Spatial pattern of land use change and its driving force in Jiangsu Province

The impact of climate change and human activities on the change in the net primary productivity of vegetation-taking Sichuan Province as an example

Vegetation is an essential component of terrestrial ecosystems, influenced by climate change and human activities. Quantifying the relative contributions of climate change and human activities to vegetation dynamics is crucial for addressing global climate change. Sichuan Province is one of the essential ecological functional areas in the upper reaches of the Yangtze River, and its vegetation change is of great significance to the environmental function and ecological security of the Yangtze River Basin and southwest China. In this paper, the modified Carnegie-Ames-Stanford Approach(CASA) model was used to estimate the monthly NPP (Net Primary Productivity) of vegetation in Sichuan Province from 2000 to 2018, and the univariate linear regression analysis was used to analyze the temporal and spatial variation of vegetation NPP in Sichuan Province from 2000 to 2018. In addition, taking vegetation NPP as an index, Pearson correlation analysis, partial correlation analysis, and second-order partial correlation analysis were carried out to quantitatively analyze the contribution of climate change and human activities to vegetation NPP. Finally, the Hurst index and nonparametric Man-Kendall significance test were used to predict the future change trend of vegetation NPP in Sichuan Province. The results show that (1) from 2000 to 2018, the NPP of vegetation in Sichuan Province has a significant increasing trend (Slope = 6.09gC·m-2·a-1), with a multi-year average of 438.72 gC·m-2·a-1, showing a trend of low in the east and high in the middle. The response of vegetation NPP to altitude is different at different elevations; (2) the contribution rates of climate change and human activities to vegetation NPP change are 4.12gC·m-2·a-1 and 1.97gC·m-2·a-1, respectively. In contrast, the impact of human activities on NPP is more significant than climate change. Human activities are the main factors affecting vegetation restoration and degradation in Sichuan Province. However, the positive contribution to NPP change is less than climate change; (3) the future vegetation NPP change trend in Sichuan Province is mainly rising, and the same direction change trend is much larger than the reverse change trend. The areas with an increasing trend in the future account for 89.187% of the total area. This research helps understand the impact of climate change and human activities on vegetation change in Sichuan Province. It offers scientific bases for vegetation restoration and ecosystem management in Sichuan and the surrounding areas.

Detecting the interaction between urban elements evolution with population dynamics model

Exploring the evolution of urban elements can improve understanding of the developmental process of city and drive such development into a better direction. However, the non-linearity and complexity of changes in urban elements have brought great challenges to understanding this process. In this paper, we propose a cross-diffusion partial differential equation based on ecological dynamics to simulate the evolutionary process of urban elements from the microscopic viewpoint. The interaction between urban elements is simulated by constructing a non-linear and spatiotemporal change equation, and the main influence between elements is evaluated by the key parameters in the discussed equation. Our model is first experimented to time-series data on population density and housing prices to analyzes the interaction of these two elements in the evolution process. We then extend the model to label data, land cover data, to obtain a quantitative expression of the interaction between different land types in the process of urban land cover change.

Impacts of Land-Use Change on Ecosystem Services Value in the South-to-North Water Diversion Project, China

The South-to-North Water Diversion Project (SNWD) in China is a trans-basin water transfer project for water resource optimization that affects ecosystem services functions along its main transfer line. Exploring the effects of land-use change on ecosystem services in the headwater and receiving areas along the SNWD is conducive to improving the protection of the surrounding ecological environment. However, previous research lacks a comparative analysis of ecosystem services values (ESVs) in these areas. In this study, the land-use dynamic degree index, land-use transfer matrix, and spatial analysis method were used to comparatively analyze the impact of land-use changes on ESVs in the headwater and receiving areas of the SNWD. The results show that cultivated land was the main land use type in the receiving areas and HAER. From 2000 to 2020, CLUDD in the headwater areas was faster than that in the receiving areas. Spatially, in general, the land-use change areas of the receiving areas were larger. During the study period, cultivated land in the headwater areas of the middle route mainly transferred to water areas and forestry areas, while built-up areas mainly occupied cultivated land in the headwater areas of the east route, receiving areas of the middle route, and receiving areas of the east route. From 2000 to 2020, the ESV increased only in the headwater areas of the middle route, while the ESV in the other three sections decreased. The variation extent of ESV in the receiving areas was greater than that in the headwater areas. The results of this study have important policy significance for land use and ecological protection in the headwater and receiving areas of the SNWD in the future.

Research on land-use evolution and ecosystem services value response in mountainous counties based on the SD-PLUS model

Rapid urbanization has caused changes in climate and environment and threatened the ecosystem with multiple risks. The ecosystem services capacity has shown a downward trend accordingly. It is significant to explore the spatio‐temporal evolution of land use and ecosystem services value (ESV) in mountainous counties at small scales, as it coordinates economic growth and ecological protection, and promotes sustainable and high‐quality development. Based on the SD‐PLUS model, the study simulated three scenarios of land‐use change in Qianshan city from 2019 to 2035: high‐growth rate, medium‐growth rate, and low‐growth rate, and studied the impacts of land‐use change on the ESV. Results showed that: (1) Under the three scenarios, the construction land in the study area increased significantly, the forest and water have a decreasing trend, and the scale of gardens partly increased. (2) In the urban built‐up areas, a significant amount of construction land is centrally expanded, whereas, in mountainous regions, construction land exhibits sporadic point expansion. And among the various factors that influence land‐use change, the impact of roads at all levels is the most significant, followed by elevation. (3) The overall ESV shows a downward trend, with the low‐growth rate scenario dropping the least (4.91%). The value distribution changes little at the space scale, and different regions demonstrate different degrees of change. From the perspective of value type, the service values of water conservation and waste treatment are significantly reduced, while that of food production is relatively stable; from the perspective of various lands with their ESV, cultivated land and forest remain stable. The study results can provide technical ideas for the coordinated economic development and ecological protection of mountainous cities and boost the implementation of green development.

Spatiotemporal Heterogeneity of Urban Land Expansion and Urban Population Growth under New Urbanization: A Case Study of Chongqing

Land urbanization (LU) and population urbanization (PU) maintain the nature of spatiotemporal heterogeneity in China. As a municipality directly administered by the central government in the mode of “large cities and large rural areas”, Chongqing’s urbanization process is the epitome of China’s urbanization process. This paper examines the spatiotemporal variability of LU and PU in Chongqing on the basis of nighttime light data, the elasticity coefficient of the coupling relationship, and GWR. The results show that (1) the urban land and urban population in Chongqing grew notably from 2008 to 2018, with average annual growth rates of 9.4% and 2.3%, respectively. (2) The coupling coordination coefficient of LU and PU in Chongqing was 0.24, and the total number of districts and counties with uncoordinated development increased, but the overall uncoordinated situation gradually improved over the period. (3) The influence of PU on LU in each district and county increased year by year, and it showed a decreasing trend from southwest to northeast in Chongqing, which indicates that LU was increasingly adapted to the construction needs of PU. The gap between LU and PU widened due to the household registration system, land fiscal policies and other policies. After the reform of the household registration system and the adjustment of new pilot policies targeting the construction of new-type urbanization, the coupling relationship between LU and PU was gradually improving to the coordinated mode. The findings indicate that Chinese urban areas should adhere to the principle of new-type urbanization construction and carry out scientific land planning strategies, strictly controlling land expansion to promote the reasonable development of population growth.

The Relationship between Climate Change, Variability, and Food Security: Understanding the Impacts and Building Resilient Food Systems in West Pokot County, Kenya

This study integrated local and scientific knowledge to assess the impacts of climate change and variability on food security in West Pokot County, Kenya from 1980–2012. It characterized rainfall and temperature from 1980–2011 and the phenology of agricultural vegetation, assessed land use and land cover (LULC) changes, and surveyed local knowledge and perceptions of the relationships between climate change and variability, land use decisions, and food (in)security. The 124 respondents were aware of long-term changes in their environment, with 68% strongly believing that climate has become more variable. The majority of the respondents (88%) reported declining rainfall and rising temperatures, with respondents in the lowland areas reporting shortened growing seasons that affected food production. Meteorological data for 1980–2011 confirmed high inter-annual rainfall variability around the mean value of 973.4 mm/yr but with no notable trend. Temperature data showed an increasing trend between 1980 and 2012 with lowlands and highlands showing changes of +1.25 °C and +1.29 °C, respectively. Land use and land cover changes between 1984 and 2010 showed cropland area increased by +4176% (+33,138 ha), while grassland and forest areas declined by –49% (–96,988 ha) and –38% (–65,010 ha), respectively. These area changes illustrate human-mediated responses to the rainfall variability, such as increased stocking after good rainfall years and crop area expansion. The mean Normalized Difference Vegetation Index (NDVI) values ranged from 0.36–0.54 within a year, peaking in May and September. For weather-related planning, respondents relied on radio (64%) and traditional forecasters (26%) as predominant information sources. Supporting continuous climate change monitoring, intensified early warning systems, and disseminating relevant information to farmers could help farmers adopt appropriate adaptation strategies.

Integrated Land Use Change Related Carbon Source/Sink Examination in Jiangsu Province

Carbon emission (CE) threatens global climate change severely, leading to the continuous strengthening of the greenhouse effect. Land use changes can greatly affect the ecosystem carbon budget and anthropogenic CE. Based on the land use grids, net ecosystem productivity (NEP), energy consumption-related CE, this study employed various methods to investigate the impact of land use change on carbon balance. The results showed 10.03% of total land use area has land use type changed between 2000 and 2015. Built-up land occupied cropland was the main land use transfer type. The period with the most intense land use changes was 2005–2010, which was constant with the process of China’s urbanization. NEP presented an overall increasing trend excluding built-up land and water areas. Temporally, CE showed an increasing trend in 2000–2015, especially in the industry sector. Spatially, areas with the high energy-related CE were mainly distributed in the south, which has a relatively high economic level. The land use intensity values of cities in Jiangsu all presented an overall increasing trend, which is related to the economic development and local endowment. Cities with higher land use intensity were usually accompanied with high CE, suppressing NEP growth. From 2000 to 2015, soil carbon storage reduced by 0.15 × 108 t, vegetation carbon storage reduced by 0.04 × 108 t, and CE reached 17.42 × 108 t. Total CE caused by land use change reached 15.46 × 108 t. The findings can make references for the low-carbon development from ecological land protection, strengthen land management, and optimize urban planning.

Analyzing the spatiotemporal pattern and driving factors of wetland vegetation changes using 2000-2019 time-series Landsat data

Probing the long-term spatiotemporal patterns of wetland vegetation changes and their response to climate change and human activities is critical to make informed decisions regarding ecosystem protection. Here, the spatiotemporal patterns and factors that drive vegetation changes in the Dongting Lake wetland from 2000 to 2019 were analyzed using monthly normalized difference vegetation index (NDVI) data at a 30 m spatial resolution. First, abrupt vegetation changes were identified using the breaks for additive season and trend approach. Moreover, the relative impacts of climatic factors on monthly vegetation changes were quantified using a partial correlation-based approach, and the effects of three specific climatic factors (temperature, precipitation, and solar radiation) and human factors on vegetation recovery and degradation were determined. Our study found that: 1) the study area is becoming greener, with NDVI increases of 0.006 per year; however, there was a pronounced interannual variation in the vegetation types; 2) more than 50% of the vegetation pixels exhibited at least two breakpoints, with ~5% of the vegetation pixels exhibiting eight breakpoints; 3) in the past 20 years, human activities have favored wetland vegetation recovery (58.85%), whereas climate change threatens wetland vegetation (59.19%). Regarding climate factors, the influence of solar radiation on vegetation was found to be stronger than that of temperature and precipitation.

Assessing Sponge Cities Performance at City Scale Using Remotely Sensed LULC Changes: Case Study Nanjing

As a result of high-density urbanization and climate change, both the frequency and intensity of extreme urban rainfall are increasing. Drainage systems are not designed to cope with this increase, and as a result, floods are becoming more common in cities, particularly in the rapidly growing cities of China. To better cope with more frequent and severe urban flooding and to improve the water quality of stormwater runoff, the Chinese government launched the national Sponge City Construction (SCC) program in 2014. The current SCC design standards and guidelines are based on static values (e.g., return periods, rainfall intensities, and volume capture ratio (VCR)). They do not fully acknowledge the large differences in climate conditions across the country and assume that the hydraulic conditions will not change over time. This stationary approach stems from the traditional engineering approach designed for grey infrastructure (following a “one size fits all” approach). The purpose of this study was to develop a methodology to assess the VCR baseline (before construction in the pre-development stage) and changes in VCR (difference between the VCR of the pre- and post-development stage). The VCR of the post-development stage is one of the required indicators of the Assessment Standard for Sponge Cities Effects to evaluate SCC projects. In this study, the VCR was derived from remote-sensing-based land use land cover (LULC) change analysis, applying an unsupervised classification algorithm on different Landsat images from 1985 to 2015. A visualization method (based upon Sankey chart, which depicts the flows and their proportions of components) and a novel and practical partitioning method for built-up regions were developed to visualize and quantify the states and change flows of LULC. On the basis of these findings, we proposed a new indicator, referred to as VCRa-L, in order to assess the changes in urban hydrology after SCC construction. This study employed the city of Nanjing as a case study and analyzed detailed information on how LULC changes over time of built-up areas. The surface area of the urban and built-up areas of Nanjing quadrupled from 11% in 1985 to 44% in 2015. In the same period, neither the entire city nor its subregions reached the VCR target of 80%. The proposed new methodology aims to support national, regional, and city governments to identify and prioritize where to invest and implement SCC measures more effectively in cities across China.

Spatiotemporal scale and integrative methods matter for quantifying the driving forces of land cover change

Land cover change (LCC) is a major part of environmental change. Exploring the spatiotemporal differences in LCC and the driving factors is the basis for comprehensive research on landscape planning, and it is of great significance for future effective and sustainable landscape management. In this respect, cross-scale research with integrated methods is worthy of more attention, although some studies have discussed the driving forces of LCCs at either regional or local scale. We combined a structural equation model and a mixed-effects model for quantifying the driving forces of LCCs across different scales in the Loess Plateau (China), which is a typical region that has experienced significant LCCs over recent decades. The impacts of biophysical and socioeconomic factors on different change trajectories (agricultural intensification, urbanization and ecological restoration) were found to be inconsistent at different temporal and spatial scales. We found that topography had a negative effect on agricultural intensification during 1990-2010 and on urbanization during 1990-2000, but it had a positive effect on ecological restoration during 2000-2015 at the regional scale. Moreover, although there was no significant impact from economic development on any type of LCCs at the regional scale, its important influence could be seen in some of the township categories. Therefore, the path and scale dependence of driving forces is an important consideration in landscape planning and management to accommodate local conditions and fine-tuned analysis as decision-making supports.

Spatial-temporal dynamics and driving factor analysis of urban ecological land in Zhuhai city, China

Ecological land is a type of land that has considerable ecological value. Understanding the evolution of urban ecological land in Zhuhai, China, holds great significance for revealing the evolution of ecological land in the Dawan District of southern China. We explored the temporal and spatial variation in urban ecological land in Zhuhai using the transformation matrix, equivalent ecological land, landscape index and ecological land center of gravity migration methods. Multivariate logistic regression was used to analyze the mechanism of ecological land change, and a transition probability map of the ecological land in the study area was drawn. The results showed the following. (1) From 1991 to 2018, the area of ecological land in Zhuhai city continuously decreased, with a reduction in area of 274.8 km2, or 32.3%. Sharp changes mainly occurred from 1991 to 2000. (2) The ecological land in the study area has gradually become fragmented, and the degree of landscape heterogeneity has increased. Affected by the expansion of the outer edge of the city to the southwest and the construction of ecological land within the city, the center of gravity of the ecological land has shifted to the northeast by 1346 m. (3) The elevation, slope, distance from built-up land and growth rate of built-up land are important factors influencing the transformation of ecological land. In the future, rivers and shallow coastal waters, tidal flats, and grasslands in the study area have the highest probability of transformation. The Jinwan District and Xiangzhou District will face severe ecological land protection pressure. The method of spatial-temporal analysis of urban ecological land developed in this paper can be applied in similar studies on other cities, and the results obtained for Zhuhai, China, have reference value for future urban planning and ecological protection work.

Exploration of Urban Interaction Features Based on the Cyber Information Flow of Migrant Concern: A Case Study of China's Main Urban Agglomerations

In the context of “space of flow”, urban interaction has become the key force impacting urban landscape evolution and urban sustainable development. Current research on urban interaction analysis is mainly conducted based on the interaction of geographical elements, the virtual flow of information in cyberspace has not been given sufficient attention, particularly the information flows with explicit geographical meaning. Considering the dramatic population migration and the explosive growth of cyberspace in China’s main urban agglomerations, we constructed the information flow of migrant attention (IFMA) index to quantify the urban information interaction derived from public migrant concern in cyberspace. Under the framework coupling spatial pattern analysis and spatial network analysis, exploration spatial data analysis (ESDA) and complex network analysis (CNA) were adopted to identify the urban interaction features depicted by IFMA index in the three main urban agglomerations in China. The results demonstrated that, in the study area: (1) The IFMA index presented a reasonable performance in depicting geographical features of cities; (2) the inconformity between urban role in the network and development positioning confirmed by national planning existed; (3) in the context of New-type urbanization of China, urban interaction feature can be a beneficial reference for urban spatial reconstruction and urban life improvement. Using the cyber information flow with geographical meaning to analyze the urban interaction characteristics can extend the research angle of urban relationship exploration, and provide some suggestion for the adjustment of urban landscape planning.

Driving Factors and Future Prediction of Land Use and Cover Change Based on Satellite Remote Sensing Data by the LCM Model: A Case Study from Gansu Province, China

Land use and cover change (LUCC) is an important issue affecting the global environment, climate change, and sustainable development. Detecting and predicting LUCC, a dynamic process, and its driving factors will help in formulating effective land use and planning policy suitable for local conditions, thus supporting local socioeconomic development and global environmental protection. In this study, taking Gansu Province as a case study example, we explored the LUCC pattern and its driving mechanism from 1980 to 2018, and predicted land use and cover in 2030 using the integrated LCM (Logistic-Cellular Automata-Markov chain) model and data from satellite remote sensing. The results suggest that the LUCC pattern was more reasonable in the second stage (2005 to 2018) compared with that in the first stage (1980 to 2005). This was because a large area of green lands was protected by ecological engineering in the second stage. From 1980 to 2018, in general, natural factors were the main force influencing changes in land use and cover in Gansu, while the effects of socioeconomic factors were not significant because of the slow development of economy. Landscape indices analysis indicated that predicted land use and cover in 2030 under the ecological protection scenario would be more favorable than under the historical trend scenario. Besides, results from the present study suggested that LUCC in arid and semiarid area could be well detected by the LCM model. This study would hopefully provide theoretical instructions for future land use planning and management, as well as a new methodology reference for LUCC analysis in arid and semiarid regions.

Monitoring spatio-temporal dynamics of urban and peri-urban land transitions using ensemble of remote sensing spectral indices-a case study of Chennai Metropolitan Area, India

Land-use/land-cover change is the most vulnerable factor in any developing urban environment. Increased infrastructure and population density tend to alter the land features which in turn will have an impact on climate change and will increase the impervious layer. Study of trends in land-use/land-cover change is required for analyzing the possible ways of managing the natural system. In this study, the spatial and temporal changes of the urban and peri-urban landscape of the Chennai Metropolitan Area (CMA), Tamil Nadu, India, were analyzed using satellite images. Imageries from Landsat 5 (TM) and Landsat 8 (OLI/TIRS) sensors were taken for the years 1988, 1997, 2006, and 2017. Ensembles of remote sensing spectral indices (NDVI, MNDWI, NDBI, and NDBaI) were calculated for the land-use/land-cover classification. The confusion matrix was used for assessing the accuracy for the year 2017. The overall accuracy of the LULC classification obtained was 91.76% with the kappa coefficient of 0.84. The results show that during the period of February 1988 to February 2017, the agriculture/fallow land, barren/semi-barren, vegetation, and water bodies/wetlands have decreased by 53.62%, 1.45%, 58.99%, and 30.59%, respectively. This decrease has contributed to an increase of 173.83% in built-up area. About 26,881 ha of agriculture/fallow land, 10,482 ha of vegetation land, and 2454 ha of water bodies/wetlands were converted to built-up and other land-use over the period. This essentially meant that CMA has changed from predominantly an agricultural area (42.21%) in 1988 to built-up area (48.72%) in 2017.

Combined Impact of Socioeconomic Forces and Policy Implications: Spatial-Temporal Dynamics of the Ecosystem Services Value in Yangtze River Delta, China

Water can carry or overturn a boat. Natural resources form the foundation of human survival and development. However, land use change caused by human urban civilization has damaged the natural environment and in turn threatened the continuation of human civilization. Accordingly, it is crucial to analyze the impacts of human activities on land use change and consequent dynamics of ecosystem service value (ESV). For the sustainable development of human beings, an investigation should be conducted to explore what type of land use behavior will be considerably beneficial to improve our relationship with the natural environment. This study analyzes the spatial–temporal dynamics of ESV of 148 counties in the Yangtze River Delta in China over three five-year periods (2000–2015) and examines the influence of socioeconomic forces and policy implications. Exploratory spatial data analysis and spatial regression were applied to facilitate the analysis. Results show that the averages of the ESV change ratios of the 148 counties in each of the aforementioned periods are −0.667%, −2.690%, and −4.668%, respectively. The number of counties that showed an ESV loss trend in the three periods are 72 (48.6%), 125 (84.4%), and 139 (93.9%), respectively. In terms of spatial pattern, ESV change demonstrates the spatial distribution characteristic of “high loss spreading from the northeast to the middle and west” with a tendency to strengthen spatial agglomeration. Results of the spatial regression analysis determine the overwhelming importance of population growth and economic advancement. The results also indicate that the development mode characterized by industrial structure, capital input, and technology upgrades can exert considerable influence on socioeconomic development, thereby affecting the change of ESV. Moreover, the constraints of policy substantially affect the changes of ESV from 2010 to 2015. Policy makers should consider the relationship between land use patterns and the ESV variation in different development stages to formulate appropriate measures, thereby reducing or preventing the loss of ecological service value and promoting sustainable development.

Intersection of Physical and Anthropogenic Effects on Land-Use/Land-Cover Changes in Coastal China of Jiangsu Province

China is experiencing substantial land-use and land-cover change (LUCC), especially in coastal regions, and these changes have caused many ecological problems. This study selected a typical region of Jiangsu Province and completed a comprehensive and detailed spatial-temporal analysis regarding LUCC and the driving forces. The results show that the rate of land-use change has been accelerating, with land-use experiencing the most substantial changes from 2005 to 2010 for most land-use types and the period from 2010 to 2015 showing a reversed changing trend. Built-up land that occupies cropland was the main characteristic of land-use type change. Southern Jiangsu and the coastline region presented more obvious land-use changes. Social-economic development was the main factor driving increased built-up land expansion and cropland reduction. In addition, land-use policy can significantly affect land-use type changes. For land-cover changes, the normalized difference vegetation index (NDVI) for the land area without land-use type changes increased by 0.005 per year overall. Areas with increasing trends accounted for 82.43% of the total area. Both precipitation and temperature displayed more areas that were positively correlated with NDVI, especially for temperature. Temperature correlated more strongly with NDVI change than precipitation for most vegetation types. Our study can be used as a reference for land-use managers to ensure sustainable and ecological land-use and coastal management.

A Land Use/Land Cover Based Green Development Study for Different Functional Regions in the Jiangsu Province, China

Land use/land cover (LULC) change can strongly affect carbon storage in terrestrial ecosystems. The rapid development of China's economy has formed different functional regions. These functional regions profoundly affect land use patterns. Thus, assessing the carbon storage induced by LULC changes is significant for green development. Selecting the typical region of the Jiangsu Province as the study area, this study first examines the research associated with the regional functional characteristics and various high accuracy data and methods have been used to greatly improve the research accuracy. The results showed that from 1995 to 2015, approximately 10.26% of the entire land area had LULC type changes. Additionally, decreases in the built-up land expansion and ecological land were the main LULC change characteristics, which are mainly affected by socioeconomic development. The total carbon storage of the Jiangsu Province decreased by 714.03 × 10⁴ t and the four regions all presented decreasing carbon storage levels. The economically developed regions presented a more obvious loss of carbon. The region with small LULC changes had a lower carbon loss. The land transfer of cultivated land to built-up land is the main transfer type causing the carbon storage loss. This study investigates the human-environmental interactions from the new perspective of functional zoning and, thus, it enriches the comparative analysis of carbon storage in functional regions and provides references for the green development of a developing country's developed areas.

Spatio-Temporal Patterns of Land Use and Cover Change from 1990 to 2010: A Case Study of Jiangsu Province, China

Land use and cover change (LUCC) is one of the most significant parts of global environmental changes, which reflects the interaction between human society and natural resources. In China, the urbanization process is experiencing a rapid sprawl since the reform and open program in 1978, and there has been a serious change in situation in the human–land relationship. In this paper, taking Jiangsu province located in the eastern coastal developed region as an example, the historic evolution process of the land use situation from 1990 to 2010 was explored. Landsat images from three periods were analyzed, using the land use transition matrix model, the land use dynamic degree model, and the land use degree model to evaluate the LUCC of Jiangsu during two research periods from 1990 to 2000 and from 2000 to 2010. Additionally, logistic regression models and some quantitative analysis were applied to identify the major potential driving factors behind the LUCC during the research period based on different dimensions. The results showed the following: (1) the most obvious change was the continuous increase of built-up area and the decrease of arable land, which reflected the deterioration of the ecological environment and the accelerate of the urbanization trend. (2) The land use change dynamic degree from 2000 to 2010 was much greater than that from 1990 to 2000. (3) Socio-economic elements and human activities were the major driving forces of LUCC in Jiangsu province. Amongst these forces, the driving factors of the population change, GDP, per capita household income, and per capita housing area have an obvious effect on the arable land loss and the built-up area expansion.

Spatial Distribution of Global Cultivated Land and Its Variation between 2000 and 2010, from Both Agro-Ecological and Geopolitical Perspectives

Food security requires a thorough understanding of the spatial characteristics of cultivated land changes on a global scale. In particular, the spatial heterogeneity of global cultivated land changes needs to be evaluated with high spatial resolution data. This study aims to analyse the spatial distribution of global cultivated land and the characteristics of its variation, by using GlobeLand30 data for 2000 and 2010 with a 30-m spatial resolution. The cultivated land percentage and rate of cultivated land use change are calculated based on 18 agro-ecological zones (AEZs), 32 geopolitical and socioeconomic regions, and 283 world regions. The results show that (1) more cultivated land is located in regions under a temperate climate and moderate moisture conditions; (2) the percentage of cultivated land is related to the gross domestic product (GDP) and population, while increases and decreases in cultivated land are related to the rural population, policy encouragement, urbanization, and economic development; and (3) the percentage of cultivated land and rate of land use change within an AEZ vary greatly due to the different socioeconomic conditions, and the values within a geopolitical area also vary, due to different natural conditions.

Retrospective Analysis of Land Use Land Cover Dynamics Using GIS and Remote sensing in Central Highlands of Ethiopia

Assessing and quantifying the current forest resources status underpins sustainable forest resources planning and management. To this end, this study was conducted to analyze the dynamics of land use cover change (LUCC) and explore their drivers at the central highlands of Dry Afromontane Chilimo-Gaji forest for the study period (1973-2015) under consideration. The result of the study indicated that landscape trends have occurred in Chilimo-Gaji forest over the last 43 years and five classes of LUCC namely shrub land, rural settlement, bare land and road, forest land and agricultural land were identified. The most commonly reported drivers of deforestation in the study area were expansion of agricultural land, rural settlements, population growth, insecurity of the tenure and rights over the land, timber production and fuel wood collection. Surprisingly, the increasing demand for agricultural land and human settlement for increasing human population underpinned by expansion of agricultural activities led to the clearing of forest land in the study area. The study reveals that the forest land cover type has lost 922.14 hectares (26.96 %) which were changed into other land cover types such as agriculture and settlement for the study period under consideration with an annually rate of 21.45 ha. However, deforestation rates showed declining trend between the time periods 2008-2015 as a result of introduction of Participatory Forest Management (PFM) schemes (1996) which involve the local community in management and sharing of the benefit obtained from the management. In order to promote sustainable forest resources management in the study area in the years to come, integrated land use planning and management and addressing key drivers of deforestation were recommended.

Analysis of the Dynamic Urban Expansion Based on Multi-Sourced Data from 1998 to 2013: A Case Study of Jiangsu Province

Recently, with the fast speed of urban expansion, research concerning the regulation of urban built-up area expansion is a significant topic, especially in Eastern China with its high urbanization level. The Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) nighttime light data has a high association with the urban-rural distribution, which provides a new method to study urban expansion effectively and with relatively high accuracy. Between 1998 and 2013, China experienced a rapid economic development period, making it crucial to learn the patterns and driving forces to better manage urban master planning and sustainable development. The urban built-up area for the research years are mapped, and the annual urban expansion speed, urbanization intensity index, and built-up area gravity center are analyzed in this paper. The results will show that the amount of the urban built-up area grows continuously from 1998 to 2008, with the development focus in southern Jiangsu, while from 2008 to 2013, the development center moves to northern Jiangsu. The main driving forces behind this urban built-up area expansion are population growth and economic development.

Exploring the Factors Driving Changes in Farmland within the Tumen/Tuman River Basin

Understanding farmland changes and their mechanisms is important for food security and sustainable development. This study assesses the farmland changes and their drivers within the Tumen River of China and the Tuman River within the Democratic People’s Republic of Korea (DPR Korea) from 1991 to 2016 (1991–2000, 2000–2010, and 2010–2016). Farmland surfaces in Tumen/Tuman River Basin (TRB) for each of the years were mapped from satellite imagery using an object-based image segmentation and a support vector machine (SVM) approach. A logistic regression was applied to discern the mechanisms underlying farmland changes. Results indicate that cultivated surfaces changes within the two regions were characterized by large differences during the three time periods. The decreases of cultivated surface of −15.55 km2 (i.e., 0.55% of total cultivated surface area in 2000) and −23.61 km2 (i.e., 0.83% of total cultivated surface area in 2016) occurred in China between 1991 and 2000 and between 2010 and 2016, respectively; while an increase of 30.98 km2 (i.e., 1.09% of total cultivated surface area in 2010) was seen between 2000 and 2010. Cultivated surfaces increased within DPR Korea side over the three time periods; a marked increase, in particular, was seen between 1991 and 2000 by 443.93 km2 (i.e., 23.43% of total cultivated surface area in 2000), while farmland increased by 140.87 km2 (i.e., 6.92% of total cultivated surface area in 2010) and 180.86 km2 (i.e., 1.78% of total cultivated surface area in 2016), respectively, between 2000 and 2010 and between 2010 and 2016. We also found that expansions and contractions in farmland within both regions of the TRB were mainly influenced by topographic, soil, climatic, and distance factors, which had different importance degrees. Among these significant forces, the temperatures in the two regions were paramount positive factors on farmland changes during 1991–2016 and slope in China and precipitation in DPR Korea were the paramount negative factors affecting farmland changes, respectively. Additionally, except for between 2000 and 2010 in DPR Korea TRB region, most of the factors significantly influencing the farmland changes revealed the same positive or negative effects in different periods, because of mountainous topography. This study allows enhancing understanding of the mechanisms underlying farmland changes in the TRB.

Impacts of urbanization on regional nonpoint source pollution: case study for Beijing, China

Due to limits on available data, the effects of urban sprawl on regional nonpoint source pollution (NPS) have not been investigated over long time periods. In this paper, the characteristics of urban sprawl from 1999 to 2014 in Beijing were explored by analyzing historical land-use data. The Event Mean Concentration data have been collected from all available references, which were used to estimate the variation in urban NPSs. Moreover, the impacts of variation in urban sprawl on regional NPSs were qualified. The results indicated that the urbanization process showed different influences on pollutants, while COD and TN were identified as key NPS pollutants. Residential areas contributed more NPS pollutants than did roads, which played a tremendous role in the control of urban NPS. The results also suggested in part that the impact of urban sprawl on the variation of COD decreased while TN increased in Beijing during the study period. These results would provide insight into the impacts of urban sprawl on NPS variation over a long period, as well as the reference for reasonable urban planning directives.

A Preliminary Study of the Carbon Emissions Reduction Effects of Land Use Control

Land use change not only directly influences carbon storage in terrestrial ecosystems but can also cause energy-related carbon emissions. This study examined spatiotemporal land use change across Jiangsu Province, China; calculated vegetation carbon storage loss caused by land use change and energy-related carbon emissions; analysed the relationship among land use change, carbon emissions and social-economic development; and optimized land use structure to maximize carbon storage. Our study found that 13.61% of the province’s land area underwent a change in type of land use between 1995 and 2010, mainly presented as built-up land expansion and cropland shrinkage, especially in southern Jiangsu. Land use change caused a 353.99 × 10⁴ t loss of vegetation carbon storage loss. Energy-related carbon emissions increased 2.5 times from 1995 to 2013; the energy consumption structure has been improved to some extent while still relying on coal. The selected social-economic driving forces have strong relationships with carbon emissions and land use changes, while there are also other determinants driving land use change, such as land use policy. The optimized land use structure will slow the rate of decline in vegetation carbon storage compared with the period between 1995 and 2010 and will also reduce energy-related carbon emissions by 12%.

Temporal and Spatial Simulation of Atmospheric Pollutant PM2.5 Changes and Risk Assessment of Population Exposure to Pollution Using Optimization Algorithms of the Back Propagation-Artificial Neural Network Model and GIS

PM2.5 pollution has become of increasing public concern because of its relative importance and sensitivity to population health risks. Accurate predictions of PM2.5 pollution and population exposure risks are crucial to developing effective air pollution control strategies. We simulated and predicted the temporal and spatial changes of PM2.5 concentration and population exposure risks, by coupling optimization algorithms of the Back Propagation-Artificial Neural Network (BP-ANN) model and a geographical information system (GIS) in Xi'an, China, for 2013, 2020, and 2025. Results indicated that PM2.5 concentration was positively correlated with GDP, SO₂, and NO₂, while it was negatively correlated with population density, average temperature, precipitation, and wind speed. Principal component analysis of the PM2.5 concentration and its influencing factors' variables extracted four components that accounted for 86.39% of the total variance. Correlation coefficients of the Levenberg-Marquardt (trainlm) and elastic (trainrp) algorithms were more than 0.8, the index of agreement (IA) ranged from 0.541 to 0.863 and from 0.502 to 0.803 by trainrp and trainlm algorithms, respectively; mean bias error (MBE) and Root Mean Square Error (RMSE) indicated that the predicted values were very close to the observed values, and the accuracy of trainlm algorithm was better than the trainrp. Compared to 2013, temporal and spatial variation of PM2.5 concentration and risk of population exposure to pollution decreased in 2020 and 2025. The high-risk areas of population exposure to PM2.5 were mainly distributed in the northern region, where there is downtown traffic, abundant commercial activity, and more exhaust emissions. A moderate risk zone was located in the southern region associated with some industrial pollution sources, and there were mainly low-risk areas in the western and eastern regions, which are predominantly residential and educational areas.