed no significant differences in the MRYRR between 1990 and 2020, with a cluster distribution of “five main nuclei and many secondary nuclei” and a spatial distribution of “gathering in the north and east, while scattered in the south and west”. (3) The level of fragmentation of rural settlements in the MRYRR has greatly decreased since 1990, with the average patch size expanding significantly. The patch complexity of rural settlements fluctuated moderately, but the connectivity between patches continued to increase, and their distribution became more clustered. (4) Social and economic factors, including rural electricity consumption, the output value of the primary industry, net income per rural resident, urbanization rate, and the effective irrigated area, most strongly impacted the changes in rural settlements in the MRYRR. The research can be utilized as a guide for reconstructing the pattern of rural land use to promote sustainable rural revitalization.

Spatiotemporal patterns and influencing factors of urban ecological space availability in coastal cities of China during rapid urbanization

Urban ecological space (UES) is crucial to the sustainable development of cities and the improvement of human well-being. Rapid urbanization tends to lead to the fragmentation of urban ecological space and functional decline. China's coastal cities are developed regions with high urbanization levels and the unique geographical location makes them have two kinds of ecological spaces, namely marine ecological spaces (MES) and terrestrial ecological spaces (TES). During rapid urbanization, the spatiotemporal changes of the urban ecological space availability (UESA) and its driving factors in China's coastal cities are still unclear. For this, this work selected 53 coastal cities in China as the research samples and applied remote sensing monitoring data of land use to analyze the spatiotemporal patterns of the UESA under different travel modes (walking, public transport, and driving) from 1990 to 2015. Then, the spatial econometric model was applied to reveal the impact of urbanization on urban ecological space availability (UESA). The main research results show: (1) generally, the marine ecological spaces availability (MESA), terrestrial ecological spaces availability (TESA), and marine and terrestrial ecological spaces availability (MTESA) of the coastal cities in China showed an increasing trend from 1990 to 2015. With the increase in travel distance, the MESA, TESA, and MTESA in the coastal cities increased accordingly. (2) however, the spatial pattern of MESA in the coastal cities showed a significant heterogeneity, The hot spots of the MESA mostly appeared in coastal cities from Zhejiang to Fujian, and the cold spots were concentrated in the Liaoning, Hebei, and Shandong. (3) The TESA and MTESA in southern coastal cities were generally higher than that in northern coastal cities. (4) The expansion of the urban built-up area (UBUA) led to the improvement of the UESA in China's coastal cities. GDP and population density were positive factors affecting the TESA and MTESA. Our research can provide scientific planning basis for coordinating marine and terrestrial ecological space and optimizing territorial space planning, which is conducive to improving the life quality of residents and promoting sustainable urban development.

Habitat Quality Assessment and Driving Factors Analysis of Guangdong Province, China

Habitat quality is a key factor in regional ecological restoration and green development. However, limited information is available to broadly understand the role of natural and human factors in influencing habitat quality and the extent of their impact. Based on remote sensing monitoring data of land use over five time points (2000, 2005, 2010, 2015, and 2020), natural factors, and socioeconomic data, we applied the InVEST model to assess habitat quality in Guangdong Province. Using a multiscale geographically weighted regression (MGWR) model, we explored the spatial scale differences in the role of natural and human factors affecting habitat quality and the degree of their influence. The highlights of the results are as follows: ① From 2000 to 2020, land-use changes in the Pearl River Delta (PRD) region were particularly obvious, with the dynamic degree of construction land being higher than that of other land-use types. Construction land has gradually occupied agricultural and ecological land, causing damage to habitats. ② The overall habitat quality in Guangdong Province is decreasing; the areas with low habitat quality values are concentrated in the PRD region and the coastal areas of Chaoshan, Maoming, and Zhanjiang, while the areas with higher habitat quality values are mainly located in the non-coastal areas in the east and west of Guangdong and the north of Guangdong. ③ The MGWR regression results showed that the normalized vegetation index had the strongest effect on habitat quality, followed by road density, gross domestic product (GDP) per unit area, slope, and average elevation, and the weakest effect on average annual precipitation. ④ The effects of average elevation, GDP per unit area, and normalized vegetation index on habitat quality were significantly positively correlated, while road density was significantly negatively correlated. These results provide a scientific basis for adjusting spatial land-use planning and maintaining regional ecological security.

Spatial Heterogeneity and Formation Mechanism of Eco-Environmental Quality in the Yellow River Basin

The Yellow River Basin (YRB) serves as a crucial ecological security barrier in China, and the scientific evaluation and understanding of the formation mechanisms of ecological environment quality (EEQ) in the YRB are of great importance for implementing dynamic regional ecosystem planning and protection. Therefore, this study aims to explore the spatiotemporal evolution characteristics and formation mechanisms of the EEQ in the YRB from 2000 to 2020, based on land use remote sensing monitoring data, utilizing research methods such as the ecological environment quality index, centroid analysis, and the geographic detector. The results are as follows: From 2000 to 2020, the overall EEQ in the YRB showed a slight increasing trend, with a significant growth trend in the upstream and middle reaches, and a decreasing trend in the downstream. The spatial heterogeneity of the EEQ in the YRB was significant, with a south—high and north—low distribution pattern overall. During the study period, the spatial distribution pattern of the EEQ was relatively stable, with a notable increase in EEQ in the northwest of the YRB. The EEQ in the study area was jointly affected by natural and socio-economic factors, with precipitation, terrain fluctuation, and temperature being the dominant factors. The upstream EEQ was most affected by temperature, the EEQ of the middle reaches was most affected by precipitation, and the downstream EEQ was more vulnerable to the interference of slope and topographic relief. The influencing factors had a synergistic effect on the EEQ, and the explanatory power of socio-economic factors for a single-factor explanation of the EEQ was relatively low, but the explanatory power of the interaction between natural and socio-economic factors was significantly enhanced. These results can provide valuable insights for guiding and informing policy-making decisions related to ecological protection in the YRB.

Identification of Ecological Management Zoning on Arid Region from the Perspective of Risk Assessment

Strengthening ecosystem monitoring and improving the efficiency of ecological risk assessment are of great significance for the sustainable development of ecosystems in an arid area. Using remote sensing monitoring data of land use, the ecological risk status of typical arid areas is assessed, its spatial heterogeneity is analyzed from the perspective of space-time, and the key areas of ecological risk management are finally identified. The results show that (1) the transformation mode of landscape ecological risk was dominated by medium–low risk to medium risk, and low risk to medium–low risk as a secondary level; in addition, the ecological risk level of the region increased. From 2000 to 2020, the transformation mode of landscape ecological risk was dominated by medium risk to medium–low risk, and medium–low risk to low risk as a secondary level; in addition, the regional ecological risk level shows a moderating trend. (2) The spatial difference in the ecological risk level in the Hexi region is obvious, showing a gradual decline from east to west, and the spatial difference in the ecological risk level in the west is significant. (3) A total of 1194 grid units are identified as key areas for ecological risk management in the Hexi region, accounting for 43% of the study area. This study provides important theoretical basis for ecosystem monitoring and risk assessment management in similar areas of arid regions.

Assessing the vulnerability to climate change of a semi-arid pastoral social–ecological system: A case study in Hulunbuir, China

Covering approximately 15% of the Earth's land surface and home to 14% of the total global population, semi-arid pastoral areas are characterized by high climatic variability and ecological vulnerability. Recurring extreme weather prodoundly shapes decision-making in semi-arid pastoral social–ecological systems (SAPSES) and their traditional natural-resource-based livelihoods. This study developed a conceptual framework of climate-livelihood vulnerability in SAPSES and evaluated the vulnerability of SAPSES to climate change effects and environmental pressure in Hulunbuir, China using a questionnaire survey and remote sensing monitoring data. Results showed that the study area were impacted substantially by climate change (0.68). However, the vulnerability was relatively low because of the moderate adaptability (0.59) and medium sensitivity of the local socio–ecological system (0.61). Natural factors, including climate variation, natural disasters and ecosystem sensitivity, were the main causes of vulnerability. The increasing vulnerability had been largely slowed by adaptive capital, the traditional cultural organization system and the collective action mechanism. Degraded grassland cover, lack of technical training and high habitation stickiness were the main reasons for increased sensitivity. Natural capital and financial capital were important factors restricting regional adaptive capacity. Therefore, promoting local livestock cooperatives, improving the provision of public services and strengthening ecological governance can help to enhance the climate change resilience and increase the stability and sustainability of SAPSES.

Simulation of coastal resource and environmental carrying capacity in the Yangtze River delta coastal zone based on shared socioeconomic pathways

Study of resource and environmental carrying capacity is an important research content of sustainable development science and the theoretical support for land space optimization. Existing research theories need to be deepened, and spatial simulation studies are relatively lacking. This study aimed to assess the current and future resource and environmental carrying capacity in the Yangtze River Delta region’s coastal zone and enhance sustainable development by exploring the application of shared socioeconomic pathway (SSPs) scenarios at the spatial pattern scale in regional resource and environmental carrying capacity simulation studies. Based on the FLUS and InVEST models, this study introduced the Coastal Resource and Environmental Carrying Capacity Index (CRECC) from the dimensions of “pressure” and “support” using land use remote sensing monitoring data and SSPs scenario data. A CRECC evaluation index system and quantitative evaluation method for the Yangtze River Delta were constructed. The results showed that from 2000 to 2020, the CRECC of the Yangtze River Delta coastal zone increased, the carrying capacity decreased, and the spatial distribution was low in the north and high in the south. The carrying capacity under the five SSP scenarios did not improve. The mismatch between natural ecological conditions and the intensity of human activities in the shoreline area was more prominent than in the study area, with the SSP1 and SSP5 scenarios being the most obvious. The supporting indicators have a more significant influence on improving CRECC than the pressure indicators, among which the supply capacity of water resources, land resources, and atmospheric environmental quality are the main limiting factors in the process of future sustainable economic-ecological development. This study provides ideas and examples for exploring spatial and temporal predictions of resources and environmental carrying capacity in coastal zones.

A dataset of vegetation phenology of Inner Mongolia (2001-2020)

Vegetation phenology is one of the sensitive indicators reflecting global climate change and vegetation growth. Inner Mongolia is an important part of the ecological security barrier of the Mongolian Plateau, and a key area for resource development, environmental protection and ecological security in China. The study on the vegetation phenological changes of Inner Mongolia is of great significance for understanding the characteristics of climate change and extreme climate events in Inner Mongolia. Based on the normalized differential vegetation index (NDVI) in the high-spatial resolution MOD13Q1 data product, we used Google Earth Engine platform to process MODIS-NDVI raw data for format conversion, projection conversion and clipping, and exported NDVI long time series data from 2000 to 2021. Then, we adopted the dynamic threshold method to obtain a dataset of vegetation phenology of Inner Mongolia from 2001 to 2020. With a resolution of 250 m, this dataset contains remote sensing monitoring data of the start of growing season (SOS), the end of growing season (EOS), and the length of growing season (LOS) in Inner Mongolia from 2001 to 2019. It can provide data support for understanding the temporal and spatial variation of vegetation phenology in Inner Mongolia and its response to climate change.

Urbanisation and ecosystem services in the Taiwan Strait west coast urban agglomeration, China, from the perspective of an interactive coercive relationship

Rapid urbanisation has triggered a series of 'urban diseases' that seriously interfere with the sustainability of ecosystem services (ESs). Scientific assessment of the interactions between urbanisation and ESs is important for improving the quality of urban development and optimising ESs. However, studies on the interactive stress relationship between urbanisation and ESs from the coupling and decoupling perspective are lacking, especially at the urban cluster scale. Considering 20 prefecture-level cities in the Taiwan Strait west coast urban agglomeration (TSWCUA), in this study we used land-use remote sensing monitoring data from 2005 to 2018 to assess the relationships between urbanisation and ESs within each coordinated development stage using a coupled coordination degree and the Tapio decoupling model. The results showed that, the urbanisation level (UL) of the TSWCUA had an overall upward trend, whereas ecosystem services value (ESV) showed a gradual decline. The coupled and coordinated relationship between UL and ESs was benign, despite long-term dysfunctional states. Overall, the number of cities with lagging ecosystem services increased. The decoupling state between urbanisation and ESV improved in a variable manner, and the weak decoupling gradually increased. The development trend in the study region was generally clear, although coordinated development was rare among the TSWCUA regions. Our study provides an empirical basis for improving the coordinated development of ULs and ESs in the TSWCUA.

Spatial-Temporal Evolution and Influencing Factors Analysis of Ecosystem Services Value: A Case Study in Sunan Canal Basin of Jiangsu Province, Eastern China

The continuing degradation of ecosystem functioning, particularly in areas of fast-growing economies, is a common challenge facing humanity today and a focus of global research on sustainable development. A typical fast-developing economic region in Southeastern China, namely Sunan Canal Basin of Jiangsu Province (SCBJ), was selected for this study. Based on remote sensing monitoring data of land use for five periods of 2000, 2005, 2010, 2015, and 2019, the ecosystem service value (ESV) of SCBJ was measured using the equivalent factor method, and the spatial and temporal evolution of the ESV was analyzed using contribution and spatial statistical methods. Panel quantile regression was employed to explore in depth the segmental effects of the ecosystem service influencing factors and to increase the understanding of ecosystem service influencing mechanisms. Our results showed the following: (1) From 2000 to 2019, the land use structure was stable, and the comprehensive land use dynamic degree was continuously reduced. There were significant differences in the single land use dynamic degree of each land type, especially for built-up land. (2) During the study period, the total ESV increased first and then decreased, with the decreasing regions mainly distributed in the southeast of SCBJ and the urban rapid expansion areas on both sides of the canal. (3) In areas with different levels of ESV, the influencing factors had different impact effects. The mean proximity index (MPI), i.e., land use integrity, had a significant enhancement effect at the low ESV region and a significant dampening effect at the high ESV region. As the quantile points increase, the positive effects of the annual mean temperature (ATE), annual mean precipitation (APR), and net primary productivity (NPP) on ecosystem services gradually increase, which increased the gap between high and low ESV areas, creating a “natural Matthew effect”, while the negative effects of economic density (GDP) and population density (POP) on ecosystem services gradually decreased.

The Impact of Cropland Use Changes on Terrestrial Ecosystem Services Value in Newly Added Cropland Hotspots in China during 2000–2020

The assessment of ecosystem services value is the basis for the realization of integrated management of these services. In recent decades, the hotspots of China’s newly added cropland have shifted to the Xinjiang oasis areas, where the ecological environment is relatively fragile. However, the impact of changes in cropland use on the terrestrial ecosystem services value (TESV) in Xinjiang, China, has not been studied in depth, and it is related to the sustainability of the dynamic balance between China’s cropland and the sustainable management of natural resources in Xinjiang. This study focuses on Xinjiang and employs the benefit transfer method and five phases (2000, 2005, 2010, 2015 and 2020) of high-resolution and finely classified remote sensing monitoring data of land use to evaluate the impact of changes in cropland use on the TESV from 2000 to 2020. The findings suggest the following: (1) The cropland area in Xinjiang grew from 6.5682 million ha in 2000 to 8.9874 million ha in 2020, demonstrating significant expansion, and it has gone through four stages: rapid expansion, steady expansion, rapid expansion and relative stability. (2) A sharp mutual conversion trend is observed between cropland and other types of land use in Xinjiang. Grassland and unused land are the main sources of new cropland, while lost cropland has been mainly converted back into grassland and construction land. (3) During 2000–2020, although the extensive expansion of cropland and conversion of cropland mainly at the expense of ecological land in Xinjiang have significantly enhanced the provision services of the terrestrial ecosystem (539.49 million USD), ecosystem regulation services (−1508.47 million USD), support services (−1084.47 million USD) and cultural services (−565.05 million USD) experienced losses. Consequently, an overall loss in the TESV has ensued. This study provides new insights that help re-examine the sustainability issue of the spatial transfer of cropland in China, and it also offers guidance for the realization of the sustainable management of natural resources in Xinjiang.

Ecological Environmental Effects and Their Driving Factors of Land Use/Cover Change: The Case Study of Baiyangdian Basin, China

Due to the combined effects of the natural environment, climate change and human activities, profound changes have occurred in terms of the eco-environmental effects of land use/cover change (LUCC) in the Baiyangdian basin. Therefore, based on land remote sensing monitoring data from 2000 to 2020, the Eco-environmental Quality Index (EQI) was introduced in this study to measure the eco-environmental effects of land use change in the Baiyangdian basin. Subsequently, the GeoDetector model was applied to detect the formation mechanism of the eco-environmental effects in the Baiyangdian basin from 2000 to 2020. The results of the study showed that cropland, woodland and grassland were the most widely distributed land use types in the Baiyangdian basin. The area of cropland declined the most and was mostly converted to construction land. The EQI increased slightly during the study period. The eco-environment of the mountainous areas in the western part of the basin and in Baiyangdian Lake was better than that of other areas. Land use intensity had a significantly stronger influence on the quality of the eco-environment than other factors. The interaction between the influencing factors was mainly a non-linear enhancement and a two-factor enhancement, with non-linear enhancement dominating.

Accounting for Carbon Sink and Its Dominant Influencing Factors in Chinese Ecological Space

Ecological space (ES), including forest ecological space (FES) and grassland ecological space (GES) in this study, is the land with natural attributes and the main functions of providing ecological services, which has a huge potential capacity for carbon sink (CS). The interannual fluctuation of the CS in ES is severe, which is affected by factors such as precipitation and temperature, but it is still controversial which is the dominant factor in affecting the fluctuation process of the CS in ES. To this end, the multi-source remote sensing monitoring data on the fine-grid scale were collected in this study, including the land use and land cover remote sensing monitoring data, the data products of moderate-resolution imaging spectroradiometer (including land surface water index, photosynthetically active radiation, enhanced vegetation index, gross primary productivity), and meteorological data (including precipitation and temperature). By coupling the vegetation photosynthesis model and soil respiration model, the CS in CES from 2010 to 2020 was calculated, and the interannual fluctuation trends and stability of CS in CES were analyzed. Furthermore, the correlation coefficient and partial correlation coefficient equation between the CS of CES with precipitation and temperature were constructed to explore the correlation between interannual fluctuation of CS in CES with meteorological factor, and to determine the dominant position of precipitation and temperature in affecting the fluctuation process of the CS in CES. The research results show that the annual average CS of per unit area in CES was 233.78 gC·m−2·a−1, and the cumulative CS was 11.83 PgC. The GES and FES contributed 6.33 PgC and 5.49 PgC of CS, respectively. From 2010 to 2020, the CS of CES showed an upward trend and was generally in a relatively stable state (the mean value of the coefficient of variation was 0.6248). However, the year with severe fluctuation of was found in this study (from 2013 to 2015), the reason is that the precipitation was too low in 2014, which indicated that climate change, especially the change of precipitation, played a important role in the fluctuation of CS in CES. The results of correlation analysis confirmed the above analysis. The change of CS in CES is highly positively correlated with the change of precipitation (the correlation coefficient is 0.085), and weakly positively correlation with temperature (the correlation coefficient was 0.026). The precipitation is the dominant influencing factor, which has a positive effect on CS in CES. Within a climate environment dominated by precipitation, precipitation and temperature jointly affect the CS in CES. It should be noted that in some regions with variable climate, precipitation and temperature had relatively little impact on CS in CES. Their fluctuations may depend more on the ecosystem’s own ecological services’ regulation ability and their response degree to changes in atmospheric CO2 concentration.

Remote Sensing Monitoring Data of Soybean Growth in Ecosystem

Remote Sensing Monitoring Data of Soybean Growth in Ecosystem

Spatial-temporal evolution of "Production-Living-Ecologica" function and layout optimization Strategy in China: a case study of Liaoning Province, China.

Based on the land remote sensing monitoring data from 2000 to 2020, this paper quantitatively analyzed the spatio-temporal evolution of "production-living-ecological" functions and the geographical dominance degree of Liaoning Province using a geospatial model, and put forward some policy suggestions. The results showed that the living function area increased by 2957 km2, the ecological function area increased by 2011 km2, and the production function area was reduced by 4968 km2. The spatial distribution of production function was higher in the middle part, lower in the east and west, and the functional index was between 0.01 and 0.21. The living function level is distributed from east to west, and the function index decreases gradually from plain to surrounding mountains. There was a significant correlation between the level of ecological function and topography, and the functional index ranged from 0.01 to 0.65. The advantageous areas of production function are located in the central plain of Liaoning and Dalian, the advantageous areas of living function are located in the central part of Liaoning, and the advantageous areas of ecological function are located in the eastern and western parts of Liaoning. Social and economic level, natural ecological environment, and regional development policy are the important factors that affect the layout of "production-production-production" function. It is suggested that the provincial government should build a comprehensive management system across administrative regions, design the ecological and environmental protection policy framework of "production-living-ecological" function, and improve the ecological protection coordination mechanism.

Spatiotemporal Dynamics and Driving Forces of Land Urbanization in the Yangtze River Delta Urban Agglomeration

Land urbanization is a comprehensive mapping of the relationship between urban production, life and ecology in urban space and a spatial carrier for promoting the modernization of cities. Based on the remote sensing monitoring data of the land use status of the Yangtze River Delta urban agglomeration collected in 2010 and 2020, the spatial differentiation characteristics and influencing factors of land urbanization in the area were analyzed comprehensively using hot spot analysis, kernel density estimation, the multi-scale geographically weighted regression (MGWR) model and other methods. The results indicated the following: (1) From 2010 to 2020, the average annual growth rate of land urbanization in the Yangtze River Delta urban agglomeration was 0.50%, and nearly 64.28% of the counties had an average annual growth rate that lagged behind the overall growth rate. It exhibited dynamic convergence characteristics. (2) The differentiation pattern of land urbanization in the Yangtze River Delta urban agglomeration was obvious from the southeast to the northwest. The hot spots of land urbanization were consistently concentrated in the southeastern coastal areas and showed a trend of spreading, while the cold spots were concentrated in the northwest of Anhui Province, showing a shrinking trend. (3) Compared with the GWR model and the OLS model, the MGWR model has a better fitting effect and is more suitable for studying the influencing factors of land urbanization. In addition, there were significant spatial differences in the scale and degree of influence of different influencing factors. Analyzing and revealing the spatiotemporal characteristics and driving mechanism of land urbanization in the Yangtze River Delta urban agglomeration has important theoretical value and practical significance for the scientific understanding of new-type urbanization and the implementation of regional integration and rural revitalization strategies.