An agent-based model of agricultural land expansion in the mountain forest of Timor Island,Indonesia

The Mutis-Timau Forest Complex,located on Timor Island,Indonesia,is a mountainous tropical forest area that gradually decreases due to deforestation and forest degradation.Previous modelling studies based on patterns indicate that deforestation primarily occurs at lower elevations and near the boundaries of forests and settlements,often associated with shifting cultivation by local farmers.This study adopts a process-based modelling approach,specifically the agent-based model,to simulate land changes,particularly farmers'expansion of agricultural land around the Mutis mountain forest.The underlying concept of this agent-based approach is the interaction between the human and environmental systems.Farmers,representing the human system,interact with the land,which represents the environmental system,through land use decision-making mechanisms.The research was conducted in the Community Forest of the Timor Tengah Utara District,one of the sites within the Mutis-Timau Forest Complex with the highest deforestation rate.Land use change simulations were performed using agent-based modelling from 1999 to 2030,considering the socio-economic conditions of farmers,spatial preferences,land use decisions,and natural transitions.The results revealed that the agricultural area increased by 14%under the Business as Usual scenario and 5%under the Reducing Emission from Deforestation and Forest Degradation scenario,compared to the initial agricultural area of 245 hectares.The probability of farmers deciding to extend agricultural activities was positively associated with the number of livestock maintained by farmers and the size of the village area.Conversely,the likelihood of farmers opting for agricultural extensification decreased with an increase in the area of private land and the farmer's age.These findings are crucial for the managers of the Mutis-Timau Forest Complex and other relevant stakeholders,as they aid in arranging actions to combat deforestation,designing proper forest-related policies,and providing support for initiatives such as reducing emissions from deforestation and forest degradation programs or further incentive schemes.

Can Industrial Structure Upgrading Restrain Industrial Land Expansion?Evidence from China

China has made great achievements in industrial development and is transforming into a powerful manufacturing country.Meanwhile,the industrial land scale is also expanding.However,whether industrial structure upgrading achieves the purpose of restraining industrial land expansion remains unanswered.By calculating the industrial land structure index(ILSI)and industrial land expansion scale(ILES),this study analyzed their temporal and spatial distribution characteristics at both regional and city levels from 2007to 2020 in China.Results show that industrial land expansion presents a different trend in the four regions,the ILES in the eastern region is the largest,and the speed of industrial land expansion has declined since 2013,but it has gradually increased since 2016.The ILSI of the eastern and central regions is higher than that of the western and northeastern regions.Furthermore,a spatial Durbin model(SDM)has been established to estimate the spatial effect of industrial structure upgrading on industrial land expansion from 2007 to2020.Notably,industrial structure upgrading has not slowed industrial land expansion.The eastern and western regions require a greater amount of industrial land while upgrading the industrial structure.The improvement of the infrastructure level and international trade level has promoted industrial land expansion.

Construction land expansion and influencing factors of typical river valley cities in Northeast China: Taking Jilin City as an example

Jilin City is a typical river valley city in Northeast China.In this paper,the authors studied the spatial and temporal expansion characteristics of the built-up areas in Jilin City from 1990 to 2020 using the analysis of expansion speed and strength,fractal dimension,barycenter coordinate transfer index and sector analysis.The ultimate-goal is to analyze the driving and restrictive factors that affect the spatial expansion of river valley cities.The results indicate that(1)the expansion speed of urban land in Jilin City has been re-latively slow in the past 30 years,while only slightly faster in 2010–2020;(2)in the spatial dimension,Jilin City mainly expanded to the south,then to the west,and extensive expansion has resulted in complex mor-phology with little stability and compactness;(3)the expansion is affected by multiple factors,of which the positive factor is industrial development,while the restrictive factors include natural factors,population loss,etc.This study provides a case for the formulation of land use policies and land space planning in river valley cities.

The influencing factors of urban land expansion in Changsha

This research systematically analyses land-use map of Changsha city in different periods of time. The spatial form and structural evolution was analysed by studying indices such as city land-use structure proportion, expansion intensity, economic flexibility, population flexibility, changing compactness index and so on. The dynamic mechanism of urban land expansion has been discussed by integrating the regional social economy development situation and many aspects such as the physiographical surrounding, population and economic development, traffic infrastructure, planning and regional development tactic and system innovation. The research indicates that the urban land expansion speed and intensity have steadily increased in Changsha from 1949 to 2004. The expansion form has been from a single external expansion to a combination form of external and internal expansion, from a circular or linear continuous form to a blocky or agglomeration shape. Overall, the urban land expansion of Changsha city is a phasic, diversified and complex process. And no matter what the stage is, it is an organic system containing multiple speed, pattern and shape, which are driven by multiple impetuses. The dominant feature at different stages was highlighted because of the balance and fluctuation between different forces, and the existing urban land border and shape have resulted from the joint efforts of these phasic forces.

Simulation of Urban Land Expansion Under Ecological Constraints in Harbin-Changchun Urban Agglomeration,China

Under the demand of urban expansion and the constraints of China’s’National Main Functional Area Planning’policy,urban agglomerations are facing with a huge contradiction between land utilization and ecological protection,especially for HarbinChangchun urban agglomeration who owns a large number of land used for the protection of agricultural production and ecological function.To alleviate this contradiction and provide insight into future land use patterns under different ecological constraints’scenarios,we introduced the patch-based land use simulation(PLUS)model and simulated urban expansion of the Harbin-Changchun urban agglomeration.After verifying the accuracy of the simulation result in 2018,we predicted future urban expansion under the constraints of three different ecological scenarios in 2026.The morphological spatial pattern analysis(MSPA)method and minimum cumulative resistance(MCR)model were also introduced to identify different levels of ecological security pattern(ESP)as ecological constraints.The predicted result of the optimal protection(OP)scenario showed less proportion of water and forest than those of natural expansion(NE)and basic protection(BP)scenarios in 2026.The conclusions are that the PLUS model can improve the simulation accuracy at urban agglomeration scale compared with other cellular automata(CA)models,and the future urban expansion under OP scenario has the least threat to the ecosystem,while the expansion under the natural expansion(NE)scenario poses the greatest threat to the ecosystem.Combined with the MSPA and MCR methods,PLUS model can also be used in other spatial simulations of urban agglomerations under ecological constraints.

Evaluating and modeling the spatiotemporal pattern of regional-scale salinized land expansion in highly sensitive shoreline landscape of southeastern Iran

Taking an area of about 2.3×10~4 km~2 of southeastern Iran, this study aims to detect and predict regional-scale salt-affected lands. Three sets of Landsat images, each set containing 4 images for 1986, 2000, and 2015 were acquired as the main source of data. Radiometric, atmospheric and cutline blending methods were used to improve the quality of images and help better classify salinized land areas under the support vector machine method. A set of landscape metrics was also employed to detect the spatial pattern of salinized land expansion from 1986 to 2015. Four factors including distance to sea, distance to sea water channels, slope, and elevation were identified as the main contributing factors to land salinization. These factors were then integrated using the multi-criteria evaluation (MCE) procedure to generate land sensitivity map to salinization and also to calibrate the cellular-automata (CA) Markov chain (CA-Markov) model for simulation of salt-affected lands up to 2030, 2040 and 2050. The results of this study showed a dramatic dispersive expansion of salinized land from 7.7 % to 12.7% of the total study area from 1986 to 2015. The majority of areas prone to salinization and the highest sensitivity of land to salinization was found to be in the southeastern parts of the region. The result of the MCE-informed CA-Markov model revealed that 20.3% of the study area is likely to be converted to salinized lands by 2050. The findings of this research provided a view of the magnitude and direction of salinized land expansion in a past-to-future time period which should be considered in future land development strategies.

Government's Role in Urban Construction Land Expansion

Focusing on urban construction land expansion,governmental influence on expansion of urban construction land in China is analyzed from fiscal decentralization,government game and land system.Due to fiscal decentralization and coupled with GDP-based performance evaluation system,local government seeks to maximizing economic profits.Whereas,land systems such as land property,land expropriation and land transfer system,let the local governments' profit seeking behavior achieved.The conclusion is that the government's role in urban construction land expansion is mainly from local governments.

Urban land expansion and its driving factors of mountain cities in China during 1990–2015

Land expansion of mountain cities in China is not systematically studied yet. This study identified 55 major mountain cities at and above prefecture level, and analyzed the land expansion characteristics and driving forces, based on visually interpreted data from TM images in 1990, 2000, 2010 and 2015. From 1990 to 2015, total built-up land area of the mountain cities increased by 3.87 times, 5.56% per year. The urban land growth was apparently accelerated after 2000, from 4.35% per year during 1990-2000 increased to 6.47% during 2000-2010 and 6.2% during 2010-2015. Compared to the urban population growth, the urban land expansion rate was 44% higher. As a result, the urban land area per capita increased, but it was still within the government control target, and also was much lower than the average of all cities in China. Urban development policy, changes to administrative divisions, GDP and population growth, and road construction were identified as the major driving forces of land expansion. Terrain conditions were not found a relevance to the urban land expansion rate during 1990-2015, but had a significant impact on the layout and shape, and also probably on the urban land efficiency.

An efficient built-up land expansion model using a modified U-Net

This paper introduces an improved convolutional neural network based on the conventional U-Net for simulating built-up land expansion.The proposed method hires a pixel-wise semantic segmentation approach considering the spatial drivers affecting urbanization as data cubes.Independent variables including altitude,slope,and distance from barren,crop,greenery,roads,and urban areas for 1998,2008,and 2018 were considered as covariates for the simulation of built-up land expansion in Tehran and Karaj regions in Iran.The proposed method was compared with the random forest(RF)algorithm as the baseline model.Evaluation using the area under the total operating characteristic indicated the superiority of our modified U-Net(0.87)over the RF(0.82)algorithm.Furthermore,evaluation using the percent correct metric indicated that our proposed model is capable of learning neighborhood effects effectively leading to simulate built-up land expansion accurately,independent from applying a cellular automata(CA)model.Therefore,the modified U-Net independent from the CA which can consider the neighborhood effects is recommended for the simulation of built-up land expansion precisely.

Factors Driving the Expansion of Construction Land:A Panel Data Study of Districts and Counties in Ningbo City,China

This paper analyzes panel data from 2003–2012 to identify the factors driving the expansion of construction land in Ningbo city;it uses panel data,regional-level,and year-by-year regression models.The results indicate the following：（1） For each 1% increase in the size of the economy,urban population,and industrial structure adjustment coefficient,the amount of construction land increased by 0.35%,0.52% and –1%,respectively.（2） The factors driving the expansion of urban construction land differed across regions.In more highly developed areas such as Yuyao,Cixi,Fenghua and the downtown area,population growth was the most obvious driving factor with coefficients of 4.880,1.383,3.036 and 0.583,respectively,in those areas.Here,the impact of industrial structure adjustment was lower than that of population growth（with coefficients of 1.235,0.307,0.145 and –0.242）,while economic development was an increasingly insignificant factor（with coefficients of –0.302,0.071,0.037 and 0.297）.On the other hand,economic development was the most important factor for the expansion of construction land in relatively less developed areas such as Xiangshan and Ninghai counties with coefficients of 0.413 and 0.195,respectively.Here,population growth（with coefficients of –0.538 and 0.132） and industrial structure adjustment（with coefficients of –0.097 and 0.067） were comparatively weaker driving factors.（3） The results of the year-by-year regression indicate the increased impact of economic development as a driving factor（from –1.531 in 2005 to 1.459 in 2012）.The influence of the population growth factor slowly declined（from 1.249 in 2005 to 0.044 in 2012） and from 2009 on was less influential than the economic development factor.The industrial structure coefficient remained negative and its influence diminished from year to year（from –5.312 in 2004 to –0.589 in 2012）.

不同类型城市建设用地扩张驱动机制比较研究——以京津冀地区为例

Different types of urban construction land are different in terms of driving factors for their expansion.Most existing studies on driving forces for urban construction land expansion have considered the construction urban land as a whole and have not examined and compared the differentiated driving forces for different types of construction land expansion.This study explored the differentiated driving mechanisms for two types of urban construction land expansion by selecting key driving factors and using spatial econometric regression and geographical detector models.The results show that there are significant differences in the driving forces for expansion between the two types of urban construction land.The driving factors of urban land expansion do not necessarily affect industrial parks.And the factors acting on expansion of both types are different in influence degree.For urban expansion,economic density growth,the value-added growth of tertiary industries,and proximity to urban centers have a negative effect.However,urbanization levels and value-added growth of secondary industries have a positive effect.The explanatory power of these factors is arranged in the following descending order:value-added growth of tertiary industries,value-added change of secondary industries,urban population growth,economic density growth,and proximity to urban centers;road network density has no significant effect.For industrial parks expansion,the value-added growth of secondary industries and road network density has a positive effect,while economic density growth has a negative effect.The explanatory power is arranged in the following descending order:value-added growth of secondary industries,road network density,and economic density growth.The findings can help implement differentiated and refined urban land use management policies.

The Measurement of Carbon Emission Effect of Construction Land Changes in Anhui Province Based on the Extended LMDI Model

In the context of ＂two-wheel drive＂ development mode, China＇s construction land shows significant expansion characteristics. The carbon emission effect of construction land changes is an important factor for the increase of carbon emissions in the atmosphere. In this study, the drivers of carbon emissions in Anhui Province from 1997 to 2011 were quantitatively measured using the improved Kaya identity and Logarithmic Mean Divisia Index. The results show that： economic growth, expansion of construction land and changes in population density have incremental effects on carbon emissions. The average contribution rate of economic growth as the first driver is 266.32 percent. The construction land expansion is an important driving factor with annual mean carbon effect of 6.4057 million tons and annual mean contribution rate of 187.30 percent. But the change in population density has little impact on carbon emission driving. Energy structure changes and energy intensity reduction have inhibitory effects on carbon emissions, of which the annual mean contribution rate is -212.06 percent and -158.115 percent respectively. The targeted policy approaches of carbon emission reduction were put forward based on the decomposition of carbon emission factors, laying a scientific basis to rationally use the land for the Government, which is conducive to build an ecological province for Anhui and achieve the purpose of emission reduction, providing a reference for the research on carbon emission effect of changes in provincial-scale construction land.

2000-2020年中国建设用地扩张侵占耕地的时空特征及其与粮食产量的空间关系

Construction land expansion is a key driver of urbanization and industrialization,yet it poses the risk of losing farmland and cascading impacts on food supply.The spatial char-acteristics of farmland occupied by construction land and its association with grain yield in China were unclear.We analyzed the characteristics of farmland converted into construction land,and its relationship with grain yield in China for 2000-2020.Construction land increased in area in central and western regions of China,and farmland decreased in area in south-eastern China.The expansion of construction land in the North China Plain,Northeast China Plain,and the Loess Plateau,occurred at the expense of farmland.Except the southeast coast of China,grain yield increase was only weakly dependent on farmland area.Patterns in which farmland was converted into construction land and grain-yield change were highly coupled in southeastern coastal China,Sichuan Basin,Shandong Peninsula,and the Hu Huanyong Line.It should be noted that expansion in construction land area does have some influence on grain production;ultimately it is greatly affected by yield per unitarea.

Urban expansion patterns and their driving forces based on the center of gravity-GTWR model:A case study of the Beijing-Tianjin-Hebei urban agglomeration

Research into urban expansion patterns and their driving forces is of great significance for urban agglomeration development planning and decision-making.In this paper,we reveal the multi-dimensional characteristics of urban expansion patterns,based on the intensity index of the urban expansion,the differentiation index of the urban expansion,the fractal dimension index,the land urbanization rate,and the center of gravity model,by taking the Beijing-Tianjin-Hebei(Jing-Jin-Ji)urban agglomeration as an example.We then build the center of gravity-geographically and temporally weighted regression(GTWR)model by coupling the center of gravity model with the GTWR model.Through the analysis of the temporal and spatial patterns and by using the center of gravity-GTWR model,we analyze the driving forces of the urban land expansion and summarize the dominant development modes and core driving forces of the Jing-Jin-Ji urban agglomeration.The results show that:1)Between 1990 and 2015,the expansion intensity of the Jing-Jin-Ji urban agglomeration showed a down-up-down trend,and the peak period was in 2005-2010.Before 2005,high-speed development took place in Beijing,Tianjin,Baoding,and Langfang;after 2005,rapid development was seen in Xingtai and Handan.2)Although the barycenter of cities in the Jing-Jin-Ji urban agglomeration has shown a divergent trend,the local interaction between cities has been enhanced,and the driving forces of urban land expansion have shown a characteristic of spatial spillover.3)The spatial development mode of the Jing-Jin-Ji urban agglomeration has changed from a dual-core development mode to a multi-core development mode,which is made up of three functional cores:the transportation core in the northern part,the economic development core in the central part,and the investment core in the southern part.The synergistic development between each functional core has led to the multi-core development mode.4)The center of gravity-GTWR model combines the analysis of spatial and temporal nonstationarity with urban spatial interaction,and analyzes the urban land expansion as a space-time dynamic system.The results of this study show that the model is a feasible approach in the analysis of the driving forces of urban land expansion.

Spatiotemporal evolution of national development zones and their impact on urban land growth in China

Development zones are important growth poles for promoting regional economic development. However, the spatiotemporal relationship between development zone construction and urban land growth is still unclear. This paper analyzes the spatiotemporal changes of national-level development zones(NDZs), approximately 219 national economic development zones, and 156 high-tech development zones during 1990–2018 in China. The impact of development zone establishment on the growth of surrounding urban land was quantitatively explored using circle buffering analysis and time series comparative analysis. The results show that China's NDZs spread from the southeast coast to the inland area from 1990 to 2018, and the establishment of the development zones has an obvious promoting effect on the surrounding urban land growth. The scope and intensity of influences of the development zone established in different periods present distinct nonstationarity in space and time. Overall, the impact on urban land(IU) of China's NDZs established in different years was mostly highest at the 100 m buffer zone radius, while the slope of the IU was mostly negative, which meant that the 100 m buffer zone radius of the development zone center was the most efficient scale to promote urban land growth. In the meantime, the curve of IU of NDZs established before 1990, during 1996–2000 and 2001–2005 has a clear inflection point, which indicates that the most efficient scales of NDZs established before 1990, during 1996–2000, and 2001–2005 are 1300 m, 900–1000 m, and 800 m, respectively. NDZs established in other periods do not have the most obvious efficient scale. The development zone played the greatest role in promoting urban land growth from 2000 to 2010. Three association modes, including post-growth, pre-growth and steady-growth, were identified based on the differences in geographical location, establishment time, and type of development zones. We quantitatively identify the impact of the growth pole of NDZs on urban land growth from the perspective of spatiotemporal evolution. The findings would provide decision-making support for optimizing the spatial relationship between development zone construction and urban land growth.