青藏高原若尔盖地区近期土地覆被变化

土地利用/覆被是全球变化和可持续发展研究中的重要问题之一.若尔盖位于青藏高原东北边缘,是全球变化的敏感响应地带,近年来因其沙化、湿地变化而受到广泛关注.以若尔盖地区土地覆被变化为研究对象,分别选取了1987、1996和2001年的Landsat 5 TM影像,根据野外标志解译出土地覆被类型,并采用Moran Ⅰ指数揭示其空间分布特征.结论表明,在研究时段中各种土地覆被类型具有不同程度变化,其中沼泽和沙地的变化范围分别为31.86 km2,7.83 km2,增长比较显著的是沙地、居民点及建设用地、撂荒地;不同时段的Moran I指数均为0.05,表明若尔盖近期土地覆被的分布属于随机类型的.在降水没有明显增加的背景下,气温渐次升高是若尔盖土地覆被变化的主要自然因子.研究结果揭示了整个若尔盖地区的土地覆被类型及其变化;讨论了沙化现象及其防治,对全球变化的区域响应和区域环境保护具有积极意义.     

以土地利用/土地覆被变化为中心的土地科学研究进展

土地利用 /土地覆被变化已成为土地科学、地球系统科学、全球环境变化及可持续发展研究中的核心领域。其研究的根本目标是实现土地资源的有效管理与可持续利用 ,这不仅是解决资源与环境问题的根本立足点 ,也是经济增长与区域可持续发展过程的重要前提。针对国际土地科学研究中最为活跃的几个前沿领域 :土地利用 /土地覆被变化、土地资源系统分析与评价、土地质量指标体系、生态环境效应及持续土地利用 ,结合近年来国内外有关的主要研究计划和项目 ,本文对以土地利用 /土地覆被变化为中心的土地科学研究进展进行了综述。     

LUCC研究的最新进展评述

土地利用/土地覆被变化(LUCC)是全球环境变化的重要组成部分和主要原因之一,进入新世纪以来,LUCC研究一直是地理学研究的前沿与热点。本文综述了2002年8月在南非德班国际地理学联合会(IGU)"2002年区域地理大会"上有关LUCC的主要研究成果,认为国际上LUCC研究在应用RS、GIS技术开展土地利用/土地覆被变化监测、评价与制图;农村与农业土地利用/土地覆被变化分析;城市土地利用/土地覆被变化分析;土地利用/土地覆被变化动力学;土地利用/土地覆被变化与生态环境等五个方面取得最新进展,反映出LUCC研究范围在进一步拓展,研究内容在进一步深化。     

土地利用/土地覆被时空分布100年数字重建——以大庆市杜尔伯特蒙古族自治县为例

长时间序列的土地利用/ 土地覆被数据是开展全球变化、可持续发展及生态安全等各项研究的重要基础。然而,早期的土地利用/ 土地覆被数据,特别是卫星遥感数据出现之前 的土地利用/ 土地覆被信息通常很难获取。利用TM、MSS 遥感影像数据和地形图、气候、地质、地貌、土壤、植被、水文等自然环境背景图件以及数据,社会经济统计数据等多源数 据,选择大庆市杜尔伯特蒙古族自治县作为典型案例区,在GIS 技术支持下建立了土地利用/ 土地覆被数字重建模型,再现了典型研究区20 世纪30 年代和50 年代土地利用/ 土地覆被空间分布状况。通过野外调查和历史文献资料对土地利用数字重建结果进行精度评价并初步得到以下结论：① 采用逐个图斑跟踪记录的方法对研究区各个时期土地利用/ 覆被变化的敏感 性进行分析,有利于揭示区域土地利用/ 土地覆被变化的规律;② 在定量、定位分析环境背景对土地利用/ 土地覆被分布及其变化的影响基础上,综合判断各种土地利用/ 土地覆被分布概率,其结果可为土地利用数字重建提供依据;③ 对1:10 万地形图提取土地利用信息的可行性与可信度分析表明,地形图中土地利用信息完全能够达到一级土地利用分类精度,同时疏林地、灌木林、沼泽地、盐碱地、沙地等二级分类信息也能获取。     

黄河三角洲土地利用与土地覆被的质量变化

土地利用／土地覆被变化（LUCC）在全球环境变化与可持续发展研究中占有重要地位。其质量变化尤能反映人类开发活动的环境效应。运用遥感信息土地分类和植被指数提取、土壤定点采样实测和统计分析相结合的方法，研究了黄河三角洲地区数年至20余年的土地利用／土地覆被的质量变化。其在区域总体上向好的方向发展，但在内部地段间存在着差异和不平衡。盐渍土改造的任务仍然十分艰巨。地力下降的隐患不可忽视。进而分析了变化的驱动力并提出土地持续利用对策。     

中国土地利用/覆被变化研究的现状与问题

土地利用 /覆被变化是全球变化的重要组成部分和原因 ,因而是全球变化领域中重要的研究方向之一。本文在评述了中国土地利用 /覆被变化研究的现状、取得的进展及存在问题的基础上 ,提出应把土地利用 /覆被变化研究的理论体系、不同空间尺度的土地利用 /覆被变化的动态模型、土地利用 /覆被变化与全球环境变化和可持续发展之间的关系作为重点加以研究 ,以提高中国土地利用 /覆被变化的研究水平。     

东北亚南北样带2001-2012年土地覆被变化分析(英文)

东北亚区域是一个资源相对集中,生态环境格局复杂,气候地带性多样,人地关系对比显著的区域。分析该区域的土地覆被格局与变化特征,对于促进全球气候变化在本区域的影响与响应研究,以及中、俄、蒙跨边境地区的区域可持续发展具有重要意义。本文以样带分析为研究手段,获取东北亚南北样带2001-2012年逐年的MODIS土地覆被数据集,建立土地覆被变化矩阵。从空间分布来看,12年间东北亚南北样带内林地大量增加,耕地少量增加,草地灌丛则大幅减少。从年际变化来看,草地灌丛的总变化量呈现总体稳定,缓步上升过程中有局部波动的特点;林地总变化量呈现出峰谷相间的起伏波动特点,但总体有上升趋势;耕地的总变化量有明显的锯齿壮起伏波动特征;整个样带区域的综合土地动态度总体稳定,有略微上涨趋势。     

土地利用/覆被变化的大气环境效应研究进展

土地利用/覆被变化是全球环境变化的重要原因,随着气候变化问题的日益突出,土地利用/覆被变化的大气环境效应已成为国内外全球变化的前沿和热点课题.通过对土地利用/覆被变化对大气环境系统的作用机制分析,认为目前土地利用/覆被变化对大气质量、大气污染以及气候变化产生了重要的影响,尤其随着快速城市化进程的推进,带来了显著的城市空气污染和热岛效应,而土地利用/覆被变化在全球尺度上的气候效应则存在较多的争论.今后应加强土地变化科学和大气科学的融合,从多尺度探讨土地利用/覆被变化的大气环境效应,并注重大气环境改善视角下的土地利用策略和空间规划研究.     

全球土地覆被时空变化与中国贡献

20世纪下半叶以来全球土地覆被发生了剧烈变化,人类活动对土地覆被变化的影响成为“人类世”最为显著的特征之一。科学评估全球土地覆被变化的时空过程和新态势,分析中国在其中扮演的角色和地位并提出优化路径,成为中国在可持续发展领域应对全球百年未有之大变局的核心任务之一。本文基于多源土地覆盖数据,运用地理空间分析方法定量刻画了全球土地覆被变化的时空演化过程,从景观尺度分析了地类间的转化关系以及全球“变绿”和森林覆盖度的变化趋势,揭示了中国对全球土地覆被时空变化的贡献。结果表明,1992—2015年全球土地覆被经历了显著变化,全球土地覆被变化度在南美洲中部、撒哈拉以南的非洲、中亚、东南亚和东亚等地形成显著的热点区。中国森林覆盖率从1990年的12.98%增至2020年的23.34%,湿地面积增长1908 km²,为维护全球生态安全贡献了力量,同时在城市用地增长、草地和其他用地减少等方面也有一定的限制作用。与全球其他国家不同,中国城市扩张占用耕地面积居全球第一位,高达7.3万km²。1999—2019年全球叶面积指数存在全球性的显著提高趋势。中国以仅占全球6.6%的植被面积,贡献了全球20%左右的叶面积增加量,引领了全球“变绿”过程。1990—2020年全球森林覆盖度变化呈现出空间集聚性。中国森林面积增长62.84万km²居全球前列,其中西南林区和秦巴山区是林地增长的主要区域,长三角、粤港澳大湾区和内蒙古东部部分地区是森林覆盖度降低的主要区域。中国未来应进一步提升经济社会发展与生态保护的均衡协调度,持续推进美丽中国建设,为全球生态安全和可持续发展贡献更大力量和更多经验。     

西南地区城市化进程加剧局地气象条件的空间差异

土地利用覆被变化对于局地气象条件的演变具有重要影响.在过去几十年我国西南地区经历了较为明显的土地利用变化,而该区域土地利用转变背景下局地气象要素的时空差异尚缺乏定量研究.本文利用中国多时期土地利用土地覆被遥感监测数据集(CNLUCC)以及中国区域地面气象要素驱动数据集(CMFD),基于土地利用转移矩阵和距平分析方法,量...     

Trends of tropical deforestation in Southeast Mexico

We assessed deforestation in Southeast Mexico (a surface area of 29 000 km² in seven states) through the comparison of land use/land cover maps at a scale of 1:250 000. This facilitated mapping of the land use/land cover change (LULCC) processes and calculation of the rates of change and the change matrix for the period 1978–2000. An original method was used to assess the accuracy of the LULCC map. The verification sites were selected through a stratified random sampling and were corroborated with aerial photographs for 1978 and 2000. Error matrices were elaborated using both hard and fuzzy set approaches in order to take into account the errors related to generalization of the map in fragmented landscapes. The results showed an average annual deforestation rate of 1.1 per cent which represents an average annual loss of 190 000 ha of forest, or an estimated total reduction of 4.2 million ha over 22 years. Furthermore, deforestation processes are concentrated in some areas such as Yucatan and Chiapas states, which registered major forest conversions to grassland and slash‐burning. The overall accuracy of the LULCC map, assessed with hard and fuzzy set approaches, was 72 per cent and 88 per cent respectively.     

The spatial local accuracy of land cover datasets over the Qiangtang Plateau,High Asia

We analyzed the spatial local accuracy of land cover (LC) datasets for the Qiangtang Plateau, High Asia, incorporating 923 field sampling points and seven LC compilations including the International Geosphere Biosphere Programme Data and Information System (IGBPDIS), Global Land cover mapping at 30 m resolution (GlobeLand30), MODIS Land Cover Type product (MCD12Q1), Climate Change Initiative Land Cover (CCI-LC), Global Land Cover 2000 (GLC2000), University of Maryland (UMD), and GlobCover 2009 (Glob-Cover). We initially compared resultant similarities and differences in both area and spatial patterns and analyzed inherent relationships with data sources. We then applied a geographically weighted regression (GWR) approach to predict local accuracy variation. The results of this study reveal that distinct differences, even inverse time series trends, in LC data between CCI-LC and MCD12Q1 were present between 2001 and 2015, with the exception of category areal discordance between the seven datasets. We also show a series of evident discrepancies amongst the LC datasets sampled here in terms of spatial patterns, that is, high spatial congruence is mainly seen in the homogeneous southeastern region of the study area while a low degree of spatial congruence is widely distributed across heterogeneous northwestern and northeastern regions. The overall combined spatial accuracy of the seven LC datasets considered here is less than 70%, and the GlobeLand30 and CCI-LC datasets exhibit higher local accuracy than their counterparts, yielding maximum overall accuracy (OA) values of 77.39% and 61.43%, respectively. Finally, 5.63% of this area is characterized by both high assessment and accuracy (HH) values, mainly located in central and eastern regions of the Qiangtang Plateau, while most low accuracy regions are found in northern, northeastern, and western regions.

     

Broad scale forest cover reconstruction from historical topographic maps

Land cover change is one of the major contributors to global change, but long-term, broad-scale, detailed and spatially explicit assessments of land cover change are largely missing, although the availability of historical maps in digital formats is increasing. The problem often lies in efficiency of analyses of historical maps for large areas. Our goal was to assess different methods to reconstruct land cover and land use from historical maps to identify a time-efficient and reliable method for broad-scale land cover change analysis. We compared two independent forest cover reconstruction methods: first, regular point sampling, and second, wall-to-wall mapping, and tested both methods for the Polish Carpathians (20,000 km²) for the 1860s, 1930s and 1970s. We compared the two methods in terms of their reliability for forest change analysis, relative to sampling error, point location and landscape context including local forest cover, area of the spatial reference unit and forest edge-to-core ratio. Our results showed that the point-based analysis overestimated forest cover in comparison to wall-to-wall mapping by 1–3%, depending on the mapping period. The reasons for the differences were mainly the backdating approach and map generalisation rather than the point grid position or sampling error. When we compared forest cover trajectories over time, we found that the point-based reconstruction captured forest cover dynamics with a comparable accuracy to the wall-to-wall mapping. More broadly, our assessment showed that historical maps can provide valuable data on long-term land cover trends, and that point-based sampling can be an efficient and accurate way to assess forest area and change trends. We suggest that our point-based approach could allow land cover mapping across much of Europe starting in the 1800s. Our findings are important because they suggest that land cover change, a key component of global change, can be assessed over large areas much further back in time than it is commonly done. This would allow to truly understand path dependencies, land use legacies, and historical drivers of land cover change.     

七套土地覆被数据在羌塘高原的精度评价（英文）

We analyzed the spatial local accuracy of land cover(LC) datasets for the Qiangtang Plateau, High Asia, incorporating 923 field sampling points and seven LC compilations including the International Geosphere Biosphere Programme Data and Information System(IGBPDIS), Global Land cover mapping at 30 m resolution(GlobeLand30), MODIS Land Cover Type product(MCD12 Q1), Climate Change Initiative Land Cover(CCI-LC), Global Land Cover 2000(GLC2000), University of Maryland(UMD), and GlobCover 2009(GlobCover). We initially compared resultant similarities and differences in both area and spatial patterns and analyzed inherent relationships with data sources. We then applied a geographically weighted regression(GWR) approach to predict local accuracy variation. The results of this study reveal that distinct differences, even inverse time series trends, in LC data between CCI-LC and MCD12 Q1 were present between 2001 and 2015, with the exception of category areal discordance between the seven datasets. We also show a series of evident discrepancies amongst the LC datasets sampled here in terms of spatial patterns, that is, high spatial congruence is mainly seen in the homogeneous southeastern region of the study area while a low degree of spatial congruence is widely distributed across heterogeneous northwestern and northeastern regions. The overall combined spatial accuracy of the seven LC datasets considered here is less than 70%, and the GlobeLand30 and CCI-LC datasets exhibit higher local accuracy than their counterparts, yielding maximum overall accuracy(OA) values of 77.39% and 61.43%, respectively. Finally, 5.63% of this area is characterized by both high assessment and accuracy(HH) values, mainly located in central and eastern regions of the Qiangtang Plateau, while most low accuracy regions are found in northern, northeastern, and western regions.     

Land Cover Status in the Koshi River Basin,Central Himalayas

The Koshi River Basin is in the middle of the Himalayas, a tributary of the Ganges River and a very important cross-border watershed. Across the basin there are large changes in altitude, habitat complexity, ecosystem integrity, land cover diversity and regional difference and this area is sensitive to global climate change. Based on Landsat TM images, vegetation mapping, field investigations and 3S technology, we compiled high-precision land cover data for the Koshi River Basin and analyzed current land cover characteristics. We found that from source to downstream, land cover in the Koshi River Basin in 2010 was composed of water body (glacier), bare land, sparse vegetation, grassland, wetland, shrubland, forest, cropland, water body (river or lake) and built-up areas. Among them, grassland, forest, bare land and cropland are the main types, accounting for 25.83%, 21.19%, 19.31% and 15.09% of the basin’s area respectively. The composition and structure of the Koshi River Basin land cover types are different between southern and northern slopes. The north slope is dominated by grassland, bare land and glacier; forest, bare land and glacier are mainly found on northern slopes. Northern slopes contain nearly seven times more grassland than southern slopes; while 97.13% of forest is located on southern slopes. Grassland area on northern slope is 6.67 times than on southern slope. The vertical distribution of major land cover types has obvious zonal characteristics. Land cover types from low to high altitudes are cropland, forest, Shrubland and mixed cropland, grassland, sparse vegetation, bare land and water bodies. These results provide a scientific basis for the study of land use and cover change in a critical region and will inform ecosystem protection, sustainability and management in this and other alpine transboundary basins.     

Urban mapping,accuracy, & image classification: A comparison of multiple approaches in Tsukuba City,Japan

The rapid growth of urban space and its environmental challenges require precise mapping techniques to represent complex earth surface features more accurately. In this study, we examined four mapping approaches (unsupervised, supervised, fuzzy supervised and GIS post-processing) using Advanced Land Observing Satellite images to predict urban land use and land cover of Tsukuba city in Japan. Intensive fieldwork was conducted to collect ground truth data. A random stratified sampling method was chosen to generate geographic reference data for each map to assess the accuracy. The accuracies of the maps were measured, producing error matrices and Kappa indices. The GIS post-processing approach proposed in this research improved the mapping results, showing the highest overall accuracy of 89.33% as compared to other approaches. The fuzzy supervised approach yielded a better accuracy (87.67%) than the supervised and unsupervised approaches. The fuzzy supervised approach effectively dealt with the heterogeneous surface features in residential areas. This paper presents the strengths of the mapping approaches and the potentials of the sensor for mapping urban areas, which may help urban planners monitor and interpret complex urban characteristics.     

基于遥感和GIS的松嫩沙地土地利用/土地覆被时空格局研究

利用1986年和2000年2期TM影像资料,建立相应的空间图形库系统,定量分析了松嫩沙地典型区近15a来土地利用数量变化,从土地利用斑块特征、斑块空间邻接关系变化和主导变化类型角度对土地利用/覆被格局进行了清晰的空间描述。结果表明,研究时段内该区土地利用量变和质变活跃。耕地面状成片、条带状延伸和斑块状空间扩展,从整体上呈现集中化特征。较大面积的草地和林地被分割、破碎化,小块盐碱化草地空间聚集与扩张。耕地与草地、草地与盐碱地空间相邻度变大,草地开垦强度增大、土地盐碱化日益严重。空间变化上表现为耕地、林地、草地和未利用地之间相互转化,以草地、林地-旱地,草地-未利用地,未利用地-旱地、水田及旱地-水田最为显著。     

黄河源地区草地退化空间特征

利用黄河源地区1985年和2000年1：100000土地利用／覆被数据,结合1：250000DEM、道路和居民点数据与野外调查资料,分析草地退化与坡向、海拔及距道路和居民点距离之间的关系．探讨黄河源区15年间土地覆被变化特征与规律。结果表明,退化草地占源区总面积的8．24％,冬春季牧场退化率显著高于夏季牧场：草地退化是黄河源区研究时段内土地利用／覆被变化最主要的特征。草地退化表现为：①阳坡退化率高于阴坡;②受人口密度影响,草地退化率与海拔高度成反比,相关系数为．0．925;③距离居民点越近。退化率越高。尤其当与居民点距离≤12km时,草地退化率与其相关系数高达-0．996;④在距道路4km以内．草地退化率与道路距离成反比．相关系数高达-0．978。1985年以来,源区的草地退化有自然因素的影响．但人类活动的影响仍起主导作用。科学地减少当地居民对草地的过分依赖是解决脆弱的江河源区环境退化的根本。     

基于Landsat 8 OLI数据与面向对象分类的昆嵛山地区土地覆盖信息提取

利用2015年Landsat 8 OLI遥感影像和DEM作为分类数据源,结合野外调查数据,采用面向对象的分类方法对昆嵛山地区土地覆盖信息进行提取,并对分类结果进行精度评价与比较分析。研究表明：面向对象分类方法提取的各地类连续且边界清晰,分类效果与实际情况基本吻合。昆嵛山地区占主导地位的土地覆盖类型是针叶林,面积为1 546.81 km²。研究区土地覆盖分类的总体精度和Kappa系数分别为91.5%和0.88,其中针叶林、草地、水体和建设用地的生产者精度均达到87%以上。相对于监督分类方法,本研究提出的土地覆盖信息提取方法的总体分类精度和Kappa系数分别提高14.7%和0.17。基于面向对象的中分辨率遥感影像,能够获取较高精度的土地覆盖信息,为大范围土地覆盖分类研究提供方法参考。     

内蒙古高原浑善达克沙地区土地利用与覆被变化及退化趋势

浑善达克沙地及其周边地区是我国北方沙尘暴多发区之一,该区的土地利用与覆被变化反映了一系列的环境与社会经济问题。基于卫星遥感信息和空间数据处理技术,并结合地面实地调查资料、气象观测和社会经济数据,得出了20世纪80年代末至90年代末这一地区土地利用与覆被变化情况。结果表明:耕地、建设用地和未利用地明显增加,草地和水域减少,变化面积最大的是草地,有944.42 km2的草地转变为其他用地类型;从变化速率来看,最快的是建设用地,增加了19.8%,其次是耕地,增加10.2%。土地利用转变的主要类型是草地向耕地和未利用地的转变,及耕地向建设用地的转变;呈退化趋势的土地面积近3倍于恢复土地面积。就土地利用与覆被变化的社会经济背景进行了深入分析。