基于镶嵌数据集的省级“一张图”影像管理

比较传统的数据管理模式,采用文件系统＋数据库系统存储管理模式。广东省“一张图”影像数据以Mr-SID的压缩形式存储,并通过ArcGIS的镶嵌数据集,完成影像数据和元数据的入库,解决了省级海量影像数据管理和应用的技术瓶颈,实践证明该管理方式可行。     

元数据和数据集一体化管理模型及应用研究

元数据和数据集是紧密联系的，基于元数据和数据集的一体化管理模型的3层体系结构，解决了元数据和数据独立管理的问题，并从数据集对象的建立、数据集对象的查询和获取、数据集对象的变更3个方面阐述了该管理模型的实现流程。最后在中山市国土房管局综合信息建设中，基于该模型和运用元数据和数据集一体化管理系统IIMS进行了应用研究。     

参考数据集的数据质量管理

地理信息团体习惯于使用现有的数据集,元数据(关于数据的数据)也随之日渐重要,数据质量正是元数据的一个重要方面。为广泛使用地理信息,出现了包括全球空间基础设施、欧洲的 INSPIRE以及国家空间数据基础设施(澳大利亚、美国)等项目。开放地理信息系统联盟 (OGC)已推出在不同应用程序间的数据转换方     

发展卫星遥感数据的定量分析方法

本文建议从四个方面发展卫星遥感数据的定量分析方法：（１）在空间数据库支持下的遥感数据处理的分析;（２）建立区域多时相,多波段怕样本知识库;     

基于ArcGIS的青藏高原地区气候大陆性格局分布研究

利用Modis温度产品数据集,应用ENVI及ArcGIS软件通过计算青藏高原地区气候大陆度指数(温度法)分析青藏高原地区的水热格局分布,结果表明：青藏高原地区气候大陆性分布呈现明显的区域性分布,且由东南至西北大陆性气候逐步加强;以喜马拉雅山脉和雅鲁藏布江为主的南部区域呈现明显的海洋性气候,且会向北方和东方扩展;以塔里木盆地为中心的地区大陆性气候十分明显,今后会更加严重。通过对青藏高原的气候大陆度的研究,得到青藏地区大陆性气候的变化,可以帮助深入了解青藏高原环境的变化过程、程度、趋势以及可能带来的后果以及对其他地区可能产生的影响,同时促进全球气候变化的研究进程。     

珠海一号高光谱场景分类数据集

高空间分辨率、高光谱分辨率、大幅宽与大数据量是高光谱卫星数据发展趋势,传统高光谱影像的像素级分类面临难以处理海量数据、无法高效获取复杂海量影像中隐含信息的困境。已有研究开始关注高光谱影像的场景级分类,并逐步建立完善高光谱遥感场景分类数据集。然而,目前的数据集制作过程多参考高空间分辨率可见光遥感场景数据集的制作方法,主要采用遥感影像的空间信息进行场景类别解译,忽视了高光谱场景的光谱信息。因此,为构建高光谱影像的遥感场景分类数据集,本文利用“珠海一号”高光谱卫星拍摄的西安地区高光谱数据,使用无监督光谱聚类辅助定位、裁剪与标注待选场景样本,结合Google Earth高分影像进行目视筛选,构建6类场景类型和737幅场景样本的珠海一号高光谱场景分类数据集。并基于光谱与空间两个视角开展场景分类实验,通过视觉词袋、卷积神经网络等方法的基准测试结果,对不同算法在现有多光谱和高光谱遥感场景分类数据集下的性能进行深入分析。本研究可为后续的高光谱影像解译研究提供了有力的数据支撑。     

海南基础地理信息数据集的设计

利用现有的基础地理信息数据,采用多种信息集成的处理方法,结合地理分析和统计模型,挖掘和开发现有多尺度基础地理信息数据中潜在的知识和可利用价值,对海南基础地理信息数据集的设计进行了详细阐述。     

基于元数据和数据集管理的空间数据共享研究

以实现地理空间数据的标准化为前提,实现数据共享及发布为目的,指出传统的基于数据集的共享模式存在着弊端,需要建立基于元数据和数据集相结合的管理机制,同时提出了元数据库设计的思想,这对于解决数据共享中的异地、异构存储是有借鉴意义的,该思想可以在数字山东的数据共享中得以实施和应用。     

点云深度学习基准数据集

为推进深度学习方法在点云配准、语义分割、实例分割等领域的发展,武汉大学联合国内外多家高等院校和研究机构发布了包含多类型场景的地面站点云配准基准数据集WHU-TLS和包含语义、实例的城市级车载点云基准数据集WHU-MLS.其中,WHU-TLS基准数据集涵盖了地铁站、高铁站、山地、公园、校园、住宅、河岸、文化遗产建筑、地下...     

植被覆盖区高精度遥感地貌场景分类数据集

地貌数据集是实现地貌自动分类和加深对地貌形态学认识的重要支撑数据之一。当前缺乏高精度地貌成因类数据集,制约了地貌遥感自动解译的发展。本文在中国东北地区以沟—弧—盆体系为主的天山—兴蒙造山系中,针对强烈的构造运动和新生代以来的火山作用、流水作用形成的地貌成因类型,制作了构造地貌、火山熔岩地貌和流水地貌3类场景数据集（GOS10m）。数据集覆盖面积约5000 km²,包括哨兵2号可见光遥感影像、SRTM1 DEM及基于DEM提取的7个地貌形态参数（山体晕渲图、坡度、DEM局部平均中值、标准偏差、坡向—向北方向偏移量、坡向—向东方向偏移量和相对偏离平均值）。单张样本图为64像素×64像素,空间分辨率为10 m。采用多模态深度学习神经网络对数据进行训练并分类,平均测试精度可达到82.63%,表明构建的数据集具有较高的质量。可为地貌成因遥感自动分类研究以及推动遥感地貌智能解译的向前发展,提供数据集支撑。     

Glacier changes using satellite data and effect of climate in Tirungkhad basin located in western Himalaya

Glaciers are widely recognized as key indicators of climate change, and melt water obtained from them is an important source of fresh water and for hydropower generation. Regular monitoring of a large number of Himalayan glaciers is important for improving our knowledge of glacier response to climate change. In the present study, Survey of India topographical maps (1966) and Landsat datasets as ETM+ (2000, 2006) and TM (2011) have been used to study glacier fluctuations in Tirungkhad basin. A deglaciation of 26.1% (29.1?km²) in terms of area from 1966 to 2011 was observed. Lower altitude small glaciers (area?<?1?km²) lost more ice (34%), while glaciers with an area <10?km² lost less (20%). The percentage of change in glacier length was 26% (31.9?km) from 1966 to 2011. The south-facing glaciers showed high percentages of loss. From 2000 to 2011, debris cover has increased by 1.34%. The analysis of the trend in meteorological data collected from Kalpa and Purbani stations was carried out by Mann Kendall non-parametric method. During the last two decades, the mean annual temperature (T_max and T_min) has increased significantly, accompanied with a fall in snow water equivalent (SWE) and rainfall. The increasing trend in temperature and decreasing trend in SWE were significant at 95% confidence level. This observation shows that the warming of the climate is probably one of the major reasons for the glacier change in the basin.     

后疫情时代全球气候变化的应对与抉择

后疫情时代,全球气候变化影响和应对呈现新趋势,突发性、全球性和关联性成为鲜明的特征.当前,要着力解决应对气候变化的重大科学问题,就必须继续务实加强基础研究,妥善处理应对全球变化的挑战和可持续发展之间的关系;根据中国国情选择自己的气候变化应对之路;进一步处理好减排与增汇、减缓与适应的关系;设立国家碳中和重大专项;制定和实...     

Land change attribution based on Landsat time series and integration of ancillary disturbance data in the Athabasca oil sands region of Canada

The Alberta Oil Sands (AOS) is a unique area in Canada undergoing significant disturbance and recovery due to a variety of anthropogenic and natural factors. Accurately quantifying these changes in space and time is important for assessing ecosystem status and trends. In this research, we implemented an approach to combine Landsat time series for the period 1984–2012 with ancillary change datasets to derive detailed change attribution in the AOS. Detected changes were attributed to causes including fire, forest harvest, surface mining, insect damage, flooding, regeneration, and several generic change classes (abrupt/gradual, with/without regeneration) with accuracies ranging from 74% to 100% for classes that occurred frequently. Lower accuracies were found for the generic gradual change classes which accounted for less than 3% of the affected area. Timing of abrupt change events were generally well captured to within ±1 year. For gradual changes timing was less accurate and variable by change type. A land-cover time series was also created to provide information on “from-to” change. A basic accuracy assessment of the land cover showed it to be of moderate accuracy, approximately 69%. Results show that fire was the major cause of change in the region. As expected, surface mine development and related activities have increased since 2000. Insect damage has become a more significant agent of change in the region. Further investigation is required to determine if insect damage is greater than past historical events and to determine if industrial development is linked to the increasing trend observed.     

Identifying coastal towns and small cities in Denmark using global population data to support climate change adaptation

ABSTRACT

Coastal settlements face many hazards from climate change. Consequently, there has been extensive focus on developing and implementing adaptation. However, these efforts have prodominantly centred on larger cities. Coastal towns and small cities (urban areas between 1000 and 100,000 people) have received little attention, despite experiencing a number of barriers to adaptation. The absence of information on the global scale of the adaptation challenge within coastal towns and small cities may have contributed to these settlements being overlooked. This paper develops a method that can be used to estimate the numbers, sizes, and locations of coastal towns and small cities worldwide from global population data (Global Human Settlement data). Denmark is used as a pilot for this method with settlements over 1000 people classified with relatively high accuracy. The method developed here represents a potentially fruitful approach to supporting coastal adaptation, as coastal towns and small cities are identifiable globally, they can be classified into types. This will support an assessment of their risk to coastal hazards, and could facilitate knowledge and practice sharing between similar coastal towns and small cities.     

遥感影像变化检测样本自动抽样

在遥感影像结合矢量数据先验信息的变化检测中,需要从分割后的影像对象中抽取一定数量、具有相同类别属性的样本,其中不可避免地抽到类别属性不一致的样本,如何剔除这些样本是抽样过程中必须解决的重点问题,在目前已有的方法中,一般是通过人工目视判别完成的。样本的自动提取是实现自动变化检测的关键环节,本文提出一种变化检测样本自动抽样方法,主要包括样本的空间布设和异常样本自动检测两个环节。该方法首先利用矢量数据提取抽样图层,用抽样图层分割遥感影像,获取影像对象。其次是根据抽样区域范围、影像对象分布特征和地形特征布设变化检测样本。然后根据样本的先验类别属性构建特征空间向量,计算样本在特征空间的局部可达密度,由局部可达密度计算样本的异常度指数,并根据特征空间密度异常指数剔除异常样本,完成变化检测样本自动提取。最后以耕地、林地和居民地为例进行了抽样试验。结果表明,邻域参数k按样本布设总数的1/5—1/3取值、异常度阈值设定为80%时,可以实现异常样本0漏检率,能够准确、高效实现变化检测样本的自动提取。     

A multi-scale spatiotemporal modeling approach to explore vegetation dynamics patterns under global climate change

Given the complexity of vegetation dynamic patterns under global climate change, multi-scale spatiotemporal explicit models are necessary in order to account for environmental heterogeneity. However, there is no efficient time-series tool to extract, reconstruct and analyze the multi-scale vegetation dynamic patterns under global climate change. To fill this gap, a Multi-Scale Spatio-Temporal Modeling (MSSTM) framework which can incorporate the pixel, scale, and time-specific heterogeneity was proposed. The MSSTM method was defined on proper time-series models for multi-temporal components through wavelet transforms. The proposed MSSTM approach was applied to a subtropical mountainous and hilly agro-forestry ecosystem in southeast China using the moderate resolution imaging spectroradiometer enhanced vegetation index (EVI) time-series data sets from 2001 to 2011. The MSSTM approach was proved to be efficient in characterizing and forecasting the complex vegetation dynamic patterns. It provided good estimates of the peaks and valleys of the observed EVI and its average percentages of relative absolute errors of reconstruction was low (6.65). The complexity of the relationship between vegetation dynamics and meteorological parameters was also revealed through the MSSTM method: (1) at seasonal level, vegetation dynamic patterns are strongly associated with climatic variables, primarily the temperature and then precipitation, with correlations slight decreasing (EVI–temperature)/increasing (EVI–precipitation) with altitudinal gradients. (2) At inter-annual scale, obvious positive correlations were primarily observed between EVI and temperature. (3) Despite very low-correlation coefficients observed at intra-seasonal scales, considerable proportions of EVI anomalies are associated with climatic variables, principally the precipitation and sunshine durations.     

陆表定量遥感反演方法的发展新动态

随着获取的遥感数据越来越多,定量遥感正处于一个飞速发展的时期。本文从反演方法和遥感数据产品生成两个主要方面对近期陆表定量遥感的发展进行评述。由于大气—陆表系统的环境变量数远远超过遥感观测数,定量遥感反演的本质是个病态反演问题。在评述机器学习方法(包括人工神经网络、支持向量回归、多元自适应回归样条函数等)的应用基础上,重点关注克服病态反演的7种正则化方法:多源数据、先验知识、最优化反演的求解约束、时空约束、多反演算法集成、数据同化和尺度转换。定量遥感发展的另外一个显著特征是由数据提供者(比如数据中心)将观测的遥感数据转换成不同的地球生物物理化学参数产品,即遥感高级产品,并服务于数据使用者。概括介绍了北京师范大学牵头研发的GLASS(Global LAnd Surface Satellite)产品的新进展与全球气候数据集的研发情况。     

基于多源空间数据的河道水域变化监测方法研究

近年来,随着经济社会的快速发展,河道水域占用情况日益增多,严重影响河道防洪、排涝等正常水域功能的发挥。以浙江省省级河道为例,以覆盖浙江全省的高分辨率航片、省级基础地理信息数据等多源空间数据为基础,结合测绘和水利标准,提出基于多源空间数据的河道水域变化监测方法。方法充分利用高精度的基础测绘空间数据,保证成果的可靠性,同时符合水利部门的规定,能够满足水利部门的实际需要。研究结果表明,2008-2012年间,浙江省省级河道水域减少情况严重,主要减少类型为建设用地。方法为水利部门全面、客观地掌握水域的无序占用情况提供了一种有效手段。     

三种卫星云量数据在青藏高原地区的比对分析

青藏高原是卫星反演云参数的热点和难点区域.选取1982年—2015年0.1°空间分辨率的Patmos-x、0.25°空间分辨率的CLARA-A2的NOAA/AVHRR下午星数据和2003年—2015年0.05°空间分辨率的Aqua/MODIS C6等3种云量数据,针对青藏高原区域,从数据的反演算法和数据的空间属性出发,...     

Populating digital earth: improving access to Chinese remote sensing data for terrestrial applications

Global change has a significant impact on the lives of humankind. Earth observation can help to better understand our earth and cope with global change. With the availability of more reliable environmental data sets, digital earth is becoming a popular way to monitor the Earth and provide information to researchers and decision makers on environment protection, disaster mitigation, and social benefits. Therefore, accessing data with lowering costs is essential for digital earth. Nevertheless, there are big challenges in ensuring the feasibility of access to Chinese remote sensing data. This paper outlines some of the main challenges in realizing data sharing, provides an analysis of the core reasons leading to these challenges, and proposes recommendations to overcome the challenges. Amongst the main challenges are differences in data policy to gain access to satellite data, diverse data formats, and delivery mechanisms. The major challenge for the decision makers is to define a more open policy and for the scientist the challenge is to implement these polices for the benefit of all. This paper proposes that governments should adopt policies encouraging more open distribution and access to their data, in order to generate an improved digital earth with increased benefits to human society.