28 research outputs found

    CITIZEN SCIENCE FOR EARTH OBSERVATION: APPLICATIONS IN ENVIRONMENTAL MONITORING AND DISASTER RESPONSE

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    Citizen science is a promising way to increase temporal and spatial coverages of in-situ data, and to aid in data processing and analysis. In this paper, we present how citizen science can be used together with Earth observation, and demonstrate its value through three pilot projects focusing on forest biomass analysis, data management in emergencies and water quality monitoring. We also provide recommendations and ideas for follow-up activities. In the forest biomass analysis pilot, in the state of Durango (Mexico), local volunteers make in-situ forest inventory measurements with mobile devices. The collected data is combined with Landsat-8 imagery to derive forest biomass map of the area. The study area includes over 390 permanent sampling plots that will provide reference data for concept validation and verification. The emergency data management pilot focuses in the Philippines, in the areas affected by the typhoons Haiyan in November 2013 and Hagupit in December 2014. Data collected by emergency workers and citizens are combined with satellite data (Landsat-8, VHR if available) to intensify the disaster recovery activities and the coordination efforts. Simple processes for citizens, nongovernmental organisations and volunteers are developed to find and utilize up to date and freely available satellite imagery for coordination purposes and for building new not-for-profit services in disaster situations. In the water quality monitoring pilot, citizens around the Baltic Sea area contribute to the algae situation awareness by collecting algae observations using a mobile application. In-situ observations are compared with surface algal bloom products based on the satellite imagery, e.g. Aqua MODIS images with 500 meter resolution. As an outcome, the usability of the citizen observations together with satellite data in the algae monitoring will be evaluated

    Kioto+ mission : Global and accurate monitoring of forest, land cover and carbon

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    This publication presents the results of a feasibility study on a proposed superhigh resolution satellite mission Kioto+. The study was conducted by an international consortium in response to the 2005 call for ideas for Earth Explorer missions of the European Space Agency (ESA). Kioto+ offers reliable and global data to near in-situ measurement accuracy on land cover and forest cover. It also gives information about their development over time. A super-high resolution optical instrument is proposed to achieve statistically representative and precise measurements. The information will greatly improve our understanding of the global carbon and water cycles, and the credibility of estimates of terrestrial carbon storage. The imagery will also give globally accurate training and validation data for wall-to-wall imaging instruments. The mission is named Kioto+ because the projected timescale of the mission (post-2011) means that it will primarily have relevance to successor treaties of the Kyoto Protocol to the FCCC of the United Nations

    Source characterization of highly oxidized multifunctional compounds in a boreal forest environment using positive matrix factorization

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    Highly oxidized multifunctional compounds (HOMs) have been demonstrated to be important for atmospheric secondary organic aerosols (SOA) and new-particle formation (NPF), yet it remains unclear which the main atmospheric HOM formation pathways are. In this study, a nitrate-ion-based chemical ionization atmospheric-pressure-interface time-of-flight mass spectrometer (CI-APi-TOF) was deployed to measure HOMs in the boreal forest in Hyytiala, southern Finland. Positive matrix factorization (PMF) was applied to separate the detected HOM species into several factors, relating these "factors" to plausible formation pathways. PMF was performed with a revised error estimation derived from laboratory data, which agrees well with an estimate based on ambient data. Three factors explained the majority (> 95 %) of the data variation, but the optimal solution found six factors, including two night-time factors, three daytime factors, and a transport factor. One nighttime factor is almost identical to laboratory spectra generated from monoterpene ozonolysis, while the second likely represents monoterpene oxidation initiated by NO3. The exact chemical processes forming the different daytime factors remain unclear, but they all have clearly distinct diurnal profiles, very likely related to monoterpene oxidation with a strong influence from NO, presumably through its effect on peroxy radical (RO2 / chemistry. Apart from these five "local" factors, the sixth factor is interpreted as a transport related factor. These findings improve our understanding of HOM production by confirming current knowledge and inspiring future research directions and provide new perspectives on using factorization methods to understand short-lived atmospheric species.Peer reviewe

    A Range of Earth Observation Techniques for Assessing Plant Diversity

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    AbstractVegetation diversity and health is multidimensional and only partially understood due to its complexity. So far there is no single monitoring approach that can sufficiently assess and predict vegetation health and resilience. To gain a better understanding of the different remote sensing (RS) approaches that are available, this chapter reviews the range of Earth observation (EO) platforms, sensors, and techniques for assessing vegetation diversity. Platforms include close-range EO platforms, spectral laboratories, plant phenomics facilities, ecotrons, wireless sensor networks (WSNs), towers, air- and spaceborne EO platforms, and unmanned aerial systems (UAS). Sensors include spectrometers, optical imaging systems, Light Detection and Ranging (LiDAR), and radar. Applications and approaches to vegetation diversity modeling and mapping with air- and spaceborne EO data are also presented. The chapter concludes with recommendations for the future direction of monitoring vegetation diversity using RS

    Citizen science for earth observation:applications in environmental monitoring and disaster response

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    Citizen science is a promising way to increase temporal and spatial coverages of in-situ data, and to aid in data processing and analysis. In this paper, we present how citizen science can be used together with Earth observation, and demonstrate its value through three pilot projects focusing on forest biomass analysis, data management in emergencies and water quality monitoring. We also provide recommendations and ideas for follow-up activities. <br><br> In the forest biomass analysis pilot, in the state of Durango (Mexico), local volunteers make in-situ forest inventory measurements with mobile devices. The collected data is combined with Landsat-8 imagery to derive forest biomass map of the area. The study area includes over 390 permanent sampling plots that will provide reference data for concept validation and verification. <br><br> The emergency data management pilot focuses in the Philippines, in the areas affected by the typhoons Haiyan in November 2013 and Hagupit in December 2014. Data collected by emergency workers and citizens are combined with satellite data (Landsat-8, VHR if available) to intensify the disaster recovery activities and the coordination efforts. Simple processes for citizens, nongovernmental organisations and volunteers are developed to find and utilize up to date and freely available satellite imagery for coordination purposes and for building new not-for-profit services in disaster situations. <br><br> In the water quality monitoring pilot, citizens around the Baltic Sea area contribute to the algae situation awareness by collecting algae observations using a mobile application. In-situ observations are compared with surface algal bloom products based on the satellite imagery, e.g. Aqua MODIS images with 500 meter resolution. As an outcome, the usability of the citizen observations together with satellite data in the algae monitoring will be evaluated

    Selective logging of tropical forests observed using L- and C-band SAR satellite data

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    Monilähteinen kuvatulkinta, päätulokset

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