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Pietro Ceccato Sylwia Trzaska Carlos Pérez García-Pando Olga Kalashnikova John del Corral Rémi Cousin 《国际地球制图》2014,29(1):19-38
Public health professionals are increasingly concerned about the potential impact that climate variability and change can have on infectious disease. The International Research Institute for Climate and Society (IRI) is developing new products to increase the public health community’s capacity to understand, use and demand the appropriate climate data and climate information to mitigate the public health impacts of climate on infectious disease, in particular meningitis and malaria. In this paper, we present the new and improved products that have been developed for: (i) estimating dust aerosol for forecasting risks of meningitis and (ii) for monitoring temperature and rainfall and integrating them into a vectorial capacity model for forecasting risks of malaria epidemics. We also present how the products have been integrated into a knowledge system (IRI Data Library Map Room, SERVIR) to support the use of climate and environmental information in climate-sensitive health decision-making. 相似文献
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Urbanisation generates greater population densities and an increase in anthropogenic heat generation. These factors elevate the urban–rural air temperature (Ta) difference, thus generating the Urban Heat Island (UHI) phenomenon. Ta is used in the fields of public health and epidemiology to quantify deaths attributable to heat in cities around the world: the presence of UHI can exacerbate exposure to high temperatures during summer periods, thereby increasing the risk of heat-related mortality. Measuring and monitoring the spatial patterns of Ta in urban contexts is challenging due to the lack of a good network of weather stations. This study aims to produce a parsimonious model to retrieve maximum Ta (Tmax) at high spatio-temporal resolution using Earth Observation (EO) satellite data. The novelty of this work is twofold: (i) it will produce daily estimations of Tmax for London at 1 km2 during the summertime between 2006 and 2017 using advanced statistical techniques and satellite-derived predictors, and (ii) it will investigate for the first time the predictive power of the gradient boosting algorithm to estimate Tmax for an urban area. In this work, 6 regression models were calibrated with 6 satellite products, 3 geospatial features, and 29 meteorological stations. Stepwise linear regression was applied to create 9 groups of predictors, which were trained and tested on each regression method. This study demonstrates the potential of machine learning algorithms to predict Tmax: the gradient boosting model with a group of five predictors (land surface temperature, Julian day, normalised difference vegetation index, digital elevation model, solar zenith angle) was the regression model with the best performance (R² = 0.68, MAE = 1.60 °C, and RMSE = 2.03 °C). This methodological approach is capable of being replicated in other UK cities, benefiting national heat-related mortality assessments since the data (provided by NASA and the UK Met Office) and programming languages (Python) sources are free and open. This study provides a framework to produce a high spatio-temporal resolution of Tmax, assisting public health researchers to improve the estimation of mortality attributable to high temperatures. In addition, the research contributes to practice and policy-making by enhancing the understanding of the locations where mortality rates may increase due to heat. Therefore, it enables a more informed decision-making process towards the prioritisation of actions to mitigate heat-related mortality amongst the vulnerable population. 相似文献
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For ages, links between environment, climate and their impacts on human health have been observed and studied. Research to improve our understanding of environmental key determinants of infectious diseases can provide innovative information for adaptation strategies and lead to new tools optimizing surveillance, vector control measures, and disease prevention. As earth observation satellites can measure meteorological and environmental parameters, NASA and CNES have separately engaged in an innovative use of their earth observation infrastructure development programs: space tools addressing public health. As NASA and CNES have fruitful cooperation for satellite development missions for years, both health programs have proposed to explore a new area of collaboration: satellites addressing health issues. As members of international organizations, NASA and CNES could promote their common views towards the Group on Earth Observations (GEO) Community of Practice for Health & Environment and the Committee on Earth Observation Satellites (CEOS) Societal Benefit Area on Health. 相似文献
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地图数据和GIS相辅相成,缺一不可.要创建GIS系统,用什么样的数据,如何获取合适的地图数据,是一个关键的决策.在日本面向公众公开的地图可以分为两种类型:一是国家政府机关,也就是国土地理院笔(Geographical Survey Institute=GSI)发行的;另一个就是民营地图出版社发行的. 相似文献
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The Earth Observation (EO) data with their advantages in spectral, spatial and temporal resolutions have demonstrated their great value in providing information about many of the components that comprise environmental systems and ecosystems for decades that are crucial to the understating of public health issues. This literature review shows that in conjunction with in situ data collection, EO data have been used to observe, monitor, measure and model many environmental variables that are associated with disease vectors. Furthermore, satellite derived aerosol optical depth has been increasingly employed to estimate ground-level PM2.5 concentrations, which have been found to associate with various health outcomes such as cardiovascular and respiratory diseases. It is suggested that Landsat-like imagery data may provide important data sources to analyse and understand contagious and infectious diseases at the local and regional scales, which are tied to urbanisation and associated impacts on the environment. There is also a great need of data products from coarse resolution imagery, such as those from moderate resolution imaging spectrometer, multiangle imaging spectroradiometer and geostationary operational environmental satellite , to model and characterise infectious diseases at the continental and global scales. The infectious diseases at greater geographical scales have become unprecedentedly significant as global climate change and the process of globalisation intensify. The relationship between infectious diseases and environmental characteristic have been explored by using statistical, geostatistical and physical models, with recent emphasis on the use of machine-learning techniques such as artificial neural networks. Lastly, we suggest that the planned HyspIRI mission is crucial for observing, measuring and modelling environmental variables impacting various diseases as it will improve both spectral resolution and revisit time, thus contributing to better prediction of occurrence of infectious diseases, target intervention and tracking of epidemic events. 相似文献
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Masek J.G. Vermote E.F. Saleous N.E. Wolfe R. Hall F.G. Huemmrich K.F. Feng Gao Kutler J. Teng-Kui Lim 《Geoscience and Remote Sensing Letters, IEEE》2006,3(1):68-72
The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) at the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center has processed and released 2100 Landsat Thematic Mapper and Enhanced Thematic Mapper Plus surface reflectance scenes, providing 30-m resolution wall-to-wall reflectance coverage for North America for epochs centered on 1990 and 2000. This dataset can support decadal assessments of environmental and land-cover change, production of reflectance-based biophysical products, and applications that merge reflectance data from multiple sensors [e.g., the Advanced Spaceborne Thermal Emission and Reflection Radiometer, Multiangle Imaging Spectroradiometer, Moderate Resolution Imaging Spectroradiometer (MODIS)]. The raw imagery was obtained from the orthorectified Landsat GeoCover dataset, purchased by NASA from the Earth Satellite Corporation. Through the LEDAPS project, these data were calibrated, converted to top-of-atmosphere reflectance, and then atmospherically corrected using the MODIS/6S methodology. Initial comparisons with ground-based optical thickness measurements and simultaneously acquired MODIS imagery indicate comparable uncertainty in Landsat surface reflectance compared to the standard MODIS reflectance product (the greater of 0.5% absolute reflectance or 5% of the recorded reflectance value). The rapid automated nature of the processing stream also paves the way for routine high-level products from future Landsat sensors. 相似文献
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Quantification and assessment of nationwide population access to health-care services is a critical undertaking for improving population health and optimizing the performance of national health systems. Rural–urban unbalance of population access to health-care services is widely involved in most of the nations. This unbalance is also potentially affected by varied weather and road conditions. This study investigates the rural and urban performances of public health system by quantifying the spatiotemporal variations of accessibility and assessing the impacts of potential factors. Australian health-care system is used as a case study for the rural–urban comparison of population accessibility. A nationwide travel time-based modified kernel density two-step floating catchment area (MKD2SFCA) model is utilized to compute accessibility of travel time within 30, 60, 120, and 240 min to all public hospitals, hospitals that provide emergency care, and hospitals that provide surgery service, respectively. Results show that accessibility is varied both temporally and spatially, and the rural–urban unbalance is distinct for different types of hospitals. In Australia, from the perspective of spatial distributions of health-care resources, spatial accessibility to all public hospitals in remote and very remote areas is not lower (and may even higher) than that in major cities, but the accessibility to hospitals that provide emergency and surgery services is much higher in major cities than other areas. From the angle of temporal variation of accessibility to public hospitals, reduction of traffic speed is 1.00–3.57% due to precipitation and heavy rain, but it leads to 18–23% and 31–50% of reduction of accessibility in hot-spot and cold-spot regions, respectively, and the impact is severe in New South Wales, Queensland, and Northern Territory during wet seasons. Spatiotemporal analysis for the variations of accessibility can provide quantitative and accurate evidence for geographically local and dynamic strategies of allocation decision-making of medical resources and optimizing health-care systems both locally and nationally. 相似文献
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World Wind是由美国宇航局(NASA)开发的三维地理信息系统,也是一款可提供丰富数据的数字地球平台,如何将多源数据实现紧密型二三维耦合是基于World Wind开发专业系统需要解决的重要问题.在.NET开发环境下,以World Wind为仿真内核,开发了水位仿真系统,研究了二三维数据耦合技术,实现了环鄱阳湖生态经济开发区的湖区与航道淹没分析和三维漫游.结果表明,仿真系统流畅地实现了任意点地形高程、水位、水深和航道级别等信息的实时查询,仿真了不同控制水位条件下的鄱阳湖区淹没范围,仿真结果能够服务于鄱阳湖水利枢纽的水位调控决策;该仿真系统在湖泊干旱特征水位等确定中也具有重要的应用价值. 相似文献
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随着环境问题的日益凸显及公众对环境问题的日益关注,如何将污染分布及发生规律、环境质量状况及变化趋势以科学、准确、直观的方式进行展示并以浅显易懂的方式传递给广大公众,是摆在环境管理者面前的一个问题.本文提出了环境监测信息空间表征定义,并介绍了基于GIS、大数据技术的环境监测信息空间表征的主要形式,包括:①点数据的空间表征;②线数据的空间表征;③面数据的空间表征;④三维可视化空间表征;⑤随时间变化的空间信息表征,以及各空间表征方法在环境监测中的应用. 相似文献
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Karen Schleeweis Samuel N. Goward Chengquan Huang John L. Dwyer Jennifer L. Dungan Mary A. Lindsey 《International Journal of Digital Earth》2016,9(10):963-980
Using the NASA Earth Exchange platform, the North American Forest Dynamics (NAFD) project mapped forest history wall-to-wall, annually for the contiguous US (1986–2010) using the Vegetation Change Tracker algorithm. As with any effort to identify real changes in remotely sensed time-series, data gaps, shifts in seasonality, misregistration, inconsistent radiometry and cloud contamination can be sources of error. We discuss the NAFD image selection and processing stream (NISPS) that was designed to minimize these sources of error. The NISPS image quality assessments highlighted issues with the Landsat archive and metadata including inadequate georegistration, unreliability of the pre-2009 L5 cloud cover assessments algorithm, missing growing-season imagery and paucity of clear views. Assessment maps of Landsat 5–7 image quantities and qualities are presented that offer novel perspectives on the growing-season archive considered for this study. Over 150,000+ Landsat images were considered for the NAFD project. Optimally, one high quality cloud-free image in each year or a total of 12,152 images would be used. However, to accommodate data gaps and cloud/shadow contamination 23,338 images were needed. In 220 specific path-row image years no acceptable images were found resulting in data gaps in the annual national map products. 相似文献
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大数据视角下的地矿工作发展与变革研究 总被引：1，自引：0，他引：1
本文提出了地矿大数据应用需要考虑地球系统和社会系统两个方面的内部规律,分析了地矿大数据的三类组成,给出了地矿大数据的四层应用架构;重点就大数据下地矿工作发展和变革提出了四项建议,包括重视数据,转变地矿工作决策模式;收集数据,夯实地矿工作决策基础;分析数据,提高地矿工作科学决策水平;开放数据,提高地矿工作服务能力和水平。 相似文献
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《制图学和地理信息科学》2013,40(2):77-102
This paper discusses the importance of determining an accurate depiction of total population and specific sub-population distribution for urban areas in order to develop an improved "denominator," which would enable the calculation of more correct rates in GIS analyses involving public health, crime, and urban environmental planning. Rather than using data aggregated by arbitrary administrative boundaries such as census tracts, we use dasymetric mapping, an areal interpolation method using ancillary information to delineate areas of homogeneous values. We review previous dasymetric mapping techniques (which often use remotely sensed land-cover data) and contrast them with our technique, Cadastral-based Expert Dasymetric System (CEDS), which is particularly suitable for urban areas. The CEDS method uses specific cadastral data, land-use filters, modeling by expert system routines, and validation against various census enumeration units and other data. The CEDS dasymetric mapping technique is presented through a case study of asthma hospitalizations in the Bronx, New York City, in relation to proximity buffers constructed around major sources of air pollution. The case study shows the impact that a more accurate estimation of population distribution has on a current environmental justice and health disparities research project, and the potential of CEDS for other GIS applications. 相似文献
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人类对地球的监测和模拟形成了大量的离散时序空间数据,如何有效表达这些数据以便为相关部门提供分析和决策依据,是众多信息系统建设过程中遇到的难题之一.利用网络地理信息系统(WebGIS)平台,综合应用了OpenGL,Ajax和JavaScript等技术,实现了离散时序空间数据的解析、渲染和地理底图的快速一体化动态可视化.该技术方法具有通用性,可以通过网络平台广泛应用于各类离散时序空间数据的监控(如对环境污染扩散实测数据)与预警(对模型数据),为政府科学决策和应急响应提供依据. 相似文献
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Many African countries are facing increasing risks of food insecurity due to rising populations. Accurate and timely information on the spatial distribution of cropland is critical for the effective management of crop production and yield forecast. Most recent cropland products (2015 and 2016) derived from multi-source remote sensing data are available for public use. However, discrepancies exist among these cropland products, and the level of discrepancy is particularly high in several Africa regions. The overall goal of this study was to identify and assess the driving factors contributing to the spatial discrepancies among four cropland products derived from remotely sensed data. A novel approach was proposed to evaluate the spatial agreement of these cropland products and assess the impact of environmental factors such as elevation dispersion, field size, land-cover richness and frequency of cloud cover on these spatial differences. Results from this study show that the overall accuracies of the four cropland products are below 65%. In particular, large disagreements are seen on datasets covering Sahel zone and along the West African coasts. This study has identified land-cover richness as the driving factor with the largest contribution to the spatial disagreement among cropland products over Africa, followed by the high frequency of cloud cover, small and fragmented field size, and elevation complexity. To improve the accuracy of future cropland products for African regions, the data producers are encouraged to take a multi-classification approach and incorporate multi-sensors into their cropland mapping processes. 相似文献
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In this study, we assessed land cover land use (LCLU) changes and their potential environmental drivers (i.e., precipitation, temperature) in five countries in Eastern & Southern (E&S) Africa (Rwanda, Botswana, Tanzania, Malawi and Namibia) between 2000 and 2010. Landsat-derived LCLU products developed by the Regional Centre for Mapping of Resources for Development (RCMRD) through the SERVIR (Spanish for “to serve”) program, a joint initiative of NASA and USAID, and NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) data were used to evaluate and quantify the LCLU changes in these five countries. Given that the original development of the MODIS land cover type standard products included limited training sites in Africa, we performed a two-level verification/validation of the MODIS land cover product in these five countries. Precipitation data from CHIRPS dataset were used to evaluate and quantify the precipitation changes in these countries and see if it was a significant driver behind some of these LCLU changes. MODIS Land Surface Temperature (LST) data were also used to see if temperature was a main driver too.Our validation analysis revealed that the overall accuracies of the regional MODIS LCLU product for this African region alone were lower than that of the global MODIS LCLU product overall accuracy (63–66% vs. 75%). However, for countries with uniform or homogenous land cover, the overall accuracy was much higher than the global accuracy and as high as 87% and 78% for Botswana and Namibia, respectively. In addition, the wetland and grassland classes had the highest user’s accuracies in most of the countries (89%–99%), which are the ones with the highest number of MODIS land cover classification algorithm training sites.Our LCLU change analysis revealed that Botswana’s most significant changes were the net reforestation, net grass loss and net wetland expansion. For Rwanda, although there have been significant forest, grass and crop expansions in some areas, there also have been significant forest, grass and crop loss in other areas that resulted in very minimal net changes. As for Tanzania, its most significant changes were the net deforestation and net crop expansion. Malawi’s most significant changes were the net deforestation, net crop expansion, net grass expansion and net wetland loss. Finally, Namibia’s most significant changes were the net deforestation and net grass expansion.The only noticeable environmental driver was in Malawi, which had a significant net wetland loss and could be due to the fact that it was the only country that had a reduction in total precipitation between the periods when the LCLU maps were developed. Not only that, but Malawi also happened to have a slight increase in temperature, which would cause more evaporation and net decrease in wetlands if the precipitation didn’t increase as was the case in that country. In addition, within our studied countries, forestland expansion and loss as well as crop expansion and loss were happening in the same country almost equally in some cases. All of that implies that non-environmental factors, such as socioeconomics and governmental policies, could have been the main drivers of these LCLU changes in many of these countries in E&S Africa. It will be important to further study in the future the detailed effects of such drivers on these LCLU changes in this part of the world. 相似文献
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基础测绘是指建立全国统一的测绘基准和测绘系统,进行基础航空摄影,获取基础地理信息的遥感资料,测制和更新国家基本比例尺地图、影像图和数字化产品,建立、更新基础地理信息系统,是关系社会发展和国民经济的一项基础工作。基础测绘工作是提高城市管理效率、履行测绘地理信息管理职能和管理水平、增强决策水平和能力的重要手段。国民经济、国防建设和社会发展急需的基础测绘成果应当及时更新。本文从腾冲市的基础测绘工作实际情况出发,介绍了腾冲市基础测绘工作现状,对当前基础测绘工作存在的问题进行分析,并针对存在的问题提出相应的对策。 相似文献
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Population has significant application value and scientific significance in resource use, public health, public transportation, disaster assessment, and environmental management. However, traditional census data can not show the population density difference within census units. Furthermore, census data are not uniform across countries, and reconciling these differences when using data from multiple countries require considerable effort. Finally, there are scale differences between census and geospatial data (e.g., land use/cover), making data analysis and needed research difficult. These challenges significantly limit the applications of census data. The advent of gridded population mapping (GPM) technology has overcome these challenges. GPM technology has developed rapidly in recent years. The research data and models are rich and diverse, and many achievements have been made. A systematic review of the current state of GPM research will help relevant researchers and data users. This article begins by summarizing the core elements of GPM research in four aspects: auxiliary data, models, accuracy, and products. It will then go on to four problems prevalent in GPM research that have direct or indirect effects on the accuracy of GPM. Finally, the article prospects GPM research from four different aspects based on the current state of research. 相似文献
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《The Cartographic journal》2013,50(4):261-273
AbstractParallel coordinates, re-orderable matrices, and dendrograms, widely used methods for visual exploration of multivariate data, are systematically integrated in a complementary manner for supporting multi-resolution visual data analysis with an enhanced overview + detail exploratory strategy. There are three main topics: (1) dynamic control across resolutions at which data are explored; (2) coordination and color mapping among the views; and (3) enhanced features of each view designed for the overview + detail exploratory tasks. A case study analysis is used to demonstrate the potential for boosting productivity for exploration tasks by coordinating the views through user-controlled resolutions within a highly interactive analysis environment. The case study is focused on a complex, geographically referenced dataset including public health, demographic and environmental components. 相似文献