Process and mechanism of arable land change in Hebei Province during the past 50 years

Hebei Province is one of the regions with most densely population, fastest economic growth and most intensive land use in China. The contradiction of land shortage sharpened by high-speed economic development with population growth has become a serious problem, which has restricted regional sustainable development.This paper revealed the basic process, regional differences of change and the gravity center of arable land area according to the long-series statistical data of arable land during the past 50 years. On the basis of the above mentioned, the major driving forces that influence the changes of the arable land are discussed. The research results indicate that there is a trend of obvious fluctuating decrease in arable land area during the last 50 years. The changes of arable land area undergo the process from increase to sharp decrease to gently decrease. The regional disparity of change in arable land area is very notable and the gravity center of arable land area moves to the northeast 49.22 km. Regarding the decrease in arable land, the direct driving forces include adjustments of agricultural structure and reclamation, and indirect driving forces include advance in technology, economic interest and population growth etc.     

On arable land changes in Shandong Province and their driving forces

The decrease of total cultivated area and the lower per capita available arable land resource are now serious problems in Shandong Province, a major agricultural province in China. These problems will become more serious along with the further development of economy. In this paper, based on the statistical information at provincial and county levels, the changes of arable land in Shandong Province and their driving forces during the last 50 years are analyzed. The general changing trends of arable land and per capita available arable land are reducing, and the trends of decrease will continue when the economy is developing. The result of GIS spatial analysis shows that the change of the arable land use in Shandong Province has a regional difference. Eight variables having influences on cultivated land change are analyzed by principal component analysis. The results show that the dynamic development of economy, pressure of social system and progress of scientific techniques in agriculture are the main causes for cultivated land reduction. The principal factors which can be considered as driving forces for arable land change include per capita net living space, total population and per ha grain yield. By using regressive equation, along with analysis on population growth and economic development, cultivated areas in Shandong Province in 2005 and 2010 are predicted respectively. The predicted cultivated areas in Shandong will be 6435.47 thousand ha in 2005 and 6336.23 thousand ha in 2010 respectively.     

On arable land changes in Shandong Province and their driving forces

IntroductionAlmost all the provinces and autonomous regions in China have experienced decrease of arable land in the processes of economic development, population growth and urbanization. The situation is more serious in Shandong Province because of the big population and being an agricultural province. From 1949 to 1999, the arable land was decreased by more than 2 million ha in this province accompanied by rapid population growth. The total population in the province in 1999 was twice of t…     

山东省耕地变化趋势及驱动力研究

根据山东省各市、县的统计资料,分析了山东省50年代以来耕地面积变化的总体趋势、空间差异和驱动因子。结果表明:经济发展动态、社会系统压力和农业科技进步是影响山东省耕地数量变化的三类因素。通过建立多元回归模型,预测出2005和2010年的耕地数量,并对研究结果应用GIS进行了空间表达。研究结果和分析结论对山东省农业可持续发展具有重要意义     

湖南省耕地动态变化及驱动机制研究

利用1949~1999年的统计和普查数据,分析探讨了湖南省近50年来耕地数量变化及区域差异,并在此基础上进一步探讨了影响耕地数量动态变化的驱动机制。结果表明:50年来,湖南省耕地总体态势逐年下降,耕地变化区域差异显著;经济增长是形成湖南省耕地数量变化的主要宏观驱动因子,耕地快速减少在发生时间上与经济发展的增长基本同步,具体则受固定资产投资规模的牵动;在空间分布上具有与地区间经济发展速度和水平的差异相一致的特点。影响耕地数量动态变化驱动机制具体表现为:非农产业的发展建设与人口城镇化的发展对耕地的冲击,种植业效益下降、耕地利用方向的调整以及管理上的不完善和疏漏等。     

区域耕地动态变化及可持续利用评价——以河北省黑龙港地区为例

耕地作为土地中的精华 ,其动态变化及可持续利用无疑是影响区域可持续发展的关键问题。河北省黑龙港地区旱、涝、盐、碱灾害严重 ,是黄淮海平原水土资源条件最差的地区。近年来 ,随着经济发展和人口增长 ,人地矛盾日益突出 ,成为该区域可持续发展的一个关键问题。本文利用黑龙港地区近 5 0年耕地长序列统计资料和近 5年的土地详查数据 ,揭示了耕地数量变化的基本过程及其空间差异 ,并进一步对耕地资源利用的可持续性进行了评价。研究表明 ,近 5 0年来 ,黑龙港地区耕地数量呈明显的波动减少趋势 ,经历了由增加→急剧减→缓慢减少的基本变化过程 ,其中在 1 95 5～ 1 95 8年和 1 96 5～ 1 978年出现两次明显的耕地流失高峰 ;全区域耕地资源利用处于临界可持续 ,其综合指数为 48.2 5。     

塔里木盆地北缘人口与经济重心演变及其关联分析

 以塔里木盆地北缘为研究靶区,利用区域重心概念及其模型,分析了过去45 a（1965-2009年）塔里木盆地北缘人口、GDP、第一产业、第二产和耕地重心演变过程,并借助相关性分析探讨了人口与GDP、第一产业、第二产业及耕地重心演变的关联性。结果表明：（1）在过去的45 a,塔里木盆地北缘人口重心、经济重心均呈现出由西向东方向迁移的趋势。GDP、第一产业、第二产业发展对人口分布起到了决定性的导向作用。而人口分布差异引起了耕地面积的变化。（2）人口与GDP、第一产业、第二产业经向迁移相关性较强,纬向上相关性不显著。（3）过去的45 a,GDP、第二产业与人口分布的不均衡性加剧,第一产业重心相对人口重心偏移距离变化较为复杂,但二者仍存在较大的不均衡性;耕地面积与人口分布的不均衡性日益变小。表明该区域的经济发展与人口分布整体协调性较差。研究成果可为研究区社会经济发展规划提供科学依据。     

21世纪初中国土地利用变化的空间格局与驱动力

Land use and land cover change as the core of coupled human-environment systems has become a potential field of land change science (LCS) in the study of global environmental change. Based on remotely sensed data of land use change with a spatial resolution of 1 km × 1 km on national scale among every 5 years, this paper designed a new dynamic regionalization according to the comprehensive characteristics of land use change including regional differentiation, physical, economic, and macro-policy factors as well. Spatial pattern of land use change and its driving forces were investigated in China in the early 21st century. To sum up, land use change pattern of this period was characterized by rapid changes in the whole country. Over the agricultural zones, e.g., Huang-Huai-Hai Plain, the southeast coastal areas and Sichuan Basin, a great proportion of fine arable land were engrossed owing to considerable expansion of the built-up and residential areas, resulting in decrease of paddy land area in southern China. The development of oasis agriculture in Northwest China and the reclamation in Northeast China led to a slight increase in arable land area in northern China. Due to the "Grain for Green" policy, forest area was significantly increased in the middle and western developing regions, where the vegetation coverage was substantially enlarged, likewise. This paper argued the main driving forces as the implementation of the strategy on land use and regional development, such as policies of "Western Development", "Revitalization of Northeast", coupled with rapidly economic development during this period.     

Spatial patterns and driving forces of land use change in China during the early 21st century

Land use and land cover change as the core of coupled human-environment systems has become a potential field of land change science (LCS) in the study of global environmental change. Based on remotely sensed data of land use change with a spatial resolution of 1 km × 1 km on national scale among every 5 years, this paper designed a new dynamic regionalization according to the comprehensive characteristics of land use change including regional differentiation, physical, economic, and macro-policy factors as well. Spatial pattern of land use change and its driving forces were investigated in China in the early 21st century. To sum up, land use change pattern of this period was characterized by rapid changes in the whole country. Over the agricultural zones, e.g., Huang-Huai-Hai Plain, the southeast coastal areas and Sichuan Basin, a great proportion of fine arable land were engrossed owing to considerable expansion of the built-up and residential areas, resulting in decrease of paddy land area in southern China. The development of oasis agriculture in Northwest China and the reclamation in Northeast China led to a slight increase in arable land area in northern China. Due to the “Grain for Green” policy, forest area was significantly increased in the middle and western developing regions, where the vegetation coverage was substantially enlarged, likewise. This paper argued the main driving forces as the implementation of the strategy on land use and regional development, such as policies of “Western Development”, “Revitalization of Northeast”, coupled with rapidly economic development during this period.     

基于主成分分析法的钦州市耕地面积变化及其驱动力分析

以钦州市为例,采用主成分分析方法,从经济、人口、农业和土地4个方面选取了13个因子,分析其在2001~2010年对耕地面积变化的影响,揭示耕地面积变化的作用机制,从而为制定合理的耕地保护政策提供依据。研究结果表明：① 钦州市耕地面积总体呈逐年下降趋势,年平均减少约460 hm²。② 钦州市耕地面积变化的主要因子是经济社会发展、人口增加和农业生产发展,这3者构成了耕地面积变化主要驱动力。③ 可以从减少建设占用、加强土地开发利用、加强农业结构调整的引导和管理等3个方面遏制钦州市耕地面积减少的势头。     

基于遥感的呼伦贝尔盟农牧业土地利用变化及其对地区农业持续发展影响的研究

随着人口的增长, 人类活动对土地利用/土地覆盖变化的影响越来越大, “人口-资源-环境”问题越来越突出,因此,土地利用/土地覆盖变化的研究尤为重要。本文利用1986年和1996 年两期陆地卫星TM 数据, 分析探讨了呼伦贝尔盟近十年来农牧业土地利用数量变化及其区域差异,并通过计算耕地重心,分析了近十年来呼伦贝尔盟耕地的空间变化规律, 在此基础上进一步探讨了呼伦贝尔盟农牧业土地利用变化对地区农业持续发展的影响。结果表明： 十年来, 呼伦贝尔盟农牧业土地利用变化很大, 耕地面积大幅度增加,草地与未利用地面积减少;农牧业土地利用变化空间差异非常明显,导致十年来呼伦贝尔盟耕地重心向西北方向移动33.15 km , 耕地生态环境发生了显着变化; 呼伦贝尔盟耕地面积大幅度增加, 对合理开发利用耕地资源, 促进地区农业持续发展起到了积极的作用。     

基于参与式调查与主成分分析的金塔绿洲变化驱动力分析

内陆河流域绿洲变化驱动机制是旱区绿洲学研究的核心内容之一。利用1963~2010年的Keyhole存档相片、KATE-200卫星航片、Landsat遥感影像等多源数据,获取了金塔绿洲空间分布及面积变化信息。在此基础上,结合参与式调查和主成分分析方法定量分析绿洲变化的驱动机制。研究表明：近47 a来金塔绿洲总体呈现增长的趋势,绿洲规模不断扩大,至2010年绿洲面积高达539.47 km²。其主要原因是气候变化、人口增加、水资源的开发利用与科技进步、社会经济发展及政策等因子的相互交织作用。气候变化是背景因子,人文因子是绿洲变化的主成分因素,且在不同历史社会背景下,其主导人文因素也不同。     

塔里木河干流土地利用/覆盖变化的社会经济驱动力分析

土地利用/覆盖变化的驱动力分析是土地利用/覆盖研究的一个主要核心内容。利用相关分析和主成分分析,探讨土地利用变化的社会经济驱动力。在驱动力分析的基础上,建立人口因素与土地利用程度的分异模型,并通过干扰度指数的计算,分析人类活动对不同景观类型的干扰强度。研究结果表明：研究区土地利用变化的主要社会经济驱动力为：人口因素、经济因素、技术因素和区域社会经济发展程度等。人类活动对建设用地的干扰强度最大,其次是林地、耕地和水域,而对于其他景观类型的干扰度则不甚明显。人口密度与土地利用程度的分异模型适用于分析现阶段人口密度与土地利用程度之间的关系,而且还可以通过预测未来人口变化状况进行土地利用程度的预测。     

耕地与建设用地变化驱动力比较分析

基于南昌市新建县1991~2005年土地利用和自然社会经济数据,采用数理统计分析方法,定量综合探讨耕地和建设用地变化驱动力。结果表明,社会经济因子对耕地、建设用地变化驱动方向和强弱顺序表现差异性;驱动因素同一性主要表现在,经济发展状况、城镇化水平和人口增长是耕地和建设用地变化的驱动因子主分量;相同驱动因素的影响敏感性也表现出差异性。     

石家庄城市化进程中的耕地变化

利用2000年遥感影像进行土地利用分类,并与1995年土地利用矢量图进行GIS空间叠置分析,结合数理统计分析,判定石家庄市1995~2000年耕地变动的方向与类型,揭示了该区耕地变化的数量特征和空间变化特征,全面分析了影响耕地变动的经济、人口、政策等主要因素,并重点研讨了城市化进程与耕地变动的关系,阐明了石家庄市在目前城镇发展的初级阶段用地的基本特征与存在问题。石家庄市土地利用变化值得注意的两个特殊点是：石家庄市耕地占用的主要原因是建设用地占地 (占耕地减少总量的52.3%,其次是农业内部调整占38%) ,与全国农业内部调整为耕地减少的首要原因 (占耕地减少总量的60%左右,建设占地30%左右) 不同;在石家庄市非农建设占地中,独立工矿用地占了较大部分 (40%)。     

苏州市耕地面积变化的社会经济驱动力差异性分析

基于1972—2005年苏州市统计数据,利用主成分分析和多元线性回归分析苏州市初级生产阶段和工业化阶段耕地面积变化的驱动因子。结果表明:人均地区生产总值和总人口的增加是导致苏州市初级生产阶段和工业化阶段耕地面积减少的最主要驱动因子;而产业结构升级在苏州市初级生产阶段对耕地面积减少起到了推动作用,在工业化阶段则减缓了经济发展对耕地占用的压力;城市化率的提高在工业化阶段对耕地面积减少起到了减缓作用。在工业化阶段,苏州市不同地区耕地面积变化的驱动因子也存在一定的差异。     

THE DRIVING FORCES OF LAND CHANGE IN THE NORTHERN PIEDMONT OF THE UNITED STATES

Driving forces facilitate or inhibit land‐use / land‐cover change. Human driving forces include political, economic, cultural, and social attributes that often change across time and space. Remotely sensed imagery provides regional land‐change data for the Northern Piedmont, an ecoregion of the United States that continued to urbanize after 1970 through conversion of agricultural and forest land covers to developed uses. Eight major driving forces facilitated most of the land conversion; other drivers inhibited or slowed change. A synergistic web of drivers may be more important in understanding land change than individual drivers by themselves.     

自然与人文交互作用下的干旱区典型绿洲耕地动态变化驱动力分析——以新疆于田绿洲为例

 绿洲是干旱区独特的自然景观,是人们生产生活的载体。如何在保持经济发展、提高人民生活水平的基础上保护有限的耕地资源,是关系到干旱区绿洲和谐以及可持续发展的重要问题。选取干旱区典型绿洲——于田县1949\_2004年的自然与人文统计资料,首先分析了五十余年来该县耕地变化的情况。然后从自然与人文两个角度对影响耕地面积变化的因子进行分析,结果表明,自然因素往往构成一定区域绿洲发展的基本限制,人为因素在短时期内,对耕地的变化起着决定性作用,这种作用如果顺应自然因素的限制,则对绿洲发展有利,绿洲稳定性增强;反之,绿洲稳定性减弱,由于新疆绿洲外围多为戈壁及沙漠,因此,对绿洲的利用要遵循自然规律,以保护绿洲为前提,合理利用水等自然资源,否则绿洲的面积随时都有可能缩小。     

沿海发达地区土地利用转换的人文驱动机制研究--以温州市为例

随着区域土地利用研究的日益深入,区域土地利用的转化及其驱动机制成为学术研究的新热点。国内外区域土地利用转化的研究表明,人文因素是区域土地利用转化主导驱动力的观点已得到共识,但其驱动机制及其驱动力的传导机制仍需进一步探讨。本文通过文献资料搜索和实地调研,揭示了90年代以来温州市土地利用转化的基本特征。指出土地利用转化的关键性人文因素主要是政策驱动力、经济驱动力与城镇化发展驱动力,这三种驱动力共同存在,相互作用,但同时也具有各自的主导传导机制。为此国家在实施区域土地利用宏观调控时,应当因地制宜,更加关注主导人文驱动力在具体区域环境下的重要程度及其结合过程。     

21世纪初中国土地利用变化的空间格局与驱动力分析

在全球环境变化研究中.以土地利用与土地覆盖动态为核心的人类一环境耦合系统研究逐渐成为土地变化科学(LCS)研究的新动向.基于覆盖中国21世纪初5年间隔的遥感卫星数据获取的1 km网格土地利用变化空间信息.依据近5年土地利用变化区域分异的显著特征,以及自然地理、经济发展与国家宏观政策因素综合考虑.设计针对21世纪初5年新的中国土地利用动态区划图,揭示土地利用变化的空间格局与驱动因素.总体上.21世纪初5年中国处于土地利用快速变化期,黄淮海平原、东南沿海地区与四川盆地城乡建设用地显著扩张,占用大规模优质农田,导致南方水田面积明显减少:西北绿洲农业发展与东北地区开垦导致北方旱地面积略有增加:受西部开发"生态退耕"政策的影响中西部地区林地面积显著增加,国家退耕还林还草政策成效明显,对区域土地覆盖状况的改善产生积极的影响:这一时段国土开发与区域发展战略的实施,包括"西部大开发"、"东北振兴"等国家重大政策,加之快速的经济发展是该阶段土地利用变化格局形成的主要驱动因素.