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9 papers found.
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A spatial assessment of the forest carbon budget for Ukraine

The spatial representation of forest cover and forest parameters is a prerequisite for undertaking a systems approach to the full and verified carbon accounting of forest ecosystems over large areas. This study focuses on Ukraine, which contains a diversity of bioclimatic conditions and natural landscapes found across Europe. Ukraine has a high potential to sequester carbon...

Developing an Individual-level Geodemographic Classification

Geodemographics is a spatially explicit classification of socio-economic data, which can be used to describe and analyse individuals by where they live. Geodemographic information is used by the public sector for planning and resource allocation but it also has considerable use within commercial sector applications. Early geodemographic systems, such as the UK’s ACORN (A...

Development of a high-resolution spatial inventory of greenhouse gas emissions for Poland from stationary and mobile sources

Greenhouse gas (GHG) inventories at national or provincial levels include the total emissions as well as the emissions for many categories of human activity, but there is a need for spatially explicit GHG emission inventories. Hence, the aim of this research was to outline a methodology for producing a high-resolution spatially explicit emission inventory, demonstrated for Poland...

Economic Development and Forest Cover: Evidence from Satellite Data

, AustriaJesús Crespo Cuaresma, Olha Danylo, Steffen Fritz, Ian McCallum, Michael Obersteiner, Linda See & Brian WalshAustrian Institute of Economic Research, Arsenal 20, 1030 Vienna, AustriaJesús Crespo Cuaresma ... Linda See in:Nature Research journals • PubMed • Google ScholarSearch for Brian Walsh in:Nature Research journals • PubMed • Google Scholar Contributions J.C.C. led the analysis as first and corresponding

Food Security Monitoring via Mobile Data Collection and Remote Sensing: Results from the Central African Republic

The Central African Republic is one of the world’s most vulnerable countries, suffering from chronic poverty, violent conflicts and weak disaster resilience. In collaboration with Doctors without Borders/Médecins Sans Frontières (MSF), this study presents a novel approach to collect information about socio-economic vulnerabilities related to malnutrition, access to resources and...

Citizen Science and Open Data: a model for Invasive Alien Species in Europe

Invasive Alien Species (IAS) are a growing threat to Europe's biodiversity. The implementation of European Union Regulation on IAS can benefit from the involvement of the public in IAS recording and management through Citizen Science (CS) initiatives. Aiming to tackle issues related with the use of CS projects on IAS topics, a dedicated workshop titled “Citizen Science and Open...

Technologies to Support Community Flood Disaster Risk Reduction

Floods affect more people globally than any other type of natural hazard. Great potential exists for new technologies to support flood disaster risk reduction. In addition to existing expert-based data collection and analysis, direct input from communities and citizens across the globe may also be used to monitor, validate, and reduce flood risk. New technologies have already...

Affordable Nutrient Solutions for Improved Food Security as Evidenced by Crop Trials

The continuing depletion of nutrients from agricultural soils in Sub-Saharan African is accompanied by a lack of substantial progress in crop yield improvement. In this paper we investigate yield gaps for corn under two scenarios: a micro-dosing scenario with marginal increases in nitrogen (N) and phosphorus (P) of 10 kg ha−1 and a larger yet still conservative scenario with...

Comparing the Quality of Crowdsourced Data Contributed by Expert and Non-Experts

There is currently a lack of in-situ environmental data for the calibration and validation of remotely sensed products and for the development and verification of models. Crowdsourcing is increasingly being seen as one potentially powerful way of increasing the supply of in-situ data but there are a number of concerns over the subsequent use of the data, in particular over data...