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30m全球地表覆盖遥感制图生产体系与实践 总被引：1，自引：0，他引：1
在以"多源影像最优化处理、参考资料服务化整合、覆盖类型精细化提取、产品质量多元检核"为主线的总体研究基础上,依托生产技术规范体系、全过程质量控制手段和支持环境,通过30m地表覆盖产品和技术设计、多源影像资料收集整合处理、分区按类型地表覆盖数据提取组织实施及数据产品集成与优化,构建了工程化的30m全球地表覆盖遥感制图生产体系,实现了预期的产品指标,完成了2000和2010两个基准年的30m地表覆盖数据产品研制。通过精度评价,该套数据产品分类精度达到80%以上。该生产体系的构建为开展较高分辨率全球地表覆盖数据产品研制、细化、更新奠定了基础,为开展大规模遥感影像信息提取、表达和应用起到了示范作用。 相似文献
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高时空分辨率的全球多类别土地覆盖数据对于地球系统的生物化学循环、气候变化等研究至关重要。目前公开的数据产品中,较高空间分辨率的全球多类别土地覆盖产品仅提供单一或短时期的数据,而全球逐年土地覆盖产品往往只有单一土地覆盖类型,难以从较长时间跨度上反映精细地物的年际变化。本文借助Google Earth Engine平台,利用现有多套全球土地覆盖产品、Landsat卫星系列影像、以及大量人工目视解译样本,结合多数据融合、时序变化检测和机器学习等的方法,研制了一套2000年—2015年全球30 m分辨率的逐年土地覆盖变化数据集AGLC-2000-2015（Annual Global Land Cover 2000-2015）。基于AGLC-2000-2015数据集,本文选择性分析了3个典型区域（中国珠江三角洲地区、青藏高原色林错湖区和亚马逊热带雨林区）的土地覆盖年际变化。结果显示,AGLC-2000-2015数据集达到了较高的精度水平：基准年份产品（AGLC-2015）的总体精度（OA）为76.10%,Kappa系数为0.72,显著优于现有30 m分辨率的全球土地覆盖产品Globeland 30（OA = 63.49%,Kappa = 0.58）、FROM-GLC（OA = 61.41%,Kappa = 0.55）和GLC-FCS30（OA = 63.46%,Kappa = 0.57）;年际间分类模型的总体精度和Kappa系数分别为84.10%和0.81,在各大洲的平均总体精度均超过80.00%,表明该模型在全球多类别土地覆盖分类中表现良好。3个典型区域的土地覆盖变化分析显示,中国珠江三角洲地区城市扩张趋势明显（195.96 km2/a）,其增量主要来源于耕地（84.88%）;青藏高原色林错湖泊对于气候变暖响应明显,湖区面积呈扩大趋势（17.95 km2/a）,湖面北岸扩张最为明显;亚马逊热带雨林南部区域毁林造田趋势明显,15 a间森林面积减少46356.53 km2,其中大部分转化为农田（39621.29 km2）。上述结果表明：AGLC-2000-2015数据集能够有效反映全球陆地区域在30 m空间分辨率下的地表覆盖分布及年际间的动态演化,为地表陆面过程研究和相关应用提供可靠的数据支撑。 相似文献
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基于30 m地表覆盖数据产品完成湿地精细化分类,能够更好地满足当前较高分辨率及较详尽全球湿地数据的应用需求。本文在深入分析湿地分类体系与细化方法的基础上,提出以湿地细化类别的定义、多元知识的分层分类、亚类数据精细化提取为主线的总体研究思路,制定了基于先验知识的对象系统筛选、基于森林数据的同位像元提取、基于最佳阈值的极大似然掩膜的主体分类方法,并应用于数据生产实践获得8个亚类信息。该方法克服了常规手段普遍存在的周期长、效率低等弊端,实现了全球较高分辨率湿地亚类数据的快速精确制图,总体分类精度达82.6%,对地理世情及其他地表覆盖研究具有借鉴意义。 相似文献
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全球30m地表覆盖遥感制图的总体技术 总被引：7，自引：0，他引：7
本文针对全球30米分辨率地表覆盖遥感制图这一世界性难题,提出了以多源影像最优化处理、参考资料服务化整合、覆盖类型精细化提取、产品质量多元化检核为主线的总体研究思路,研发了影像几何与辐射重建、异质异构服务化集成、对象化分层分类、知识化检核处理等主体技术方法;用于制定了相应数据产品规范、生产技术规范,研发了多项生产型软件,用于研制了2000和2010两个基准年的全球）30米地表覆盖数据产品,将空间分辨率提高了1个数量级。 相似文献
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基于知识的GlobeLand30耕地数据质量检查方法与工程实践 总被引：3，自引：0，他引：3
全球地表覆盖数据产品GlobeLand30研制的一项重要任务是设计和研发数据质量检查方法,降低地表覆盖10大类型分类提取的错判率与漏判率.本文以耕地为例,分析了影响全球耕地信息提取的主要质量因素,凝练了耕地的地域分布、人文相关知识、时空稳定性、物候特征等方面的知识,构建了基于知识的数据质量检查规则,设计了由整体到局部、分区域检查与修改交互式处理的策略,形成了一种基于知识的全球耕地数据质量检查方法;并利用该方法开展了GlobeLand30耕地数据质量检查,将耕地数据精度提高到了83.06%.该方法对地理国情及其他地表覆盖研究具有借鉴意义. 相似文献
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亚马孙河流域地表覆盖时空变化影响着全球气候和生态系统的稳定,目前亚马孙河流域地表覆盖的研究广泛,具有海量数据和信息,但缺少系统性的时空知识体系。为了更好地了解亚马孙河流域地表覆盖时空变化知识,本文首先引入本体建模理论,提出了亚马孙河流域地表覆盖时空变化知识建模方法,利用Protégé工具完成了亚马孙河流域地表覆盖模式层的设计和构建;然后利用提取的亚马孙河流域地表覆盖时空变化数据、时空变化信息和景观格局指数等,完成了亚马孙河流域的建模,从而为亚马孙河流域的分析决策提供支撑。 相似文献
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全球地表覆盖遥感制图与关键技术研究项目要求对两个基准年度(2000年,2010年)的全球覆盖30 m分辨率遥感数据进行辐射处理,转换到地表反射率,数据以Landsat TM/ETM+为主,HJ-1A/B CCD数据为补充。海量数据中有些不适宜进行绝对大气校正,为了保证全球覆盖,对这些数据设计开发了一套自动的相对辐射处理及精度验证流程算法,利用相邻数据重叠区域进行相对辐射校正的方式,将数据由Oigital Number(DN)值直接转换为地表反射率,精度验证以MODIS地表反射率产品MOD09GA作为参考,比较对应波段数据的相对一致性,算法采用了图像分块处理技术及OpenMP加速技术提高效率,实际应用结果表明该算法流程可以满足项目对辐射处理精度、速度及自动化程度的要求。 相似文献
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全球土地覆盖制图在过去的10年中取得重要进展,空间分辨率从300 m增加至30 m,分类详细程度也有所提高,从10余个一级类到包含29类的二级分类体系。然而,利用光学遥感数据在大空间范围制图方面仍有诸多挑战。本文主要介绍在农田、居住区、水体和湿地制图方面的挑战,讨论在使用多时相和多传感器遥感数据上的困难,这将是未来遥感应用的趋势。由于各种地表覆盖数据产品有自己定义的地表覆盖类型体系和处理流程,通过调和以及集成各种全球土地覆盖制图产品能够满足新的应用目的,并且可以最大程度地利用已有的土地覆盖数据。然而,未来全球土地覆盖制图需要能够按照新应用需求动态生成地表覆盖数据产品的能力。过去的研究表明有效地提高局部尺度制图的分类精度,更好的算法、更多种特征变量(新类型的数据或特征)以及更具代表性的训练样本都非常重要。我们却认为特征变量的使用更重要。本文提出了一个全球土地覆盖制图的新范式。在这个新范式中,地表覆盖类型的定义被分解为定性指标的类、定量指标的植被郁闭度和高度。非植被类型通过它们的光谱和纹理信息提取。复合考虑类、郁闭度和高度3种指标来定义和区别包含植被的地表覆盖类型。郁闭度和高度不能在分类算法中提取,需要借助其他直接测量或间接反演方法。新的范式还表明,一个普遍适用的训练样本集有效地提高了在非洲大陆尺度土地覆盖分类。为了确保更加容易地实现从传统的土地覆盖制图到全球土地覆盖制图新范式的转变,建议构建一体化的数据管理和分析系统。通过集成相关的观测数据、样本数据和分析算法,逐步建成全球土地覆盖制图在线系统,构建全球地表覆盖制图门户网站,为数据生产者、数据用户、专业研究人员、决策人员搭建合作互助的平台。 相似文献
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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). 相似文献
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NOAA/AVHRR Global Vegetation Index (GVI) data of Asia in 1983 and 1987 were used to evaluate their usefulness for global land cover monitoring. Color composite images of monthly GVI data and color composite images of principal components from 12 successive monthly GVI data were found to be useful for visual interpretation of seasonal vegetation dynamics. The results of cluster analysis applied to monthly GVI data for a one‐year period, indicate that unsupervised classification method is useful for global or continental land cover classification without ground truth. In order to detect land cover changes, the difference between the 1983 and 1987 12‐month GVI data was calculated. The results show that it is difficult to detect land cover changes due to cloud contamination in monthly GVI data and poor registration of GVI products. 相似文献
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Ian McCallum Michael Obersteiner Sten Nilsson Anatoly Shvidenko 《International Journal of Applied Earth Observation and Geoinformation》2006,8(4):246-255
Global change issues are high on the current international political agenda. A variety of global protocols and conventions have been established aimed at mitigating global environmental risks. A system for monitoring, evaluation and compliance of these international agreements is needed, with each component requiring comprehensive analytical work based on consistent datasets. Consequently, scientists and policymakers have put faith in earth observation data for improved global analysis. Land cover provides in many aspects the foundation for environmental monitoring [FAO, 2002a. Proceedings of the FAO/UNEP Expert Consultation on Strategies for Global Land Cover Mapping and Monitoring. FAO, Rome, Italy, 38 pp.]. Despite the significance of land cover as an environmental variable, our knowledge of land cover and its dynamics is poor [Foody, G.M., 2002. Status of land cover classification accuracy assessment. Rem. Sens. Environ. 80, 185–201]. This study compares four satellite derived 1 km land cover datasets freely available from the internet and in wide use among the scientific community. Our analysis shows that while these datasets have in many cases reasonable agreement at a global level in terms of total area and general spatial pattern, there is limited agreement on the spatial distribution of the individual land classes. If global datasets are used at a continental or regional level, agreement in many cases decreases significantly. Reasons for these differences are many—ranging from the classes and thresholds applied, time of data collection, sensor type, classification techniques, use of in situ data, etc., and make comparison difficult. Results of studies based on global land cover datasets are likely influenced by the dataset chosen. Scientists and policymakers should be made aware of the inherent limitations in using current global land cover datasets, and would be wise to utilise multiple datasets for comparison. 相似文献
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地表覆盖分类数据对区域森林叶面积指数反演的影响 总被引：2，自引：0，他引：2
以江西省吉安市为研究区,将5种全球地表覆盖分类数据(包括美国地质调查局(USGS)、马里兰大学(UMD)和波士顿大学(BU)生成的3套数据和欧洲生成的2套数据)以及由TM影像生成的区域地表覆盖分类数据,分别与MODIS1km反射率资料结合,利用基于4尺度几何光学模型的LAI反演方法生成研究区的LAI。在1km和4km两种尺度上将反演的LAI与TM资料生成的LAI进行比较,评价地表覆盖分类数据对LAI反演结果的影响。结果表明,TM和欧洲太空局的GLOBCOVER地表覆盖分类数据用于反演LAI的结果较好,在1km尺度上,反演的LAI与统计模型估算的TMLAI相关的R2分别为0.44和0.40,在4km尺度上的R2分别为0.57和0.54;其次为波士顿大学的MODIS地表覆盖分类数据,据其反演的LAI与TMLAI相关的R2在1km和4km尺度上分别为0.38和0.51;而马里兰大学的UMD和欧洲的GLC2000地表覆盖分类数据会导致反演的LAI存在较大误差,据其反演的LAI与TMLAI之间的一致性较差,在1km和4km两种尺度上平均偏低20%左右;LAI的反演结果对聚集度系数具有强的敏感性。该研究表明,为了提高区域/全球LAI反演精度,需要有高质量的地表覆盖分类数据。 相似文献
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KennedyOkelloWERE 《遥感学报》2010,14(1):180-196
<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. 相似文献
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Jamal Jokar Arsanjani 《International Journal of Digital Earth》2019,12(6):642-660
Global land cover maps are important sources of information for a wide range of studies including land change analysis and climate change research. While the global land cover maps attempt to present a consistent and homogenous data in terms of the production process, the existing datasets offer coarse resolution data, e.g. 1000 m for IGBP DISCover and 300 m for GlobeCover 2009 that is oftentimes challenging. Recently, GlobeLand30 data based on Landsat archive for two timestamps of 2000 and 2010 has been released. It presents a finer spatial resolution of 30 m, which provides numerous opportunities for a wide range of studies. The main objective of this study is to use this dataset for characterizing global land cover patterns, monitoring, and identifying extreme land change cases with their types and magnitude. The findings reveal massive land change patterns including deforestation, desertification, shrinkage of water bodies, and urbanization across the globe. The results and discussions of this research can help policy-makers, environmental planners, ecosystem services providers and climate change researchers to gain finer insights about the forms of global land change. Future research calls for further investigation of the underlying causes of the massive changes and their consequences on our ecosystems and human populations. 相似文献
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Mahendra S. Lodhi Prasanna K. Samal Shivaji Chaudhry L. M. S. Palni P. P. Dhyani 《Journal of the Indian Society of Remote Sensing》2014,42(2):461-467
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. 相似文献
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There is much interest in using volunteered geographic information (VGI) in formal scientific analyses. This analysis uses VGI describing land cover that was captured using a web-based interface, linked to Google Earth. A number of control points, for which the land cover had been determined by experts allowed measures of the reliability of each volunteer in relation to each land cover class to be calculated. Geographically weighted kernels were used to estimate surfaces of volunteered land cover information accuracy and then to develop spatially distributed correspondences between the volunteer land cover class and land cover from 3 contemporary global datasets (GLC-2000, GlobCover and MODIS v.5). Specifically, a geographically weighted approach calculated local confusion matrices (correspondences) at each location in a central African study area and generated spatial distributions of user's, producer's, portmanteau, and partial portmanteau accuracies. These were used to evaluate the global datasets and to infer which of them was 'best’ at describing Tree cover at each location in the study area. The resulting maps show where specific global datasets are recommended for analyses requiring Tree cover information. The methods presented in this research suggest that some of the concerns about the quality of VGI can be addressed through careful data collection, the use of control points to evaluate volunteer performance and spatially explicit analyses. A research agenda for the use and analysis of VGI about land cover is outlined. 相似文献