Mechanism Of Land Use Change Research Articles

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 and Forecast of Land Use Based on Patch-generating Land Usage Simulation (PLUS) Model: A Case of Shaanxi Province in China

China has witnessed a substantial number of land-use type shifts and broken land-use distribution patterns as a result of massive irrational exploitation, which has led to problems like a significant loss of environmental habitability and declining ecosystem functioning. Investigating the origins and mechanisms of land-use change is essential. The results show that earlier land-use models, which also lacked simulation studies and projections of land-use changes in Shaanxi Province over a 20-year timeframe, find it difficult to integrate quantitative and spatial pattern forecasts. This paper uses the patch-generating land usage simulation (PLUS) model to assess Shaanxi Province's land use patterns between 2000 and 2020 and predict land usage for the year 2025.Farmland, woodlands, and grassland are the three main land types that make up most of the Shaanxi Province's total area. Forests make up most of the land that will be transferred between 2000 and 2020, while agriculture makes up most of the land that will be transferred. Most of the elements influencing the spread of all land use types were rainfall and Normalized Difference Vegetation Index (NDVI). The central and southern regions of Shaanxi province will primarily experience changes in land use by 2025.This research offering a resource for Shaanxi Province's science of land use structure and efficient land resource allocation.

Spatial heterogeneity characteristics and driving mechanism of land use change in Henan Province, China

We conducted a scientific quantitative analysis of the spatiotemporal evolution and driving factors of land use in Henan Province using a spatial zoning approach. The province was divided into five distinctive regions. Employing methods, such as information mapping, we analyzed land use data for 1990, 2000, 2010, and 2020, investigating spatiotemporal evolution and differences. Additionally, we employed a geographic detector model to explore the dominant factors behind land use changes in 2010 and 2020. Primary land classes in Henan Province included cultivated land, forests, and construction, with cultivated land transitioning mainly to forests and construction. However, regional analyses revealed diverse outcomes. In the Yudong area, cultivated land dominated with an 80% area proportion, shifting mostly to construction. In the Yubei area, grassland transformed into cultivated land and forests, with escalating grassland loss. The Yuxi area exhibited a 40% forest area proportion, with frequent mutual conversions between forests, cultivated land, and grassland. Spatiotemporal evolution indicated active changes in cultivated land. The geographic detector revealed a shift in influential factors from natural to economic drivers for cultivated land changes in Henan Province between 2010 and 2020. By uncovering land use disparities across regions, we contribute suggestions for sustainable development decisions regarding land use in Henan.

Responses of Soil C, N, and P Stoichiometrical Characteristics, Enzyme Activities and Microbes to Land Use Changes in Southwest China Karst

The present study aim is to elucidate the effect and influencing mechanism of land use change on soil C, N, and P stoichiometric characteristics, soil enzyme activity and the microbial community in the karst ecosystem of southwest China. The three typical successive evolution land use types of original forest land, slope farmland and shrub-grassland were selected as the study objects in the present study. Additionally, the change in the laws and relationships of soil, the C, N, and P stoichiometric characteristics, the five soil enzyme activities of urease, sucrose, alkaline phosphatase, amylase and protease, and soil microbial community during the land use evolution process were studied. Results showed that (1) during the evolution process of the three land use types, soil C, N, and P stoichiometric characteristics, enzyme activities and microbial PLFAs (phospholipid fatty acids) varied significantly or extremely significantly; (2) in the three land use types studied, there were significant or extremely significant correlations between soil C, N, and P stoichiometric characteristics, enzyme activities and microbial PLFAs; (3) the ecological project of returning farmland to woodland had remarkable ecological effects on increasing soil C and N sink, repairing soil microbial community and improving soil quality; (4) artificial afforestation should be used as the most important and preferential measure for karst vegetation restoration and reconstruction. The present results not only provided scientific bases for land sustainable utilization, vegetation restoration and reconstruction, but also had important value in reducing the release and increasing the sequestration of soil C and N in karst ecosystems of Southwest China.

Spatial and Temporal Evolution and Driving Mechanisms of Water Conservation Amount of Major Ecosystems in Typical Watersheds in Subtropical China

The water conservation function of ecosystems is a research hot spot in the field of water resources, and it is also an important ecological service function of terrestrial ecosystems and a key point in eco-hydrology research. With the increasing frequency of human activities and climate change, how to reveal the response of ecosystem water conservation function to the changing environment is a scientific problem that needs to be urgently addressed in ecological hydrology research. To reveal the eco-hydrological processes under the changing environment, this study was based on the distributed hydrological model (SWAT) and used water conservation amount (WCA) as an indicator to assess the water conservation capacity of ecosystems. Scenario analysis and statistical analysis were also used to determine the spatial and temporal evolution of the WCAs of farmland, forest, and grassland ecosystems under a changing environment and to further investigate the influence mechanisms of land use change and climate change on the WCA. The findings show that (1) the climate conditions in the Hanjiang watershed have determined the distribution pattern of the ecosystem’s WCA. The spatial distribution patterns of the WCA of each ecosystem differed significantly between the dry season and the wet season. Under the combined influence of human activities and climate change, there was no significant change in the spatial distribution pattern of the WCA. (2) Climate change patterns, which were dominated by precipitation and influenced by evapotranspiration, determined the changes in the WCA of ecosystems. In addition, there were significant spatial differences in the response of the watershed WCA under changing environments in the dry season. Differences in land use type and local climate change were the main reasons for such differences. (3) There were differences in the WCA and the response to changing environments among ecosystems. Forest ecosystems had the highest WCA; grassland ecosystems were the most sensitive to land use change. This study can provide a theoretical basis for alleviating the increasingly serious water resource problems in the basin and ensuring water and ecological security in the basin.

Land use optimization in Ningbo City with a coupled GA and PLUS model

Industrialization and urbanization have resulted in a series of problems such as an excessive intensity of land utilization and an unbalanced structure of land use. Contradictions and conflicts regarding different uses of land are becoming increasingly problematic. The question of how to coordinate the competition among the driving factors of land resources and how to balance and optimize land use types with different functions are urgent problems related to achieving sustainable development. In this study, the traditional model of the land use change process and a machine learning algorithm were integrated to establish an optimal land use allocation model considering macro-quantity control and spatial unit allocation. Taking Ningbo as an example, on the basis of considering the function of land resources and the driving mechanism of land use change, genetic algorithm (GA) and patch-generating land use simulation (PLUS) model were used to optimize the quantitative structure and spatial layout of production−living−ecological land (PLEL), respectively. The GA-PLUS model demonstrated strong robustness. The results show that Ningbo covers a total land area of 9816 km2, and the rates of increase in the area of production land (PL), living land (LL) and ecological land (EL) in Ningbo from 2010 to 2018 were −2.04%, 10.07% and −0.69%, respectively. The main problems were the unbalanced distribution of PLEL, the disordered expansion of industrial production land (IPL) and LL, occupying 3.07% of agricultural production land and 0.67% of EL. Guided by Sustainable Development Goals, the construction goals related to the Beautiful China policy and the development planning goals of Ningbo city, the collaborative optimization of the quantitative structure and spatial layout of PLEL in Ningbo can be realized through the GA-PLUS model. In terms of quantitative structure, Ningbo needs to control the total amount of construction land in the future, and improve the proportion of LL and EL, about 13.04% and 51.75%. In terms of spatial layout, it is necessary to build industrial clusters for IPL in coastal areas, improve the suitability of EL in the north of Ningbo, and address the fact that it is difficult for LL to expand due to the influence of the complex terrain in Yuyao and Xiangshan. The results of this study can guide the optimization and development path of the territorial space of Ningbo, and provide technical support for decision-makers to formulate targeted land space planning and realize regional sustainable development.

Land use intensification in a dry-hot valley reduced the constraints of water content on soil microbial diversity and multifunctionality but increased CO2 production

Conversion of abandoned land (mainly savanna) into cropland generally occurs in fragile ecosystems such as dry-hot valleys (DHVs) in southwest China, with the intent of increasing land productivity and conducting ecological restoration. However, the effects of conversion on soil microbial communities and carbon turnover of savanna ecosystems remain unclear, since savannas could be a vital but overlooked carbon sink. To illustrate the ecological consequences of land-use change (LUC) for savanna ecosystems, a 1-year field experiment was conducted in DHVs of southwest China. The soil properties, microbial respiration, and metagenomics from two different land-use types (grassland and mango plantation) were examined to reveal the effects of regional LUC on soil C turnover and microbial traits. Conversion from degraded grassland into cropland increased the contribution of soil microclimate to the microbial community composition, reduced the constraints of soil water content (SWC), and further decreased nutrient availability. LUC reshaped the composition and structure of soil bacterial communities. Specifically, soil dominant microbes that belonged to Actinobacteria and Proteobacteria were significantly enriched by conversion, while rare microbes that belonged to a wider range of phyla were generally depleted, leading to an overall decrease in community diversity. In addition, LUC-induced changes in soil characteristics and microbial communities further decreased soil multifunctionality as well as the carbon use efficiency of microbes. Intensified microbial respiration and a significant increase in the soil CO2 efflux were observed following LUC, which could drive changes in soil microbial community composition and functions (such as growth and regeneration). In summary, through simultaneously reducing constraints on SWC and decreasing nutrient availability, conversion from degraded grassland to cropland in a DHV decreased soil microbial diversity and multifunctionality, and increased microbial respiration and soil CO2 efflux. Our study provides new insights for understanding the role and mechanisms of LUC in soil carbon turnover in ecologically fragile areas such as DHVs.

Land Use Change Simulation in Rapid Urbanizing Regions: A Case Study of Wuhan Urban Areas.

Until now, few studies have used the mainstreaming models to simulate the land use changes in the cities of rapid urbanizing regions. Therefore, we aimed to develop a methodology to simulate the land use changes in rapid urbanizing regions that could reveal the land use change trend in the cities of the regions. Taking the urban areas of Wuhan, a typical rapid urbanizing region in China, as the study area, this study built a Markov chain–artificial neural network (ANN)–cellular automaton (CA) coupled model. The model used land use classification spatial data with a spatial resolution of 5 m in 2010 and 2020, obtained by remote sensing image interpretation, and data on natural and socio-economic driving forces for land use change simulation. Using the coupled model, the land use patterns of Wuhan urban areas in 2020 were simulated, which were validated in comparison with the actual land use data in 2020. Finally, the model was used to simulate the land uses in the study area in 2030. The model validation indicates that the land use change simulation has a high accuracy of 90.7% and a high kappa coefficient of 0.87. The simulated land uses of the urban areas of Wuhan show that artificial surfaces will continue to expand, with an area increase of approximately 7% from 2020 to 2030. Moreover, the area of urban green spaces will also increase by approximately 7%, while that of water bodies, grassland, cropland, and forests will decrease by 12.6%, 13.6%, 34.9%, and 1.3%, respectively, from 2020 to 2030. This study provides a method of simulating the land use changes in the cities of rapid urbanizing regions and helps to reveal the patterns and driving mechanisms of land use change in Wuhan urban areas.

Analysis of Land Use Change and Driving Mechanisms in Vietnam during the Period 2000–2020

High-accuracy, long-time-series and large-scale land classification mapping are essential for assessing the evolutionary patterns of land systems and developing sustainability studies. In this paper, using Google Earth Engine (GEE) and Landsat satellite remote sensing images, based on the Random Forest (RF) algorithm, we carried out remote sensing classification to obtain a year-by-year land use/cover data set in Vietnam over the past 21 years (2000–2020). Further applying principal component analysis and multiple linear regression methods, we examined the spatio-temporal characteristics, dynamic changes and driving mechanisms of land use change. The results show the following: (1) The RF classification algorithm supported by the GEE can quickly and accurately obtain a land use/cover data set. The overall classification accuracy is 0.91 ± 0.01. (2) The land cover types in Vietnam are dominated by woodland and cropland, with an area share of 54.62% and 37.90%, respectively. In the past 20 years, the area of built-up land has increased the most (+93.49%), followed by the area of water bodies (+54.19%), while the area of woodland has remained almost unchanged. (3) The expansion of built-up land is driven by regional economic development; the area changes in cropland, water bodies and woodland are influenced by both national economic development and climate change. The results of the study provide a basis for assessing land use policies in Vietnam and a reference methodological framework for rapid land mapping and analysis in other countries in the China–Indochina Peninsula.

A Study on the Spatio-Temporal Land-Use Changes and Ecological Response of the Dongting Lake Catchment

Catchments support the survival and development of humans in a region and investigating the mechanism of land-use changes and ecological responses in catchments is of great significance for improving watershed ecological service functions. Taking the Dongting Lake catchment as the study area, this study used spatial analysis, an ecosystem service value (ESV)-equivalent factor method, grid method, and other spatial analysis methods to explore land-use changes and the corresponding ecological service value response from 1990 to 2015, to provide an important theoretical reference for ecological service management, regional planning and ecological service function improvement in the Dongting Lake Basin. Our findings are as follows: (1) apart from a trend of notable expansion in construction land, the land-use types in the Dongting Lake catchment did not change significantly. (2) Grassland had the fastest transfer-out rate; forest land were cultivated land comparably transferred to each other with a larger area, where both were simultaneously and continuously transferred out as construction land; water areas, wetlands, and construction land were all transferred in, where construction land had the fastest transfer rate. (3) The total ESV of the watershed first increased and then decreased, but the overall change was small; spatially, the wetlands and water areas had a higher ESV, whereas construction land and cultivated land had lower ESVs. (4) Soil protection, gas exchange, climate regulation, biodiversity, and water conservation are always the main ecosystem service functions of a catchment, where the service function of the catchment ecosystem is greater than the productive function. The increase in construction land was the main factor for the increased differences between the spatial distributions of the soil, raw materials, biodiversity protection, and gas exchange.

Evolution of land use in coal-based cities based on the ecological niche theory: A case study in Shuozhou City, China

With the rapid development changes and the special land-use patterns, coal-based cities (CBCs) have faced many critical sustainability issues such as the effective use of land resources, the mitigation of land supply-demand contradictions. How does the development of CBCs in China affected local land-use changes and what status does each land type occupy? The relevant mechanisms are not clear. Shuozhou City, a typical growth CBC in China, was therefore selected as the research area to investigate the land use evolution by introducing the theory of land use ecological niche (LUEN). The dynamic changes of land use from 1990 to 2018 were analyzed, and cultivated land played a significant role in the process of land transformation with the highest utilization degree, followed by grassland and construction land. The cultivated land and mining land occupied the economic niche, construction land occupied the social niche, and forest land, grassland, and water area occupied the natural niche. From 2010 to 2015, construction land and mining land occupied the prevailing position of the land-use system. The substantial expansion and compression of the land use ecological niche in Shuozhou City were in the early stage of city development, and there was not a major change in the later stage. In general, the spatial distribution of land use ecological niche was in the east-west direction. Therefore, the production function zone, living function zone, and ecological function zone were delineated. The status, role, and function of land use type should be prioritized when developing land-use planning, considering the mechanisms of land-use change. Governments should actively break through the restrictions of coal resources mining on land use change while giving full play to the role of land resource assets in promoting sustainable development.

Transition from subsistence grazing to nature-based recreation: A nuanced view of land abandonment in a mountain social-ecological system, southwestern Cape, South Africa

Over the last 50 years, studies have shown a decline in the use of mountain lands, a phenomenon termed land abandonment. We investigate the causal mechanisms of land use change in a mountain catchment important for regional water supplies in the southwestern Cape of South Africa. Uniquely, we include nature-based recreational land use types typically excluded from land abandonment studies. We repeated a structured questionnaire originally conducted with landowners 38 years previously and analysed orthoimages from 1948, 1972 and 2014. To identify and contextualise causal mechanisms of change we used thematic analysis and generated narratives from in-depth interviews with landowners. The land use system in 1948 and 1972 was dominated by livestock-based, subsistence agriculture and small-scale farming. This transitioned to agricultural intensification on the lowlands and small portions of the mountains and the utilisation of mountains for non-economic nature-based recreation and ecotourism. The use of frequent small, low intensity-controlled fires was prevalent in the past. More recently, fires have been actively suppressed resulting in the build-up of biomass and the development of infrequent, extensive, high-intensity wildfires. Land use change in the mountains was driven primarily by socio-economic drivers, including socio-economic benefits related to globalisation and economic growth, and not by concerns over land degradation or resource depletion. Our findings support evidence that shows that people’s responses to economic opportunities drive local determinants of land use change and highlights the importance of perceptions in driving land use transitions. We show that existing models of land abandonment are likely overly deterministic in that they do not consider social and cultural factors that may cause a landowner to continue using their land for semi-economic or non-economic reasons. While there is merit in large-scale remote sensing studies, we emphasise the importance of using mixed remote sensing and social science methods for informing models of land use change.

Particulate nutrient loss from drylands to grasslands/forestlands in a large-scale highly erodible watershed

Abstract Land use structure is an important factor affecting soil nutrient loss but the influencing mechanism of land use change on particulate nutrient loss is still unclear in large-scale ecological restoration regions. In this study, an integrated, physically-based modeling framework was put forward to identify the dynamic effects of land use change on particulate nitrogen (N) and phosphorus (P) loss in Jinghe River Watershed (JRW), China. Results indicate that: (i) The proposed modeling framework is a robust tool for quantifying the dynamic effects of land use change on particulate nutrient loss and evaluating agricultural planting stategies at multiple spatial and temporal scales; (ii) The increase of dry land and low-coverage grassland, and the decrease of forestland and high- and middle-coverage grassland from 1985 to 1995 led to a sharp increase of particulate N and P loss load, which increased by 39.06% and 42.69% respectively. (iii) The significant decrease in both dry land and low-coverage grassland from 1995 to 2005 caused the decrease of particulate N and P loss load by 28.22% and 31.99% respectively. This is because the forestland increased but dryland decreased, and the low-coverage grassland was transformed into middle- and high-coverage grassland during this period; and (iv) There was no decrease but increase by 13.65% and 13.50% for particulate N and P loss from 2005 to 2010 because the erosive rainstorm and runoff volume in 2010 were both larger than that in 2005. Results provide effective data support for scientific decision-makers and land management practices in the loess hilly and gully region.

Understanding the drivers of deforestation and agricultural transformations in the Northwestern uplands of Cambodia

At the end of the 1990s, the Northwestern uplands of Cambodia were one of the last forest frontiers of the country. In a region that was the last Khmer Rouge stronghold, the opening of former conflict zones after a peace agreement initiated a vast movement of agricultural colonization. This movement was economically triggered by high market demand for agricultural commodities such as maize and cassava and fueled by a massive flow of spontaneous in-migration of land-poor farmers from lowland regions around the entire country. Focused on four upland districts along a pioneer front of Northwestern Cambodia, we analyzed historical trajectories of land use/cover changes using a chronological series of Landsat data from 1976 to 2016. We identified key drivers of deforestation using demographic data and qualitative information from local actors and other relevant stakeholders. We found a 65 percent forest cover loss due to conversion by smallholders into agricultural land for maize and cassava cultivation over a period of 15 years. The underlying mechanisms of land use change were further investigated to understand the diversity of individual farm trajectories and decision-making processes in relation to land conversion. These elements of diagnosis are essential to engage farming communities in innovative land use systems and to develop sustainable alternatives to boom crops that have led to the current situation of land degradation and economic instability.

Study on Spatial Model of Land Use Based on CA - Markov Model after Returning Cropland to Forest

At present, the frontier of global environmental change research is land use / cover change, and an important way to understand global land change is to analyze and study typical areas. In order to study the law and the driving mechanism of land use change in the loess hilly and gully region, this paper takes the county south ditch watershed as an example, takes the remote sensing image of the basin in 1995, 2005 and 2015 as the data source, combined with the topographic data, And the spatial and temporal dynamics of land use before and after returning farmland to forest in Nangou watershed was analyzed. Finally, based on the land use situation in 2015, a variety of CA criteria were used to carry out modeling analysis to predict the land use in 2025 Type of purpose. And thus hope for the region to implement the scientific implementation of the project of returning farmland to forest.

Modeling dynamic urban land-use change with geographical cellular automata and generalized pattern search-optimized rules

ABSTRACTA novel generalized pattern search (GPS)-based cellular automata (GPS-CA) model was developed to simulate urban land-use change in a GIS environment. The model is built on a fitness function that computes the difference between the observed results produced from remote-sensing images and the simulated results produced by a general CA model. GPS optimization incorporating genetic algorithms (GAs) searches for the minimum difference, i.e. the smallest accumulated residuals, in fitting the CA transition rules. The CA coefficients captured by the GPS method have clear physical meanings that are closely associated with the dynamic mechanisms of land-use change. The GPS-CA model was applied to simulate urban land-use change in Kunshan City in the Yangtze River Delta from 2000 to 2015. The results show that the GPS method had a smaller root mean squared error (0.2821) than a logistic regression (LR) method (0.5256) in fitting the CA transition rules. The GPS-CA model thus outperformed the LR-CA model, with an overall accuracy improvement of 4.7%. As a result, the GPS-CA model should be a superior tool for modeling land-use change as well as predicting future scenarios in response to different conditions to support the sustainable urban development.

Study on Driving Mechanisms of Land Use Change in the Coastal Area of Jiangsu, China

ABSTRACT Bao, G.Y.; Huang, H.; Gao, Y.N., and Wang, D.B., 2017. Study on driving mechanisms of land use change in coastal area of Jiangsu, China. In: Lee, J.L.; Griffiths, T.; Lotan, A.; Suh, K.-S., and Lee, J. (eds.), The 2nd International Water Safety Symposium. Journal of Coastal Research, Special Issue No. 79, pp. 104–108. Coconut Creek (Florida), ISSN 0749-0208. Based on the 5 periods of satellite images, land use structure and changes of 3 cities in the Jiangsu coastal area were analyzed, and the relationship between land use structure and environmental factors was analyzed by “CLUE-S model + Logistic regression”. The results showed that, for land use change in the past 15 years, the changes in cultivated land, grassland and construction land were the highest. Land use change is mainly located in urban and surrounding areas, followed by farmland mainly located in the coastal zone. This study uses GIS spatial analysis and CLUE-S + Logistic regression model analysis, correlation analysis and regressio...

土地利用碳排放效应及其低碳管理研究进展

PDF HTML阅读 XML下载 导出引用 引用提醒 土地利用碳排放效应及其低碳管理研究进展 DOI: 10.5846/stxb201406271334 作者: 作者单位: 上海市城市化生态过程与生态恢复重点实验室,上海市城市化生态过程与生态恢复重点实验室,上海市城市化生态过程与生态恢复重点实验室 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目(41401638);上海市浦江人才计划项目(14PJ1402800);上海市教育委员会科研创新项目(14ZS053) Progress in research on land use effects on carbon emissions and low carbon management Author: Affiliation: Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration,Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration,Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:土地利用是造成全球温室气体排放量迅猛增长的重要因素,但由于土地利用的碳排放在时间和空间上受社会经济活动与自然过程的共同作用,相对自然生态系统碳排放的过程和机制更加复杂,因此,其研究也越来越多地受到包括学者、政府决策者、企业、非政府组织等利益相关者的关注,并被诸多能源与生态环境领域的国内外重大科学研究计划列为核心内容。通过对土地利用的直接和间接碳排放效应及其低碳管理的国内外研究进展进行综述,较全面地对上述研究中已取得的成果以及尚存在的不足与挑战进行了总结,并对未来研究应如何完善现有研究的不足提出了几点展望,以期为科学编制低碳目标导向的土地利用规划提供理论基础和实践管理经验,从而全面引导城市的低碳发展。 Abstract:Land use has played an important role in causing rapid increase of greenhouse gas emissions. As reported in the literature, nearly one third of global carbon emissions during the last hundred years has come from changes in land use/cover and the transformation of land management modes. In this paper, the latter is called the direct effect of land use on carbon emissions. The remaining two thirds of carbon emissions were caused by anthropogenic activities on different types of land. This is defined as indirect effect of land use on carbon emissions. Unveiling the mechanisms of how land use affects carbon emissions and determining the anthropogenic controls and regulatory countermeasures needed to achieve low-carbon targets are key research subjects with strategic importance for socioeconomic development. However, the mechanisms by which land use affects carbon emissions, especially in rapidly urbanizing regions, are still unclear, and are more complicated than those of natural ecosystems. This is because of the complex nature of land-use influenced both by human socio-economic and natural ecological factors. Thus, research relevant to these issues has been attracting more and more attention from stakeholders such as scholars, policymakers, enterprises, and non-governmental organizations. Such research has been targeted as core content in many scientific research programs in the energy and environmental disciplines around the world. In order to have a comprehensive understanding of the state of the art in land use effects on carbon emissions, and for low carbon management, this paper summarizes the achievements in the existing literature. It also provides a review of the existing gaps and challenges from the perspectives of carbon inventory accounting, mechanisms of both direct and indirect carbon emissions from land use, and carbon mitigation management. It was found that 1) in past decades, a large amount of research has been conducted on land-use-induced carbon-inventory accounting at both country and regional scales, and on the effect of land use on the carbon cycle of some typical natural ecosystems, such as forests and grasslands. In contrast, studies on the mechanisms of land use change driven both by socioeconomic and natural processes, and on their influence on carbon emissions at city scale, lag behind. 2) The current literature on low carbon management focuses more on the planning and regulation of specific types of land use, such as urban green space or residential land, or on the optimization of the amount and composition structure of total urban land. Systematic control and regulating principles, together with roadmaps for detailed implementation, have not yet been provided. Future studies aimed at correcting current deficiencies are proposed to provide the theoretical knowledge and practical experience needed for achieving low-carbon-target-oriented, land-use planning. 参考文献 相似文献 引证文献

Land-use change arising from rural land exchange: an agent-based simulation model

Introduction Land exchange can be a major factor driving land-use change in regions with high pressure on land, but is generally not incorporated in land-use change models. Here we present an agent-based model to simulate land-use change arising from land exchange between multiple agent types representing farmers, nature organizations, and estate owners. Methods The RULEX model (Rural Land EXchange) was calibrated and applied to a 300 km 2 case study area in the east of the Netherlands. Decision rules about which actor will sell and buy land, as well as which specific land to buy or sell are based on historical observations, interviews, and choice experiments. Results A reconstruction of land-use change for the period 2001‐2009 demonstrates that RULEX reproduces most observed land-use trends and patterns. Given that RULEX simulates only one mechanism of land-use change, i.e. land exchange, it is conservative in simulating change. Conclusions With this model, we demonstrate the potential of incorporating land market processes in an agent-based, land-use change model. This supports understanding of land-use change that is brought about by ownership change, which is an important process in areas where pressure on land is high. The soundness of the process representation was corroborated by stakeholders within the study area. Land exchange models can be used to assess the impact of changes in climate, markets, and policy on land use change, and help to increase effectiveness of alternative land purchasing strategies by stakeholders or spatial planning policy.

The intensity change of urban development land: Implications for the city master plan of Guangzhou, China

The Chinese economy has experienced substantial development over the last thirty years. This growth has resulted in an enormous expansion of China's urban areas and it has also led to a growing scarcity of land resources. Consequently, there is currently an urgent need to mitigate the conflict between the needs of growing urban areas and the shrinking supply of land resources. Understanding land-use intensity and its changes can provide important information to find mitigating measures for this conflict in the demand for land. Previous studies have found that increasing the utilization efficiency of land resources is one of the most effective ways to resolve this issue. This study focuses on the city of Guangzhou, which is an intensively developed megalopolis. A number of different data sources have been analyzed to find the characteristics and changes in urban land use in Guangzhou, including: Landsat data from 1979, 1990, 2000, and 2009; relative socioeconomic data from the Guangzhou statistic yearbooks; and the master plans of Guangzhou. The results indicate that the area of developed land has continued to increase. Urban development land intensity and its change were then explored using a Back Propagation neural network model of the city. Although the analysis revealed that urban development land did not have a higher intensity overall, it also showed that there was a sectional upward trend throughout the study period. Consequently, there is a potential to improve the land-use intensity of Guangzhou. A linear regression model was then adopted to explore the mechanism of land use change. The results reveal that rapid industrialization and urbanization have improved land-use intensity in Guangzhou. The per capita urban road area and per capita GDP show a strong relationship when compared with land-use intensity. Using the relative city master plans, the authors have argued that local government in Guangzhou has taken active steps to address land issues to promote the city's socioeconomic development; however, a scientific city master plan in the study area is still necessary to ensure the effective utilization of the city's limited land resources.