Land-use change models are important tools for integrated environmental management. Through scenario analysis they can help to identify near-future critical locations in the face of environmental change. A dynamic, spatially explicit, land-use change model is presented for the regional scale: CLUE-S. The model is specifically developed for the analysis of land use in small regions (e.g., a watershed or province) at a fine spatial resolution. The model structure is based on systems theory to allow the integrated analysis of land-use change in relation to socio-economic and biophysical driving factors. The model explicitly addresses the hierarchical organization of land use systems, spatial connectivity between locations and stability. Stability is incorporated by a set of variables that define the relative elasticity of the actual land-use type to conversion. The user can specify these settings based on expert knowledge or survey data. Two applications of the model in the Philippines and Malaysia are used to illustrate the functioning of the model and its validation.

以滇池流域为研究对象,基于1999年、2002年两期TM遥感解译数据和区域自然与社会经济数据,应用Dyna-CLUE模型模拟2008年滇池土地利用空间分布。结合滇池流域土地利用变化趋势与退耕还林政策,设定了三种土地需求情景,模拟2022年区域土地利用空间分布情况。研究结果表明：① 两期模拟结果Kappa系数分别为0.6814与0.7124,具有高度的一致性,表明Dyna-CLUE模型在滇池流域有较强的适用性。② 三种情景的模拟结果显示,至2022年流域内未利用地、耕地显著减少,建设用地、林地显著增加,水域与草地相对变化较小,因加大退耕还林政策实施力度,三种情景中,位于官渡区、呈贡区、嵩明县及晋宁县的耕地与林地呈现不同的变化情况。③ 滇池流域建设用地扩张,增加了滇池非点源污染负荷。不合理的土地利用布局,将会恶化滇池水质,加剧水环境压力。研究结果可为未来滇池流域土地利用合理规划与非点源污染控制提供参考依据和决策支持。

Taking Dianchi Lake Watershed as a study area, we use Dyna-CLUE to simulate the land use spatial distribution pattern of the Dianchi Lake Watershed in 2008 in combination with the interpretation data from TM image in 1999 and 2002 and local natural and socio-economic data. According to the trend of land use change in the Dianchi Lake Watershed and the policy of returning farmland to forestland, three scenarios of land use change from 2008 to 2022 were constructed, and land use spatial pattern in 2022 in the study area was stimulated under the above-mentioned scenarios by using the Dyna-CLUE model. The results show that Kappa coefficients of the two simulated results from1999 to 2008 and from 2002 to 2008 were 0.6814 and 0.7124, compared with the interpretation data of 2008. The simulated results were credible and the Dyna-CLUE model has a good applicability in simulating land use change in the Dianchi Lake Watershed. The simulation results of the three scenarios show that the unused land and farmland will be reduced significantly, construction land and woodland will increase rapidly, and water bodies and grassland will change a little. Because of the difference in the policy of returning farmland to forestland, farmland and forestland in Guandu district, Chenggong district, Songming county and Jinning county will be different under the three scenarios. The expansion of construction land in the watershed will increase the load of non-point source pollution in the Dianchi Lake. Unreasonable distribution of land use will result in further deterioration of the water quality and increase the pressure on the water environment in the Dianchi Lake. The research can provide scientific support for rational planning of land use and prevention of non-point source pollution.

Land use in the northeast region of Thailand has changed dramatically in the past two decades. These changes are mainly due to the government policies, which launched a scheme to promote rubber plantation during 2003-2013 targeting to solve the problem of poverty in the region. At least 50,000 ha of paddy fields were found to be converted to other land use types between 2002 and 2012. This study was conducted in Nong Khai and Bueng Kan province of northeast Thailand, where massive rubber plantation is going on prompting significant amount of land-use change, with the objective of investigating how land-use changes will affect on food availability in future. We analyzed land-use changes of the past and simulated future land uses using GIS and Landsat Thematic Mapper Data. The most obvious change was the decrease in paddy field and an increase in rubber plantation. This eventually leads to decreased paddy production affecting food supply of farm households. The land use projections for 2032 were done for three scenarios using Dyna-CLUE model. Unlike business as usual scenario, which will further decrease the paddy area, other scenarios with different land use policies if implemented will help protect paddy areas and thus achieving higher food production locally. The lack of implementation of proper spatial policies will lead to a further loss of paddy areas at macro level. The smallholder farmers may be highly vulnerable to land use-change and experience significant food crop losses, food insecurity and income loss when they change the land to rubber and there is market failure.

As the second largest island in Japan, Hokkaido provides precious land resources for the Japanese people. Meanwhile, as the food base of Japan, the gradual decrease of the agricultural population and more intensive agricultural practices on Hokkaido have led its arable land use to change year by year, which has also caused changes to the whole land use pattern of the entire island of Hokkaido. To realize the sustainable use of land resources in Hokkaido, past and future changes in land use patterns must be investigated, and target-based land use planning suggestions should be given on this basis. This study uses remote sensing and GIS technology to analyze the temporal and spatial changes of land use in Hokkaido during the past two decades. The types of land use include cultivated land, forest, waterbody, construction, grassland, and others, by using the satellite images of the Landsat images in 2000, 2010, and 2019 to achieve this goal to make classification. In addition, this study used the coupled Markov-FLUS model to simulate and analyze the land use changes in three different scenarios in Hokkaido in the next 20 years. Scenario-based situational analysis shows that the cultivated land in Hokkaido will drop by about 25% in 2040 under the natural development scenario (ND), while the cultivated land area in Hokkaido will remain basically unchanged in cultivated land protection scenario (CP). In forest protection scenario (FP), the area of forest in Hokkaido will increase by 1580.8 km2. It is believed that the findings reveal that the forest land in Hokkaido has been well protected in the past and will be protected well in the next 20 years. However, in land use planning for future, Hokkaido government and enterprises should pay more attention to the protection of cultivated land.

为了了解黄河三角洲湿地景观类型演变最优模拟模型以及景观的变化趋势,本文采用1996、2006、2016年3期黄河三角洲分类影像,分别利用CA-Markov、LCM、2种模型叠加开展变化模拟。研究发现：① 在相同驱动力因子影响下,空间模拟上LCM比CA-Markov好,数量模拟上,CA-Markov比LCM更贴合,对于变化较大研究区,综合2种模型优势来模拟该湿地变化最佳;② 对于较强的人为、自然灾害干扰,会对模拟精度有影响。在LCM模型中,驱动力相同情况下,生成适宜性图像的转移子模型数量越多,模拟精度越高。对于CA-Markov模型,比例误差系数适宜的设置对数量模拟的精度也有提升;③ 在保持2006-2016年的变化趋势下,综合2种模型模拟的2026年自然湿地面积1252.69 km ²,人工湿地面积1265.00 km ²,非湿地面积924.51 km ²。从2026年黄河三角洲模拟的结果可看出,自然、非湿地的面积减少,人工湿地大量的增加并不断向浅海区域扩张。通过对黄河三角洲湿地变化进行预测分析,可为湿地资源的合理有效利用与管理等提供科学依据。

Exploring land use change is crucial to planning land space scientifically in a region. Taking the ecological conservation area (ECA) in western Beijing as the study area, we employ ArcGIS 10.2, landscape pattern index and multiple mathematical statistics to explore the temporal and spatial variation of land use from 2000 to 2020. Patch-generating Land Use Simulation (PLUS), Future Land Use Simulation (FLUS) and Markov models were used to simulate and predict the current land use in 2020. The models were evaluated for accuracy, and the more accurate PLUS model was selected and used to simulate and predict the potential land use in the study area in 2030 under two management scenarios. The main findings of this research are: (1) From 2000 to 2020, the construction land increased constantly, and the area of cultivated land and grassland decreased significantly. (2) For predicting the spatial distribution of land use in the study area, the PLUS model was more accurate than the FLUS model. (3) The land-use prediction of the study area in 2030 shows that the area of grassland, forest and water is approximately equal to their corresponding value in 2020, but the construction land increased constantly by occupying the surrounding cultivated land. According to this research, the continuous decrease of cultivated land in favor of increasing construction land will cause losses to the ecological service function of the ECA, which is not beneficial to the sustainable development of the region. Relevant departments should take corresponding measures to reduce this practice and promote sustainable development, particularly in the southern and western areas of the ECA where there is less construction land.

. Land cover (LC) determines the energy exchange, water and carbon cycle between Earth's spheres. Accurate LC information is a fundamental parameter for the environment and climate studies. Considering that the LC in China has been altered dramatically with the economic development in the past few decades, sequential and fine-scale LC monitoring is in urgent need. However, currently, fine-resolution annual LC dataset produced by the observational images is generally unavailable for China due to the lack of sufficient training samples and computational capabilities. To deal with this issue, we produced the first Landsat-derived annual China land cover dataset (CLCD) on the Google Earth Engine (GEE) platform, which contains 30 m annual LC and its dynamics in China from 1990 to 2019. We first collected the training samples by combining stable samples extracted from China's land-use/cover datasets (CLUDs) and visually interpreted samples from satellite time-series data, Google Earth and Google Maps. Using 335 709 Landsat images on the GEE, several temporal metrics were constructed and fed to the random forest classifier to obtain classification results. We then proposed a post-processing method incorporating spatial–temporal filtering and logical reasoning to further improve the spatial–temporal consistency of CLCD. Finally, the overall accuracy of CLCD reached 79.31 % based on 5463 visually interpreted samples. A further assessment based on 5131 third-party test samples showed that the overall accuracy of CLCD outperforms that of MCD12Q1, ESACCI_LC, FROM_GLC and GlobeLand30. Besides, we intercompared the CLCD with several Landsat-derived thematic products, which exhibited good consistencies with the Global Forest Change, the Global Surface Water, and three impervious surface products. Based on the CLCD, the trends and patterns of China's LC changes during 1985 and 2019 were revealed, such as expansion of impervious surface (+148.71 %) and water (+18.39 %), decrease in cropland (−4.85 %) and grassland (−3.29 %), and increase in forest (+4.34 %). In general, CLCD reflected the rapid urbanization and a series of ecological projects (e.g. Gain for Green) in China and revealed the anthropogenic implications on LC under the condition of climate change, signifying its potential application in the global change research. The CLCD dataset introduced in this article is freely available at https://doi.org/10.5281/zenodo.4417810 (Yang and Huang, 2021).

As an important production base for livestock and a unique ecological zone in China, the northeast Tibetan Plateau has experienced dramatic land use/land cover (LULC) changes with increasing human activities and continuous climate change. However, extensive cloud cover limits the ability of optical remote sensing satellites to monitor accurately LULC changes in this area. To overcome this problem in LULC mapping in the Ganan Prefecture, 2000–2018, we used the dense time stacking of multi-temporal Landsat images and random forest algorithm based on the Google Earth Engine (GEE) platform. The dynamic trends of LULC changes were analyzed, and geographical detectors quantitatively evaluated the key driving factors of these changes. The results showed that (1) the overall classification accuracy varied between 89.14% and 91.41%, and the kappa values were greater than 86.55%, indicating that the classification results were reliably accurate. (2) The major LULC types in the study area were grassland and forest, and their area accounted for 50% and 25%, respectively. During the study period, the grassland area decreased, while the area of forest land and construction land increased to varying degrees. The land-use intensity presents multi-level intensity, and it was higher in the northeast than that in the southwest. (3) Elevation and population density were the major driving factors of LULC changes, and economic development has also significantly affected LULC. These findings revealed the main factors driving LULC changes in Gannan Prefecture and provided a reference for assisting in the development of sustainable land management and ecological protection policy decisions.

Understanding the driving forces of land use/cover change (LUCC) is a requisite to mitigate and manage effects and consequences of LUCC. This study aims to analyze drivers of LUCC in New England, USA. It combines meta-study, GIS, and machine learning to identify the important factors of LUCC in the area. Firstly, we conducted a meta-study of the research on LUCC in the New England area and specifically focused on the driving forces analysis. The meta-analysis revealed that the LUCC studies in the research area were highly related with many other research topics, and population and economic factors were the most mentioned drivers of the LUCC. The drivers of LUCC in this study area for the past several decades were relatively well analyzed. However, the study of the main driving forces of recent LUCC is lacking. Then, the determinants of LUCC for the recent years were quantitatively assessed using the random forests (RF) model along with geospatial data processing. Two planning regions in Connecticut and one planning region in Massachusetts were selected to serve as the case study areas. Investigated variables included environmental and biophysical variables, location measures of infrastructure and existing land use, political variables, and demographic and social variables. These drivers were examined for their relations with LUCC processes. Their importance as driving forces was ranked by the RF method. The results show both consistency and inconsistency between the meta-analysis and the RF method. We found that this mixed method can enhance our understanding of driving forces of LUCC and improve the selection quality of important drivers for modeling LUCC. With more solid information, better land management advices for sustainable development may also be provided.

模拟城市土地利用空间变化格局的研究,对未来区域规划以及实现可持续发展具有十分积极的作用。以往基于FLUS的研究栅格尺度较大,如何模拟快速发展中城市的复杂土地利用变化过程,挖掘土地利用变化驱动机制值得进一步探讨。本文构建了耦合FLUS和Markov的城市土地利用格局拟合框架,创新性地引入房价指标表征社会经济属性,以深圳为研究区,基于30 m空间分辨率小栅格尺度的土地利用分类数据和基础地理、路网河网、感兴趣点等多源空间变量,模拟不同发展情景下的未来城市土地利用空间格局,并通过随机森林进行土地利用变化驱动因素分析。研究结果表明:本文提出的耦合FLUS和Markov方法相较于传统CA模型（RFA-CA和Logistic-CA）精度更高（FoM=0.22）,能更准确地模拟快速发展中城市的土地利用变化过程;多情景土地利用格局制图结果验证了城市发展过程中生态控制线的重要性,进一步说明本文拟合框架在未来城市规划布局中的参考价值;医院、娱乐场所等的基础设施和公交、路网密度等的基础交通比自然因素（高程、坡度）对城市发展的影响更大,到海岸线距离会在一定程度上限制深圳内部土地利用变化过程。本研究所构建模型及精细制图结果,可为城市区域规划和空间格局模拟等相关研究提供参考依据和理论基础。

作为联结大气圈和地圈的纽带,水文循环同时承受气候变化和土地利用/覆被变化（LUCC）的双重影响,然而大多数的水文响应研究主要关注未来气候变化对径流的影响,忽略了未来LUCC的作用。因此,本文的研究目的是评估未来气候变化和LUCC对径流的共同影响。首先采用2种全球气候模式（BCC-CSM1.1和BNU-ESM）输出,基于DBC降尺度模型得到未来气候变化情景;然后,利用CA-Markov模型预测未来LUCC情景;最后,通过设置不同的气候和LUCC情景组合,采用SWAT模型模拟汉江流域的未来径流过程,定量评估气候变化和LUCC对径流的影响。结果表明：① 未来时期汉江流域的年降水量、日最高、最低气温相较于基准期（1966—2005年）,在RCP 4.5和RCP 8.5浓度路径下,分别增加4.0%、1.8 ℃、1.6 ℃和3.7%、2.5 ℃、2.3 ℃;② 2010—2050年间,流域内林地和建设用地的面积占比将分别增加2.8%和1.2%,而耕地和草地面积占比将分别减少1.5%和2.5%;③ 与单一气候变化或LUCC情景相比,气候变化和LUCC共同影响下的径流变化幅度最大,在RCP 4.5和RCP 8.5浓度路径下未来时期年平均径流分别增加5.10%、2.67%,且气候变化对径流的影响显著大于LUCC。本文的研究结果将有助于维护未来气候变化和LUCC共同影响下汉江流域的水资源规划与管理。

As a link between the atmosphere and the geosphere, the hydrological cycle is affected by both climate change and Land Use/Cover Change (LUCC). However, most existing research on runoff response focused mainly on the impact of the projected climate variation, neglecting the influence of future LUCC variability. Therefore, the objective of this study is to examine the co-impacts of both projected climate change and LUCC on runoff generation. Firstly, the future climate scenarios under BCC-CSM1.1 and BNU-ESM are both downscaled and corrected by the Daily Bias Correction (DBC) model. Secondly, the LUCC scenarios are predicted based on the Cellular Automaton-Markov (CA-Markov) model. Finally, the Soil and Water Assessment Tool (SWAT) model is used to simulate the hydrological process under different combinations of climate and LUCC scenarios, with the attempt to quantitatively evaluate the impacts of climate change and LUCC on runoff generation. In this study, the Hanjiang River basin is used as the case study area. The results show that: (1) compared with the base period (1966-2005), the annual rainfall, daily maximum and minimum air temperatures during 2021-2060 will have an increase of 4.0%, 1.8 ℃, 1.6 ℃ in RCP4.5 scenario, respectively, while 3.7%, 2.5 ℃, 2.3 ℃ in RCP8.5 scenario, respectively. (2) During 2010-2050, the area proportions of forest land and construction land in the study area will increase by 2.8% and 1.2%, respectively, while those of farmland and grassland will decrease by 1.5% and 2.5%, respectively. (3) Compared with the single climate change or LUCC scenario, the variation range of future runoff under both climate and LUCC is the largest, and the influence of climate change on future runoff is significantly greater than that of LUCC. This study is helpful to maintain the future water resources planning and management of the Hanjiang River basin under future climate and LUCC scenarios.

城镇化快速发展导致区域的生态系统服务衰减,威胁城市的生态安全;掌握城市群地区生态系统服务权衡/协同关系量化,对提升生态系统服务总体效益和维护区域生态安全至关重要。以粤港澳大湾区为研究区域,利用InVEST模型对粤港澳大湾区1995—2018年间产水服务、固碳服务、土壤保持服务、食物供给服务共4项生态系统服务进行评估,设定历史趋势情景、规划情景和生态保护情景,借助GeoSOS-FLUS模型进行2030年生态系统服务情景分析,探讨各种生态系统服务之间的权衡/协同关系。结果表明：① 1995—2018年间,粤港澳大湾区产水服务出现增加趋势,固碳服务、土壤保持服务和食物供给服务出现下降趋势。② 不同类型生态系统服务变化存在明显的区域异质性,产水服务高值区域其值增大,低值区域其值减小;固碳服务低值区域,其值下降更大;除香港外,土壤保持量减小的区域呈零星状分布;食物供给高值及减小的最大值位于东莞、佛山、中山和深圳等中部区域。③ 产水服务在规划情景下达到最佳,固碳服务和土壤保持服务在生态保护情景下最佳,历史趋势情景下食物供给服务最佳,生态系统服务综合效益在生态保护情景下达到最佳。④ 历史趋势情景下生态系统服务之间的权衡程度最大,生态保护情景下各项生态系统服务之间的协同程度较高。基于生态耦合模型进行粤港澳大湾区生态系统服务估算,揭示生态系统服务权衡或协同的变化关系及作用机理,可为区域生态系统服务管理和社会经济发展规划提供参考。

The Guangdong-Hong Kong-Macao Greater Bay Area is facing the challenge of the increasingly serious lack of ecosystem services, which greatly hinders the implementation of the national construction strategy and the sustainable economic development of the Greater Bay Area. It is critical to understand the quantification of ecosystem services trade-offs / synergies relationships in urban agglomeration so as to enhance the overall effectiveness of ecosystem services and maintenance. Two models are introduced in this paper. Firstly, a future land-use simulation （GeoSOS-FLUS） model was employed for a 12-year （up to 2030） land-use distribution under three scenarios, namely, history trend, planning and ecological protection, respectively. Secondly, 4 ecosystem services from 1995 to 2030, which are water service, the carbon sequestration, soil conservation, and food supply, are evaluated by using InVEST model in the study area. Then, trade-off or collaborative relationship between each pair of ecosystem service types are explored and discussed. The results are as follows. （1） The water service increased from 1995 to 2008 while the carbon sequestration, soil conservation and food supply decreased. （2） Each ecological service exhibits an obvious spatiotemporal heterogeneity, in which the water services of areas with high value increase while areas with low value decrease; the carbon sequestration drops greater in lower value area than in the other. Except Hong-Kong, soil conservation of other areas have showed a decreasing trend, which are found sporadically in the entire area; the high and reduced food supply are distributed in central regions such as Dongguan, Foshan, Zhongshan and Shenzhen. （3） Optimal status can be reached for the four ecosystem services, namely, water service under planning scenario, carbon sequestration and soil conservation under ecological protection scenario, food supply under history trend scenario, and comprehensive benefit of ecosystem service under ecological protection scenario. （4） The maximized trade-off relationship between ecosystem services are observed under history trend scenario and the maximized synergies relationship under ecological protection scenario, which witnessed has a stable development trend in 1995-2018. In summary, the estimation of ecosystem service of the Greater Bay Area and explanation to the mechanism of the synergistic effects of the ecosystem service with the ecological coupling models can bring to light the relationship and mechanism among different ecosystem services, and further provide reference for regional ecosystem service management and socio-economic development plan.

There is fragmented land and fragile ecological environment in the loess hilly and gully region. With the rapid population growth and socio-economic development in recent years, the degree of fragmentation has been further aggravated. Therefore, based on the interpretation data of remote sensing images in 1990, 2000 and 2015, this paper uses Fragstats 4.2 to obtain the best analysis scale combined with the standard method and moving window method. On this basis, the spatial differentiation characteristics of each landscape index are explored; The spatial and temporal evolution process of watershed landscape fragmentation is revealed; The spatial autoregressive model is used to analyze the impact factors contributing to landscape fragmentation. The results show that with the change of grain size and extent, some landscape indices show a regularity to certain degree. The 90 m grid size and 900 m square window size are the best analysis scales in the Fenhe River Basin; patch density, contagion, effective grid size, and Shannon's diversity index have a spatial agglomeration effect in the three periods, and the spatial agglomeration type distribution has strong similarity. From 1990 to 2015, the spatial pattern of landscape fragmentation in the study area has obviously changed; the slope, elevation and distance from the construction land are the main factors affecting landscape fragmentation of river basin during the three periods. The research results can provide reference for landscape fragmentation analysis in Northwest China, and provide basis for future regional landscape pattern optimization and effective land management.