Snow water equivalent over Eurasia in the next 50 years projected by aggregated CMIP3 models

Based on remote sensing snow water equivalent (SWE) data, the simulated SWE in 20C3M experiments from 14 models attending the third phase of the Coupled Models for Inter-comparison Project (CMIP3) was first evaluated by computing the different percentage, spatial correlation coefficient, and standard deviation of biases during 1979–2000. Then, the diagnosed ten models that performed better simulation in Eurasian SWE were aggregated by arithmetic mean to project the changes of Eurasian SWE in 2002–2060. Results show that SWE will decrease significantly for Eurasia as a whole in the next 50 years. Spatially, significant decreasing trends dominate Eurasia except for significant increase in the northeastern part. Seasonally, decreasing proportion will be greatest in summer indicating that snow cover in warmer seasons is more sensitive to climate warming. However, absolute decreasing trends are not the greatest in winter, but in spring. This is caused by the greater magnitude of negative trends, but smaller positive trends in spring than in winter. The changing characteristics of increasing in eastern Eurasia and decreasing in western Eurasia and over the Qinghai-Tibetan Plateau favor the viewpoint that there will be more rainfall in North China and less in the middle and lower reaches of the Yangtze River in summer. Additionally, the decreasing rate and extent with significant decreasing trends under SRES A2 are greater than those under SRES B1, indicating that the emission of greenhouse gases (GHG) will speed up the decreasing rate of snow cover both temporally and spatially. It is crucial to control the discharge of GHG emissions for mitigating the disappearance of snow cover over Eurasia.     

土地利用和气候变化对森林生态系统地上生物量的影响模拟——以江西省泰和县为例（英文）

Global and regional environmental changes such as land use and climate change have significantly integrated and interactive effects on forest. These integrated effects will undoubtedly alter the distribution, function and succession processes of forest ecosystems. In order to adapt to these changes, it is necessary to understand their individual and integrated effects. In this study, we proposed a framework by using coupling models to gain a better understanding of the complex ecological processes. We combined an agent-based model for land use and land cover change(ABM/LUCC), an ecosystem process model(PnET-Ⅱ), and a forest dynamic landscape model(LANDIS-Ⅱ) to simulate the change of forest aboveground biomass(AGB) which was driven by land use and climate change factors for the period of 2010–2050 in Taihe County of southern China, where subtropical coniferous plantations dominate. We conducted a series of land use and climate change scenarios to compare the differences in forest AGB. The results show that:(1) land use, including town expansion, deforestation and forest conversion and climate change are likely to influence forest AGB in the near future in Taihe County.(2) Though climate change will make a good contribution to an increase in forest AGB, land use change can result in a rapid decrease in the forest AGB and play a vital role in the integrated simulation. The forest AGB under the integrated scenario decreased by 53.7%(RCP2.6 + land use), 57.2%(RCP4.5 + land use), and 56.9%(RCP8.5 + land use) by 2050, which is in comparison to the results under separate RCPs without land use disturbance.(3) The framework can offer a coupled method to better understand the complex and interactive ecological processes, which may provide some supports for adapting to land use and climate change, improving and optimizing plantation structure and function,and developing measures for sustainable forest management.     

Evaluating the reliability of global historical land use scenarios for forest data in China

Global historical land use scenarios are widely used to simulate the climatic and ecological effects of changes in land cover; however, reliability evaluation of these scenarios for data on China's forests is missing. By using a historical document-derived Chinese forest dataset(CHFD) for the years 1700–2000, we evaluated the reliability of data on forests in China over three global scenarios—SAGE(Center for Sustainability and the Global Environment), PJ(Pongratz Julia), and KK10(Kaplan and Krumhardt 2010)—through trend-related, quantitative, and spatial comparisons. The results show the following:(1) Although the area occupied by forests in China in the SAGE, PJ, KK10, and CHFD datasets decreased over the past 300 years, there were large differences between global scenarios and CHFD. The area occupied by forests in China in the SAGE scenario for 1700–1990 was 20%–40% more than that according to CHFD, and that occupied by forests in the KK10 from 1700 to 1850 was 32%–46% greater than that in CHFD. The difference between the PJ and CHFD was lower than 20% for most years.(2) Large differences were detected at the provincial and grid cell scales, where the PJ scenario was closer to CHFD in terms of total forested area. Provinces with large differences in terms of trend and quantity were 84% and 92% of all provinces, respectively. Grid cells with relative differences greater than 70% accounted for 60%–80% of all grids.(3) These global historical land use scenarios do not accurately reveal the spatiotemporal pattern of Chinese forests due to differences in the data sources, methods of reconstruction, and spatial scales.     

An approach to spatially explicit reconstruction of historical forest in Northeast China

The spatially explicit reconstruction of historical land-cover datasets plays an important role in studying the climatic and ecological effects of land-use and land-cover change（LUCC）. Using potential natural vegetation（PNV） and satellite-based land use data, we determined the possible maximum distribution extent of forest cover in the absence of human disturbance. Subsequently, topography and climate factors were selected to assess the suitability of land for cultivation. Finally, a historical forest area allocation model was devised on the basis of the suitability of land for cultivation. As a case study, we used the historical forest area allocation model to reconstruct forest cover for 1780 and 1940 in Northeast China with a 10-km resolution. To validate the model, we compared satellite-based forest cover data with our reconstruction for 2000. A one-sample t-test of absolute bias showed that the two-tailed significance was 0.12, larger than the significant level 0.05, suggesting that the model has strong ability to capture the spatial distribution of forests. In addition, we calculated the relative difference of our reconstruction at the county scale for 1780 in Northeast China. The number of counties whose relative difference ranged from-30% to 30% is 99, accounting for 74.44% of all counties. These findings demonstrated that the provincial forest area could be transformed into forest cover maps well using the model.     

热带森林覆被的时空动态评价——以印度Malkangiri district of Orissa为例

Tropical forests have been recognized as having global conservation importance. However,they are being rapidly destroyed in many regions of the world. Regular monitoring of forests is necessary for an adaptive management approach and the successful implementation of ecosystem management. The present study analyses the temporal changes in forest ecosystem structure in tribal dominated Malkangiri district of Orissa,India,during 1973-2004 period based on digitized forest cover maps using geographic information system (GIS) and interpretation of satellite data. Three satellite images Landsat MSS (1973),Landsat TM (1990) and IRS P6 LISS III (2004) were used to determine changes. Six land cover types were delineated which includes dense forest,open forest,scrub land,agriculture,barren land and water body. Different forest types were also demarcated within forest class for better understanding the degradation pattern in each forest types. The results showed that there was a net decrease of 475.7 km2 forest cover (rate of deforestation = 2.34) from 1973 to 1990 and 402.3 km2 (rate of deforestation = 2.27) from 1990 to 2004. Forest cover has changed over time depending on a few factors such as large-scale deforestation,shifting cultivation,dam and road construction,unregulated management actions,and social pressure. A significant increase of 1222.8 km2 agriculture area (1973-2004) clearly indicated the conversion of forest cover to agricultural land. These alterations had resulted in significant environmental consequences,including decline in forest cover,soil erosion,and loss of biodiversity. There is an urgent need for rational management of the remaining forest for it to be able to survive beyond next decades. Particular attention must be paid to tropical forests,which are rapidly being deforested.     

Lake evolution and its implication for environmental changes in China during 1950–2000

Lakes in China have undergone considerable environmental changes during the past 50 years, e.g. lake level, water area changes, as did in the past several thousands years. The enhanced human activities, such as land reclamation, application of chemical fertilizer, land use and cover, irrigation and industrialization in the catchment etc., have played an important role on the recent decades＇ changes of these lakes, although constrained to a great extent by the natural impact. Comparative study on variations of lake volume （water level, depth and area） in the eastern and western lake regions of China during 1950-2000 indicated that, lake volume in the eastern region had approximately undergone a two-stage change, i.e. a dramatic decrease from the 1950s to 1970s, and a continuous increase between the 1980s and 1990s; while, in the western region, lake volume had been decreasing nearly all the time. Further studies on some typical lakes concluded that, climatic change was a primary factor for the variations of lake volume during the past 50 years, although human activities showed important effect.     

1985-2015 年渤海海岸线和围填海的时空变迁研究（英文）

Extraction and analysis of the shoreline and land reclamation patterns are important for studies on topics such as the dynamics of coastal wetland ecological environments, transportation and exchange of material energy in coastal regions, and recruitment of fishery resources. Spatial-temporal variations in the shoreline and land reclamation in the Bohai Sea were analyzed based on 49 Landsat images of 7 periods from 1985 to 2015. The following conclusions were drawn.(1) The extracted shoreline data based on visual interpretation had high precision, and the shoreline extraction errors could be controlled within the theoretical range.(2) Over the past 30 years, the shoreline of the Bohai Sea has exhibited an average rate of change of 188.47 m/a and an average accretion distance of 3.55×10~3 m toward the sea. The fastest rate of shoreline change occurred in Laizhou Bay(134.78 m/a), followed by Bohai Bay(128.20 m/a) and Liaodong Bay(61.69 m/a).(3) The average rate of reclamation was 3.25×10~4 ha/a in the Bohai Sea, where the total area of aquaculture land, unused land, and salt land exceeded 60% of the total reclamation area.(4) The geometric shape of the bay became increasingly complicated from year to year, and the geometric center of gravity of the bay moved rapidly toward the sea. In addition, the area of the bay showed a significant decreasing trend. Therefore, to protect the function and structure of the ecosystem in coastal regions, we must control the scale and rate of land reclamation in the future.     

The simulation of LUCC based on Logistic-CA-Markov model in Qilian Mountain area,China

The Qilian mountain area was examined for using the Logistic-CA-Markov coupling model combined with GIS spatial analyst technology to research the transformation of LUCC, driving force system and simulate future tendency of variation. Results show that:(1) Woodland area decreased by 12.55%, while grassland, cultivated land, and settlement areas increased by 0.22%, 7.92%, and 0.03%, respectively, from 1986 to 2014. During the period of 1986 to 2000, forest degradation in the middle section of the mountain area decreased by 1,501.69 km~2. Vegetation cover area improved, with a net increase of grassland area of 38.12 km~2 from 2000 to 2014.(2) For constructing the system driving force, the best simulation scale was 210m×210m. Based on logistic regression analysis, the contribution(weight) of composite driving forces to land use and cover change was obtained, and the weight value was more objectively compared with AHP and MCE method.(3) In the natural scenarios, it is predicted that land use and cover distribution maps of Qilian mountain area in 2028 and 2042, and the Lee-Sallee index test was adopted. Over the next 27 years(2015–2042), farmland, woodland, grassland, settlement areas show an increasing trend, especially settlements with an obvious change of 0.56%. The area of bare land will decrease by 0.89%. Without environmental degradation, tremendous structural change of LUCC will not occur, and typical characteristic of the vertical zone of the mountain would remain. Farmland and settlement areas will increase, but only in the vicinity of Qilian and Sunan counties.     

近10年洞庭湖区土地利用变化时空特征

The research on the land use/cover change is one of the frontiers and the hot spots in the global change research. Based on the Chinese resource and environment spatial-temporal database,and using the Landsat TM and ETM data of 1990 and 2000 respectively, we analyzed the spatial-temporal characteristics of land use/cover changes in the Dongting Lake area during the last decade. The result shows that during the last ten years there were three land-use types that had changed remarkably. The cultivated land decreased by 0.57% of the total cultivated land. The built-up land and water area expanded, with an increase of 8.97% and 0.43% respectively. The conversion between land use types mostly happened among these three land-use types, especially frequently between cultivated land and water area. The land-use change speed of land-use type is different. Three cities experienced the greatest degree of land-use change among all the administrative districts, which means that the land use in these cities changed much quickly. The following changed area was the west and south of the Dongting Lake area. The slowest changed area is the north and east area.     

Predictions of future hydrological conditions and contribution of snow and ice melt in total discharge of Shigar River Basin in Central Karakoram, Pakistan

The high mountains of Hindu-Kush Karakoram and Himalaya(HKKH) contain a large volume of snow and ice, which are the primary sources of water for the entire mountainous population of HKKH. Thus, knowledge of these available resources is very important in relation to their sustainable use. A Modified Positive Degree Day Model was used to simulate daily discharge with the contribution of snow and ice melt from the Shigar River Basin, Central Karakoram, Pakistan. The basin covers an area of 6,921 km2 with an elevation range of 2,204 to 8,611 m a.s.l.. Forty percent of the total area is glaciated among which 20% is covered by debris and remaining 80% by clean ice and permanent snow. To simulate daily discharge, the entire basin was divided into 26 altitude belts. Remotely sensed land cover types are derived by classifying Landsat images of 2009. Daily temperature and precipitation from Skardu meteorological station is used to calibrate the glacio-hydrological model as an input variable after correlating data with the Shigar station data(r=0.88). Local temperature lapse rate of 0.0075 °C/m is used. 2 °C critical temperature is used to separate rain and snow from precipitation. The model is calibrated for 1988~1991 and validated for 1992~1997. The model shows a good Nash-Sutcliffe efficiency and volume difference in calibration(0.86% and 0.90%) and validation(0.78% and 6.85%). Contribution of snow and ice melt in discharge is 32.37% in calibration period and 33.01% is validation period. The model is also used to predict future hydrological regime up to 2099 by using CORDEX South Asia RCM considering RCP4.5 and RCP8.5 climate scenarios.Predicted future snow and ice melt contributions in both RCP4.5 and RCP8.5 are 36% and 37%, respectively. Temperature seems to be more sensitive as compared to other input variables, which is why the contribution of snow and ice in discharge varies significantly throughout the whole century.     

基于SSP-RCP不同情景的京津冀地区土地覆被变化模拟

如何实现自然与人文双重驱动下的特大城市群地区土地覆被变化的情景模拟,不仅是当前土地覆被变化研究领域的热点问题,也是城镇化可持续发展研究的核心主题之一。本文在对现有土地覆被变化情景模型缺陷进行分析和修正的基础上,构建了自然要素与人文要素耦合驱动的土地覆被情景曲面建模（SSMLC）方法。结合IPCC 2020年发布的共享社会经济路径（SSPs）与典型浓度路径（RCPs）组合的CMIP6 SSP1-2.6、SSP2-4.5和SSP5-8.5的气候情景数据,以及人口、GDP、交通、政策等人文参数,分别实现了SSP1-2.6、SSP2-4.5和SSP5-8.5情景下的京津冀土地覆被变化的情景模拟。模拟结果表明：SSMLC对京津冀地区土地覆被变化模拟的总体精度为93.52%;京津冀地区的土地覆被在2020—2040时段内的变化强度最高（3.12%/10a）,2040年以后的变化强度将逐渐减缓;在2020—2100年间,建设用地增加速度最快,增加率为5.07%/10a。湿地的减少速度最快,减少率为3.10%/10a。2020—2100时段内的京津冀土地覆被在SSP5-8.5情景下的变化强度整体高于在SSP1-2.6和SSP2-4.5情景下的变化强度;GDP、人口、交通和政策等人文因子对京津冀地区耕地、建设用地、湿地和水体的影响强度高于对其他土地覆被类型的影响强度。研究结果证实了SSMLC模型能够有效模拟和定量刻画京津冀地区土地覆被空间分布格局在未来不同情景的时空变化趋势和强度,模拟结果可为京津冀协同一体化的国土空间优化配置与规划、以及生态环境建设提供辅助依据和数据支撑。     

Predicting and assessing changes in NPP based on multi-scenario land use and cover simulations on the Loess Plateau

Land use/cover change(LUCC)is a major factor affecting net primary production(NPP).According to the LUCC of the Loess Plateau from 2005 to 2015,the LUCC patterns in 2025 in three scenarios were predicted by using the Future Land Use Simulation(FLUS)model.Furthermore,taking the average NPP of various land use/cover types in 16 years as the reference scale,the changes in NPP in multi-scenario simulations are predicted and an-alyzed,and the impact of different land use/cover transfers on NPP is quantified.The results are as follows:(1)The land use/cover changes greatly in the baseline and fast development scenarios,and changes relatively little in the ecological protection scenarios.(2)The changes in NPP in different scenarios reflected the significant difference in the ecological protection effect.All the three scenarios promote an NPP increase,but the ecological protection sce-nario can promote NPP increases the most.(3)The changes in NPP caused by LUCC in the three scenarios reflected the significant difference in the various land use/cover types pro-tection effect.Analyzing and predicting NPP changes in multi-scenario LUCC simulations in the future can provide a theoretical basis for decision makers to judge the future changes in ecological environments and ecological protection effects against different policy back-grounds.     

Scenarios of land system change in the Lao PDR: Transitions in response to alternative demands on goods and services provided by the land

Sudden and gradual land use changes can result in different socio-ecological systems, sometimes referred to as regime shifts. The Lao PDR (Laos) has been reported to show early signs of such regime shifts in land systems with potentially major socio-ecological implications. However, given the complex mosaic of different land systems, including shifting cultivation, such changes are not easily assessed using traditional land cover data. Moreover, regime shifts in land systems are difficult to simulate with traditional land cover modelling approaches. A novel simulation approach was employed that focused on simulating changes in land systems rather than focusing on land cover. With the CLUmondo model we simulated three scenarios of potential developments between the years 2010 and 2030 assuming different degrees of international market integration and sustainable growth objectives. Although all scenarios show a decline of shifting cultivation systems, the respective orientation of markets and land governance resulted in strongly different land change trajectories. The land system changes are strongly location dependent and different trajectories are found in different parts of the country. Some scenarios show clear elements of land sparing with intensification of land management in the valleys and re-growth of forest on sloping land. Other scenarios show elements of enhanced multi-functionality. The approach addressed methodological challenges in simulating land system regime shifts and complex mosaic landscapes while accounting for societal demands for different types of goods and services from land systems. The land systems approach allows a nuanced representation of different types of forests and agricultural systems such as shifting cultivation and commercial agricultural plantations. Simulation results contribute to a debate about desired future land use on the national scale including its environmental and socio-economic implications.     

流域土地覆被变化水文效应的模拟——以长江上游源头区梭磨河为例

为分析地表覆被变化的水文效应,以半分布式的地形指数模型 (TOPOMODEL) 为基础,对梭磨河流域1960~1999年逐日流量过程进行了模拟。结果表明,对于流域面积2536km² 的梭磨河流域,该模型也能取得较好的模拟结果。模拟了流域40年来气候波动和地表覆被变化对流域水文的影响。最后在4种不同的流域土地覆被情景下模拟了1960~1999年逐日径流过程。对于实际蒸散发与潜在蒸发有300多mm差距的梭磨河流域,在其它条件不变的情况下,随着流域土地覆被和冠层最大截流量的增加,冠层截流蒸发和流域总蒸发增加,植被蒸腾和土壤表面蒸发减少,土壤水分增加而流域水分含量和饱和层含水量减少。地表径流、地表以下径流、总径流减小。重现期小于20年的洪峰流量减小,但对40年一遇的洪峰流量影响很小,甚至有增加洪峰流量的作用。     

不同土地-气候情景下三江源地区产水和水土流失评价（英文）

探讨三江源地区产水和土壤保持对整个青藏高原地区、黄河流域、长江流域及澜沧江流域的生态稳定和人类社会的可持续发展具有重要意义。以4期(2000年、2005年、2010年、2015年)土地利用现状数据、降水及气温日值数据集、1∶1000000中国土壤数据库为研究的数据源,结合居民点、道路、河流等矢量数据及人口、经济栅格数据集和CCSM4通用气候模式预测成果数据,以三江源地区为案例区,基于FLUS模型和降尺度校正方法设计4种土地利用发展情景和2种气候变化情景,应用InVEST模型对研究区域2030年不同情景下的产水和土壤侵蚀进行定量模拟。结果表明:(1)不同土地利用发展情景下,草地仍然是三江源地区的优势土地利用类型,面积占比始终大于67%。(2)RCP4.5气候情景下,年产水量和土壤侵蚀量增加幅度分别超过7%和3.9%;RCP8.5气候情景下,年产水量和土壤侵蚀量的减少幅度分别超过3.3%和1.3%。(3)气候变化在产水量和土壤侵蚀量变化中起主导作用。气候变化对产水量变化的贡献率高达89.97%–98.00%,对土壤侵蚀模数变化的贡献率在60.49%–95.64%之间;而土地利用类型变化对区域产水量变化的贡献率仅在2.00%–10.03%之间,对土壤侵蚀模数变化的贡献率在4.36%–39.91%之间。因此,三江源地区土地开发策略应综合考虑区域发展、退耕还林还草的投入及产生的生态效益等多方面问题。     

流域LUCC水文效应研究中的若干问题探讨

随着全球变化研究的深入,土地利用/覆被变化(LUCC)的水文效应研究日益成为热点问题。综合国内外研究进展,论文就流域土地利用/覆被变化水文效应研究中的几个问题进行了总结和探讨：子流域和水文响应单元是分布式水文模型对流域基本空间单元的理想划分;对国内外现有的土地利用分类系统进行了适当的调整和归并,建立了基于水文响应研究的土地利用分类系统,将土地利用分为9个Ⅰ级类和21个II级类;土地利用/覆被变化情景分析的常用方法有参照对比法、历史反演法、模型预测法、极端土地利用法、土地利用空间配置法等。     

Exploring the impacts of future tourism development on land use/cover changes

Land use/cover changes (LUCC) are central to tourism because land is used in multiple ways as a resource for tourism-focused activities. Tourism is essentially a geographical phenomenon, encompassing the movement and flow of people (seen as the demand side) and spatial distribution patterns relating to land use consumption (seen as the supply side). However, the impacts of tourism on LUCC are difficult to track and monitor. Contributing factors of this problem include a lack of empirical studies, shortage of micro-level LUCC datasets, and scarce methodological frameworks which can be used for assessments. This paper aims to provide a LUCC modelling approach in order to explore the impacts of tourism development on built-up areas. We developed a Cellular automata model (CA) which integrates Markovian transition probabilities and logistic regression transition suitability maps. LUCC rules for tourism development are framed within the national land use policy guidelines for the development of new tourism accommodation establishments (TAE). This primarily takes into consideration land cover compatibility and the proposed development's proximity to the coastline.Three scenarios were established to explore the impacts of tourism development in LUCC for the year 2020 in a Portuguese coastal region: business as usual (BAU); tourism trends (TOUR); and natural restrictions (NATR). TOUR results indicate that the tourism and urban land use/cover growth is higher and focuses heavily on the coastal region (within 5,000 m) when compared to the other scenarios. The overall results for BAU and NATR show a general convergence with the land use policy guidelines in terms of tourism nucleation and new TAE distance to the coastline.     

Predicting plausible impacts of sets of climate and land use change scenarios on water resources

Our world is changing at an unprecedented rate in terms of climate and land use, but these changes can affect our water resources. Hence, we need a methodology that can predict both their individual and agglomerative ramifications. Using the Little Miami River (LMR) watershed as a case study, this paper describes a spatial analytical approach integrating mathematical modeling and geographical information sciences to quantitatively examine the relative importance of the separate and combined hydrologic and water quality impacts of climate and land use changes.The Hydrologic Simulation Program - Fortran (HSPF) model was chosen in this study to simulate stream flow and nutrient transport process. Five hypothetical climate change scenarios were used to cover the possible ranges of variability in the year 2050. An enhanced population-coupled Markov-Cellular Automata (CA-Markov) land use model was developed to predict the 2050 land use pattern. When these scenarios were incorporated into the HSPF model, the future conditions in the LMR basin were postulated. The findings demonstrated that: 1) the LMR watershed would experience an increase in flow and nutrients under the 2050 land use projection, 2) stream flow and water quality impacts would be amplified when both climate and land use changes were simultaneously considered, 3) land use change (and in the case of the LMR watershed, urbanization) could help to alleviate water shortage during the dry years, 4) total phosphorus and nitrogen would increase under all future climate and land use scenarios; the highest increase was found under the combined wettest and future land use scenarios, and 5) the described approach is effective in simulating the hydrologic and water quality effects of climate and land use changes in a basin scale. These results are relevant to planners; they can be useful in formulating realistic watershed management policies and mitigation measures.     

北京市土地利用空间格局演化模拟及预测

土地利用空间格局的演化模拟可定量地从空间尺度揭示区域土地利用变化的驱动因素,是厘清未来时期内土地变化的重要途径。基于CLUE-S模型,以北京市为研究案例,结合1985、2000和2010年三期土地利用数据,运用Logistic逐步回归方法识别了北京市各种土地利用类型演化的驱动因素,对北京市土地利用空间格局进行模拟。在此基础上,基于北京市社会经济发展、土地利用规划、资源禀赋及生态保护等不同情景,对北京市2020年土地利用空间分布格局进行模拟及预测。结果表明：①不同的时期内,驱动因子对不同土地利用类型的影响呈现差异性,其中交通因素及社会经济因素对土地利用类型的转化率影响较显著,坡度对各个土地利用类型的影响较大。②通过对2010年北京市土地利用变化的模拟结果来看,Kappa指数为87.03%,说明预测结果与实际土地利用情况有较好的一致性。③预测结果显示,北京市的城市发展均表现为继续向外扩展,且以东南、东北为主要扩展方向,但扩张的程度存在差异。