发扬夏坚白院士精神,倡导尊重知识、重视知识产权的行业之风

前不久,报章上出现了这样一条消息:国家信息产业部、国家版权局、商务部、财政部四部委联合下发了<关于计算机预装正版操作系统软件有关问题的通知>.根据通知精神,从现在开始没有预装正版操作系统的PC产品将无法上市销售.     

搜酷

强悍的摄像机作为索尼XR系列摄像机的开篇之作,HDRXR520E集众多项级配置于一身,采用了在低光照环境下有着出色表现的Exmor R CMOS感光元件,     

中国最美的古村落(十) 浙中奇绝 乌石古村

最吸引人的是这里的建筑,古民居外墙都由一小块一小块的乌石垒成,粗犷的外形与凝重的黑色相结合,结构精巧独特,给人以"鬼斧神工"的感觉,据说最早的乌石屋已有近三百年的历史.     

电脑族每天必喝的四杯茶

1.上午一杯绿茶绿茶中含强效的抗氧化剂以及维生素C,不但可以清除体内的自由基,还能分泌出对抗紧张压力的荷尔蒙。绿茶中所含的少量咖啡因可以刺激中枢神经,振奋精神。不过最好在白天饮用,以免影响睡眠。2.下午一杯菊花茶菊花有明目清肝的作用,有些人就干脆用菊花加上枸杞一起泡来喝,或     

国家测绘局跨世纪青年学术带头人李清泉教授

李清泉教授生于1965年1月,安徽天长人,中共党员,工学博士,武汉大学副校长,湖北省第八、九届政协委员,第二届"湖北省五四青年奖章"获得者,湖北省青年联合会第十届委员会副主席,武汉市青年联合会第十届委员会副主席,李清泉教授先后承担了教学、科研、产业和财务管理以及大量社会工作.     

同江:一曲赫哲族船歌

同江位于三江平原北端,黑龙江与松花江汇流处南岸的三角地带,是有百年历史的国际口岸城市,由佳木斯市代管。清末设立临江州,1905年辟为通商口岸,1914年以黑龙江、松花江在此合一而改名同江。东接抚远,南邻饶河,北与俄列宁斯科耶隔水相望,边境线长166公里,设有国家一类口岸。同江有八岔、街津口两个赫哲族乡,这是一个只有四千人口,却在漫     

中国最美的古村落(一)千古太极奇村——俞源探秘

俞源的经典在于村落结构的设计:村中有大小七个水塘组成北斗七星的格局,村内的28幢主要建筑则按照天上的28星宿排布。     

万维网GIS的若干关键技术及其实现

提出基于J2EE多层体系结构的WebGIS系统,能够平衡好服务器、应用服务器、客户端负载,极大地提高系统的响应速度;对海量的矢量数据与影像数据采用不同的压缩方式,在数据不失真的情况下尽量减少数据的传输量,减轻网络的负载;栅格数据与矢量数据的"无缝"叠加,更加形象清楚地发布空间数据;基于0racle Spatial关系数据库的WebGIS,使系统更加安全可靠.     

飞地:孤悬在外的领土

从明清之交,到解放初的三百多年间,在(四川)峨眉县普兴乡境内,曾有一个地名叫何沟(亦叫梅沟)的小山村,只有十几户人家,却直属嘉定府管辖,毗连的夹江,峨眉、洪雅、乐山四县,无权过问,是一个"世外桃源",当地人称它是"飞地"……梅沟成为一个四不管的角落.     

数字

1.26亿吨近日,黑龙江省煤田地质勘察队在鹤岗市萝北县江滨农场境内发现一处总面积为124.88平方公里,储量约1.26亿吨,煤层平     

Next generation of global land cover characterization,mapping, and monitoring

Land cover change is increasingly affecting the biophysics, biogeochemistry, and biogeography of the Earth's surface and the atmosphere, with far-reaching consequences to human well-being. However, our scientific understanding of the distribution and dynamics of land cover and land cover change (LCLCC) is limited. Previous global land cover assessments performed using coarse spatial resolution (300 m–1 km) satellite data did not provide enough thematic detail or change information for global change studies and for resource management. High resolution (∼30 m) land cover characterization and monitoring is needed that permits detection of land change at the scale of most human activity and offers the increased flexibility of environmental model parameterization needed for global change studies. However, there are a number of challenges to overcome before producing such data sets including unavailability of consistent global coverage of satellite data, sheer volume of data, unavailability of timely and accurate training and validation data, difficulties in preparing image mosaics, and high performance computing requirements. Integration of remote sensing and information technology is needed for process automation and high-performance computing needs. Recent developments in these areas have created an opportunity for operational high resolution land cover mapping, and monitoring of the world. Here, we report and discuss these advancements and opportunities in producing the next generations of global land cover characterization, mapping, and monitoring at 30-m spatial resolution primarily in the context of United States, Group on Earth Observations Global 30 m land cover initiative (UGLC).     

土地覆盖变化信息自适应抽样策略及其精度评估

提出了一种面向土地覆盖变化信息局域精度评估的自适应型抽样策略。结合待研究地图的土地覆盖变化信息局部特征（如土地覆盖变化类别、斑块大小、异质性和优势度）,探讨与土地覆盖变化信息精度显著相关的协变量,以预测精度的标准误差作为判断标准,识别需要提高精度预测结果可靠性的区域,以自适应地和逐步定位的方式进行样本采集。基于武汉地区的精度评价结果,自适应的抽取增加100个训练样本使得预测精度的确定系数提高了50.66%,而简单随机抽取的增加样本使得预测精度的确定系数提高了17.22%。试验表明,自适应型抽样策略能显著提高土地覆盖变化信息局域精度预测的抽样效益,减少预测精度的不确定性。模型选择的结果表明,土地覆盖变化类别和优势度指数是最优的协变量组合。     

Approaches for Linking People,Place, and Environment for Human Dimensions Research

Abstract

Much of the human dimensions of environmental change research emphasize the mapping and modeling of land use and land cover patterns over space and time, and the linkages between people, place, and environment as proximate and distal forces of landscape dynamics. Spatial digital technologies, framed within a GIScience (GISc) context, figure prominently in the characterization of land use and land cover through remote sensing technologies, and in the assessment of social and demographic factors and local and regional site and situation considerations achieved through global positioning systems, data visualizations, and spatial and statistical analyses. Here, we describe some fundamental approaches for linking data across thematic domains, essential for the study of human‐environment interactions. The goal is to generate compatible data sets that extend across social, biophysical, and geographical domains so that the causes and consequences of land use and land cover dynamics might be explored within a spatially‐explicit context.     

Application of Earth Remote Sensing and GIS in Mapping Land Cover Patterns in Kinangop Division, Kenya

<正>Land cover is a fundamental variable that links many facets of the natural environment and a key driver of global environmental change.Alterations in its status can have significant ramifications at local,regional and global levels.Hence,it is imperative to map land cover at a range of spatial and temporal scales with a view to understanding the inherent patterns for effective characterization,prediction and management of the potential environmental impacts.This paper presents the results of an effort to map land cover patterns in Kinangop division,Kenya,using geospatial tools.This is a geographic locality that has experienced rapid land use transformations since Kenya's independence culminating in uncontrolled land cover changes and loss of biodiversity.The changes in land use/cover constrain the natural resource base and presuppose availability of quantitative and spatially explicit land cover data for understanding the inherent patterns and facilitating specific and multi-purpose land use planning and management.As such,the study had two objectives viz.(i) mapping the spatial patterns of land cover in Kinangop using remote sensing and GIS and;(ii) evaluating the quality of the resultant land cover map.ASTER satellite imagery acquired in January 23,2007 was procured and field data gathered between September l0 and October 16,2007.The latter were used for training the maximum likelihood classifier and validating the resultant land cover map.The land cover classification yielded 5 classes,overall accuracy of 83.5%and kappa statistic of 0.79,which conforms to the acceptable standards of land cover mapping. This qualifies its application in environmental decision-making and manifests the utility of geospatial techniques in mapping land resources.     

Measures of spatio-temporal accuracy for time series land cover data

Remote sensing is a useful tool for monitoring changes in land cover over time. The accuracy of such time-series analyses has hitherto only been assessed using confusion matrices. The matrix allows global measures of user, producer and overall accuracies to be generated, but lacks consideration of any spatial aspects of accuracy. It is well known that land cover errors are typically spatially auto-correlated and can have a distinct spatial distribution. As yet little work has considered the temporal dimension and investigated the persistence or errors in both geographic and temporal dimensions. Spatio-temporal errors can have a profound impact on both change detection and on environmental monitoring and modelling activities using land cover data. This study investigated methods for describing the spatio-temporal characteristics of classification accuracy. Annual thematic maps were created using a random forest classification of MODIS data over the Jakarta metropolitan areas for the period of 2001–2013. A logistic geographically weighted model was used to estimate annual spatial measures of user, producer and overall accuracies. A principal component analysis was then used to extract summaries of the multi-temporal accuracy. The results showed how the spatial distribution of user and producer accuracy varied over space and time, and overall spatial variance was confirmed by the principal component analysis. The results indicated that areas of homogeneous land cover were mapped with relatively high accuracy and low variability, and areas of mixed land cover with the opposite characteristics. A multi-temporal spatial approach to accuracy is shown to provide more informative measures of accuracy, allowing map producers and users to evaluate time series thematic maps more comprehensively than a standard confusion matrix approach. The need to identify suitable properties for a temporal kernel are discussed.     

Comparison and relative quality assessment of the GLC2000, GLOBCOVER,MODIS and ECOCLIMAP land cover data sets at the African continental scale

Land cover dynamics at the African continental scale is of great importance for global change studies. Actually, four satellite-derived land cover maps of Africa now available, e.g. ECOCLIMAP, GLC2000, MODIS and GLOBCOVER, are based on images acquired in the 2000s. This study aims at stressing the compliances and the discrepancies between these four land cover classifications systems. Each of them used different mapping initiatives and relies on different mapping standards, which supports the present investigation. In order to do a relative comparison of the four maps, a preamble was to reconcile their thematic legends into more aggregated categories after a projection into the same spatial resolution. Results show that the agreement between the four land cover products is between 56 and 69%. While all these land cover datasets show a reasonable agreement in terms of surface types and spatial distribution patterns, mapping of heterogeneous landscapes in the four products is not very successful. Land cover products based on remote sensing imagery can indeed significantly be improved by using smarter algorithms, better timing of image acquisition, improved class definitions. Either will help to improve the accuracy of future land cover maps at the African continental scale. Data producers may use the areas of spatial agreement for training area selection while users might need to verify the information in the areas of disagreement using additional data sources.     

Assessing land use/cover changes: a nationwide multidate spatial database for Mexico

A nationwide multidate GIS database was generated in order to carry out the quantification and spatial characterization of land use/cover changes (LUCC) in Mexico. Existing cartography on land use/cover at a 1:250,000 scale was revised to select compatible inputs regarding the scale, the classification scheme and the mapping method. Digital maps from three different dates (the late 1970s, 1993 and 2000) were revised, evaluated, corrected and integrated into a GIS database. In order to improve the reliability of the database, an attempt was made to assess the accuracy of the digitalisation procedure and to detect and correct unlikely changes due to thematic errors in the maps. Digital maps were overlaid in order to generate LUCC maps, transition matrices and to calculate rates of conversion. Based upon this database, rates of deforestation between 1976 and 2000 were evaluated as 0.25 and 0.76% per year for temperate and tropical forests, respectively.     

Multi-resolution integration of land cover for sub-pixel estimation of urban impervious surface and forest cover

Abstract

A methodology is presented for estimating percent coverage of impervious surface (IS) and forest cover (FC) within Landsat thematic mapper (TM) pixels of urban areas. High-resolution multi-spectral images from Quickbird (QB) play a key role in the sub-pixel mapping process by providing information on the spatial distributions of ISs and FCs at 2.4 m ground sampling intervals. Thematic classifications, also derived from the Landsat imagery, have then been employed to define relationships between 30 m Landsat-derived greenness values and percent IS and FC. By also utilizing land cover/land use classification derived from Landsat and defining unique relationships for urban sub-classes (i.e. residential, commercial/industrial, open land), confusion between impervious and fallow agricultural lands has been overcome. Test results are presented for Ottawa-Gatineau, an urban area that encompasses many aspects typical of the North American urban landscape. Multiple QB scenes have been acquired for this urban centre, thereby allowing us to undertake an in-depth study of the error budgets associated with the fractional inference process.     

Land Cover Mapping for Namdapha National Park (Arunachal Pradesh), India Using Harmonized Land Cover Legends

Since last few decades RS-GIS is playing vital role in studying and mapping spatiotemporal responses of land cover, however, as a matter of fact, the mapping outputs largely depend on the expert's/user's preferences because location specific and people specific land cover classification systems are adopted autonomously for image classification in GIS. This may actually lead to an ambiguous definition of a particular land cover type when such different maps are compared at global level. In 1993, FAO and UNEP started efforts for development of a software tool know as LCCS which is a comprehensive standardized tool capable of providing land cover characterization to all possible land cover types in the world regardless of spatial relevance, mapping scale, data collection method etc. Adding to the global efforts of land cover legend harmonization and mapping, this study presents development of harmonized land cover legends for Namdapha National Park located in north-eastern Indian Himalayan region using LCCS and subsequent mapping. The potential of Remote Sensing (RS) and Geographical Information Systems (GIS) in forest/land cover mapping is very well recognized. Therefore, adopting the developed harmonized legends for the study area, land cover mapping was done using RS-GIS approach.