The use of spectral data is seen as a fast and non-destructive method capable of monitoring pastu... more The use of spectral data is seen as a fast and non-destructive method capable of monitoring pasture biomass. Although there is great potential in this technique, both end users and sensor manufacturers are uncertain about the necessary sensor specifications and achievable accuracies in an operational scenario. This study presents a straightforward parametric method able to accurately retrieve the hyperspectral signature of perennial ryegrass (Lolium perenne) canopies from multispectral data collected within a two-year period in Australia and the Netherlands. The retrieved hyperspectral data were employed to generate optimal indices and continuum-removed spectral features available in the scientific literature. For performance comparison, both these simulated features and a set of currently employed vegetation indices, derived from the original band values, were used as inputs in a random forest algorithm and accuracies of both methods were compared. Our results have shown that both ...
Global scale land cover (LC) mapping has interested many researchers over the last two decades as... more Global scale land cover (LC) mapping has interested many researchers over the last two decades as it is an input data source for various applications. Current global land cover (GLC) maps often do not meet the accuracy and thematic requirements of specific users. This study aimed to create an improved GLC map by integrating available GLC maps and reference datasets. We also address the thematic requirements of multiple users by demonstrating a concept of producing GLC maps with user-specific legends. We used a regression kriging method to integrate Globcover-2009, LC-CCI-2010, MODIS-2010 and Globeland30 maps and several publicly available GLC reference datasets. Overall correspondence of the integrated GLC map with reference LC was 80% based on 10-fold crossvalidation using 24,681 sample sites. This is globally 10% and regionally 6-13% higher than the input map correspondences. Based on LC class presence probability maps, expected LC proportion maps at coarser resolution were created and used for characterizing mosaic classes for land system modelling and biodiversity assessments. Since more reference datasets are becoming freely accessible, GLC mapping can be further improved by using the pool of all available reference datasets. LC proportion information allow tuning LC products to specific user needs.
Previous analyses of the effects of uncertainty in precipitation fields on the output of EU Crop ... more Previous analyses of the effects of uncertainty in precipitation fields on the output of EU Crop Growth Monitoring System (CGMS) demonstrated that the influence on simulated crop yield was limited at national scale, but considerable at local and regional scales. We aim to propagate uncertainty due to precipitation in the crop model by Monte Carlo sampling of the precipitation field. We use an error model fitted to a highly accurate precipitation dataset (ELDAS) which was available for the year 2000. Our error model consisted of two components. The first is an additive component generating precipitation residues over the entire spatial domain. The residues are generated by quantile-based back transformation of standard Gaussian fields using a set of histograms for different CGMS precipitation bins. The second component is multiplicative and generates binary rain/no-rain events on locations where the CGMS precipitation records report nil precipitation. Our results demonstrate that the model generates realistic patterns of precipitation and reproduces the histograms of the reference precipitation dataset well. A remaining problem is the inability to model prolonged dry spells which is due to our model choice. The precipitation realizations were used as input in a crop growth model. The first results indicate that the uncertainty in precipitation is sufficient to sustain divergence in the soil moisture ensemble, but not in the leaf area index ensemble.
According to the latest report of the Intergovernmental Panel on Climate Change (IPCC), emissions... more According to the latest report of the Intergovernmental Panel on Climate Change (IPCC), emissions must be cut by 41–72 % below 2010 levels by 2050 for a likely chance of containing the global mean temperature increase to 2 °C. The AFOLU sector (Agriculture, Forestry and Other Land Use) roughly contributes with a quarter (~ 10–12 PgCO2e.yr<sup>−1</sup>) of the net anthropogenic GHG emissions mainly from deforestation, fire, wood harvesting, and agricultural emissions including croplands, paddy rice and livestock. In spite of the importance of this sector, it is unclear where are the regions in the planet with AFOLU emissions hotspots, and how uncertain these emissions are. Here we present a novel spatially comparable dataset containing annual mean estimates of gross AFOLU emissions (CO<sub>2</sub>, CH<sub>4</sub>, N<sub>2</sub>O), associated uncertainties, and leading emission sources, in a spatially disaggregated mann...
This paper describes an interactive web-based near real-time (NRT) forest monitoring system using... more This paper describes an interactive web-based near real-time (NRT) forest monitoring system using four levels of geographic information services: 1) the acquisition of continuous data streams from satellite and community-based monitoring using mobile devices, 2) NRT forest disturbance detection based on satellite time-series, 3) presentation of forest disturbance data through a web-based application and social media and 4) interaction of the satellite based disturbance alerts with the end-user communities to enhance the collection of ground data. The system is developed using open source technologies and has been implemented together with local experts in the UNESCO Kafa Biosphere Reserve, Ethiopia. The results show that the system is able to provide easy access to information on forest change and considerably improves the collection and storage of ground observation by local experts. Social media leads to higher levels of user interaction and noticeably improves communication among...
The use of spectral data is seen as a fast and non-destructive method capable of monitoring pastu... more The use of spectral data is seen as a fast and non-destructive method capable of monitoring pasture biomass. Although there is great potential in this technique, both end users and sensor manufacturers are uncertain about the necessary sensor specifications and achievable accuracies in an operational scenario. This study presents a straightforward parametric method able to accurately retrieve the hyperspectral signature of perennial ryegrass (Lolium perenne) canopies from multispectral data collected within a two-year period in Australia and the Netherlands. The retrieved hyperspectral data were employed to generate optimal indices and continuum-removed spectral features available in the scientific literature. For performance comparison, both these simulated features and a set of currently employed vegetation indices, derived from the original band values, were used as inputs in a random forest algorithm and accuracies of both methods were compared. Our results have shown that both ...
Global scale land cover (LC) mapping has interested many researchers over the last two decades as... more Global scale land cover (LC) mapping has interested many researchers over the last two decades as it is an input data source for various applications. Current global land cover (GLC) maps often do not meet the accuracy and thematic requirements of specific users. This study aimed to create an improved GLC map by integrating available GLC maps and reference datasets. We also address the thematic requirements of multiple users by demonstrating a concept of producing GLC maps with user-specific legends. We used a regression kriging method to integrate Globcover-2009, LC-CCI-2010, MODIS-2010 and Globeland30 maps and several publicly available GLC reference datasets. Overall correspondence of the integrated GLC map with reference LC was 80% based on 10-fold crossvalidation using 24,681 sample sites. This is globally 10% and regionally 6-13% higher than the input map correspondences. Based on LC class presence probability maps, expected LC proportion maps at coarser resolution were created and used for characterizing mosaic classes for land system modelling and biodiversity assessments. Since more reference datasets are becoming freely accessible, GLC mapping can be further improved by using the pool of all available reference datasets. LC proportion information allow tuning LC products to specific user needs.
Previous analyses of the effects of uncertainty in precipitation fields on the output of EU Crop ... more Previous analyses of the effects of uncertainty in precipitation fields on the output of EU Crop Growth Monitoring System (CGMS) demonstrated that the influence on simulated crop yield was limited at national scale, but considerable at local and regional scales. We aim to propagate uncertainty due to precipitation in the crop model by Monte Carlo sampling of the precipitation field. We use an error model fitted to a highly accurate precipitation dataset (ELDAS) which was available for the year 2000. Our error model consisted of two components. The first is an additive component generating precipitation residues over the entire spatial domain. The residues are generated by quantile-based back transformation of standard Gaussian fields using a set of histograms for different CGMS precipitation bins. The second component is multiplicative and generates binary rain/no-rain events on locations where the CGMS precipitation records report nil precipitation. Our results demonstrate that the model generates realistic patterns of precipitation and reproduces the histograms of the reference precipitation dataset well. A remaining problem is the inability to model prolonged dry spells which is due to our model choice. The precipitation realizations were used as input in a crop growth model. The first results indicate that the uncertainty in precipitation is sufficient to sustain divergence in the soil moisture ensemble, but not in the leaf area index ensemble.
According to the latest report of the Intergovernmental Panel on Climate Change (IPCC), emissions... more According to the latest report of the Intergovernmental Panel on Climate Change (IPCC), emissions must be cut by 41–72 % below 2010 levels by 2050 for a likely chance of containing the global mean temperature increase to 2 °C. The AFOLU sector (Agriculture, Forestry and Other Land Use) roughly contributes with a quarter (~ 10–12 PgCO2e.yr<sup>−1</sup>) of the net anthropogenic GHG emissions mainly from deforestation, fire, wood harvesting, and agricultural emissions including croplands, paddy rice and livestock. In spite of the importance of this sector, it is unclear where are the regions in the planet with AFOLU emissions hotspots, and how uncertain these emissions are. Here we present a novel spatially comparable dataset containing annual mean estimates of gross AFOLU emissions (CO<sub>2</sub>, CH<sub>4</sub>, N<sub>2</sub>O), associated uncertainties, and leading emission sources, in a spatially disaggregated mann...
This paper describes an interactive web-based near real-time (NRT) forest monitoring system using... more This paper describes an interactive web-based near real-time (NRT) forest monitoring system using four levels of geographic information services: 1) the acquisition of continuous data streams from satellite and community-based monitoring using mobile devices, 2) NRT forest disturbance detection based on satellite time-series, 3) presentation of forest disturbance data through a web-based application and social media and 4) interaction of the satellite based disturbance alerts with the end-user communities to enhance the collection of ground data. The system is developed using open source technologies and has been implemented together with local experts in the UNESCO Kafa Biosphere Reserve, Ethiopia. The results show that the system is able to provide easy access to information on forest change and considerably improves the collection and storage of ground observation by local experts. Social media leads to higher levels of user interaction and noticeably improves communication among...
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Papers by Sytze de Bruin