Land-cover classification of China: integrated analysis of AVHRR imagery and geophysical data

Over last two decades, numerous studies have used remotely sensed data from the Advanced Very High Resolution Radiometer (AVHRR) sensors to map land use and land cover at large spatial scales, but achieved only limited success. In this paper, we employed an approach that combines both AVHRR images and geophysical datasets (e.g. climate, elevation). Three geophysical datasets are used in this study: annual mean temperature, annual precipitation, and elevation. We first divide China into nine bio-climatic regions, using the long-term mean climate data. For each of nine regions, the three geophysical data layers are stacked together with AVHRR data and AVHRR-derived vegetation index (Normalized Difference Vegetation Index) data, and the resultant multi-source datasets were then analysed to generate land-cover maps for individual regions, using supervised classification algorithms. The nine land-cover maps for individual regions were assembled together for China. The existing land-cover dataset derived from Landsat Thematic Mapper (TM) images was used to assess the accuracy of the classification that is based on AVHRR and geophysical data. Accuracy of individual regions varies from 73% to 89%, with an overall accuracy of 81% for China. The results showed that the methodology used in this study is, in general, feasible for large-scale land-cover mapping in China.

Decision tree classification of land cover from remotely sensed data

Decision tree classification algorithms have significant potential for land cover mapping problems and have not been tested in detail by the remote sensing community relative to more conventional pattern recognition techniques such as maximum likelihood classification. In this paper, we present several types of decision tree classification algorithms arid evaluate them on three different remote sensing data sets. The decision tree classification algorithms tested include an univariate decision tree, a multivariate decision tree, and a hybrid decision tree capable of including several different types of classification algorithms within a single decision tree structure. Classification accuracies produced by each of these decision tree algorithms are compared with both maximum likelihood and linear discriminant function classifiers. Results from this analysis show that the decision tree algorithms consistently outperform the maximum likelihood and linear discriminant function classifiers in regard to classf — cation accuracy. In particular, the hybrid tree consistently produced the highest classification accuracies for the data sets tested. More generally, the results from this work show that decision trees have several advantages for remote sensing applications by virtue of their relatively simple, explicit, and intuitive classification structure. Further, decision tree algorithms are strictly nonparametric and, therefore, make no assumptions regarding the distribution of input data, and are flexible and robust with respect to nonlinear and noisy relations among input features and class labels.

Land-cover changes in an urban lake watershed in a mega-city, Central China

Urbanization can exert a profound influence on land covers and landscape characteristics. In this study, we characterize the impact of urbanization on land cover and lacustrine landscape and their consequences in a large urban lake watershed, Donghu Lake watershed (the largest urban lake in China), Central China, by using Landsat TM satellite images of three periods of 1987, 1993 and 1999 and ground-based information. We grouped the land covers into six categories: water body, vegetable land, forested land, shrub-grass land, open area and urban land, and calculated patch-related landscape indices to analyze the effects of urbanization on landscape features. We overlaid the land cover maps of the three periods to track the land cover change processes. The results indicated that urban land continuously expanded from 9.1% of the total watershed area in 1987, to 19.4% in 1993, and to 29.6% in 1999. The vegetable land increased from 7.0% in 1987, 11.9% in 1993, to 13.9% in 1999 to sustain the demands of vegetable for increased urban population. Concurrently, continuous reduction of other land cover types occurred between 1987 and 1999: water body decreased from 30.4% to 23.8%, and forested land from 33.6% to 24.3%. We found that the expansion of urban land has at least in part caused a decrease in relatively wild habitats, such as urban forest and lake water area. These alterations had resulted in significant negative environmental consequences, including decline of lakes, deterioration of water and air quality, and loss of biodiversity.

The characteristics of land cover and macroscopical ecology changes in the source region of three rivers in Qinghai-Tibet plateau during last 30 years

We obtained four phases of land cover spatial data sets by interpreting MSS images of middle and late 1970s and three phases of TM images of late 1980s, 2004 and 2008 based on field investigation in Three Rivers' Source Region. We analyzed the temporal and spatial characteristics of land cover and macro ecological changes in Three Rivers' Source Region in Qinghai-Tibet plateau since middle and late 1970s. Indicated by land cover condition index change rate and land cover change index, land cover and macroscopical ecological condition degenerated (7090 period Zc -0.63, LCCI -0.58)-obviously degenerated (9004 period, Zc -0.94, LCCI -1.76)-slightly meliorated (0408 period, Zc 0.06, LCCI 0.33). This course was jointly driven by climate change, grassland stocking pressure and implement of ecological construction project.

Application of Dempster-Shafer evidence theory to unsupervised classification in multisource remote sensing

The aim of this paper is to show that Dempster-Shafer evidence theory may be successfully applied to unsupervised classification in multisource remote sensing. Dempster-Shafer formulation allows for consideration of unions of classes, and to represent both imprecision and uncertainty, through the definition of belief and plausibility functions. These two functions, derived from mass function, are generally chosen in a supervised way. In this paper, the authors describe an unsupervised method, based on the comparison of monosource classification results, to select the classes necessary for Dempster-Shafer evidence combination and to define their mass functions. Data fusion is then performed, discarding invalid clusters (e.g. corresponding to conflicting information) thank to an iterative process. Unsupervised multisource classification algorithm is applied to MAC-Europe'91 multisensor airborne campaign data collected over the Orgeval French site. Classification results using different combinations of sensors (TMS and AirSAR) or wavelengths (L- and C-bands) are compared. Performance of data fusion is evaluated in terms of identification of land cover types. The best results are obtained when all three data sets are used. Furthermore, some other combinations of data are tried, and their ability to discriminate between the different land cover types is quantified

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 x 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.

China's changing landscape during the 1990s: Large-scale land transformations estimated with satellite data

Land-cover changes in China are being powered by demand for food for its growing population and by the nation's transition from a largely rural society to one in which more than half of its people are expected to live in cities within two decades. Here we use an analysis of remotely sensed data gathered between 1990 and 2000, to map the magnitude and pattern of changes such as the conversion of grasslands and forests to croplands and the loss of croplands to urban expansion. With high-resolution ( 30 m) imagery from Landsat TM for the entire country, we show that between 1990 and 2000 the cropland area increased by 2.99 million hectares and urban areas increased by 0.82 million hectares. In northern China, large areas of woodlands, grasslands and wetlands were converted to croplands, while in southern China large areas of croplands were converted to urban areas. The land-cover products presented here give the Chinese government and international community, for the first time, an unambiguous understanding of the degree to which the nation's landscape is being altered. Documentation of these changes in a reliable and spatially explicit way forms the foundation for management of China's environment over the coming decades.

Landscape change detection of the newly created wetland in Yellow River Delta

Four models are employed in the landscape change detection of the newly created wetland. The models include ones for patch connectivity. ecological diversity, human impact intensity and mean center of land cover. The landscape data of the newly created wetland in Yellow River Delta in 1984, 1991, and 1996 are produced from the unsupervised classification and the supervised classification on the basis of integrating Landsat TM images of the newly created wetland in the four seasons of the each year. The result from operating the models into the data shows that the newly created wetland landscape in Yellow River Delta had a great chance. The driving focus of the change are mainly from natural evolution of the newly created wetland and rapid population growth, especially non-peasant population growth in Yellow River Delta because a considerable amount of oil and gas fields have been found in the Yellow River Delta. For preventing the newly created wetland from more destruction and conserving benign Succession of the ecosystems in the newly created wetland, six measures are suggested on the basis of research results. (C) 2003 Elsevier Science B.V. All rights reserved.

Validating MODIS-derived land surface evapotranspiration with in situ measurements at two AmeriFlux sites in a semiarid region

Reducing uncertainties in the estimation of land surface evapotranspiration (ET) from remote-sensing data is essential to better understand earth-atmosphere interactions. This paper demonstrates the applicability of temperature-vegetation index triangle (T-s-VI) method in estimating regional ET and evaporative fraction (EF, defined as the ratio of latent heat flux to surface available energy) from MODIS/Terra and MODIS/Aqua products in a semiarid region. We have compared the satellite-based estimates of ET and EF with eddy covariance measurements made over 4 years at two semiarid grassland sites: Audubon Ranch (AR) and Kendall Grassland (KG). The lack of closure in the eddy covariance measured surface energy components is shown to be more serious at MODIS/Aqua overpass time than that at MODIS/Terra overpass time for both AR and KG sites. The T-s-VI-derived EF could reproduce in situ EF reasonably well with BIAS and root-mean-square difference (RMSD) of less than 0.07 and 0.13, respectively. Surface net radiation has been shown to be systematically overestimated by as large as about 60 W/m(2). Satisfactory validation results of the T-s-VI-derived sensible and latent heat fluxes have been obtained with RMSD within 54 W/m(2). The simplicity and yet easy use of the T-s-VI triangle method show a great potential in estimating regional ET with highly acceptable accuracy that is of critical significance in better understanding water and energy budgets on the Earth. Nevertheless, more validation work should be carried out over various climatic regions and under other different land use/land cover conditions in the future.

Analysis of arable land loss and its impact on rural sustainability in Southern Jiangsu Province of China

Rapid urbanization and industrialization in southern Jiangsu Province have consumed a huge amount of arable land. Through comparative analysis of land cover maps derived from TM images in 1990, 2000 and 2006, we identified the trend of arable land loss. It is found that most arable land is lost to urbanization and rural settlements development. Urban settlements, rural settlements, and industrial park-mine-transport land increased, respectively, by 87 997 ha (174.65%), 81 041 ha (104.52%), and 12 692 ha (397.99%) from 1990 to 2006. Most of the source (e.g., change from) land covers are rice paddy fields and dryland. These two covers contributed to newly urbanized areas by 37.12% and 73.52% during 1990-2000, and 46.39% and 38.86% during 2000-2006. However, the loss of arable land is weakly correlated with ecological service value, per capita net income of farmers, but positively with grain yield for some counties. Most areas in the study site have a low arable land depletion rate and a high potential for sustainable development. More attention should be directed at those counties that have a high depletion rate but a low potential for sustainable development. Rural settlements should be controlled and rationalized through legislative measures to achieve harmonious development between urban and rural areas, and sustainable development for rural areas with a minimal impact on the ecoenvironment. (C) 2009 Elsevier Ltd. All rights reserved.

毛乌素沙地土地利用/土地覆被变化研究

毛乌素沙地是我国十二大沙漠之一，地处北方干旱半干旱区向亚湿润区过渡地带，长期以来，不合理的人类土地利用，结合当地脆弱的环境生态特征，引起了严重的现代荒漠化过程，是我国北方荒漠化研究的重点地区。本文着重从自然和人文学科密切合作的角度，对毛乌素沙地土地利用／土地覆被变化的内在作用机制进行了研究，得到以下主要结论： 1. 利用多年实地观测数据资料，考察了毛乌素沙地四种主要草地类型代表性植物群落地上生物量响应气候因子波动的变化规律，建立了植物地上生物量对气候因子的逐月回归模型，揭示出如下规律：①各种气候因子对不同类型草地以及同一类型不同生长阶段草地都产生不同的影响作用;②同一气候因子在植物不同生长阶段上，对生物量形成的重要性程度存在差异：③在植物生长期内，每个生长阶段的生物量都对后一时期的生物量产生显著影响，说明植物生长的连续性对于生物量的形成和积累是重要的;④在植物的凋枯期，各种气候因子基本上都不对生物量产生显著影响;⑤水分因子对毛乌素沙地几乎各种类型草地的生物量，都是重要的影响因子，毛乌素沙地降水状况在不同年份的显著波动对草地植物地上生物量的影响，不仅直接构成了土地覆被变化的重要组成部分，而且还影响到土地利用的方式、方法和后果。 2. 在考察毛乌素沙地草地地上生物量对气候因子变化的响应规律中，利用逐月动态回归建模方法改进了传统的累积气候因子回归建模方法。逐月回归模型与累积回归模型的比较显示，逐月动态回归模型的优势表现在三个方面：①可以提供累积回归模型无法揭示的作用规律;②模拟更加精确;③可以预测不同气候条件下群落地上生物量的变化范围。 3. 利用风速、降水和潜在蒸发等气象记录资料，建立了毛乌素沙地气候因子影响沙尘暴频率的作用模型，定量地考察了沙地各处气候因子对沙尘暴频率的影响作用。研究表明，气候因素是导致毛乌素沙地沙尘暴发生的主导原因，在沙地各处，气候因子可以解释沙尘暴频率分布格局总信息的比率分别为：乌审召83.6%，乌审旗77.5%，河南82.4%，鄂托克旗79.8%，新街73.1%，伊金霍洛旗82%。 4. 在定量考察气候因素对沙尘暴频率影响作用的基础上，对影响沙尘暴频率格局的自然和人为因素进行了定量分离，研究表明：人为影响因素对对沙尘暴发生起次要作用，解释沙尘暴频率分布格局信息的比率分别为：乌审召16.4%，乌审旗22.5%，河南17.6%，鄂托克旗20.2%，新街26.9%，伊金霍洛旗18%。 自然和人为因素影响作用的定量分离研究表明，毛乌素沙地人为因素的影响作用表现出空间上的差异性：①从方位上说，呈现自东向中、西部递减的梯度：②从地点上说，城镇附近人为影响作用远高于农村地区;③从土地利用方式上说，农垦种植业区域高于畜牧业区域。 5. 在实地观测基础上，建立了裸露沙面和植被覆盖沙面风蚀输沙率模型，定量考察了植被覆盖率与风蚀输沙率之间的关系。研究表明：当植被覆盖率达到60%以上，可以保护地表土壤使风蚀在大多数条件下不致发生;当覆盖率达到40%，可以使风蚀输沙大为减少;而当植被覆盖率低于10%，植被覆盖基本不能对地表土壤起到有效的防护作用。 6. 应用植被覆盖地表风蚀输沙率模型，考察了沙地不同风速条件下植被有效覆盖率。根据当地气象台站的多年气象记录，沙地最大风速在20m/s左右，这样的风速条件下，保证风蚀不致发生的植被有效覆盖率为65%左右;在沙地常见的大风风速14-16m/s下，植被有效覆盖率大致为50-55%;对于沙地一般的中等风速l0-12m/s．植被有效覆盖率为40%。植被覆盖对风蚀的影响作用也可以理解为，植被覆盖使沙粒起动风速发生了增大效应，研究表明：与裸露沙面沙粒起动风速4.5m/s对照，70%植被覆盖率使起动风速改变为15.4m/s;60%植被覆盖率使起动风速改变为12.1m/s;40%植被覆盖率使起动风速改变为8.Om/s;而在10%植被覆盖条件下，起动风速为5.Om/s，改变量很小，说明植被覆盖的保护作用极其有限。 7. 基于野外实地观测，比较了沙地五种常见植物种和二种人工防护材料防风效应上的差异。研究表明，防风效应由高到低的次序是，沙蒿>芨芨草>杨柴和牛心朴子>沙障>栅栏>旱柳;就乔、灌、草和人工材料而言，防风效应的次序是，灌木植被>草本植被>人工材料>乔木植被。植物和人工防护材料降低风速的比率与风速呈现二次函数关系，不同植物种或人工材料，降低风速比率都表现出不同的规律，在一般情况下，降低风速效应随着风速的增大而降低。 8. 通过不同植物种防风效应的比较研究，对毛乌素沙地植被生态建设的实践有一定的指导意义。毛乌素沙地的植被建设中对植被类型和植物种类的选择，应该遵循如下原则：①选取防风固沙效应好的植物种类;②应该考虑植物水分供给与需求的平衡状况，实行适地适树;③植物防护效应应该与当地风蚀气候在时间上较好地匹配，在春季等风蚀严重季节，植被覆盖应该具有较好的防风效应。 9. 在现实中，各种影响风蚀的因素是同时发挥作用的。将风蚀影响因素分解为风速、湿润度和植被覆盖率（以及植被类型）三个方面，在此基础上，建立了风蚀影响因素的综合作用的概念模型和沙丘活动性指数定量模型。湿润程度低、风速高、植被覆盖率低的地区，是风蚀最为严重的地区;在湿润程度高、风速低、植被覆盖率高的地区，是风蚀最弱的地区;在其他地区，风蚀状况根据三个方面因素的综合状况来决定。 10. 利用风蚀影响因子综合作用的沙丘活动性指数模型，从空间、时间、植被类型变化角度，考察了毛乌素沙地的风蚀变化状况。得到如下结论：①随着空间变化，风速、降水等气候因素也随之存在差异，导致沙丘活动性指数的变化规律是，西北部鄂托克旗沙丘活动性最高，乌审旗次之，其他几个站差别不太显著，这是由各地降水、气温、沙粒粒径等因素共同决定;②随着时间的变化，气候、植被生长等方面的状况随之发生改变，导致沙丘活动性发生变化，春季最高，冬季次之，夏秋季最低：③随着沙丘植被覆盖类型的变化，沙丘活动性也发生显著变化，在一般情况下，乔木覆盖沙丘活动性>草本植物覆盖沙丘>灌木覆盖沙丘。 11. 在实地调查土地利用现实状况及其社会、经济和政策影响因素的基础上，建立了我国北方干旱半干旱区土地利用决策机制的概念模型，分析了与土地利用密切相关的农牧民一政府一环境科学家这三个社会群体对土地利用的立场和影响作用力上的差异，分析了毛乌素沙地土地利用的现状及其影响因素，探讨了现实中不可持续土地利用行为发生的社会、经济和政策原因。 12. 在实地调查基础上，分别利用产出一费用分析法和过程影响因素分析法，建立了毛乌素沙地土地利用经济收益的定量模型。产出一分析研究表明，无论是农垦种植业，还是草地畜牧业，农牧民从这两种土地利用方式都只能获得较低下的经济收益。造成这种状况的原因，主要在于两个方面：一是低下且不断处于波动之中的农牧业产品物价，二是沉重的农牧业税收。 13. 将影响农牧业产出的因素，划分为四个方面：土地面积（牲畜头数）、环境状况、管理水平和利用强度，在此基础上建立了定量的影响作用模型。研究表明：环境状况指数每增加0.1，农牧业经济收益增加26%;管理水平因子每提高0.1，农牧业经济收益增加12.7%;农牧业经济收益最优的土地利用强度在0.4左右，在此之前，随着利用强度的增加，经济收益随之增大，而在此之后，随着利用强度的增大，经济收益逐渐降低，当土地利用强度达到0.9左右时，呈现负的经济收益。 14. 毛乌素沙地实施土地资源可持续利用，必须从技术的革新和社会经济政策等因素的调整两条途径同时入手，二者缺一不可。通过改进和应用节水灌溉、风能光能利用、生物增产技术，尽可能地提高各种资源的利用效率;通过应用免耕或浅耕技术，尽量减轻土地利用对资源和环境的破坏;通过栽培、速生技术，提高植被建设的成效和速度。而通过税收、物价政策的调整，尽可能地提高农牧民经济收益增长的速度，减轻土地利用压力;通过政府与人民之间对话和合作机制的建立，让广大农牧民参与到土地利用的决策和管理的过程中去;通过土地利用管理政策、措施的调整和完善，调动农牧民保护资源的积极性和自觉性;通过激励机制的建立，引导农牧民土地利用向着可持续的方向发展。 15. 实现毛乌素沙地土地资源可持续利用的有效途径，在于这样几个方面：①建立和完善政府及其管理部门与人民之间有效的对话和合作机制，让广大农牧民参与到土地利用决策和管理的过程中去：②实行产业结构调整，转变片面追求经济增长的做法，制订适应当地自然条件和生态特征的发展模式;③降低农牧业税收、稳定并提高农牧业产品的物价，增加农牧民经济收入，减轻土地利用压力;④进一步改进和完善土地利用管理政策和法规;⑤建立有效激励机制，引导农牧民土地利用向着可持续的方向发展：⑥努力改进节水灌溉技术、生物增产技术，提高土地利用的科技水平：⑦改进环境保护和植被建设决策的科学性，提高植被建设的成效。

Biodiversity changes in the lakes of the Central Yangtze

The Central Yangtze ecoregion in China includes a number of lakes, but these have been greatly affected by human activities over the past several decades, resulting in severe loss of biodiversity. In this paper, we document the present distribution of the major lakes and the changes in size that have taken place over the past 50 years, using remote sensing data and historical observations of land cover in the region. We also provide an overview of the changes in species richness, community composition, population size and age structure, and individual body size of aquatic plants, fishes, and waterfowl in these lakes. The overall species richness of aquatic plants found in eight major lakes has decreased substantially during the study period. Community composition has also been greatly altered, as have population size and age and individual body size in some species. These changes are largely attributed to the integrated effects of lake degradation, the construction of large hydroelectric dams, the establishment of nature reserves, and lake restoration practices.

黄土高原小流域土地类型分类及制图研究——以固原市上黄试区为例

文章以固原市上黄试区为研究对象,在综合性、主导性和实用性分类原则的指导下,建立了黄土高原小流域尺度上的土地类型分类体系,并借助Arcview/Arcinfo/Erdas等地理信息系统软件对分类结果进行了制图。以期为今后相同地貌类型和尺度下的土地类型分类研究奠定工作基础,同时为上黄试区水土流失治理与土地资源的合理配置提供科学依据。