, 闫慧敏, 刘纪远Spatial pattern of land use intensity in China in 2000
LIUFang, YANHuimin, LIUJiyuan通讯作者:
收稿日期:2015-11-8
修回日期:2016-04-11
网络出版日期:2016-07-25
版权声明:2016《地理学报》编辑部本文是开放获取期刊文献，在以下情况下可以自由使用：学术研究、学术交流、科研教学等，但不允许用于商业目的.
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1 引言
土地利用变化是影响生物多样性和生态服务功能及其稳定性的主要驱动力[1-3]。土地利用变化包括了土地覆被变化和土地利用强度变化[4]。当前土地科学的相关研究主要关注土地覆被变化及其对生态环境的影响,如气候变化[5-6],生物多样性[7],粮食安全[8]等,而忽略了同一类型内部利用强度的差异,而这种细微差异对碳、氮、水等物质循环、生物多样性以及生态系统服务功能具有重要的影响[9-12]。此外,随着人口和粮食消耗的持续增加,土地资源短缺趋势增强[13],合理提高现有土地资源的利用强度是保证土地可持续利用、提高粮食产量和保障国家粮食安全的重要途径[14-15]。因此,继续将目前的土地覆被类型分布数据应用于全球变化模拟分析中已经不再能够准确描述土地利用对生态系统过程和全球变化的影响,必须建立能够适用于在区域层面度量土地利用强度分类、度量指标和方法,度量指标需要能够刻画土地利用强度在空间格局、时间尺度、景观镶嵌关系、变化的可逆性等方面变化[16-18]。尽管土地利用强度及其变化的重要性逐渐达到共识,但过去几十年尚未作为主流课题开展研究[4]。因此,迫切需要将土地科学由土地利用类型变化的研究延伸至土地利用强度变化的研究。在有限土地资源的前提下,由于人口增加进而引发土地产品和服务的需求增加最终造成土地利用强度的提高[19],人口压力[20]及由此引发的市场刺激 [21-22]都会激发人类通过各种方式来驱动有限土地资源上产出和效率的提高,如提高管理方式（如耕地的雨养与灌溉,化肥、农药、土地资源等生产要素的投入等）。这些促进土地集约化利用的因素决定了不同区位土地资源利用强度的空间差异,有限土地资源上不同程度的需求压力和土地管理方式也就是土地利用强度分类系统构建的依据。Ellis等[23]将土地覆被类型结合灌溉和人口密度建立了第一幅全球土地利用强度图。Asselen等[18]建立了描述农业利用与自然植被镶嵌结构的全球土地利用强度分类体系和数据集。Václavík等[24]结合土地利用强度、环境要素和社会经济指标获得全球土地利用特征数据集。然而,在大多数区域上土地利用强度的定量化刻画及其空间格局仍然缺乏清晰的认识[15, 25]。土地利用强度时空过程的刻画需要详尽的监测数据和空间表达[26],当前土地利用强度数据集的空间分辨率较为粗糙（10 km）,在刻画土地利用强度空间异质性方面具有局限性,此外耕地利用强度的影响因素较多,而当前分类系统中仅考虑了灌溉、牲畜类型和密度等要素,而未考虑表征频度特征的耕作熟制等重要信息。
2000年前后,中国经历了新一轮快速的城市化和工业化进程,由土地市场形成初期过渡为“切实保护耕地”和“生态环境建设”并重的两个阶段,中国土地利用面积、分布及利用强度呈现新的特征：土地城市化速度加快,建设用地扩展占用优质耕地资源[27];“西部大开发、东北振兴、中部崛起”等区域发展战略加速人口及劳动力流动[27],农村劳动力的流失引起耕地利用方式和强度的改变[28];同时,国家惠农政策的实施通过激励农民的种粮积极性[29]影响了耕地利用强度[19];国家林业重点工程和生态保护工程使得林地面积增加,同时部分林地转变为单一林种种植园[30];“退牧还草”工程使得草地生态系统呈恢复趋势[31],但草畜平衡管理可能刺激天然草地转为人工草地,草场利用强度提高[32]。土地利用强度的变化直接影响土地系统可持续能力,在保障人口增长和粮食需求的同时兼顾保护生态系统功能背景下,掌握21世纪初中国土地利用强度特征,实现生态—经济—社会系统的协调和可持续发展是当前面临的重要使命。当前国内土地利用强度研究以耕地、城市土地利用集约度研究为主,其他土地利用类型较少涉及[33-40]。在省级或区域尺度上多采用面向农户或地块单元的问卷调查的方法[33-34]。该方法能有效刻画典型样区土地利用强度的变化及其驱动因素,但空间表达能力较弱,且需要大量的人力和物力,不适于大尺度土地利用强度的研究。在全国尺度上主要以省级或县域单元的统计数据为基础[35-40],不足以体现空间细致的差异性。针对全国尺度、高空间分辨率且面向所有土地利用类型的土地利用强度的空间表达未见报道,因此,无法从全国宏观层面把握土地利用强度的空间格局,精细尺度上刻画土地利用强度的空间异质性。
本文集成空间分辨率为1 km的中国土地利用成分栅格数据,反映人类活动强度的人口密度、牲畜类型及密度、灌溉雨养耕地分布和耕作熟制等空间化指标要素构建土地利用强度分类系统,获得2000年空间分辨率1 km的中国土地利用强度分布图,分析土地利用强度的空间分布特征及分异规律,为认识经济发展和生态保护双重驱动下中国土地利用强度的变化轨迹提供方法和数据基础。
2 数据与方法
2.1 数据来源与处理
参与构建土地利用强度分类系统的指标要素包括土地利用、灌溉和雨养耕地分布、耕作熟制,人口密度分布和牲畜类型及密度分布等（图1）。
显示原图|下载原图ZIP|生成PPT图1中国土地利用强度的空间化指标要素
-->Fig. 1Spatial explicit indicators for land use intensity in China
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（1）土地利用 本文中2000年土地利用数据来源于中国科学院地理科学与资源研究所“全国耕地资源遥感监测与耕地保护对策研究”项目组的全国土地利用百分比成分栅格数据库。该数据集是基于1999年和2000年获取的Landsat TM/ETM+遥感影像（30 m）,人工交互目视解译获得,数据质量可靠[41]。数据集中每个成分栅格记录了栅格内各类土地利用类型所占的面积比例,其分辨率为1 km。
（2）灌溉和雨养耕地分布 耕地的灌溉和雨养体现了耕地的水资源条件和管理方式。该数据集来自于全球粮食安全支撑数据分析产品（GFSAD1000 V1.0,http://geography.wr.usgs.gov/science/croplands/）,基于已有的2000年1 km全球耕地数据产品分解获得,数据质量可靠[42-46]。该数据集涵盖了耕地空间分布和面积,以及雨养和灌溉耕作的信息。为了检验该数据在中国的精度,选取全国1974个县域（剔除数据缺失的县域）统计数据中的耕地灌溉面积,与基于GFSAD 1000的耕地灌溉面积进行相关性分析,表明二者显著线性相关（p < 0.001）。因此,GFSAD 1000数据可以体现中国耕地灌溉水平的整体差异。
（3）耕作熟制 耕作熟制体现了耕地利用的频度特征,在本文中用于耕地利用强度的进一步细化。该数据是基于2000年MODIS/EVI（500 m,8天）时序曲线进行提取获得。采用时间序列谐波分析（HANTS）对EVI时序曲线进行去噪重构,结合农业气象站点的作物物候观测资料采用峰值检测法来提取多熟种植信息[47-49]。
（4）人口密度分布 人口数量是决定人类活动对环境影响的重要指标[50],且经常用于指示人类活动与自然环境相互作用的强度[20, 23]。本文将人口密度分布与林地分布空间叠加,采用人口分布的密集程度表征林地利用强度。此外,采用县域人口分布多寡对水资源的利用压力表征水域利用强度。2000年人口密度空间分布栅格数据来源于中国科学院资源环境科学数据中心（http://www.resdc.cn）,空间分辨率为1 km,栅格属性值代表了平方公里范围内的总人口数。由于该数据集缺乏台湾的数据,故采用GPW（Gridded Population of the World）（http://sedac.ciesin.columbia.edu/data/collection/gpw-v3）中台湾人口密度数据对其进行完善。参考已有研究[23],将人口密度分为三级：> 100人/km2为人口密集区,1~100人/km2为人口稀疏区,< 1人/km2为人口极稀区。
（5）牲畜类型及密度分布 牲畜类型和数量直接影响草地利用的强度,本文根据牲畜分布密度对草地利用强度进行空间分类。牲畜密度分布数据来自世界牲畜研究所（ILRI）提供的全球牲畜栅格数据库[51],该数据库基于2000年前后的多源数据集建模实现,涵盖了全球牲畜的类型和密度的空间分布信息,空间分辨率为1 km。考虑到不同类型牲畜的食草方式和食草量不同,引入“热带牲畜单位（TLU）”对牲畜数量进行标准化得到牲畜密度综合指数,计算方法详见Petz等[52]。采用自然断点法将牲畜密度综合指数分为三级：> 10 TLU/km2为牲畜密集区,1~10 TLU /km2为牲畜稀疏区,< 1 TLU /km2为牲畜极稀区。
2.2 土地利用强度分类系统
参考Anderson等[53]提出的理想土地利用分类系统的基本准则,本文确定土地利用强度分类系统的分类准则包括：① 适用性：适用于区域尺度空间范围的研究;② 全面性：涵盖研究区域所有可能存在的类型;③ 层次性：多层次的分类系统便于不同分类的细化和整合;④ 可重复性：在时间维度上分类操作具备可重复性;⑤ 主导性：考虑到混合像元的影响,以主导性原则确定栅格的主导类型。Tab. 1
表1
表1土地利用强度分类系统
Tab. 1Land use intensity classification system
| 一级类 | 二级类 | 描述 |
|---|---|---|
| 人工地类 | 城市 | 城市分布集中区,人口集中 |
| 村庄和工矿用地 | 农村居民点和工矿用地,人口数量多但景观相对破碎化 | |
| 半人工地类(耕地) | 三季水田 | 三季种植的水田 |
| 二季水田 | 两季种植的水田 | |
| 一季水田 | 一季种植的水田 | |
| 三季灌溉 | 三季种植的灌溉旱地 | |
| 二季灌溉 | 两季种植的灌溉旱地 | |
| 一季灌溉 | 一季种植的灌溉旱地 | |
| 三季雨养 | 三季种植的雨养旱地 | |
| 二季雨养 | 两季种植的雨养旱地 | |
| 一季雨养 | 一季种植的雨养旱地 | |
| 休耕地 | 闲置起来以备播种的可耕地 | |
| 半天然地类 (林地、草地和水域) | 高强度利用林地 | 人口分布较密集(> 100人/km2) |
| 低强度利用林地 | 人口分布较稀疏(1~100人/km2) | |
| 自然林地 | 人口分布极为稀少(< 1人/km2) | |
| 高强度利用草地 | 牲畜分布较密集(> 10 TLU/km2) | |
| 低强度利用草地 | 牲畜分布较稀疏(1~10 TLU /km2) | |
| 自然草地 | 牲畜分布极为稀少(< 1 TLU /km2) | |
| 高强度利用水域 | 人口分布较密集(> 100人/km2)的县域内的水域 | |
| 低强度利用水域 | 人口分布较稀疏(1~100人/km2)的县域内的水域 | |
| 自然水域 | 人口分布极为稀少(< 1人/km2)的县域内的水域 | |
| 天然地类(未利用地) | 未利用地 | 沙地、戈壁、盐碱地、沼泽、裸土地和裸岩石砾地 |
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土地利用强度反映了人类活动对自然生态系统的影响程度,本文从体现人类活动的空间格局、利用方式、时间强度以及景观破碎度和影响的可逆性方面来选取测度指标,构建土地利用强度分类系统（表1）。具体而言,根据地表被人类活动干扰程度及其可逆性（恢复至天然土地的难易程度）分为4个一级类型,分别为：① 人工地类,即不透水地表,几乎不可逆;② 半人工地类,即地表土壤层被频繁扰动,可逆;③ 半天然地类,即地表土壤层被偶尔扰动,植被频繁被扰动;④ 天然地类,即地表土壤和植被几乎未被扰动。针对具体地类选取反映人类活动强度的特定指标进一步分类,获得22个二级类型。人工地类根据人口集中程度和景观破碎化程度分为2个二级类,即城市、村庄和工矿用地。半人工地类根据灌溉条件和耕作熟制分为10个二级类,分别为三季水田、二季水田、一季水田、三季灌溉、二季灌溉、一季灌溉、三季雨养、二季雨养、一季雨养和休耕地。半天然地类针对不同土地覆被类型（林地、草地和水域）分别分为高强度利用、低强度利用和自然三个等级,共计9个二级类,林地根据人口分布密集程度分为高强度利用林地、低强度利用林地和自然林地;草地根据牲畜分布密集程度分为高强度利用草地、低强度利用草地和自然草地;水域根据县域人口密集程度对水资源利用的压力分为高强度利用水域、低强度利用水域和自然水域。天然地类包括1个二级类,即未利用地。
3 结果与分析
3.1 中国土地利用强度总体特征
21世纪初,中国半天然地类所占面积比例最大,占全国总面积的58.93%,天然地类和半人工地类面积比例相当,分别为21%和19.36%,人工地类面积比例最小,仅为0.71%。人工地类中城市、村庄和工矿用地的比例相当。半人工地类的土地利用强度涵盖10个级别,其中一季雨养旱地的比例最高,占半人工地类面积的34.69%;其次是一季灌溉旱地,比例为18.29%;一季水田、二季水田和二季灌溉旱地的比例相当,分别为12%、11.11%和10.52%。半天然地类利用强度因土地覆被类型的不同而存在差异。从不同强度利用的面积比例来看,水域的利用强度最高,高强度利用水域面积比例达到32.17%,低强度利用水域面积比例为43.21%。草地的利用强度次之,低强度利用草地的比例最大,为42%;其次是自然草地面积,比例为34.54%;牲畜密度较大的高强度利用草地比例为23.46%。就林地而言,人迹罕至的自然林地的面积比例最大,为56.09%;其次是人口密度较少的低强度利用林地,面积比例为24.83%;而人类稠密区的高强度利用林地面积比例仅为19.09%。3.2 中国土地利用强度宏观空间格局
中国土地利用强度空间分异显著,整体分布特征为,以胡焕庸线为界,人口分布密集的东南部,土地利用强度呈现类型多样化和强度多级化,且整体强度高于人口稀疏的西北地区（图2）。此外,分别在经度和纬度两个维度以1°间距统计土地利用强度类型的面积比例。在纬度方向,整体以半天然地类和半人工地类为主,天然地类在纬度31.5°N~39.5°N范围内面积比例达到20%以上,且在纬度35.5°N~37.5°N达到最大,该范围内有中国最大的塔克拉玛干沙漠。在经度维度,随着经度的增加,土地利用强度类型由以天然地类和半天然地类为主逐渐转变为半天然地类和半人工地类为主。
显示原图|下载原图ZIP|生成PPT图22000年中国土地利用强度空间分布
-->Fig. 2Spatial distribution of land use intensity in China in 2000
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3.3 中国土地利用强度区域化分异
土地利用强度的空间分异还体现为不同土地利用强度类型的区域化集聚分布。结合中国农业综合区域的空间分区,本文对二级土地利用强度类型进行面积统计（表2,图3）,进一步归纳分析。Tab. 2
表2
表22000年中国土地利用强度一级类型分区比例统计
Tab. 2Proportion statistics on the first-level land use intensity at regional level in China in 2000
| 分区 | 人工地类(%) | 半人工地类(%) | 半天然地类(%) | 天然地类(%) |
|---|---|---|---|---|
| 东北区 | 13.20 | 17.88 | 10.12 | 2.20 |
| 内蒙及长城沿线区 | 5.42 | 8.74 | 10.22 | 2.87 |
| 黄淮海区 | 35.57 | 19.22 | 1.09 | 0.11 |
| 黄土高原区 | 5.10 | 8.81 | 4.23 | 0.07 |
| 长江中下游区 | 15.98 | 18.81 | 10.80 | 0.10 |
| 西南区 | 4.64 | 14.65 | 12.99 | 0.03 |
| 华南区 | 13.62 | 6.15 | 6.56 | 0.02 |
| 甘新区 | 5.78 | 5.07 | 12.89 | 70.93 |
| 青藏区 | 0.70 | 0.66 | 31.09 | 23.67 |
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显示原图|下载原图ZIP|生成PPT图32000年中国土地利用强度二级类型分区比例统计
-->Fig. 3Proportion statistics on the second-level land use intensity at regional level in China in 2000
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人工地类主要分布在黄淮海区、长江中下游区、华南区和东北区。其中黄淮海区建设用地面积最大,长江中下游区和四川盆地的建设用地总面积低于黄淮海平原,但其利用强度较高,城市面积比例均大于70%。
半人工地类在黄淮海区、长江中下游区和东北区的分布面积较广。从利用强度上来看,长江中下游区、华南区和四川盆地的利用强度较高,其中水田比例最大,分别占耕地面积的71.29%、45.70%和30.42%,耕作熟制以一、二季为主,存在三季种植,多熟种植的比例分别为58.11%、64.35%和44.57%。黄淮海区的耕地利用强度次之,以灌溉耕地为主,灌溉和水田比例合计76%,耕作熟制一季、二季比例相当,分别为48.60%和49.80%。东北区的灌溉和水田比例为46.02%,其中水田比例达到13.40%且为一季种植。内蒙及长城沿线区、青藏区、黄土高原区和甘新区的耕地利用强度较低,这些区域雨养旱地广泛分布,分别占各区域耕地面积的86.94%、72.92%、68.86%和63.08%,一季种植比例均超过85%。
半天然地类在青藏区分布面积最广,其次是西南区和甘新区。而针对该地类土地利用强度的综合评估来看,黄淮海区的高强度利用面积比例最高,达到55.94%;东北区和青藏区利用强度较低,自然类的面积比例较高。不同土地覆被类型的利用强度亦存在空间差异。林地分布集中在东北区、长江中下游区、西南区和华南区。长江中下游区和西南区的林地利用强度较高,分别有63.47%和62.41%的林地属于非自然林地。华南区林地利用强度次之,非自然林地比例为52.92%。东北区林地以自然林地为主,占该区域林地面积的78.28%。草地广泛分布在内蒙及长城沿线区、甘新区和青藏区,草地利用强度依次递减。高强度利用草地在内蒙及长城沿线区的比例最高,占区域草地总面积的38.01%;其次是甘新区,占区域草地总面积的15.55%;青藏区以自然草地为主,占区域草地总面积的58.51%,但局部区域存在高强度利用草地。长江中下游区的水域利用强度较高,因为该区域人口分布密集,在西南区和华南区也有类似情况。值得注意的是,黄淮海区水域面积不大,且人口分布密度低于以上区域,但水域利用强度极高,其中高强度利用水域比例达到100%,表明该区域水资源承载压力较大。
天然地类的土地利用程度最低,集中分布在人口稀疏区如甘新区和青藏区,其中甘新区的分布面积最广,占总面积的70.93%,主要因为该区域有大片的沙漠存在。
3.4 中国土地利用强度省际格局
本文对中国省级单元土地利用强度类型进行了面积比例统计,分析土地利用强度的省际格局特征（图4）。
显示原图|下载原图ZIP|生成PPT图42000年中国省级单元土地利用强度一级类型面积统计
-->Fig. 4Area statistics on the first-level land use intensity in each province of China in 2000
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山东省的人工地类面积最大,占全国人工地类总面积的12.03%,其次是江苏省、河北省、广东省和河南省,比例分别为8.87%、8.85%、7.84%和7.07%。半人工地类在黑龙江省、河南省、四川省、山东省、内蒙古自治区、河北省的分布较广,面积均在10×104 km2以上。半天然地类在西藏自治区、内蒙古自治区和新疆维吾尔自治区有广泛分布,分别占全国半天然地类总面积的18.36%、12.82%和10.05%。全国有50.05%的天然地类分布在新疆维吾尔自治区,其次是内蒙古自治区和青海省,面积占比分别为15.47%和13.82%。
按照各省市区内部不同土地利用强度类型的比重来看,澳门、香港、上海市、天津市和北京市的人工地类比例均大于10%,澳门以超过50%的人工地类比例位居全国首位。江苏省、山东省和河南省半人工地类比例较高,均达到70%以上,天津市、河北省、安徽省亦有超过50%的半人工地类的分布。西藏自治区的半天然地类面积比例位居首位,达到85.41%,全国共计17个省市区的半天然地类的面积比例超过60%,主要分布在南部和西部省市区。新疆维吾尔自治区的天然地类面积比例最高,达到61.63%;其次是甘肃省、青海省、内蒙古自治区和西藏自治区,其他各省市区的天然地类比例均低于10%。
为了进一步挖掘省级尺度土地利用强度的分布规律,本文按其地理位置将全部省市区划分为东部、中部和西部[54],并对土地利用强度类型进行分区统计和比较,可看出不同分区间省级差异明显。按照不同一级土地利用强度类型来看（图5）,随着土地利用强度下降,东部省市区所占的比重逐级递减,西部省市区所占比重逐级递增,中部省市区中半人工地类所占比重最大,天然地类比重最小。按照东、中、西部地区内部不同一级土地利用强度类型所占比例来看（图6）,东部和中部省市区均以半人工地类和半天然地类为主,比例合计96%以上,而西部省市区则以半天然地类和天然地类占主导,比例合计90.10%。由此可知,东部省市区土地利用强度高于中、西部省市区,西部省市区土地利用强度最低。
显示原图|下载原图ZIP|生成PPT图52000年中国不同土地利用强度类型在东、中、西部的分布比例
-->Fig. 5Distribution of the first-level land use intensity in Eastern, Central, and Western China in 2000
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显示原图|下载原图ZIP|生成PPT图62000年中国东、中、西部地区内部不同土地利用强度类型比例
-->Fig. 6Proportions of the first-level land use intensity in Eastern, Central, and Western China in 2000
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按照二级土地利用强度类型所占比例的分布情况来看（图7）,东部省市区人工地类中城市、村庄和工矿用地的平均比例及值域范围均高于中部和西部省市区,人类活动较为活跃,水田和灌溉耕地的平均比重较高,且水田略高于灌溉耕地。此外,该区域高强度利用林地比重高于中、西部,比例为11.68%。中部省市区以不同利用强度的林地比例最高,高、中、低强度利用林地比例为10.17%、14.84%和19.37%。其次是灌溉耕地和水田,其中前者比例略高于后者,不同于东部省市区。西部省市区以未利用地的平均比例最高,为16.31%,其次是不同利用强度的林草地,且草地比重整体高于林地,不同于半天然地类以林地为主的东、中部省市区。高强度利用草地比例远高于东、中部省市区,平均比例为12.87%。
显示原图|下载原图ZIP|生成PPT图72000年中国东、中、西部地区土地利用强度二级类型比例统计
-->Fig. 7Proportion statistics of the second-level land use intensity in Eastern, Central, and Western China in 2000
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4 结论与讨论
4.1 结论
本文结合遥感数据、社会经济数据,依据人类活动强度构建中国土地利用强度二级分类系统,获得空间分辨率为1 km的2000年全国土地利用强度空间分布图,刻画全国、区域和省际尺度上中国土地利用强度空间格局特征。主要结论包括：（1）综合地表覆被、人口分布、农林牧渔业经济活动等信息,建立既能够反映人类土地利用活动对地表在空间维度与时间维度的改变,又能够体现土地由人工地类恢复至天然地类的可逆性的土地利用强度分类体系。该分类体系包括4个一级类型和22个二级类型：根据地表扰动的强度、频率以及可逆性,一级分类包括：人工地类、半人工地类、半天然地类和天然地类;二级分类中,人工地类分类依据为人口集中程度和景观破碎化程度,半人工地类分类依据为灌溉条件和耕作制度,半天然地类分类依据为不同土地覆被类型（林地、草地和水域）上的人口分布密度及牲畜分布密度。全国人工地类、半人工地类、半天然地类和天然地类的面积比例分别为0.71%、19.36%、58.93%和21%。
（2）中国土地利用强度呈现明显的宏观空间格局,以胡焕庸线为界,人口分布密集的东南部土地利用强度类型多样,且整体程度高于人口稀疏的西北地区。在纬度方向,整体以半天然地类和半人工地类为主,随着经度增加,土地利用强度类型由以天然地类和半天然地类为主逐渐转变为半天然地类和半人工地类为主,土地利用强度呈增强趋势。
土地利用强度类型呈区域化集聚分布,人工地类主要分布在黄淮海区、长江中下游区、华南区和东北区,黄淮海区面积居首但利用强度低于长江中下游区。半人工地类在黄淮海区、长江中下游区和东北区的分布面积较广,而在长江中下游区、华南区和四川盆地的利用强度较高。半天然地类在青藏区分布面积最广,但利用程度相对较低,黄淮海区的半天然地类的利用强度最高。天然地类集中分布在人口稀疏区如甘新区和青藏区。
（3）土地利用强度省际格局差异明显。东部省市区土地利用强度高于中部省市区,西部省市区土地利用强度最低。由不同土地利用类型构成比例可知,随着土地利用强度的下降,东部省市区所占的面积比例逐级递减,西部省市区所占比例逐级递增。东部和中部省市区均以半人工地类和半天然地类为主,而西部省市区则以半天然地类和天然地类占主导。东部省市区人工地类平均比例及值域范围均高于中部和西部省市区,东、中部省市区半人工地类和半天然地类中林地比重均较大,不同之处在于前者水田平均比例高于灌溉旱地。西部省市区未利用地的平均比例最高,且草地的面积比重和利用程度均高于东、中部省市区。
4.2 讨论
土地利用强度空间格局的详尽刻画是监测土地利用变化的社会环境影响和识别土地利用强度变化的驱动因素的关键。土地利用强度分类系统的构建是土地利用强度空间制图的基础。与以往的土地利用强度分类系统及制图研究[18, 23-24]有如下区别：① 针对不同的地类,未采用统一的分类指标,而是尽可能选取与其密切相关的指标。以林地和草地为例,草地资源作为牲畜的食物来源,其放牧强度与牲畜的密度关系密切[55]。林地则有所不同,林地的采伐强度与人口密度密切有关[56]。② 就耕地利用强度分类而言,除了考虑灌溉条件外,本文引入了表征耕作频度的熟制数据来进一步细化耕地利用强度的分类。该指标通过时间维度上增加耕地资源投入来体现耕地管理的集约化程度,被Boserup认为是反映土地利用强度的较好指标[4]。③ 与已有研究相比,指标要素和分类结果的空间分辨率提高。除耕作熟制数据外,其他指标的分辨率均为1 km。耕作熟制数据分辨率为500 m,通过重采样与其他指标要素保持一致,最终获得空间分辨率为1 km的土地利用强度分类结果。该结果可以提高土地利用强度的空间异质性表达,降低其用于模拟地球系统循环的不确定性。④ 土地利用强度变化是一个多尺度、多维度的过程,是诸多人与土地交互过程的综合,因而土地利用强度系统构建过程中多指标的选择体现了土地利用强度的不同维度和特征,如反映耕地的利用强度的指标考虑了管理方式的不同（灌溉与雨养）,以及利用的时间强度（耕作熟制）,因此,多指标的综合较单一指标更能充分刻画土地利用强度。与当前国内土地利用强度研究主要关注耕地和城市用地类型[33-40]不同的是,本文综合考虑了土地利用的所有类型,为不同土地利用方式与强度对资源环境承载力的影响评估提供更为系统和客观的基础信息。土地利用强度显著的空间分异特征由自然、社会、经济和政策等诸多因素共同作用造成[26]。土地利用强度综合了影响着土地系统变化的自然与人文驱动要素,为深入分析土地系统的历史变化成因、认识人类活动的影响提供重要的数据。The authors have declared that no competing interests exist.
参考文献 原文顺序
文献年度倒序
文中引用次数倒序
被引期刊影响因子
| [1] | Der LUI Index reduziert die verschiedenen, miteinander korrelierten Dimensionen der menschlichen Landnutzung im Grünland zu einer kontinuierlichen Variable und kann dazu dienen, die Abh01ngigkeit verschiedener Organismengruppen und Prozesse von der menschlichen Landnutzung zu prüfen. In Verbindung mit detaillierten Analysen kann die Verwendung dieses Index helfen, die relative Bedeutung der menschlichen Landnutzung im Vergleich zu anderen lokalen oder regionalen Faktoren zu erkennen. |
| [2] | Abstract Ecosystem resilience depends on functional redundancy (the number of species contributing similarly to an ecosystem function) and response diversity (how functionally similar species respond differently to disturbance). Here, we explore how land-use change impacts these attributes in plant communities, using data from 18 land-use intensity gradients that represent five biomes and >2800 species. We identify functional groups using multivariate analysis of plant traits which influence ecosystem processes. Functional redundancy is calculated as the species richness within each group, and response diversity as the multivariate within-group dispersion in response trait space, using traits that influence responses to disturbances. Meta-analysis across all datasets showed that land-use intensification significantly reduced both functional redundancy and response diversity, although specific relationships varied considerably among the different land-use gradients. These results indicate that intensified management of ecosystems for resource extraction can increase their vulnerability to future disturbances. Ecology Letters (2010) 13: 76鈥86 |
| [3] | This issue of Current Opinion in Environmental Sustainability provides an overview of recent advances in Land System Science while at the same time setting the research agenda for the Land System Science community. Land System Science is not just representing land system changes as either a driver or a consequence of global environmental change. Land systems also offer solutions to global change through adaptation and mitigation and can play a key role in achieving a sustainable future earth. The special issue assembles 14 articles that entail different perspectives on land systems and their dynamics, synthesizing current knowledge, highlighting currently under-researched topics, exploring scientific frontiers and suggesting ways ahead, integrating a plethora of scientific disciplines. |
| [4] | |
| [5] | Land-use and land-cover change research needs to pay more attention to processes of land-cover modification, and especially to agricultural land intensification. The objective of this paper is to review the different modelling approaches that have been used in land-use/land-cover change research from the perspective of their utility for the study and prediction of changes in land-use intensification. After clarifying the main concepts used, the different modelling approaches that have been used to study land-use change are examined, case study evidence on processes and drivers of land-use intensification are discussed, and a conclusion is provided on the present ability to predict changes in land-use intensity. The analysis suggests there are differences in the capability of different modelling approaches to assess changing levels of intensification: dynamic, process-based simulation models appear to be better suited to predict changes in land-use intensity than empirical, stochastic or static optimisation models. However, some stochastic and optimisation methods may be useful in describing the decision-making processes that drive land management. Case study evidence highlight the uncertainties and surprises inherent in the processes of land-use intensification. This can both inform model development and reveal a wider range of possible futures than is evident from modelling alone. Case studies also highlight the importance of decision-making by land managers when facing a range of response options. Thus, the ability to model decision-making processes is probably more important in land-use intensification studies then the broad category of model used. For this reason, landscape change models operating at an aggregated level have not been used to predict intensification. In the future, an integrated approach to modelling 鈥 that is multidisciplinary and cross-sectoral combining elements of different modelling techniques 鈥 will probably best serve the objective of improving understanding of land-use change processes including intensification. This is because intensification is a function of the management of physical resources, within the context of the prevailing social and economic drivers. Some of the factors that should be considered when developing future land-use change models are: the geographic and socio-economic context of a particular study, the spatial scale and its influence on the modelling approach, temporal issues such as dynamic versus equilibrium models, thresholds and surprises associated with rapid changes, and system feedbacks. In industrialised regions, predicting land-use intensification requires a better handling of the links between the agriculture and forestry sectors to the energy sector, of technological innovation, and of the impact of agri-environment policies. For developing countries, better representation of urbanisation and its various impacts on land-use changes at rural-urban interfaces, of transport infrastructure and market change will be required. Given the impossibility of specific predictions of these driving forces, most of the modelling work will be aimed at scenario analysis. |
| [6] | Common understanding of the causes of land-use and land-cover change is dominated by simplifications which, in turn, underlie many environment-development policies. This article tracks some of the major myths on driving forces of land-cover change and proposes alternative pathways of change that are better supported by case study evidence. Cases reviewed support the conclusion that neither population nor poverty alone constitute the sole and major underlying causes of land-cover change worldwide. Rather, peoples鈥 responses to economic opportunities, as mediated by institutional factors, drive land-cover changes. Opportunities and constraints for new land uses are created by local as well as national markets and policies. Global forces become the main determinants of land-use change, as they amplify or attenuate local factors. |
| [7] | Land-use intensification is a major threat to biodiversity. So far, however, studies on biodiversity impacts of land-use intensity (LUI) have been limited to a single or few groups of organisms and have not considered temporal variation in LUI. Therefore, we examined total ecosystem biodiversity in grasslands varying in LUI with a newly developed index called multidiversity, which integrates the species richness of 49 different organism groups ranging from bacteria to birds. Multidiversity declined strongly with increasing LUI, but changing LUI across years increased multidiversity, particularly of rarer species. We conclude that encouraging farmers to change the intensity of their land use over time could be an important strategy to maintain high biodiversity in grasslands. |
| [8] | Land system changes are central to the food security challenge. Land system science can contribute to sustainable solutions by an integrated analysis of land availability and the assessment of the tradeoffs associated with agricultural expansion and land use intensification. A land system perspective requires local studies of production systems to be contextualised in a regional and global context, while global assessments should be confronted with local realities. Understanding of land governance structures will help to support the development of land use policies and tenure systems that assist in designing more sustainable ways of intensification. Novel land systems should be designed that are adapted to the local context and framed within the global socio-ecological system. Such land systems should explicitly account for the role of land governance as a primary driver of land system change and food production. |
| [9] | Scenarios of changes in biodiversity for the year 2100 can now be developed based on scenarios of changes in atmospheric carbon dioxide, climate, vegetation, and land use and the known sensitivity of biodiversity to these changes. This study identified a ranking of the importance of drivers of change, a ranking of the biomes with respect to expected changes, and the major sources of uncertainties. For terrestrial ecosystems, land-use change probably will have the largest effect, followed by climate change, nitrogen deposition, biotic exchange, and elevated carbon dioxide concentration. For freshwater ecosystems, biotic exchange is much more important. Mediterranean climate and grassland ecosystems likely will experience the greatest proportional change in biodiversity because of the substantial influence of all drivers of biodiversity change. Northern temperate ecosystems are estimated to experience the least biodiversity change because major land-use change has already occurred. Plausible changes in biodiversity in other biomes depend on interactions among the causes of biodiversity change. These interactions represent one of the largest uncertainties in projections of future biodiversity change. |
| [10] | |
| [11] | |
| [12] | |
| [13] | 党的"十八大"报告提出了建设生态文明,要求推动能源生产和消费革命,这给重塑能源,实现可持续发展提出了新要求、指明了新方向。未来相当长的时间内,要实现经济社会的可持续发展,控制能源消费总量是关键;而优化能源结构,构建"煤炭、石油和天然气、非化石能源"三足鼎立的能源供应格局,则可从"质"上重塑能源、促进可持续发展;加快能源外交新布局,可从合作中推动经济社会与能源的可持续发展。与此同时,应通过科技创新与体制改革为可持续发展创造良好的外部环境与制度保障。 . 党的"十八大"报告提出了建设生态文明,要求推动能源生产和消费革命,这给重塑能源,实现可持续发展提出了新要求、指明了新方向。未来相当长的时间内,要实现经济社会的可持续发展,控制能源消费总量是关键;而优化能源结构,构建"煤炭、石油和天然气、非化石能源"三足鼎立的能源供应格局,则可从"质"上重塑能源、促进可持续发展;加快能源外交新布局,可从合作中推动经济社会与能源的可持续发展。与此同时,应通过科技创新与体制改革为可持续发展创造良好的外部环境与制度保障。 |
| [14] | Increasing population and consumption are placing unprecedented demands on agriculture and natural resources. Today, approximately a billion people are chronically malnourished while our agricultural systems are concurrently degrading land, water, biodiversity and climate on a global scale. To meet the world's future food security and sustainability needs, food production must grow substantially while, at the same time, agriculture's environmental footprint must shrink dramatically. Here we analyse solutions to this dilemma, showing that tremendous progress could be made by halting agricultural expansion, closing 'yield gaps' on underperforming , increasing cropping efficiency, shifting diets and reducing waste. Together, these strategies could double food production while greatly reducing the environmental impacts of agriculture. |
| [15] | Future increases in land-based production will need to focus more on sustainably intensifying existing production systems. Unfortunately, our understanding of the global patterns of land use intensity is weak, partly because land use intensity is a complex, multidimensional term, and partly because we lack appropriate datasets to assess land use intensity across broad geographic extents. Here, we review the state of the art regarding approaches for mapping land use intensity and provide a comprehensive overview of available global-scale datasets on land use intensity. We also outline major challenges and opportunities for mapping land use intensity for cropland, grazing, and forestry systems, and identify key issues for future research. |
| [16] | <h2 class="secHeading" id="section_abstract">Abstract</h2><p id="">Land cover change has always had a central role in land change science. This central role is largely the result of the possibilities to map and characterize land cover based on observations and remote sensing. This paper argues that more attention should be given to land use and land functions and linkages between these. Consideration of land functions that provide a wide range of goods and services makes more integrated assessments of land change possible. The increasing attention to multifunctional land use is another incentive to develop methods to assess changes in land functions. A number of methods to quantify and map the spatial extent of land use and land functions are discussed and the implications for modeling are identified based on recent model approaches in land change science. The mixed use of land cover, land use and land function in maps and models leads to inconsistencies in land change assessments. Explicit attention to the non-linear relations between land cover, land use and land function is essential to consistently address land change. New methods to map and quantify land function dynamics will enhance our ability to understand and model land system change and adequately inform policies and planning.</p> |
| [17] | Aim: To map and characterize anthropogenic transformation of the terrestrial biosphere before and during the Industrial Revolution, from 1700 to 2000. Location: Global. Methods: Anthropogenic biomes (anthromes) were mapped for 1700, 1800, 1900 and 2000 using a rule-based anthrome classification model applied to gridded global data for human population density and land use. Anthropogenic transfo... |
| [18] | Abstract Current global scale land-change models used for integrated assessments and climate modeling are based on classifications of land cover. However, land-use management intensity and livestock keeping are also important aspects of land use, and are an integrated part of land systems. This article aims to classify, map, and to characterize Land Systems (LS) at a global scale and analyze the spatial determinants of these systems. Besides proposing such a classification, the article tests if global assessments can be based on globally uniform allocation rules. Land cover, livestock, and agricultural intensity data are used to map LS using a hierarchical classification method. Logistic regressions are used to analyze variation in spatial determinants of LS. The analysis of the spatial determinants of LS indicates strong associations between LS and a range of socioeconomic and biophysical indicators of human-environment interactions. The set of identified spatial determinants of a LS differs among regions and scales, especially for (mosaic) cropland systems, grassland systems with livestock, and settlements. (Semi-)Natural LS have more similar spatial determinants across regions and scales. Using LS in global models is expected to result in a more accurate representation of land use capturing important aspects of land systems and land architecture: the variation in land cover and the link between land-use intensity and landscape composition. Because the set of most important spatial determinants of LS varies among regions and scales, land-change models that include the human drivers of land change are best parameterized at sub-global level, where similar biophysical, socioeconomic and cultural conditions prevail in the specific regions. |
| [19] | China's urbanization has resulted in significant changes in both agricultural land and agricultural land use. However, there is limited understanding about the relationship between the two primary changes occurring to China's agricultural land 鈥 the urban expansion on agricultural land and agricultural land use intensity. The goal of this paper is to understand this relationship in China using panel econometric methods. Our results show that urban expansion is associated with a decline in agricultural land use intensity. The area of cultivated land per capita, a measurement about land scarcity, is negatively correlated with agricultural land use intensity. We also find that GDP in the industrial sector negatively affects agricultural land use intensity. GDP per capita and agricultural investments both positively contribute to the intensification of agricultural land use. Our results, together with the links between urbanization, agricultural land, and agricultural production imply that agricultural land expansion is highly likely with continued urban expansion and that pressures on the country's natural land resources will remain high in the future. |
| [20] | |
| [21] | |
| [22] | <a name="Abs1"></a>Data on farming systems in Petén, Guatemala, were used to develop an agricultural intensity index. The index can be used to assign an intensity “score” to a given farming system based on the array of practices used by the farmer, each practice’s contribution to production intensity, and the scale at which these practices are used. The scores assigned to 118 farmers in three study areas in Petén were analyzed through analysis of variance (ANOVA) to identify the factors that account for the variation in intensity levels, as measured through the index. The analyses reveal that the factors influencing agricultural intensity in Petén vary greatly from one study area to the next. This is due to differences in livelihood opportunities and strategies that, in turn, affect how agriculture fits into the local economy and how and why intensification is pursued. Variation in intensity levels can best be understood by considering the factors at the household and sub-regional scales that influence (a) whether farmers feel a need to intensify, (b) whether they see some benefit in doing so, and (c) whether they have the resources required to intensify production through particular strategies. Close attention must be paid to these factors by conservation and development organizations seeking to influence land use patterns and conserve forest in Petén. |
| [23] | PubMed comprises more than 23 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites. |
| [24] | Land use is a key driver of global environmental change. Unless major shifts in consumptive behaviours occur, land-based production will have to increase drastically to meet future demands for food and other commodities. One approach to better understand the drivers and impacts of agricultural intensification is the identification of global, archetypical patterns of land systems. Current approaches focus on broad-scale representations of dominant land cover with limited consideration of land-use intensity. In this study, we derived a new global representation of land systems based on more than 30 high-resolution datasets on land-use intensity, environmental conditions and socioeconomic indicators. Using a self-organizing map algorithm, we identified and mapped twelve archetypes of land systems for the year 2005. Our analysis reveals similarities in land systems across the globe but the diverse pattern at sub-national scales implies that there are no 'one-size-fits-all' solutions to sustainable land management. Our results help to identify generic patterns of land pressures and environmental threats and provide means to target regionalized strategies to cope with the challenges of global change. Mapping global archetypes of land systems represents a first step towards better understanding the global patterns of human-environment interactions and the environmental and social outcomes of land system dynamics. |
| [25] | Large knowledge gaps currently exist that limit our ability to understand and characterise dynamics and patterns of land-use intensity: in particular, a comprehensive conceptual framework and a system of measurement are lacking. This situation hampers the development of a sound understanding of the mechanisms, determinants, and constraints underlying changes in land-use intensity. On the basis of a review of approaches for studying land-use intensity, we propose a conceptual framework to quantify and analyse land-use intensity. This framework integrates three dimensions: (a) input intensity, (b) output intensity, and (c) the associated system-level impacts of land-based production (e.g. changes in carbon storage or biodiversity). The systematic development of indicators across these dimensions would provide opportunities for the systematic analyses of the trade-offs, synergies and opportunity costs of land-use intensification strategies. |
| [26] | 土地利用集约化是粮食安全、经 济发展与生态保护等多重压力作用下人类土地利用的必然选择。积极推进土地利用集约化进程,使其向可持续集约化方向发展,对于中国这样人多地少的国家而言, 具有尤为重要的意义。土地利用集约化研究兴起于20世纪60年代,但源流更远的农业生产潜力研究、农业生产要素配置研究等与土地集约利用有关的研究成果, 同样加深了人们对土地利用集约化规律的认识。由于这些工作分散于多个学科领域,相关成果并未得到很好梳理。为了弥补这一不足,本文重点围绕基本特征与测度 指标、极值问题与潜力研究、驱动因素与限制因素、环境影响与可持续集约化等4个方面,简要回顾了至今为止土地利用集约化方面的主要研究成果,并概要介绍了 监测和制图、路径选择、政策选择、城镇用地"集约化"等有待进一步探讨的主要问题。 . 土地利用集约化是粮食安全、经 济发展与生态保护等多重压力作用下人类土地利用的必然选择。积极推进土地利用集约化进程,使其向可持续集约化方向发展,对于中国这样人多地少的国家而言, 具有尤为重要的意义。土地利用集约化研究兴起于20世纪60年代,但源流更远的农业生产潜力研究、农业生产要素配置研究等与土地集约利用有关的研究成果, 同样加深了人们对土地利用集约化规律的认识。由于这些工作分散于多个学科领域,相关成果并未得到很好梳理。为了弥补这一不足,本文重点围绕基本特征与测度 指标、极值问题与潜力研究、驱动因素与限制因素、环境影响与可持续集约化等4个方面,简要回顾了至今为止土地利用集约化方面的主要研究成果,并概要介绍了 监测和制图、路径选择、政策选择、城镇用地"集约化"等有待进一步探讨的主要问题。 |
| [27] | <p>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.</p> |
| [28] | A massive amount of rural labor in China has migrated to urban areas and transferred to non-agricultural employment. This has resulted in issues regarding how to effectively arrange land that was contracted to them under the household contract responsibility system. Using survey data collected in Jiangsu Province and a multinomial logit model, this article discusses three methods of land arrangement utilized by rural–urban migrant workers (family farming, land transfer and abandonment) and examines the correlates of land arrangement methods. We find that there is a significantly positive relation between family size and the family farming option. The improvements in human capital, higher wages, greater job stability, and a longer commute time between migrants’ cities of employment and their hometown are significantly correlated with land transfer or abandonment. These findings can elucidate China’s land policy in the context of massive rural–urban migration. |
| [29] | 选取耕地保护“新政”时期的1999-2007 年为研究时段,以耕地面积与粮食产量变化的分歧原因—耕地生产力变化为切入点,通过比较分析、空间与计量分析探寻粮食安全的关键影响因素。结果表明:农民种粮积极性变化决定着耕地集约利用是影响粮食安全的关键;2003-2007 年农民种粮积极性的持续提高主要来自市场粮价的上涨;粮食直补仅在开始实施的年份激发了农民对种粮收益的预期。此外,本文从提高农民种粮积极性、优化粮食生产投入及改进耕地保护模式3方面,提出了耕地保护发展的政策建议。 . 选取耕地保护“新政”时期的1999-2007 年为研究时段,以耕地面积与粮食产量变化的分歧原因—耕地生产力变化为切入点,通过比较分析、空间与计量分析探寻粮食安全的关键影响因素。结果表明:农民种粮积极性变化决定着耕地集约利用是影响粮食安全的关键;2003-2007 年农民种粮积极性的持续提高主要来自市场粮价的上涨;粮食直补仅在开始实施的年份激发了农民对种粮收益的预期。此外,本文从提高农民种粮积极性、优化粮食生产投入及改进耕地保护模式3方面,提出了耕地保护发展的政策建议。 |
| [30] | As the economies of developing countries grow, and the purchasing power of their inhabitants increases, the pressure on the environment and natural resources will continue to increase. In the specific case of China, impressive economic growth during the last decades exemplifies this process. Specifically, we focus on how changing economic dynamics are influencing land-use and land-cover change in Xishuangbanna, China. Xishuangbanna has the richest flora and fauna of China, but increasing demand for natural rubber and the expansion of rubber plantations is threatening this high-diversity region. We quantified land-use/land-cover change across Xishuangbanna using Landsat images from 1976, 1988, and 2003. The most obvious change was the decrease in forest cover and an increase in rubber plantations. In 1976, forests covered approximately 70% of Xishuangbanna, but by 2003 they covered less than 50%. Tropical seasonal rain forest was the forest type most affect by the expansion of rubber plantations, and a total of 139,576 ha was lost. The increase of rubber plantations below 800 m, shifted agricultural activities to higher elevations, which resulted in deforestation of mountain rain forest and subtropical evergreen broadleaf forest. Although these changes have affected the biodiversity and ecosystem services, we believe that long-term planning and monitoring can achieve a balance between economic and social needs of a growing population and the conservation of a highly diverse flora and fauna. Below 800 m , we recommend that no more rubber plantations be established, existing forest fragments should be protected, and riparian forests should be restored to connect fragments. Future rubber plantations should be established in the abandoned arable or shrublands at higher elevations, and tea or other crops should be planted in the understory to improve economic returns and reduce erosion. |
| [31] | 在3S技术支持下,结合景观格局定量分析方法,基于30m分辨率 的土地利用/覆被数据,对中国退牧还草工程区2000-2010年土地利用/覆被时空分布特征进行研究.通过利用土地利用转移矩阵和动态度来判定土地利用 变化的速度和区域差异,并在斑块类型和景观水平上分析研究区景观格局特征,探讨土地利用格局变化的生态效应.结果表明:①近10年来,研究区土地利用/覆 被类型以草地和其他类用地为主,整体内部结构稳定少动.草地变化面积仅占2000年草地总面积的0.37％;林地、湿地、耕地和人工表面的面积均有所增 加;其他类用地面积有所减少.②全区土地综合动态度均小于0.1％,土地利用/覆被变幅较小,除人工表面较活跃外,其他各类型变化相对缓慢,且各省土地利 用区域差异较小.③研究区内景观基质未发生改变,区域景观破碎度递减,景观多样性水平上升,景观聚集度和连续性微弱下降,景观整体保持较完整态势.退牧还 草工程的实施使土地利用/覆被结构和景观格局均得以优化. . 在3S技术支持下,结合景观格局定量分析方法,基于30m分辨率 的土地利用/覆被数据,对中国退牧还草工程区2000-2010年土地利用/覆被时空分布特征进行研究.通过利用土地利用转移矩阵和动态度来判定土地利用 变化的速度和区域差异,并在斑块类型和景观水平上分析研究区景观格局特征,探讨土地利用格局变化的生态效应.结果表明:①近10年来,研究区土地利用/覆 被类型以草地和其他类用地为主,整体内部结构稳定少动.草地变化面积仅占2000年草地总面积的0.37％;林地、湿地、耕地和人工表面的面积均有所增 加;其他类用地面积有所减少.②全区土地综合动态度均小于0.1％,土地利用/覆被变幅较小,除人工表面较活跃外,其他各类型变化相对缓慢,且各省土地利 用区域差异较小.③研究区内景观基质未发生改变,区域景观破碎度递减,景观多样性水平上升,景观聚集度和连续性微弱下降,景观整体保持较完整态势.退牧还 草工程的实施使土地利用/覆被结构和景观格局均得以优化. |
| [32] | 草畜平衡问题是中国草地畜牧业的核心问题，草畜平衡的理论依据、计算参数存在着争议和分歧。本文主要依据中国载畜量和草畜平衡研究成果，总结了中国草畜平衡研究和实践上的困境。指出以平衡理论为基础的草畜平衡，对主要由降水驱动的干旱、半干旱草地并不具有指导意义。草地生产力时空变异大，根据平均生产力和家畜平均采食量核算的草畜平衡无法做到动态平衡；“季节畜牧业”、“关键场”等理论在解决草畜时空相悖上也充满挑战。家畜单位、存栏数量、合适放牧率等主要估算参数的争议，还不能为草畜平衡实践提供切实可行的决策依据。探索草畜适应性动态管理，协调草地生产的生态、社会和经济功能，应是中国草畜平衡未来的研究重点。 . 草畜平衡问题是中国草地畜牧业的核心问题，草畜平衡的理论依据、计算参数存在着争议和分歧。本文主要依据中国载畜量和草畜平衡研究成果，总结了中国草畜平衡研究和实践上的困境。指出以平衡理论为基础的草畜平衡，对主要由降水驱动的干旱、半干旱草地并不具有指导意义。草地生产力时空变异大，根据平均生产力和家畜平均采食量核算的草畜平衡无法做到动态平衡；“季节畜牧业”、“关键场”等理论在解决草畜时空相悖上也充满挑战。家畜单位、存栏数量、合适放牧率等主要估算参数的争议，还不能为草畜平衡实践提供切实可行的决策依据。探索草畜适应性动态管理，协调草地生产的生态、社会和经济功能，应是中国草畜平衡未来的研究重点。 |
| [33] | |
| [34] | 集约度变化是土地利用变化研究的核心问题，而目前对西部地区耕地 利用集约度特征及原因解释的研究较少。该文采取参与式农村评估法（participatory rural appraisal，PRA），以大渡河上游典型河谷与半山区为例，共调查农户357户，通过Tobit和OLS估计方法，定量对比分析了河谷与半山区耕 地利用集约度及其影响因素。研究表明：河谷区和半山区在耕地利用集约度上存在显著差异。无论是资本集约度还是劳动集约度，河谷区均高于半山区。影响河谷与 半山区耕地利用集约度差异的因素有承包耕地面积、人均实际耕地面积、家庭固定资产、离集镇的距离、二三产业收入、农业劳动力、年需换工数量、人情往来支出 等。耕地资源禀赋和农业劳动力数量是导致集约度差异的关键因素，农业生产条件或环境和家庭收入水平对其有重要影响。 . 集约度变化是土地利用变化研究的核心问题，而目前对西部地区耕地 利用集约度特征及原因解释的研究较少。该文采取参与式农村评估法（participatory rural appraisal，PRA），以大渡河上游典型河谷与半山区为例，共调查农户357户，通过Tobit和OLS估计方法，定量对比分析了河谷与半山区耕 地利用集约度及其影响因素。研究表明：河谷区和半山区在耕地利用集约度上存在显著差异。无论是资本集约度还是劳动集约度，河谷区均高于半山区。影响河谷与 半山区耕地利用集约度差异的因素有承包耕地面积、人均实际耕地面积、家庭固定资产、离集镇的距离、二三产业收入、农业劳动力、年需换工数量、人情往来支出 等。耕地资源禀赋和农业劳动力数量是导致集约度差异的关键因素，农业生产条件或环境和家庭收入水平对其有重要影响。 |
| [35] | 研究目的:研究中国城市土地利用集约度的时空变异规律特征,用来 宏观指导城市土地资源的利用.研究方法:综合评价法,秩相关系数法,聚类分析法.研究结果:(1)1996-2002年中国大多数地区城市土地利用集约度 得到提高,包括福建省、河北省等,而以辽宁省、四川省为代表的10个地区则出现下降趋势,其中以安徽省下降最为显著;(2)东、中、西部地区城市土地利用 集约程度存在明显的递减趋势,其中上海市、北京市最高,甘肃省最低;(3)人口变化是城市土地利用集约度最独特、最具活力的驱动力,政策、经济和技术因素 是重要的外部驱动力.研究结论:应用综合评价法进行城市土地利用集约度评价,其评价结果与现实情况基本吻合,具有一定的可行性. . 研究目的:研究中国城市土地利用集约度的时空变异规律特征,用来 宏观指导城市土地资源的利用.研究方法:综合评价法,秩相关系数法,聚类分析法.研究结果:(1)1996-2002年中国大多数地区城市土地利用集约度 得到提高,包括福建省、河北省等,而以辽宁省、四川省为代表的10个地区则出现下降趋势,其中以安徽省下降最为显著;(2)东、中、西部地区城市土地利用 集约程度存在明显的递减趋势,其中上海市、北京市最高,甘肃省最低;(3)人口变化是城市土地利用集约度最独特、最具活力的驱动力,政策、经济和技术因素 是重要的外部驱动力.研究结论:应用综合评价法进行城市土地利用集约度评价,其评价结果与现实情况基本吻合,具有一定的可行性. |
| [36] | 以价值形态的农作物种植成本为表征指标,对我国 1980-2002年农地利用集约度的变化特征进行了年际间、不同种植业之间与不同区域之间的比较研究.结果表明:①近20多年来,我国农地利用的集约度 不断提高,但在1985-1986年、1993-1994年与1998-2002年,农地利用的集约度出现过三次明显的下降;②我国农地利用主要以物质成 本投入为主;物质成本投入相对稳定,而劳力成本的投入变化较大,其变化同总成本变化同步;③不同种植业生产的集约度有一定差异,但在总的时序变化规律上差 异不明显;④不同区域之间农地利用集约度的变化特征差异显著.低收入地区农地利用集约度的提高幅度比高收入地区大;高收入地区集约度的提高主要依赖于物质 成本的投入,劳力成本投入增加不明显,而低收入地区劳力成本与物质成本的投入比例基本相当,且在1991年以后,劳力成本的投入比例超过了物质成本;从集 约度的波动上看,集约度下降的阶段,收入高的地区下降幅度大,而收入低的地区下降幅度小. . 以价值形态的农作物种植成本为表征指标,对我国 1980-2002年农地利用集约度的变化特征进行了年际间、不同种植业之间与不同区域之间的比较研究.结果表明:①近20多年来,我国农地利用的集约度 不断提高,但在1985-1986年、1993-1994年与1998-2002年,农地利用的集约度出现过三次明显的下降;②我国农地利用主要以物质成 本投入为主;物质成本投入相对稳定,而劳力成本的投入变化较大,其变化同总成本变化同步;③不同种植业生产的集约度有一定差异,但在总的时序变化规律上差 异不明显;④不同区域之间农地利用集约度的变化特征差异显著.低收入地区农地利用集约度的提高幅度比高收入地区大;高收入地区集约度的提高主要依赖于物质 成本的投入,劳力成本投入增加不明显,而低收入地区劳力成本与物质成本的投入比例基本相当,且在1991年以后,劳力成本的投入比例超过了物质成本;从集 约度的波动上看,集约度下降的阶段,收入高的地区下降幅度大,而收入低的地区下降幅度小. |
| [37] | 经济的快速发展引致了对建设用地的大量需求，人地矛盾日益尖锐。倡导城市建设用地的集约利用是实现经济社会可持续发展的有效途径，而提高土地利用集约水平需要掌握其影响因素的作用机理，辨识主导因素。本研究基于影响土地集约利用的经济、制度和生态因素等构建了土地集约利用影响机理的一般理论分析框架，并利用我国1989年～2004年的社会经济和土地利用数据构建计量经济模型对其进行实证研究。研究的结果表明：经济发展和土地市场化发育程度是影响对土地利用集约化水平的重要因素；政府对农地的保护制度在一定程度上激励用地者集约利用土地；而对生态环境的保护是控制土地利用集约度限制性因素；从整体上看，市场化发育水平是影响我国土地利用集约程度的关键性和根本性原因。 . 经济的快速发展引致了对建设用地的大量需求，人地矛盾日益尖锐。倡导城市建设用地的集约利用是实现经济社会可持续发展的有效途径，而提高土地利用集约水平需要掌握其影响因素的作用机理，辨识主导因素。本研究基于影响土地集约利用的经济、制度和生态因素等构建了土地集约利用影响机理的一般理论分析框架，并利用我国1989年～2004年的社会经济和土地利用数据构建计量经济模型对其进行实证研究。研究的结果表明：经济发展和土地市场化发育程度是影响对土地利用集约化水平的重要因素；政府对农地的保护制度在一定程度上激励用地者集约利用土地；而对生态环境的保护是控制土地利用集约度限制性因素；从整体上看，市场化发育水平是影响我国土地利用集约程度的关键性和根本性原因。 |
| [38] | 基于中国农产品成本收益资料与中国农业统计年鉴等基础数据,在对耕地利用集约度进行内部结构划分的基础上,系统分析了1980-2006年间中国粮食作物劳动集约度和资本集约度及其构成的时空变化规律。结果表明:国家尺度上的劳动集约度由1980年的398.5日/hm2快速降低到2006年的130.25日/hm2,下降幅度达67.37%,下降的阶段性明显。资本集约度总量不断上升,其中种子、化肥和农药等增产性资本投入比重逐渐减小,在四大资本投入类型中所占比重由90.36%(1980年)下降到73.44%(2006年),相反,作为省工性投入的机械,所占比重由9.64%(1980年)迅速增加到26.56%(2006年),资本投入的内部结构变化逐渐成为影响中国粮食单产的重要因素。区域尺度上,经济发达地区劳动投入相对较少,资本投入,尤其是省工性资本投入比重较大,农户在耕地利用中更加注重追求劳动生产率;而经济相对落后地区劳动集约度较高,资本集约度较低,资本投入中仍以增产性投入为主,体现了当地农民在耕地利用中追求土地生产率最大化的经营目标。 . 基于中国农产品成本收益资料与中国农业统计年鉴等基础数据,在对耕地利用集约度进行内部结构划分的基础上,系统分析了1980-2006年间中国粮食作物劳动集约度和资本集约度及其构成的时空变化规律。结果表明:国家尺度上的劳动集约度由1980年的398.5日/hm2快速降低到2006年的130.25日/hm2,下降幅度达67.37%,下降的阶段性明显。资本集约度总量不断上升,其中种子、化肥和农药等增产性资本投入比重逐渐减小,在四大资本投入类型中所占比重由90.36%(1980年)下降到73.44%(2006年),相反,作为省工性投入的机械,所占比重由9.64%(1980年)迅速增加到26.56%(2006年),资本投入的内部结构变化逐渐成为影响中国粮食单产的重要因素。区域尺度上,经济发达地区劳动投入相对较少,资本投入,尤其是省工性资本投入比重较大,农户在耕地利用中更加注重追求劳动生产率;而经济相对落后地区劳动集约度较高,资本集约度较低,资本投入中仍以增产性投入为主,体现了当地农民在耕地利用中追求土地生产率最大化的经营目标。 |
| [39] | 为揭示1990-2011年中国耕地利用集约度的时空变化特征， 采用能值理论的研究方法，将耕地利用集约度分解为生产要素集约度和复种指数2个指标的乘积，剖析了中国农业机械、化肥、农药、农膜、劳动力等五大生产要素 集约度和复种指数的时空变化规律。结果表明：1990-2011年，包括农业机械、化肥、农药和农膜4种生产要素的工业辅助能集约度呈线性增长趋势，而劳 动集约度则呈现显著的线性下降趋势，1996年工业辅助能集约度在生产要素集约度中所占比例首次超过50%，表明20世纪90年代中期中国开始进入现代农 业发展阶段；期间复种指数增长率为0.1794，其对于耕地利用集约度的提高起到了关键性作用；1996年劳动集约度高的主要是处于传统农业生产阶段中的 西部农业省份，而工业辅助能集约度高的大都是初步或基本进入现代农业发展阶段的经济发展水平高或工业基础好的省份；1996-2008年，沿海经济发达 区、西部地区和部分粮食主产区劳动集约度下降幅度较大而工业辅助能集约度上升幅度大；1996-2008年，复种指数下降是导致南方水稻主产区耕地利用集 约度下降的主要原因，而绝大多数北方地区耕地利用集约度增长也主要是由于复种指数的增长。 . 为揭示1990-2011年中国耕地利用集约度的时空变化特征， 采用能值理论的研究方法，将耕地利用集约度分解为生产要素集约度和复种指数2个指标的乘积，剖析了中国农业机械、化肥、农药、农膜、劳动力等五大生产要素 集约度和复种指数的时空变化规律。结果表明：1990-2011年，包括农业机械、化肥、农药和农膜4种生产要素的工业辅助能集约度呈线性增长趋势，而劳 动集约度则呈现显著的线性下降趋势，1996年工业辅助能集约度在生产要素集约度中所占比例首次超过50%，表明20世纪90年代中期中国开始进入现代农 业发展阶段；期间复种指数增长率为0.1794，其对于耕地利用集约度的提高起到了关键性作用；1996年劳动集约度高的主要是处于传统农业生产阶段中的 西部农业省份，而工业辅助能集约度高的大都是初步或基本进入现代农业发展阶段的经济发展水平高或工业基础好的省份；1996-2008年，沿海经济发达 区、西部地区和部分粮食主产区劳动集约度下降幅度较大而工业辅助能集约度上升幅度大；1996-2008年，复种指数下降是导致南方水稻主产区耕地利用集 约度下降的主要原因，而绝大多数北方地区耕地利用集约度增长也主要是由于复种指数的增长。 |
| [40] | 土地利用问题日益成为中国经济发展的重要约束力之一。快速城镇化背景下城镇和乡村的快速扩张吞噬了宝贵的土地资源,粗放非集约的利用方式更加剧了土地资源的浪费。从国土空间集约利用的影响机理出发分析中国县域国土空间集约的影响机理对指导集约利用实践以及宏观集约利用政策瞄准和政策矫正都具有特殊意义。综合运用OLS模型、空间面板滞后模型和空间面板自相关模型以GIS 和Matlab 为技术平台,构建中国县域发展基础数据库(1992-2010 年),定量刻画中国2286 个县级单元的空间集约利用度时空变化格局,计量分析社会经济发展、自然环境本底、区位交通地理、宏观战略政策和历史基础5 大类变量17 项具体因素的影响机理。研究结果表明,空间面板数据模型的整体显著性和可信度检验略高于一般面板数据OLS模型;在固定相关效应后对各因素的影响机制进行了检验,表明工业化、城镇化、经济发展水平、区位、交通和宏观战略政策等因素对县域国土空间集约利用的影响较为明显。自然环境因素弱于社会经济因素。被忽略的历史因素对县域国土空间集约利用具有极显著的影响。未来县域国土空间集约利用应因势利导,强化有利因素,减小不利因素影响。提高工业化和城镇化发展水平和质量。发挥市场的主导作用,完善土地市场和运行机制。优化国土空间集约利用调控政策和管治手段,制定差别化的空间集约利用政策。以资源环境承载力为基础和约束最大限度地提高投入和产出水平。 . 土地利用问题日益成为中国经济发展的重要约束力之一。快速城镇化背景下城镇和乡村的快速扩张吞噬了宝贵的土地资源,粗放非集约的利用方式更加剧了土地资源的浪费。从国土空间集约利用的影响机理出发分析中国县域国土空间集约的影响机理对指导集约利用实践以及宏观集约利用政策瞄准和政策矫正都具有特殊意义。综合运用OLS模型、空间面板滞后模型和空间面板自相关模型以GIS 和Matlab 为技术平台,构建中国县域发展基础数据库(1992-2010 年),定量刻画中国2286 个县级单元的空间集约利用度时空变化格局,计量分析社会经济发展、自然环境本底、区位交通地理、宏观战略政策和历史基础5 大类变量17 项具体因素的影响机理。研究结果表明,空间面板数据模型的整体显著性和可信度检验略高于一般面板数据OLS模型;在固定相关效应后对各因素的影响机制进行了检验,表明工业化、城镇化、经济发展水平、区位、交通和宏观战略政策等因素对县域国土空间集约利用的影响较为明显。自然环境因素弱于社会经济因素。被忽略的历史因素对县域国土空间集约利用具有极显著的影响。未来县域国土空间集约利用应因势利导,强化有利因素,减小不利因素影响。提高工业化和城镇化发展水平和质量。发挥市场的主导作用,完善土地市场和运行机制。优化国土空间集约利用调控政策和管治手段,制定差别化的空间集约利用政策。以资源环境承载力为基础和约束最大限度地提高投入和产出水平。 |
| [41] | Land-Use/land Cover Changes (LUCC) are a direct consequence of human and nature interactions. China's Land Use/cover Datasets (CLUD) were updated regularly at five-year intervals from the late 1980s to the year of 2010 with standard procedures based on Landsat TM/ETM + images. A dynamic zoning method was proposed to analyze major land-use conversions. The spatiotemporal characteristics, differences, and causes of land-use changes at a national scale were then examined. The main findings are summarized as follows: Land-Use Changes (LUC) across China indicated a significant variation in spatial and temporal characteristics in the past 20 years between the 20th and 21st centuries. The amount of cropland change decreased in the south and increased in the north, but the total area remained almost unchanged. The reclaimed cropland was shifted from northeast to northwest. The built-up lands were expanded rapidly, which were mainly distributed in the east and gradually spread out to the midwest. Woodland decreased first and then increased, but desert area was inverted. Grassland continued decreasing. Different spatial patterns of LUC in China were found between the late 20th century and the early 21st century. The original 13 LUC zones were replaced by 15 units with changes of boundaries in some zones. The main spatial characteristics of these changes included (1) an accelerated expansion of built-up land in the Huang-Huai-Hai region, the coastal areas of southeastern China, the midstream area of the Yangtze River, and the Sichuan Basin; (2) the shifted land reclamation in the north from Northeast China and eastern Inner Mongolia to the oasis agricultural areas in Northwest China; (3) the continuous transform from rain-fed farmlands in Northeast China to paddy fields; and (4) the effectiveness of the "Grain-for-Green" project in the southern agricultural-pastoral ecotones of Inner Mongolia, the Loess Plateau, and mountainous areas of southwestern China. In recent two decades, although climate change in the north impacted the change in cropland, policy regulation and economic driving forces were still the primary causes of LUC across China. During the first decade of the 21st century, the anthropogenic factors that drove variations in land-use patterns have shifted the emphasis from one-way land development to both development and conservation. The "dynamic zoning method" was used to analyze changes in the spatial patterns of zoning boundaries, the internal characteristics of zones, and the growth and decrease of units. The results revealed "the pattern of the change process," namely the process of LUC and regional differences in characteristics at different stages. The growth and decrease of zones during this dynamic LUC zoning, variations in unit boundaries, and the characteristics of change intensities between the former and latter decades were examined. The patterns of alternative transformation between the "pattern" and "process" of land use and the reasons for changes in different types and different regions of land use were explored. |
| [42] | A Global Irrigated Area Map (GIAM) has been produced for the end of the last millennium using multiple satellite sensor, secondary, Google Earth and groundtruth data. The data included: (a) Advanced Very High Resolution Radiometer (AVHRR) 3-band and Normalized Difference Vegetation Index (NDVI) 10 km monthly time-series for 1997-1999, (b) Syst猫me pour l'Observation de la Terre Vegetation (SPOT ... |
| [43] | 2009c). The other three studies used a combination of national statistics and geospatial tech-niques (Goldewijk et al. 2009; Portmann, Siebert, and D02ll 2009; Ramankutty et al. 2008; Siebertand D02ll 2008, 2009). 2009.09. 010. Khan, S., and MA Hanjra. 2008. |
| [44] | This study examines the suitability of 250 m MODIS (MODerate Resolution Imaging Spectroradiometer) data for mapping global cropland extent. A set of 39 multi-year MODIS metrics incorporating four MODIS land bands, NDVI (Normalized Difference Vegetation Index) and thermal data was employed to depict cropland phenology over the study period. Sub-pixel training datasets were used to generate a set of global classification tree models using a bagging methodology, resulting in a global per-pixel cropland probability layer. This product was subsequently thresholded to create a discrete cropland/non-cropland indicator map using data from the USDA-FAS (Foreign Agricultural Service) Production, Supply and Distribution (PSD) database describing per-country acreage of production field crops. Five global land cover products, four of which attempted to map croplands in the context of multiclass land cover classifications, were subsequently used to perform regional evaluations of the global MODIS cropland extent map. The global probability layer was further examined with reference to four principle global food crops: corn, soybeans, wheat and rice. Overall results indicate that the MODIS layer best depicts regions of intensive broadleaf crop production (corn and soybean), both in correspondence with existing maps and in associated high probability matching thresholds. Probability thresholds for wheat-growing regions were lower, while areas of rice production had the lowest associated confidence. Regions absent of agricultural intensification, such as Africa, are poorly characterized regardless of crop type. The results reflect the value of MODIS as a generic global cropland indicator for intensive agriculture production regions, but with little sensitivity in areas of low agricultural intensification. Variability in mapping accuracies between areas dominated by different crop types also points to the desirability of a crop-specific approach rather than attempting to map croplands in aggregate. |
| [45] | We report on a global cropland extent product at 30-m spatial resolution developed with two 30-m global land cover maps (i.e. FROM-GLC, Finer Resolution Observation and Monitoring, Global Land Cover; FROM-GLC-agg) and a 250-m cropland probability map. A common land cover validation sample database was used to determine optimal thresholds of cropland probability in different parts of the world to generate a cropland/noncropland mask according to the classification accuracies for cropland samples. A decision tree was then applied to combine two 250-m cropland masks: one existing mask from the literature and the other produced in this study, with the 30-m global land cover map FROM-GLC-agg. For the smallest difference with country-level cropland area in Food and Agriculture Organization Corporate Statistical (FAOSTAT) database, a final global cropland extent map was composited from the FROM-GLC, FROM-GLC-agg, and two masked cropland layers. From this map FROM-GC (Global Cropland), we estimated the global cropland areas to be 1533.83 million hectares (Mha) in 2010, which is 6.95 Mha (0.45%) less than the area reported by the Food and Agriculture Organization (FAO) of the United Nations for the year 2010. A country-by-country comparison between the map and the FAOSTAT data showed a linear relationship (FROM-GC = 1.05*FAOSTAT 鈭1.2 (Mha) with =鈥0.97). Africa, South America, Southeastern Asia, and Oceania are the regions with large discrepancies with the FAO survey. |
| [46] | Information related to land cover is immensely important to global change science. In the past decade, data sources and methodologies for creating global land cover maps from remote sensing have evolved rapidly. Here we describe the datasets and algorithms used to create the Collection 5 MODIS Global Land Cover Type product, which is substantially changed relative to Collection 4. In addition to using updated input data, the algorithm and ancillary datasets used to produce the product have been refined. Most importantly, the Collection 5 product is generated at 500-m spatial resolution, providing a four-fold increase in spatial resolution relative to the previous version. In addition, many components of the classification algorithm have been changed. The training site database has been revised, land surface temperature is now included as an input feature, and ancillary datasets used in post-processing of ensemble decision tree results have been updated. Further, methods used to correct classifier results for bias imposed by training data properties have been refined, techniques used to fuse ancillary data based on spatially varying prior probabilities have been revised, and a variety of methods have been developed to address limitations of the algorithm for the urban, wetland, and deciduous needleleaf classes. Finally, techniques used to stabilize classification results across years have been developed and implemented to reduce year-to-year variation in land cover labels not associated with land cover change. Results from a cross-validation analysis indicate that the overall accuracy of the product is about 75% correctly classified, but that the range in class-specific accuracies is large. Comparison of Collection 5 maps with Collection 4 results show substantial differences arising from increased spatial resolution and changes in the input data and classification algorithm. |
| [47] | 农业土地利用活动是人类作用于地球系统最为直接的扰动因素，其变化会因改变生态系统过程与格局以及生态系统资源有效性而对生态系统功能在局地到全球尺度都产生重要的影响。中国南方普遍实施的多熟种植制度是高强度土地利用的重要特征之一，在中国传统的三熟农业区之一——江西省鄱阳湖区域，以农户为管理单元的农业种植制度由于受到洪水风险、经济效益及农业政策的调节，其时空格局动态也因此更加复杂。以分布在鄱阳湖平原的农田为研究区，结合多时相MODIS影像表达的作物生长规律和农业物候观测记录，检测并分析农业多熟种植的时空格局特征。研究结果表明空间分辨率500m、8d合成的MODIS/EVI时间序列数据能够定量表达出农业种植的多熟制特征，可以应用于区域农业多熟种植制度时空分析，研究区种植制度时空格局的形成是农户对气候、社会经济及粮食安全状况响应及适应的结果。在空间和时间上清晰地认识农业多熟种植的特征，将会对掌握高强度土地利用的过程和特点，模拟与评估土地利用对粮食安全及生态环境安全的影响有重要的意义。 . 农业土地利用活动是人类作用于地球系统最为直接的扰动因素，其变化会因改变生态系统过程与格局以及生态系统资源有效性而对生态系统功能在局地到全球尺度都产生重要的影响。中国南方普遍实施的多熟种植制度是高强度土地利用的重要特征之一，在中国传统的三熟农业区之一——江西省鄱阳湖区域，以农户为管理单元的农业种植制度由于受到洪水风险、经济效益及农业政策的调节，其时空格局动态也因此更加复杂。以分布在鄱阳湖平原的农田为研究区，结合多时相MODIS影像表达的作物生长规律和农业物候观测记录，检测并分析农业多熟种植的时空格局特征。研究结果表明空间分辨率500m、8d合成的MODIS/EVI时间序列数据能够定量表达出农业种植的多熟制特征，可以应用于区域农业多熟种植制度时空分析，研究区种植制度时空格局的形成是农户对气候、社会经济及粮食安全状况响应及适应的结果。在空间和时间上清晰地认识农业多熟种植的特征，将会对掌握高强度土地利用的过程和特点，模拟与评估土地利用对粮食安全及生态环境安全的影响有重要的意义。 |
| [48] | 多熟种植是高强度农业土地利用的重要特征,但由于缺乏在空间和时间上清晰描述农业多熟种植和作物种植历时空分布的数据,使得区域尺度农田生态系统碳动态估计、农田生产力监测与模拟等有很大的不确定性。黄淮海农业区是以冬小麦-夏玉米二熟制为主的我国粮食主产区,冬小麦和夏玉米分别为光合作用途径为C3和C4的作物,已有研究证明如果在估算生态系统生产力时不考虑一年两季作物及其光能利用率的差异则会导致生产力估算结果过低。研究结合农业气象站点地面作物物候观测数据和空间分辨率500m、8d合成的MOD IS时间序列数据,分析研究区二熟制作物的生长过程、物候特征和作物历的空间差异,发展基于EVI和LSWI时间序列曲线检测多熟区各季作物种植历的方法,获取黄淮海农业区空间表述清晰的熟制和各季作物的生长开始与结束时间数据,并应用农业气象站点数据对方法和所获取的作物历数据进行了比较验证。论述的方法和提取的各季作物的作物历时空数据将能够应用于区域尺度农田生产力估算、生物地球化学循环模拟和农业生态系统监测。 . 多熟种植是高强度农业土地利用的重要特征,但由于缺乏在空间和时间上清晰描述农业多熟种植和作物种植历时空分布的数据,使得区域尺度农田生态系统碳动态估计、农田生产力监测与模拟等有很大的不确定性。黄淮海农业区是以冬小麦-夏玉米二熟制为主的我国粮食主产区,冬小麦和夏玉米分别为光合作用途径为C3和C4的作物,已有研究证明如果在估算生态系统生产力时不考虑一年两季作物及其光能利用率的差异则会导致生产力估算结果过低。研究结合农业气象站点地面作物物候观测数据和空间分辨率500m、8d合成的MOD IS时间序列数据,分析研究区二熟制作物的生长过程、物候特征和作物历的空间差异,发展基于EVI和LSWI时间序列曲线检测多熟区各季作物种植历的方法,获取黄淮海农业区空间表述清晰的熟制和各季作物的生长开始与结束时间数据,并应用农业气象站点数据对方法和所获取的作物历数据进行了比较验证。论述的方法和提取的各季作物的作物历时空数据将能够应用于区域尺度农田生产力估算、生物地球化学循环模拟和农业生态系统监测。 |
| [49] | Double-and triple-cropping in a year have played a very important role in meeting the rising need for food in China.However,the intensified agricultural practices have significantly altered biogeochemical cycles and soil quality.Understanding and mapping cropping intensity in China鈥瞫 agricultural systems are therefore necessary to better estimate carbon,nitrogen and water fluxes within agro-ecosystems on the national scale.In this study,we investigated the spatial pattern of crop calendar and multiple cropping rotations in China using phenological records from 394 agro-meteorological stations(AMSs)across China.The results from the analysis of in situ field observations were used to develop a new algorithm that identifies the spatial distribution of multiple cropping in China from moderate resolution imaging spectroradiometer(MODIS)time series data with a 500 m spatial resolution and an 8-day temporal resolution.According to the MODIS-derived multiple cropping distribution in 2002,the proportion of cropland cultivated with multiple crops reached 34%in China.Double-cropping accounted for approximately 94.6%and triple-cropping for 5.4%.The results demonstrat that MODIS EVI(Enhanced Vegetation Index)time series data have the capability and potential to delineate the dynamics of double-and triple-cropping practices.The resultant multiple cropping map could be used to evaluate the impacts of agricultural intensification on biogeochemical cycles. |
| [50] | Summary In the early 1970s Ehrlich and Holdren devised a simple equation in dialogue with Commoner identifying three factors that created environmental impact. Thus, impact (I) was expressed as the product of (1) population, (P); (2) affluence, (A); and (3) technology, (T). This article tracks the various forms the IPAT equation has taken over 30 years as a means of examining an underlying shift among many environmentalists toward a more accepting view of the role technology can play in sustainable development. Although the IPAT equation was once used to determine which single variable was the most damaging to the environment, an industrial ecology view reverses this usage, recognizing that increases in population and affluence can, in many cases, be balanced by improvements to the environment offered by technological systems. |
| [51] | |
| [52] | Vast areas of rangelands across the world are grazed with increasing intensity, but interactions between livestock production, biodiversity and other ecosystem services are poorly studied. This study explicitly determines trade-offs and synergies between ecosystem services and livestock grazing intensity on rangelands. Grazing intensity and its effects on forage utilization by livestock, carbon sequestration, erosion prevention and biodiversity are quantified and mapped, using global datasets and models. Results show that on average 4% of the biomass produced annually is consumed by livestock. On average, erosion prevention is 10% lower in areas with a high grazing intensity compared to areas with a low grazing intensity, whereas carbon emissions are more than four times higher under high grazing intensity compared to low grazing intensity. Rangelands with the highest grazing intensity are located in the Sahel, Pakistan, West India, Middle East, North Africa and parts of Brazil. These high grazing intensities result in carbon emissions, low biodiversity values, low capacity for erosion prevention and unsustainable forage utilization. Although the applied models simplify the processes of ecosystem service supply, our study provides a global overview of the consequences of grazing for biodiversity and ecosystem services. The expected increasing future demand for livestock products likely increase pressures on rangelands. Global-scale models can help to identify targets and target areas for international policies aiming at sustainable future use of these rangelands. |
| [53] | ABSTRACT New demands on our land resources require more stringent controls and management practices. The administration of these controls requires better and more frequent information concerning land use. Although new tools became available to aid in acquiring and processing the data, a major lack in uniform techniques for identifying the land use was a major problem. Creation of a more standard form of classification of land use, based on the capabilities inherent in the various forms of remote sensors and other data sources was a necessary step.A classification has been created, and published in preliminary form, by the Geological Survey of the United States Department of Interior. It is presented as Geological Survey 671, entitled "A Land Use Classification System for Use With Remote Sensor Data". This paper discusses the origin, development, and controlling influences of that classification system. |
| [54] | <p>城市脆弱性是指城市在发展过程中抵抗资源、生态环境、经济、社会发展等内外部自然要素和人为要素干扰的应对能力。当这种抗干扰的应对能力低于某一临界阈值时,城市即进入脆弱状态。城市脆弱性是城市资源脆弱性、生态环境脆弱性、经济脆弱性和社会脆弱性的综合体现。城市脆弱性的评价与调控研究对提升中国城镇化质量、实现可持续发展具有重要意义。采用系统分析方法和综合指数评价法,从资源、生态环境、经济和社会4个方面确定10项分指数、选取36个具体指标,构建了中国城市脆弱性综合测度指标体系,并确定测度标准值,对中国地级以上城市脆弱性及其空间分异做了总体评价。研究表明,中国城市脆弱性呈现明显的“级差化”分异特征,总体处于中度脆弱状态。按照这种差异,将中国城市脆弱程度划分为低度脆弱、较低脆弱、中度脆弱、较高脆弱和高度脆弱5个级别。城市脆弱性呈现显著的“梯度化”和“集群化”空间分异,东部地区城市脆弱性明显低于中西部地区,城市群地区脆弱性低于其它地区。城市脆弱性与城市规模存在一定的对应关系,规模越大的城市脆弱性相对越小。资源型城市脆弱性明显高于综合性城市,职能综合性强的城市脆弱性相对较低。城市经济增长的快慢不能反映城市脆弱性的高低,经济高速增长并不意味着城市脆弱性就低。如何科学测度城市综合脆弱性,如何应对和降低城市脆弱性,是本研究试图回答的问题。该研究为丰富城市脆弱性与城市可持续发展理论,为解决快速城市化、工业化进程中的城市资源枯竭、生态环境破坏、经济增长方式的转变及系列社会问题等提供科学依据。</p> . <p>城市脆弱性是指城市在发展过程中抵抗资源、生态环境、经济、社会发展等内外部自然要素和人为要素干扰的应对能力。当这种抗干扰的应对能力低于某一临界阈值时,城市即进入脆弱状态。城市脆弱性是城市资源脆弱性、生态环境脆弱性、经济脆弱性和社会脆弱性的综合体现。城市脆弱性的评价与调控研究对提升中国城镇化质量、实现可持续发展具有重要意义。采用系统分析方法和综合指数评价法,从资源、生态环境、经济和社会4个方面确定10项分指数、选取36个具体指标,构建了中国城市脆弱性综合测度指标体系,并确定测度标准值,对中国地级以上城市脆弱性及其空间分异做了总体评价。研究表明,中国城市脆弱性呈现明显的“级差化”分异特征,总体处于中度脆弱状态。按照这种差异,将中国城市脆弱程度划分为低度脆弱、较低脆弱、中度脆弱、较高脆弱和高度脆弱5个级别。城市脆弱性呈现显著的“梯度化”和“集群化”空间分异,东部地区城市脆弱性明显低于中西部地区,城市群地区脆弱性低于其它地区。城市脆弱性与城市规模存在一定的对应关系,规模越大的城市脆弱性相对越小。资源型城市脆弱性明显高于综合性城市,职能综合性强的城市脆弱性相对较低。城市经济增长的快慢不能反映城市脆弱性的高低,经济高速增长并不意味着城市脆弱性就低。如何科学测度城市综合脆弱性,如何应对和降低城市脆弱性,是本研究试图回答的问题。该研究为丰富城市脆弱性与城市可持续发展理论,为解决快速城市化、工业化进程中的城市资源枯竭、生态环境破坏、经济增长方式的转变及系列社会问题等提供科学依据。</p> |
| [55] | Semi-nomadic pastoralism was replaced by sedentary pastoralism in Inner Mongolia during the 1960's in response to changes in land use policy and increasing population. Large increases in numbers of livestock and pastoralist households (11- and 9-fold, respectively) during the past 60 yrs have variously degraded the majority of grasslands in Inner Mongolia (78 M ha) and jeopardize the livelihoods of 24 M inhabitants. A prevailing strategy for alleviating poverty and grassland emphasizes intensification of livestock production systems to maintain both pastoral livelihoods and large livestock numbers. We consider this strategy unsustainable because maximization of livestock revenue incurs high supplemental feed costs, marginalizes net household income, and promotes larger flock sizes to create a positive feedback loop driving grassland . We offer an alternative strategy that increases both livestock production efficiency and net pastoral income by marketing high quality animal products to an increasing affluent Chinese economy while simultaneously reducing livestock impacts on grasslands. We further caution that this strategy be designed and assessed within a social-ecological framework capable of coordinating market expansion for livestock products, sustainable livestock carrying capacities, modified pastoral perceptions of success, and incentives for ecosystem services to interrupt the positive feedback loop that exists between subsistence pastoralism and grassland in Inner Mongolia. |
| [56] | Deforestation due to ever-increasing activities of the growing human population has been an issue of major concern for the global environment. It has been especially serious in the last several decades in the developing countries. A population-deforestation model has been developed by the authors to relate the population density with the cumulative forest loss, which is defined and computed as the total forest loss until 1990 since prior to human civilisation. NOAA-AVHRR-based land cover map and the FAO forest statistics have been used for 1990 land cover. A simulated land cover map, based on climatic data, is used for computing the natural land cover before the human impacts. With the 1990 land cover map as base and using the projected population growth, predictions are then made for deforestation until 2025 and 2050 in both spatial and statistical forms. |
