Monitoring and Prediction of the Earth’s Climate: a future Perspective
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Erkki Tomppo, Hakan Olsson, Goran Stahl, Mats Nilsson, Olle Hagner, Matti Katila, Combining national forest inventory field plots and remote sensing data for forest databases, Remote Sensing of Environment, Volume 112, Issue 5, Earth Observations for Terrestrial Biodiversity and Ecosystems Special Issue, 15 May 2008, Pages 1982-1999, ISSN 0034-4257, DOI: 10.1016/j.rse.2007.03.032. (http://www.sciencedirect.com/science/article/B6V6V-4S02DB8-2/2/5181c1ac4afee9775e093c5967d5a001) Abstract: Information about forest cover is needed by all of the nine societal benefit areas identified by the Group of Earth Observation (GEO). In particular, the biodiversity and ecosystem areas need information on landscape composition, structure of forests, species richness, as well as their changes. Field sample plots from National Forest Inventories (NFI) are, in combination with satellite data, a tremendous resource for fulfilling these information needs. NFIs have a history of almost 100 years and have developed in parallel in several countries. For example, the NFIs in Finland and Sweden measure annually more than 10,000 field plots with approximately 200 variables per plot. The inventories are designed for five-year rotations. In Finland nationwide forest cover maps have been produced operationally since 1990 by using the k-NN algorithm to combine satellite data, field sample plot information, and other georeferenced digital data. A similar k-NN database has also been created for Sweden. The potentials of NFIs to fulfil diverse information needs are currently analyzed also in the COST Action E43 project of the European Union. In this article, we provide a review of how NFI field plot information has been used for parameterization of image data in Sweden and Finland, including pre-processing steps like haze correction, slope correction, and the optimization of the estimation variables. Furthermore, we review how the produced small-area statistics and forest cover data have been used in forestry, including forest biodiversity monitoring and habitat modelling. We also show how remote sensing data can be used for post-stratification to derive the sample plot based estimates, which cannot be directly estimated from the spectral data. Keywords: National forest inventory; k-NN estimation; Post-stratification; Biodiversity monitoring; Habitat modelling; Satellite images
(http://www.sciencedirect.com/science/article/B6V3S-4XKBYVH-7/2/d6b49eb53bb6b7d713361599609cde26) Abstract: A more flexible policy basis from which to manage our planet in the 21st century is desirable. As one contribution, we note that synergies between space exploration and the preservation of our habitat exist, and that protecting life on Earth requires similar concepts and information as investigations of life beyond the Earth, including the expansion of human presence in space. Instrumentation and data handling to observe both planetary objects and planet Earth are based on similar techniques. Moreover, while planetary surface operations are conducted under different conditions, the technology to probe the surface and subsurface of both the Earth and other planets requires similar tools, such as radar, seismometers, and drilling devices. The Earth observation community has developed some exemplary tools and has featured successful international cooperation in data handling and sharing that could be equally well applied to robotic planetary exploration. Here we propose a network involving both communities that will enable the interchange of scientific insights and the development of new policies and management strategies. Those tools can provide a vital forum through which the management of this planet can be assisted, and in which a new bridge between the Earth-centric and space-centric communities can be built. Keywords: Earth observation; Space exploration; Astrobiology; Space weather; Biodiversity; International space cooperation
(http://www.sciencedirect.com/science/article/B6X1D-4M69JPV-1/2/67a3e8e39caa30de0c42e07334548dd6) Abstract: 'Achieving comprehensive, coordinated, and sustained Earth observations for the benefit of humankind.' The need to collect, organize, standardize Earth observation data for the benefit of a planetary community of users has been recognized since more than a century: in the recent period, after World War Two, the `World Meteorological Convention' adopted a strategy in Washington in 1947, which led to the creation of WMO in 1951 (World Meteorological Organization). An important step took place, next, when ICSU (International Council of Scientific Unions now named International Council for Science), upon a suggestion of Lloyd Berkner, initiated in 1952 the organization of the International Geophysical Year (1957-1958) with a special focus on Earth observation from space. Indeed, the launching of Earth observation satellites was put forward as one of the major objectives of IGY (International Geophysical Year). This goal was reached beautifully with the successful launches of Sputnik on 4 October 1957 by the USSR and of Explorer I on 31 January 1958 by the USA. Sputnik, purposely spherically shaped, brought the first high-altitude atmospheric data through the observation of the drag exerted by the atmosphere on the spacecraft. Explorer I, equipped with a Geiger counter, led to the discovery of the `Van Allen belts' surrounding the Earth. The development, at a tremendous pace, of experimental satellites observing the Earth, the planets, and the Universe followed then immediately. As early as 1960, the concept of meteorology satellites emerged with the launch of the first weather satellite in polar orbit, TIROS. It took then almost 20 years before reaching the stage of implementing operational meteorological satellites in polar sun-synchronous or in geostationary orbits: at that time, meteorologists had learned how to incorporate meteorological space data into weather-forecast systems. The aim of this paper is to describe schematically the gradual implementation of an Earth observation system of systems associating in situ and space observations as well as numerical modelling in order to provide humankind with the necessary tools for Earth science, sustainable development, and security. To cite this article: P. Bauer et al., C. R. Geoscience 338 (2006). Keywords: Global Earth observation; International endeavour; Europe; Earth planet; Meteorology; Ozone; Ocean; Land; Climate; Environment; Monitoring; Observation globale de la Terre; Demarche internationale; Europe; Planete Terre; Meteorologie; Ozone; Ocean; Terres emergees; Climat; Environnement; Surveillance
(http://www.sciencedirect.com/science/article/B6V6V-4RPKYPN-1/2/194da0d45f42c8f615c24b242b4f992d) Abstract: Many investigators need and use global land cover maps for a wide variety of purposes. Ironically, after many years of very limited availability, there are now multiple global land cover maps and it is not readily apparent (1) which is most useful for particular applications or (2) how to combine the different maps to provide an improved dataset. The existing global land cover maps at 1 km spatial resolution have arisen from different initiatives and are based on different remote sensing data and employed different methodologies. Perhaps more significantly, they have different legends. As a result, comparison of the different land cover maps is difficult and information about their relative utility is limited. In an attempt to compare the datasets and assess their strengths and weaknesses we harmonized the thematic legends of four available coarse-resolution global land cover maps (IGBP DISCover, UMD, MODIS 1-km, and GLC2000) using the LCCS-based land cover legend translation protocols. Analysis of the agreement among the global land cover maps and existing validation information highlights general patterns of agreement, inconsistencies and uncertainties. The thematic classes of Evergreen broadleaf trees, Snow and Ice, and Barren show high producer and user accuracy and good agreement among the datasets, while classes of mixed tree types show high commission errors. Overall, the results show a limited ability of the four global products to discriminate mixed classes characterized by a mosaic of trees, shrubs, and herbaceous vegetation. There is a strong relationship between class accuracy, spatial agreement among the datasets, and the heterogeneity of landscapes. Suggestions for future mapping projects include careful definition of mixed unit classes, and improvement in mapping heterogeneous landscapes. Keywords: Global land cover; Validation; Harmonization; LCCS
(http://www.sciencedirect.com/science/article/B6V6V-4JHMY4D-1/2/7b1af5b1d371ec0bbc0077d907cd48ef) Abstract: Within the past decade, several global land cover data sets derived from satellite observations have become available to the scientific community. They offer valuable information on the current state of the Earth's land surface. However, considerable disagreements among them and classification legends not primarily suited for specific applications such as carbon cycle model parameterizations pose significant challenges and uncertainties in the use of such data sets. This paper addresses the user community of global land cover products. We first review and compare several global land cover products, i.e. the Global Land Cover Characterization Database (GLCC), Global Land Cover 2000 (GLC2000), and the MODIS land cover product, and highlight individual strengths and weaknesses of mapping approaches. Our overall objective is to present a straightforward method that merges existing products into a desired classification legend. This process follows the idea of convergence of evidence and generates a `best-estimate' data set using fuzzy agreement. We apply our method to develop a new joint 1-km global land cover product (SYNMAP) with improved characteristics for land cover parameterization of the carbon cycle models that reduces land cover uncertainties in carbon budget calculations. The overall advantage of the SYNMAP legend is that all classes are properly defined in terms of plant functional type mixtures, which can be remotely sensed and include the definitions of leaf type and longevity for each class with a tree component. SYNMAP is currently used for parameterization in a European model intercomparison initiative of three global vegetation models: BIOME-BGC, LPJ, and ORCHIDEE. Corroboration of SYNMAP against GLCC, GLC2000 and MODIS land cover products reveals improved agreement of SYNMAP with all other land cover products and therefore indicates the successful exploration of synergies between the different products. However, given that we cannot provide extensive validation using reference data we are unable to prove that SYNMAP is actually more accurate. SYNMAP is available on request from Martin Jung. Keywords: Land cover; Carbon cycle; Fuzzy logic; Remote sensing; Global Uwe Schindler, Michael Diepenbroek, Generic XML-based framework for metadata portals, Computers & Geosciences, Volume 34, Issue 12, December 2008, Pages 1947-1955, ISSN 0098-3004, DOI: 10.1016/j.cageo.2008.02.023. (http://www.sciencedirect.com/science/article/B6V7D-4SF3052-1/2/f89e379a9b89daa85242f2f2c1068dcc) Abstract: We present a generic and flexible framework for building geoscientific metadata portals independent of content standards for metadata and protocols. Data can be harvested with commonly used protocols (e.g., Open Archives Initiative Protocol for Metadata Harvesting) and metadata standards like DIF or ISO 19115. The new Java-based portal software supports any XML encoding and makes metadata searchable through Apache Lucene. Software administrators are free to define searchable fields independent of their type using XPath. In addition, by extending the full-text search engine (FTS) Apache Lucene, we have significantly improved queries for numerical and date/time ranges by supplying a new trie-based algorithm, thus, enabling high-performance space/time retrievals in FTS-based geo portals. The harvested metadata are stored in separate indexes, which makes it possible to combine these into different portals. The portal-specific Java API and web service interface is highly flexible and supports custom front-ends for users, provides automatic query completion (AJAX), and dynamic visualization with conventional mapping tools. The software has been made freely available through the open source concept. Keywords: Spatial data infrastructure; Metadata portal; Metadata standard; Open archives; Full-text search; Apache Lucene
(http://www.sciencedirect.com/science/article/B6WJ7-4TG8P52-3/2/1a1d8504acc84476b95786e1fe689f11) Abstract: Global Earth Observation (GEO) is one of the most important sources of information for environmental resource management and disaster prevention. With budgets for GEO increasingly under pressure, it is becoming important to be able to quantify the returns to informational investments. For this, a clear analytical framework is lacking. By combining Bayesian decision theory with an empirical, stakeholder-oriented approach, this paper attempts to develop such a framework. The analysis focuses on the use of satellite observations for Dutch water quality management in the North Sea. Dutch water quality management currently relies on information from `in situ' measurements but is considering extending and deepening its information base with satellite observations. To estimate returns to additional investments in satellite observation, we analyze the added value of an extended monitoring system for the management of eutrophication, potentially harmful algal blooms and suspended sediment and turbidity in the North Sea. First, we develop a model to make the potential contribution of information to welfare explicit. Second, we use this model to develop a questionnaire and interpret the results. The results indicate that the expected welfare impact of investing in satellite observation is positive, but that outcomes strongly depend on the accuracy of the information system and the range of informational benefits perceived. Keywords: Value of information; Bayesian decision theory; Marine water quality; Water resource management; Stakeholder consultation; Satellite observation
(http://www.sciencedirect.com/science/article/B6V3S-4R68NKN-2/2/167e50cd3a236c4b0e3d4f0778d02229) Abstract: Early warning systems represent an innovative and effective approach to mitigate the risk associated with natural hazards. Early warning technologies are now available for almost all natural hazards and systems are already in operation in all parts of the world. Nevertheless, recent disasters such as the Indian Ocean tsunami in 2004 and Katrina hurricane in 2005, highlighted inadequacies in early warning technologies. Efforts towards the development of a global warning system are necessary for turning the tide in early warning processes and technologies. There is a pressing need for a globally comprehensive early warning system based on existing systems. The global system should be a mechanism which can consolidate scientific information and evidences, package this knowledge in a form usable to international and national decision makers and actively disseminate this information to those users. The proposed Global Environmental Alert Service (GEAS) will provide information emanating from monitoring, Earth observing and early warning systems to users in a near-real-time mode and bridge the gap between the scientific community and policy makers. Characteristics and operational aspects of such a service, GEAS, are discussed. Keywords: Global alert service; Environmental decision making; Natural disasters; Global earth observation; Early warning
(http://www.sciencedirect.com/science/article/B6X1D-4Y41V17-2/2/5dab4f40e0c3aa71dd49d75504fe31aa) Abstract: The Earth is surrounded by a layer of relatively thin gas, the mass of which is mainly concentrated in the first kilometres. With an exponential decrease of the density of the atmosphere as a function of altitude, 99.9% of this mass is located in the first 50 km. In addition, the composition of major species is homogeneous up to about 85 km, contrarily to what happens beyond. This is the homosphere. This layer of atmosphere, considered in this special issue, is also that which we breathe and which we unfortunately often pollute. All this justifies considering it as of vital importance, in the most basic sense of the word. However, in studying it, it is not possible to ignore what is happening beyond, from where comes, in particular, solar radiation, just as we cannot ignore what happens below the continents and the oceans, where solar radiation is absorbed, diffused and re-emitted to the top by the Earth's surface as infrared radiation. We must therefore keep in mind what are the layers that surround the homosphere, the importance of observing them and also give some examples of possible interactions which may exist with the surrounding layers; these are the objectives of these introductory remarks. Another general consideration must be made here, concerning the problems, which have existed until the middle of the 20th century, of how to observe the atmosphere in situ at all the altitudes. However, since then, the development of engineering involving balloons, rockets, aircrafts and artificial satellites has revolutionized our knowledge of this observational atmosphere; this is the second message of these remarks. Keywords: Upper atmosphere; Homosphere; Heterosphere; Magnetosphere; Liquid and solid Earth's surfaces; Haute atmosphere; Homosphere; Heterosphere; Magnetosphere; Surfaces liquides et solides de la Terre
(http://www.sciencedirect.com/science/article/B6V6V-4VY6FT1-3/2/1f865bcbd461c84d4957c56270cc4192) Abstract: We present an approach for monitoring and forecasting landscape level indicators of the condition of protected area (PA) ecosystems including changes in snowcover, vegetation phenology and productivity using the Terrestrial Observation and Prediction System (TOPS). TOPS is a modeling framework that integrates operational satellite data, microclimate mapping, and ecosystem simulation models to characterize ecosystem status and trends. We have applied TOPS to investigate trends and patterns in landscape indicators using test cases at both national and park-level scales to demonstrate the potential utility of TOPS for supporting efforts by the National Park Service to develop standardized indicators for protected area monitoring. Our analysis of coarse resolution satellite-derived normalized difference vegetation index (NDVI) measurements for North America from 1982-2006 indicates that all but a few PAs are located in areas that exhibited a sustained decline in vegetation condition. We used Yosemite National Park as our park-level test case, and while no significant trends in NDVI were detected during the same period, evidence of drought-induced vegetation mortality and recovery patterns dominated the 25-year record. In our Yosemite analysis, we show that analyzing MODIS (Moderate Resolution Imaging Spectro-radiometer) products (vegetation indices, absorbed radiation, land surface temperature and gross primary production) in conjunction with ground-based measurements, such as runoff, lends additional utility to satellite-based monitoring of ecosystems indicators, as together they provide a comprehensive view of ecosystem condition. Analyses of MODIS products from 2001-2006 show that year-to-year changes in the onset of spring at Yosemite were as large as 45 days, and this signal in the satellite data record is corroborated by observed changes in spring runoff patterns. Finally, we applied TOPS to assess long-term climate impacts on ecosystem condition at the scale of an individual park. When driven by projected climatic changes at Yosemite of 4-6 [degree sign]C warming by 2100 with no changes in precipitation patterns, TOPS predicts significantly reduced winter snowpack and an earlier onset of the growing season, resulting in prolonged summer drought and reduced vegetation productivity. Keywords: Terrestrial Observation and Prediction System (TOPS); Protected areas monitoring; Ecological forecasting; Ecosystem modeling; Yosemite National Park; MODIS
(http://www.sciencedirect.com/science/article/B6V52-4M4CN95-1/2/0df6fc32512b1ece7f9dbf2925109c64) Abstract: Governments around the world, as well as private industry, invest heavily in remote sensing spacecraft to obtain data about natural and environmental resources, climate change, and the relationship of earth science to human health and quality of life. Numerous studies have been undertaken to describe and measure the value of the data from these spacecraft in order to justify further investments. The studies use a wide variety of methods and generally find a large range of benefits, from quite small to very large, in part because of differences in methodologies. This article offers a general framework for measuring the value of information. The framework serves two purposes. One is provision of a comprehensive and common basis by which to conduct and evaluate studies of the value of earth science. The second is to better inform decision makers about the value of data. Decision makers comprise three communities: consumers and producers of information, public officials whose job is to invest in data acquisition and information development (including sensors and other hardware, algorithm design and software tools, and a trained labor force), and the public at large. Yüklə 411,35 Kb. Dostları ilə paylaş:
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