Comparisons of cropland area from multiple datasets over the past 300 years in the traditional cultivated region of China

Land use/cover change is an important parameter in the climate and ecological simulations. Although they had been widely used in the community, SAGE dataset and HYDE dataset, the two representative global historical land use datasets, were little assessed about their accuracies in regional scale. Here, we carried out some assessments for the traditional cultivated region of China （TCRC） over last 300 years, by comparing SAGE2010 and HYDE （v3.1） with Chinese Historical Cropland Dataset （CHCD）. The comparisons were performed at three spatial scales： entire study area, provincial area and 60 km by 60 km grid cell. The results show that （1） the cropland area from SAGE2010 was much more than that from CHCD moreover, the growth at a rate of 0.51% from 1700 to 1950 and -0.34% after 1950 were also inconsistent with that from CHCD. （2） HYDE dataset （v3.1） was closer to CHCD dataset than SAGE dataset on entire study area. However, the large biases could be detected at provincial scale and 60 km by 60 km grid cell scale. The percent of grid cells having biases greater than 70% （〈-70% or 〉70%） and 90% （〈-90% or 〉90%） accounted for 56%-63% and 40%-45% of the total grid cells respectively while those having biases range from -10% to 10% and from -30% to 30% account for only 5%-6% and 17% of the total grid cells respectively. （3） Using local historical archives to reconstruct historical dataset with high accuracy would be a valu- able way to improve the accuracy of climate and ecological simulation.     

Spatio-temporal analysis of cropland change in the Guanzhong area,China, from 1650 to 2016

As one of the most critical impact factors of global change, historical land-use change is an indispensable input in climate and environment simulations. To better understand the cropland change in the Guanzhong area, gazetteers, statistics, and survey data were collected as data sources. Methods of registered tax-paying cropland data collection, selection of time points, and data interpolation and calibration were used to reconstruct changes in the cropland area. The cropland area data at the county level were allocated to 1 km×1 km grid cells. The total cropland area in the Guanzhong area was influenced by changes in population, wars, natural disasters, and land-use types, and it fluctuated from 1650 to 2016. From 1780 to 1830, the cropland expanded in the northern and western parts of Guanzhong area, and the cropland in the north of Qinling Mountains increased slightly. The spatial pattern of cropland reached its maximum range in 1980, and the cropland area declined in the whole study area, especially in the cities of Xi'an and Xianyang in 2016. The comparison between HYDE 3.2 and the data obtained in this study showed that the grid cells of HYDE 3.2 exhibit lower values of cropland area fractions in the Guanzhong Basin and higher values in high-altitude areas around the Guanzhong Basin as compared to those in this study.     

TMPA降水数据在澜沧江流域干旱监测中的评估(英文)

Drought is one of the most destructive disasters in the Lancang River Basin, which is an ungauged basin with strong heterogeneity on terrain and climate. Our validation suggested the version-6 monthly TRMM multi-satellite precipitation analysis (TMPA; 3B43 V.6) product during the period 1998 to 2009 is an alternative precipitation data source with good accuracy. By using the standard precipitation index (SPI), at the grid point (0.25°×0.25°) and sub-basin spatial scales, this work assessed the effectiveness of TMPA in drought monitoring during the period 1998 to 2009 at the 1-month scale and 3-months scale; validated the monitoring accuracy of TMPA for two severe droughts happened in 2006 and 2009, respectively. Some conclusions are drawn as follows. (1) At the grid point spatial scale, in comparison with the monitoring results between rain gauges (SPI1g) and TMPA grid (SPI1s), both agreed well at the 1-month scale for most of the grid points and those grid points with the lowest critical success index (CSI) are distributed in the middle stream of the Lancang River Basin. (2) The same as SPI1s, the consistency between SPI3s and SPI3g is good for most of the grid points at the 3-months scale, those grid points with the lowest were concentrated in the middle stream and downstream of the Lancang River Basin. (3) At the 1-month scale and 3-months scale, CSI ranged from 50% to 76% for most of the grid points, which demonstrated high accuracy of TMPA in drought monitoring. (4) At the 3-months scale, based on TMPA basin-wide precipitation estimates, though we tended to overestimate (underestimate) the peaks of dry or wet events, SPI3s detected successfully the occurrence of them over the five sub-basins at the most time and captured the occurrence and development of the two severe droughts happened in 2006 and 2009. This analysis shows that TMPA has the potential for drought monitoring in data-sparse regions.     

基于DEM的山区气温地形修正模型——以陕西省耀县为例

In mountainous area, spatial interpolation is the traditional method to calculate air temperature by use of observed temperature data. Due to lack of sufficient observation data in mountainous areas many precise interpolation methods could give only coarse result which could not meet the demand of precision agriculture and local climate exploration. Based on DEMs of 25 m resolution, a reversed model is constructed, with which temperature is simulated to the corresponding slope unit from the solar radiation. Taking Yaoxian county as a test area, and mean monthly temperature data as basic information sources, which are collected from 15 weather stations around Yaoxian county in Shaanxi province from the year of 1970 to 2000, a simulation for the solar radiation cell by cell is completed. By simulating solar radiation at each slope and flat cell unit, the terrain revised temperature model could be realized. A comparison between the simulated temperature and the radiation temperature from TM6 thermal infrared image shows that the terrain improved model gets a finer temperature distribution at local level. The accuracy of simulated temperature in mountainous area is higher than it is in flat area.     

陕甘宁地区植被恢复对气候变化和人类活动的响应(英文)

The "Grain for Green Project" initiated by the governments since 1999 were the dominant contributors to the vegetation restoration in the agro-pastoral transitional zone of northern China. Climate change and human activities are responsible for the improvement and degradation to a certain degree. In order to monitor the vegetation variations and clarify the causes of rehabilitation in the Shaanxi-Gansu-Ningxia Region, this paper, based on the MODIS-NDVI and climate data during the period of 2000-2009, analyzes the main charac-teristics, spatial-temporal distribution and reasons of vegetation restoration, using methods of linear regression, the Hurst Exponent, standard deviation and other methods. Results are shown as follows. (1) From 2000 to 2009, the NDVI of the study area was improved progres-sively, with a linear tendency being 0.032/10a, faster than the growth of the Three-North Shelter Forest Program (0.007/10a) from 1982 to 2006. (2) The vegetation restoration is characterized by two fast-growing periods, with an "S-shaped" increasing curve. (3) The largest proportion of the contribution to vegetation restoration was observed in the slightly improved area, followed by the moderate and the significantly improved area; the degraded area is distributed sporadically over southern part of Ningxia Hui Autonomous Region as well as eastern Dingbian of Shaanxi province, Huanxian and Zhengyuan of Gansu province. (4) Climate change and human activities are two driving forces in vegetation restoration; more-over anthropogenic factors such as "Grain for Green Project" were the main causes leading to an increasing trend of NDVI on local scale. However, its influencing mechanism remains to be further investigated. (5) The Hurst Exponent of NDVI time series shows that the vegetation restoration was sustainable. It is expected that improvement in vegetation cover will expand to the most parts of the region.     

Change analysis of rice area and production in China during the past three decades

Rice＇s spatial-temporal distributions, which are critical for agricultural, environ- mental and food security research, are affected by natural conditions as well as socio-eco- nomic developments. Based on multi-source data, an effective model named the Spatial Production Allocation Model （SPAM） which integrates arable land distribution, administrative unit statistics of crop data, agricultural irrigation data and crop suitability data, was used to get a series of spatial distributions of rice area and production with 10-km pixels at a national scale -it was applied from the early 1980s onwards and used to analyze the pattern of spatial and temporal changes. The results show that significant changes occurred in rice in China during 1980-2010. Overall, more than 50% of the rice area decreased, while nearly 70% of rice production increased in the change region during 1980-2010. Spatially, most of the increased area and production were in Northeast China, especially, in Jilin and Heilongjiang; most of the decreased area and production were located in Southeast China, especially, in regions of rapidly urbanization in Guangdong, Fujian and Zhejiang. Thus, the centroid of rice area was moved northeast approximately 230 km since 1980, and rice production about 320 km, which means rice production moved northeastward faster than rice area because of the significant rice yield increase in Northeast China. The results also show that rice area change had a decisive impact on rice production change. About 54.5% of the increase in rice pro- duction is due to the expansion of sown area, while around 83.2% of the decrease in rice production is due to contraction of rice area. This implies that rice production increase may be due to area expansion and other non-area factors, but reduced rice production could largely be attributed to rice area decrease.     

苏北废黄河三角洲近岸沉积物分异特征及输运趋势(英文)

The delta evolution and erosion process of the abandoned Yellow River Delta(AYRD) have been extensively studied. However, the variation of sediment at a large littoral scale along the north coast of Jiangsu is less understood. In this study, the data of surface sediment samples obtained in the littoral area of the Yellow River Delta in 2006 and 2012 is used to study the sediment variability and sediment transport trends by using the geostatistics analysis tool and the grain size trend analysis model. In order to ensure the applicability of the model, the geostatistics method is used to determine the characteristic distance(Dc) with the average range value(Ao) of grain size parameter. Filtering method(removing data that not at a sampling station) is used to improve accuracy of data selection. The results show that sedimentary spatial correlation in Lianyun Port area and southern part of the abandoned Yellow River Delta(AS) is better than that in the northern part of the abandoned Yellow River Delta(AN). Sediment in the area is found to be anisotropy at the northeast–southeast direction. The grain size trend analysis reveals that the sediment trend is towards bayhead and southerly in the Haizhou Bay, southeasterly along the shoreline in the south Lianyun Port, northwesterly in AN and easterly–southeasterly in AS respectively. The investigation of possible relationships between Dc, Ao, sediment transport and delta evolution shows a close link between Dc and Ao of one sediment combination. It is also found that sediment transport trends could reasonably represent the delta evolution to a certain degree.     

基于多回归模型和空间精度验证的地质灾害易发性评价研究（英文）

Geological disasters not only cause economic losses and ecological destruction, but also seriously threaten human survival. Selecting an appropriate method to evaluate susceptibility to geological disasters is an important part of geological disaster research. The aims of this study are to explore the accuracy and reliability of multi-regression methods for geological disaster susceptibility evaluation, including Logistic Regression(LR), Spatial Autoregression(SAR), Geographical Weighted Regression(GWR), and Support Vector Regression(SVR), all of which have been widely discussed in the literature. In this study, we selected Yunnan Province of China as the research site and collected data on typical geological disaster events and the associated hazards that occurred within the study area to construct a corresponding index system for geological disaster assessment. Four methods were used to model and evaluate geological disaster susceptibility. The predictive capabilities of the methods were verified using the receiver operating characteristic(ROC) curve and the success rate curve. Lastly, spatial accuracy validation was introduced to improve the results of the evaluation, which was demonstrated by the spatial receiver operating characteristic(SROC) curve and the spatial success rate(SSR) curve. The results suggest that: 1) these methods are all valid with respect to the SROC and SSR curves, and the spatial accuracy validation method improved their modelling results and accuracy, such that the area under the curve(AUC) values of the ROC curves increased by about 3%–13% and the AUC of the success rate curve values increased by 15%–20%; 2) the evaluation accuracies of LR, SAR, GWR, and SVR were 0.8325, 0.8393, 0.8370 and 0.8539, which proved the four statistical regression methods all have good evaluation capability for geological disaster susceptibility evaluation and the evaluation results of SVR are more reasonable than others; 3) according to the evaluation results of SVR, the central-southern Yunnan Province are the highest sus-ceptibility areas and the lowest susceptibility is mainly located in the central and northern parts of the study area.     

Classification of full-polarization ALOS-PALSAR imagery using SVM in arid area of Dunhuang

Classification is an important process in interpretation of synthetic aperture radar(SAR) imagery. As an advanced instrument for remote sensing, the polarimetric SAR has been applied widely in many fields. The main aim of this paper is to explore the ability of the full-polarization SAR data in classification. The study area is a part of Dunhuang, Gansu Province, China. An L-band full-polarization image of Dunhuang which includes quad-polarization modes was acquired by the ALOS-PALSAR(Advanced Land Observing Satellite–the Phased Array type L-band Synthetic Aperture Radar). Firstly, new characteristic information was extracted by the difference operation, ratio operation, and principal component transform based on the full-polarization(HH, HV or VH, VV) modes SAR data. Then the single-, dual-, full-polarization SAR data and new SAR characteristic information were used to analyze quantitatively the classification accuracy based on the Support Vector Machines(SVM). The results show that classification overall accuracy of single-polarization SAR data is poor, and the highest is 56.53% of VV polarization. The classification overall accuracy of dual-polarization SAR is much better than single-polarization, the highest is 74.77% of HV VV polarization data. The classification overall accuracy of full-polarization SAR is 80.21%, adding the difference characteristic information, ratio characteristic information and the first principal component(PC1) respectively, the overall accuracy increased by 3.09%, 3.38%, 4.14% respectively. When the full-polarization SAR data in combination with the all characteristic information, the classification overall accuracy reached to 91.01%. The full-polarization SAR data in combination with the band math characteristic information or the PC1 can greatly improve classification accuracy.     

中国城市扩展对气温观测的影响及其高估程度(英文)

Since the implementation of the reform and opening up policy in China in the late 1970s, some meteorological stations ’entered’ cities passively due to urban expansion. Changes in the surface and built environment around the stations have influenced observations of air temperature. When the observational data from urban stations are applied in the interpolation of national or regional scale air temperature dataset, they could lead to overestimation of regional air temperature and inaccurate assessment of warming. In this study, the underlying surface surrounding 756 meteorological stations across China was identified based on remote sensing images over a number of time intervals to distinguish the rural stations that ’entered’ into cities. Then, after removing the observational data from these stations which have been influenced by urban expansion, a dataset of background air temperatures was generated by interpolating the observational data from the remaining rural stations. The mean urban heat island effect intensity since 1970 was estimated by comparing the original observational records from urban stations with the background air temperature interpolated. The result shows that urban heat island effect does occur due to urban expansion, with a higher intensity in winter than in other seasons. Then the overestimation of regional air temperature is evaluated by comparing the two kinds of grid datasets of air temperature which are respectively interpolated by all stations’ and rural stations’ observational data. Spatially, the overestimation is relatively higher in eastern China than in the central part of China; however, both areas exhibit a much higher effect than is observed in western China. We concluded that in the last 40 years the mean temperature in China increased by about 1.58℃, of which about 0.01℃ was attributed to urban expansion, with a contribution of up to 0.09℃ in the core areas from the overestimation of air temperature.     

栅格化属性精度损失的评估方法及其尺度效应分析——以四川省1:25 万土地覆被数据为例

选择在600 m~30 km 16 个尺度上,在ArcGIS 中利用常用的面积最大值法(Rule ofMaximum Area,RMA) 对2005 年四川省1:25 万土地覆被矢量数据进行栅格化,并采用两种属性精度损失评估方法：传统的常规分析方法和一种新的基于栅格单元分析方法,来对比分析在这两种评估方法下RMA栅格化的属性(这里是指面积) 精度损失随尺度的变化特征。结果表明：(1) 在同一尺度下采用基于栅格单元方法分析所得的研究区平均属性精度损失大于常规分析方法分析得到的平均属性精度损失,且二者之间的差异在1~10 km内很明显,当栅格单元大于10km时,两种方法得到的平均属性精度损失的差值稳定,且其随尺度的变化曲线趋于平行;(2) 基于栅格单元分析方法不仅能够准确地定量估计RMA栅格化的属性精度损失,而且能客观地反映属性精度损失的空间分布规律;(3) 对四川省1:25 万土地覆被数据进行面积最大值法(RMA)栅格化的适宜尺度域最好不要超过800 m,在该尺度域内数据工作量适宜,且RMA栅格化属性精度损失小于2.5%。     

空间尺度上推方法的精度评价——以内蒙古锡林郭勒盟土地利用数据为例

不同的空间尺度上推方法会导致不同程度的信息丢失、信息歪曲等后果;但目前少有研究在较长的尺度序列上、对不同尺度上推方法所得成果开展精度分析。本研究首先提出尺度上推方法精度评价的三个准则,即:保持土地类型构成特征、保持土地面积精度、保持土地空间分布格局和斑块形态;继而使用格点中心值、最大面积斑块、最大聚合面积斑块等3种尺度上推方法,配合100 m～50 km土地利用数据开展尺度转化实验;最后基于上述评价准则和尺度上推实验所得的系列输出结果,分析了不同尺度上推方法的精度。研究表明:(1)格点中心值上推方法能更好地保留区域土地类型构成、土地面积精度等特征;(2)锡林郭勒盟地区土地研究的适宜尺度应小于10 km,最大不应超过30 km;(3)在尺度上推过程中,土地斑块的平均面积、形态以及空间分布格局对尺度上推成果精度有着重要影响。     

基于GIS的新疆气温数据栅格化方法研究

以新疆99个气象台站1971-2010年年平均气温为数据源,采用多元回归结合空间插值的方法对新疆区域气温数据进行栅格化研究。建立了年平均气温与台站经纬度和海拔高度的多元回归模型,对于残差数据的插值采用了反距离权重法(IDW) 、普通克立格法 (Kriging)和样条函数法(Spline)3种目前应用广泛的空间插值方法,针对于这3种方法进行了基于MAE和RMSIE的交叉验证和对比分析,结果表明在新疆的年平均气温的GIS插值方案中,IDW方法精度总体要高于其他两种插值方法。     

多元统计回归及地理加权回归方法在多尺度人口空间化研究中的应用

对统计型人口数据进行格网形式的空间化可更直观地展示人口的空间分布,但不同的人口空间化建模方法和不同的格网尺度在表达人口空间化结果方面存在差异。本文在人口特征分区的基础上,引入DMSP/OLS夜间灯光对城镇用地进行再分类,采用多元统计回归和地理加权回归方法(GWR),开展人口统计数据空间化多尺度模型研究,生成1 km、5 km和10 km等3个尺度的2010年安徽省人口空间数据,并对3个尺度下2个模型结果进行精度评价与比较。结果表明：人口空间数据精度不仅与建模所用方法关系密切,还受到建模格网尺度大小的影响。基于多元统计回归方法的模型估计人口数与实际人口的平均相对误差值随着尺度的增加而降低,而基于GWR方法获得的人口空间数据误差值随着尺度的增加而升高。整体来看,基于GWR方法的1 km研究尺度的人口空间数据平均相对误差最低(22.31%)。区域地形地貌条件与人口空间数据误差有较强的关联,地貌类型复杂的山区人口空间数据误差较大。     

土地覆被类型空间格局与地形因子的定量关联及其应用

以全国1∶25万土地覆被数据、全国公里网格DEM数据和县级行政区划数据为基础,首先,在国家尺度上宏观分析地形因子对土地覆被类型空间分布格局的影响,土地覆被类型空间分布宏观格局受海拔高度、坡度、地表起伏度的影响明显,而与坡向的关系并不显著;其次,以县级行政单元为统计分析样本,利用多元线性回归分析方法,在国家和区域两个尺度建立土地覆被类型面积占比与主要地形因子之间的定量模型,在6类土地覆被类型中,除草地以外,其他5类土地覆被类型的面积占比均与地形因子之间呈显著相关关系,显著性由高到低的排列顺序依次为森林、农田、荒漠、聚落和湿地水体;最后,以相关性最好的森林的空间分布为例,说明了将所建立的模型应用于栅格单元上某种土地覆被类型面积占比估算的可能性,虽然估算结果与实际情况存在差异,但总体趋势基本保持一致,特别是土地覆被类型面积占比大的区域。     

Torrent risk zonation in the Upstream Red River Basin based on GIS

This paper explores the methodology for compiling the torrent hazard and risk zonation map by means of GIS technique for the Red River Basin in Yunnan province of China, where is prone to torrent. Based on a 1:250,000 scale digital map, six factors including slope angle, rainstorm days, buffer of river channels, maximum runoff discharge of standard area, debris flow distribution density and flood disaster history were analyzed and superimposed to create the torrent risk evaluation map. Population density, farmland percentage, house property, and GDP as indexes accounting for torrent hazards were analyzed in terms of vulnerability mapping. Torrent risk zonation by means of GIS was overlaid on the two data layers of hazard and vulnerability. Then each grid unit with a resolution of 500 m × 500 m was divided into four categories of the risk: extremely high, high, moderate and low. Finally the same level risk was combined into a confirmed zone, which represents torrent risk of the study area. The risk evaluation result in the upper Red River Basin shows that the extremely high risk area of 13,150 km2 takes up 17.9% of the total inundated area, the high risk area of 33,783 km2 is 45.9%, the moderate risk area of 18,563 km2 is 25.2% and the low risk area of 8115 km2 is 11.0%.     

中国传统农区过去300年耕地重建结果的对比分析

土地覆被变化是气候与生态效应模拟研究的重要参量。SAGE和HYDE两个全球历史土地利用数据集在相关研究中得到广泛应用, 但在区域尺度上的应用, 其可靠性如何, 至今少有论及。以我国学者重建的传统农区历史耕地数据集(CHCD) 为基础, 从全区、省区和网格(60 km×60 km) 三个空间尺度, 对SAGE (2010) 和HYDE3.1 数据集中有关中国传统农区历史耕地重建结果进行对比分析, 结果表明:(1) SAGE (2010) 数据集对中国传统农区耕地数量重建是以单一线性插补而得, 其中1700-1950 年是以0.51%的年均增长率线性递增, 1950 年后是以0.34%年均速率线性递减, 这种“标准化”变化趋势不能客观反映传统农区土地垦殖的真实历史, 耕地面积也明显高估, 与CHCD数据集不具有可比性;(2) HYDE3.1 数据集吸纳了区域性研究成果, 使其在总量上与CHCD数据集较为接近, 具有较好的可比性, 但其在省区和网格尺度上与CHCD存在显著差异, 其中相对差异率超过70% (< -70%或> 70%) 的网格占比高达56%~63%, 超过90% (< -90%或> 90%) 的网格占比也高达40%~45%;而相对差异率介于-10%~10%的网格占比仅为5%~6%, 介于-30%~30%的网格占比也仅为17%左右;(3) 充分利用我国丰富的历史文献, 建立更高精度的中国区域历史土地利用数据集, 是提高区域气候与生态效应模拟研究质量的重要保障。     

夜间灯光数据在不同尺度对社会经济活动的预测

以广东省为研究范围,采用双对数线性回归模型、香农信息熵模型和差别指数模型,从21个尺度分析NPP-VIIRS夜间灯光数据与经济普查数据中的企业数、企业从业人员数、营利收入以及资产总值的相关性。结果显示:①夜间灯光数据对经济活动的预测精度随尺度的增大而提升,在预测能力上,城市尺度高于镇街尺度,镇街尺度高于500 m网格尺度。②在更为精细的19个网格尺度分析中发现,1 km网格尺度出现预测精度的显著提升,在10 km网格尺度预测精度提升相对较高并达到了0.69,在35 km网格尺度预测精度开始趋于稳定,不再随着网格尺度显著增长。③在0.5～50 km网格尺度之间,网格尺度越精细,产业类型越呈现单一和不均衡分布的发展特征。随着网格尺度的增加,研究区内的产业类型越趋于多样化和均衡分布的发展特征。     

土地利用数据尺度转换的精度损失分析

由于栅格数据便于空间分析,因而通常将矢量数据转化成栅格数据来进行空间分析.在转化过程中,选用不同的栅格大小,其面积和精度损失是不同的.针对这个问题,以重庆市110万的土地利用矢量数据为例,探讨了不同栅格大小下,各种土地利用类型在转化过程的面积和精度损失.研究表明(1)栅格大小＜100m时,其精度损失均＜3.3%.(2)在1000m时,其精度损失达到50%以上的地类有湖泊、水库坑塘、滩地、农村居民点用地、工交建设用地、戈壁、裸岩石地、平原区旱地和坡度＞25°的旱地,这些地类的平均图斑大小均在＜51hm2.(3)在30m～1000m间,平均图斑大小＜82hm2的地类随着栅格的由小变大,其面积变得比实际面积小;平均图斑大小＞101hm2的地类中除高盖度的草地和河渠之外,却与此相反.     

清代中期苏皖地区耕地数据网格化处理及精度对比

格点化区域历史土地利用数据是进行历史土地利用/土地覆被变化环境效应模拟的基础。本文基于苏皖地区耕地垦殖倾向,分别采用清代中期苏皖地区省域及县域耕地数据进行网格化降尺度处理,分配至10 km×10 km的网格中,并将两种分配结果进行对比评估来定量探讨数据的空间范围大小对格点化数据的精度影响。得到以下结果:①用苏皖省域耕地数据和县域耕地数据模拟的网格化结果之间存在差异,平均差异率为16.61%。相对差异率较小(-10%~10%)的网格有24.55%,较大(>70%或<-70%)的网格有13.3%,主要存在于洪泽湖流域及苏北北部沿江平原(黄河改道前入海口处)。②苏皖地区清代中期耕地的空间分布具有一定的地域差异。耕地垦殖率较高的地区主要集中于苏南平原地区的太仓市和昆山市北部,苏皖西北部的砀山县、丰县和沛县,垦殖率均在80%以上;而苏北北部旧黄河入海口、洪泽湖流域、太湖流域及安徽南部山区丘陵地区垦殖率较低,多在10%左右。③1735 年耕地主要分布于海拔高度≤100 m,坡度≤2°的地区。到1980s 时,不同坡度下的垦殖率有较大增加。