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22
Article Capability of C-Band SAR for Operational Wetland Monitoring at High Latitudes
, 2012
"... Abstract: Wetlands store large amounts of carbon, and depending on their status and type, they release specific amounts of methane gas to the atmosphere. The connection between wetland type and methane emission has been investigated in various studies and utilized in climate change monitoring and mo ..."
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Abstract: Wetlands store large amounts of carbon, and depending on their status and type, they release specific amounts of methane gas to the atmosphere. The connection between wetland type and methane emission has been investigated in various studies and utilized in climate change monitoring and modelling. For improved estimation of methane emissions, land surface models require information such as the wetland fraction and its dynamics over large areas. Existing datasets of wetland dynamics present the total amount of wetland (fraction) for each model grid cell, but do not discriminate the different wetland types like permanent lakes, periodically inundated areas or peatlands. Wetland types differently influence methane fluxes and thus their contribution to the total wetland fraction should be quantified. Especially wetlands of permafrost regions are expected to have a strong impact on future climate due to soil thawing. In this study ENIVSAT ASAR Wide Swath data was tested for operational monitoring of the distribution of areas with a long-term SW near 1 (hSW) in northern Russia (SW = degree of saturation with water, 1 = saturated), which is a specific characteristic of peatlands. For the whole northern Russia, areas with hSW were delineated and discriminated from dynamic and open water bodies for the years 2007
SoilGrids1 km—global soil information based on automated mapping
- PLoS ONE
"... Background: Soils are widely recognized as a non-renewable natural resource and as biophysical carbon sinks. As such, there is a growing requirement for global soil information. Although several global soil information systems already exist, these tend to suffer from inconsistencies and limited spat ..."
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Background: Soils are widely recognized as a non-renewable natural resource and as biophysical carbon sinks. As such, there is a growing requirement for global soil information. Although several global soil information systems already exist, these tend to suffer from inconsistencies and limited spatial detail. Methodology/Principal Findings: We present SoilGrids1km — a global 3D soil information system at 1 km resolution — containing spatial predictions for a selection of soil properties (at six standard depths): soil organic carbon (g kg21), soil pH, sand, silt and clay fractions (%), bulk density (kg m23), cation-exchange capacity (cmol+/kg), coarse fragments (%), soil organic carbon stock (t ha21), depth to bedrock (cm), World Reference Base soil groups, and USDA Soil Taxonomy suborders. Our predictions are based on global spatial prediction models which we fitted, per soil variable, using a compilation of major international soil profile databases (ca. 110,000 soil profiles), and a selection of ca. 75 global environmental covariates representing soil forming factors. Results of regression modeling indicate that the most useful covariates for modeling soils at the global scale are climatic and biomass indices (based on MODIS images), lithology, and taxonomic mapping units derived from conventional soil survey (Harmonized World Soil Database). Prediction accuracies assessed using 5–fold cross-validation were between 23–51%. Conclusions/Significance: SoilGrids1km provide an initial set of examples of soil spatial data for input into global models at
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 ..."
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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 quality. This paper examined crowdsourced data from the Geo-Wiki crowdsourcing tool for land cover validation to determine whether there were significant differences in quality between the answers provided by experts and non-experts in the domain of remote sensing and therefore the extent to which crowdsourced data describing human impact and land cover can be used in further scientific research. The results showed that there was little difference between experts and non-experts in identifying human impact although results varied by land cover while experts were better than non-experts in identifying the land cover type. This suggests the need to create training materials with more examples in those areas where difficulties in identification were encountered, and to offer some method for contributors to reflect on the information they contribute, perhaps by feeding back the evaluations of their contributed data or by making additional training materials available. Accuracies were also found to be higher when the volunteers were more consistent in their responses at a given location and when they indicated higher confidence, which suggests that these additional pieces of
A campaign to collect volunteered geographic Information on land cover and human
, 2012
"... Abstract This paper outlines experiences with a recent campaign to collect volunteered geographic information (VGI) on land cover and human impact using the Geo-Wiki crowdsourcing tool (humanimpact.geo-wiki.org). A targeted campaign approach was adopted with the aim of gathering data for the valida ..."
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Abstract This paper outlines experiences with a recent campaign to collect volunteered geographic information (VGI) on land cover and human impact using the Geo-Wiki crowdsourcing tool (humanimpact.geo-wiki.org). A targeted campaign approach was adopted with the aim of gathering data for the validation of a map of land availability for biofuels. At the same time, experimentation was undertaken to assess the quality of information from the crowd. Some initial results of the campaign are presented along with lessons learned and future developments.
Mapping the global distribution of livestock
- PLoS ONE
"... Livestock contributes directly to the livelihoods and food security of almost a billion people and affects the diet and health of many more. With estimated standing populations of 1.43 billion cattle, 1.87 billion sheep and goats, 0.98 billion pigs, and 19.60 billion chickens, reliable and accessibl ..."
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Livestock contributes directly to the livelihoods and food security of almost a billion people and affects the diet and health of many more. With estimated standing populations of 1.43 billion cattle, 1.87 billion sheep and goats, 0.98 billion pigs, and 19.60 billion chickens, reliable and accessible information on the distribution and abundance of livestock is needed for a many reasons. These include analyses of the social and economic aspects of the livestock sector; the environmental impacts of livestock such as the production and management of waste, greenhouse gas emissions and livestock-related land-use change; and large-scale public health and epidemiological investigations. The Gridded Livestock of the World (GLW) database, produced in 2007, provided modelled livestock densities of the world, adjusted to match official (FAOSTAT) national estimates for the reference year 2005, at a spatial resolution of 3 minutes of arc (about 565 km at the equator). Recent methodological improvements have significantly enhanced these distributions: more up-to date and detailed sub-national livestock statistics have been collected; a new, higher resolution set of predictor variables is used; and the analytical
Affordable nutrient solutions for improved food security as evidenced by crop trials. PLoS One 2013
"... 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 p ..."
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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 ha21 and a larger yet still conservative scenario with proposed N and P applications of 80 and 20 kg ha21 respectively. The yield gaps are calculated from a database of historical FAO crop fertilizer trials at 1358 locations for Sub-Saharan Africa and South America. Our approach allows connecting experimental field scale data with continental policy recommendations. Two critical findings emerged from the analysis. The first is the degree to which P limits increases in corn yields. For example, under a micro-dosing scenario, in Africa, the addition of small amounts of N alone resulted in mean yield increases of 8 % while the addition of only P increased mean yields by 26%, with implications for designing better balanced fertilizer distribution schemes. The second finding was the relatively large amount of yield increase possible for a small, yet affordable amount of fertilizer application. Using African and South American fertilizer prices we show that the level of investment needed to achieve these results is considerably less than 1 % of Agricultural GDP for both a micro-dosing scenario and for the scenario involving higher yet still conservative fertilizer application rates. In the latter scenario realistic mean yield increases ranged between 28 to 85 % in South America and 71 to 190 % in Africa (mean plus one standard deviation). External investment in this low technology
Using Crowdsourcing to Examine Land Acquisitions in Ethiopia
"... This contribution was double-blind reviewed as extended abstract. Land grabbing is a global phenomenon that has radically increased since 2005. Global and national estimates are highly uncertain due to the rapid pace of acquisition and lack of transparency. Here we demonstrate that through the use o ..."
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This contribution was double-blind reviewed as extended abstract. Land grabbing is a global phenomenon that has radically increased since 2005. Global and national estimates are highly uncertain due to the rapid pace of acquisition and lack of transparency. Here we demonstrate that through the use of the Geo-Wiki crowdsourcing tool and volunteers, we can estimate areas of settlement and cultivation that are part of large-scale land transactions for known areas where land acquisitions have taken place as well as for Ethiopia as a whole. 1
www.mdpi.com/journal/ijgi Article Extracting Urban Land Use from Linked Open Geospatial Data
"... Abstract: The ever-increasing availability of linked open geospatial data provides an unprecedented source of geo-information to describe urban environments. This wealth of data should be turned into actionable knowledge: for example, open data could be used as a proxy or substitute for closed or ex ..."
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Abstract: The ever-increasing availability of linked open geospatial data provides an unprecedented source of geo-information to describe urban environments. This wealth of data should be turned into actionable knowledge: for example, open data could be used as a proxy or substitute for closed or expensive information. The successful employment of linked open geospatial data can pave the way for innovative solutions to smart city problems. In this paper, we illustrate a set of experiments that, starting from linked open geospatial data, execute a knowledge discovery process to predict urban semantics. More specifically, we leverage geo-information about points of interests as input in a classification model of land use at a moderate spatial resolution (250 meters) over wide urban areas in Europe. We replicate our experiments in different European cities—Milano, München, Barcelona and Brussels—to ensure the repeatability and generality of our approach, and we explain the experimental conditions, as well as the employed datasets to guarantee reproducibility. We extensively report on quantitative and qualitative evaluation results, to judge the validity, as well as the limitations of our proposed approach.
International Journal of Digital Earth Rating crowdsourced annotations: evaluating contributions of variable quality and completeness Rating crowdsourced annotations: evaluating contributions of variable quality and completeness
"... Crowdsourcing has become a popular means to acquire data about the Earth and its environment inexpensively, but the data-sets obtained are typically imperfect and of unknown quality. Two common imperfections with crowdsourced data are the contributions from cheats or spammers and missing cases. The ..."
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Crowdsourcing has become a popular means to acquire data about the Earth and its environment inexpensively, but the data-sets obtained are typically imperfect and of unknown quality. Two common imperfections with crowdsourced data are the contributions from cheats or spammers and missing cases. The effect of the latter two imperfections on a method to evaluate the accuracy of crowdsourced data via a latent class model was explored. Using simulated and real data-sets, it was shown that the method is able to derive useful information on the accuracy of crowdsourced data even when the degree of imperfection was very high. The practical potential of this ability to obtain accuracy information within the geospatial sciences and the realm of Digital Earth applications was indicated with reference to an evaluation of building damage maps produced by multiple bodies after the 2010 earthquake in Haiti. Critically, the method allowed data-sets to be ranked in approximately the correct order of accuracy and this could help ensure that the most appropriate data-sets are used.
