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  • Articles  (16)
  • Architecture, Civil Engineering, Surveying  (12)
  • Computer Science  (4)
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  • Articles  (16)
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  • 1
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    Remote Sensing, Vol. 8, Pages 585: Crop Area Mapping Using 100-m Proba-V Time Series (2016)
    MDPI Publishing
    Details
    Publication Date: 2016-07-12
    Description: A method was developed for crop area mapping inspired by spectral matching techniques (SMTs) and based on phenological characteristics of different crop types applied using 100-m Proba-V NDVI data for the season 2014–2015. Ten-daily maximum value NDVI composites were created and smoothed in SPIRITS (spirits.jrc.ec.europa.eu). The study sites were globally spread agricultural areas located in Flanders (Belgium), Sria (Russia), Kyiv (Ukraine) and Sao Paulo (Brazil). For each pure pixel within the field, the NDVI profile of the crop type for its growing season was matched with the reference NDVI profile based on the training set extracted from the study site where the crop type originated. Three temporal windows were tested within the growing season: green-up to senescence, green-up to dormancy and minimum NDVI at the beginning of the growing season to minimum NDVI at the end of the growing season. Post classification rules were applied to the results to aggregate the crop type at the plot level. The overall accuracy (%) ranged between 65 and 86, and the kappa coefficient changed from 0.43–0.84 according to the site and the temporal window. In order of importance, the crop phenological development period, parcel size, shorter time window, number of ground-truth parcels and crop calendar similarity were the main reasons behind the differences between the results. The methodology described in this study demonstrated that 100-m Proba-V has the potential to be used in crop area mapping across different regions in the world.
    Electronic ISSN: 2072-4292
    Topics: Architecture, Civil Engineering, Surveying , Geography
    Published by MDPI Publishing
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  • 2
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    Remote Sensing, Vol. 8, Pages 170: Testing the Contribution of Stress Factors to Improve Wheat and Maize Yield Estimations Derived from Remotely-Sensed Dry Matter Productivity (2016)
    MDPI Publishing
    Details
    Publication Date: 2016-02-26
    Description: According to Monteith’s theory, crop biomass is linearly correlated with the amount of absorbed photosynthetically active radiation (APAR) and a constant radiation use efficiency (RUE) down-regulated by stress factors such as CO2 fertilisation, temperature and water stress. The objective was to investigate the relative importance of these stress factors in relation to regional biomass production and yield. The production efficiency model Copernicus Global Land Service-Dry Matter Productivity (CGLS-DMP), which follows Monteith’s theory, was modified and evaluated for common wheat and silage maize in France, Belgium and Morocco using SPOT VEGETATION for the period 1999–2012. For each study site the stress factor that has the highest correlation with crop yield was retained. The correlation between crop yield data and cumulative modified DMP, CGLS-DMP, fAPAR, and NDVI values were analysed for different crop growth stages. A leave-one-year-out cross validation was used to test the robustness of the model. On average, R2 values increased from 0.49 for CGLS-DMP to 0.68 for modified DMP, RMSE (t/ha) decreased from 0.84–0.61, RRMSE (%) reduced from 13.1–8.9, MBE (t/ha) decreased from 0.05–0.03 and the index of model performance (E1) increased from 0.08–0.28 for the selected sites and crops. The best results were obtained by including combinations of the most appropriate stress factors for each selected region and cumulating the modified DMP during part of the growing season that includes the reproductive stage. Though no single solution to the improvement of a global product could be demonstrated, our findings encourage an extension of the methodology to other regions of the world.
    Electronic ISSN: 2072-4292
    Topics: Architecture, Civil Engineering, Surveying , Geography
    Published by MDPI Publishing
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  • 3
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    Deep-sea protection: coordinate efforts (2014)
    American Association for the Advancement of Science (AAAS)
    Details
    Publication Date: 2014-06-21
    Description: 〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Gobin, Charlotte -- da Fonseca, Gustavo A B -- New York, N.Y. -- Science. 2014 Jun 20;344(6190):1352. doi: 10.1126/science.344.6190.1352.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Global Environment Facility, Washington, DC 20433, USA. cgobin@thegef.org. ; Global Environment Facility, Washington, DC 20433, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/24948729" target="_blank"〉PubMed〈/a〉
    Keywords: *Air Pollutants ; *Carbon Dioxide ; Conservation of Natural Resources/*methods ; *Seawater
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
    Published by American Association for the Advancement of Science (AAAS)
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  • 4
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    Remote Sensing, Vol. 10, Pages 1642: Synergistic Use of Radar Sentinel-1 and Optical Sentinel-2 Imagery for Crop Mapping: A Case Study for Belgium (2018)
    MDPI
    Details
    Publication Date: 2018
    Description: A timely inventory of agricultural areas and crop types is an essential requirement for ensuring global food security and allowing early crop monitoring practices. Satellite remote sensing has proven to be an increasingly more reliable tool to identify crop types. With the Copernicus program and its Sentinel satellites, a growing source of satellite remote sensing data is publicly available at no charge. Here, we used joint Sentinel-1 radar and Sentinel-2 optical imagery to create a crop map for Belgium. To ensure homogenous radar and optical inputs across the country, Sentinel-1 12-day backscatter mosaics were created after incidence angle normalization, and Sentinel-2 normalized difference vegetation index (NDVI) images were smoothed to yield 10-daily cloud-free mosaics. An optimized random forest classifier predicted the eight crop types with a maximum accuracy of 82% and a kappa coefficient of 0.77. We found that a combination of radar and optical imagery always outperformed a classification based on single-sensor inputs, and that classification performance increased throughout the season until July, when differences between crop types were largest. Furthermore, we showed that the concept of classification confidence derived from the random forest classifier provided insight into the reliability of the predicted class for each pixel, clearly showing that parcel borders have a lower classification confidence. We concluded that the synergistic use of radar and optical data for crop classification led to richer information increasing classification accuracies compared to optical-only classification. Further work should focus on object-level classification and crop monitoring to exploit the rich potential of combined radar and optical observations.
    Electronic ISSN: 2072-4292
    Topics: Architecture, Civil Engineering, Surveying , Geography
    Published by MDPI
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  • 5
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    Tailored e-Health services for the dementia care setting: a pilot study of ‘eHealthMonitor’ (2015)
    BioMed Central
    Details
    Publication Date: 2015-07-29
    Description: Background: The European eHealthMonitor project (eHM) developed a user-sensitive and interactive web portal for dementia care: the eHM Dementia Portal (eHM-DP). It aims to provide targeted and personalized support for informal caregivers of people with dementia in a home-based care setting. The objective of the pilot study was to obtain feedback on the eHM-DP from two user perspectives (caregivers and medical professionals), focusing on caregiver empowerment, decision aid, and the perceived benefits of the eHM-DP. Methods: The study on the eHM-DP was conducted from March 2014 to June 2014. The methodological approach followed a user-participatory design with a total number of 42 participants. The study included caregivers of people with dementia and medical professionals (MPs) from the metropolitan region of Erlangen-Nürnberg (Bavaria, Germany). Study participants were interviewed face-to-face with semi-structured, written interviews. Results: Caregivers indicated a high degree of perceived support by the eHM-DP and of provided decision aid. In total, 89 % of caregivers and 54 % of MPs would use the eHM-DP if access were provided. The primary benefits participants perceived were the acquisition of individualized information, computerized interaction between caregivers and MPs, empowerment in health-related decisions and comprehensive insights into the progress of the disease. Major recommendations for improving the eHM-DP encompassed: an active search functionality based on predefined terms, the implementation of a chatroom for caregivers, an upload function and alerts for MPs, as well as the overall design. Conclusions: Our study is the first to have provided new insights and results on an interactive and needs-oriented web portal, endeavouring towards empowerment and assistance in decision making for caregivers as well as MPs within the realm of caring for patients with dementia. The acceptance and willingness to use the eHM-DP emphasizes the potential of eHealth services for community-based dementia care settings.
    Electronic ISSN: 1472-6947
    Topics: Computer Science , Medicine
    Published by BioMed Central
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  • 6
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    Wheat Yield Estimation from NDVI and Regional Climate Models in Latvia (2020)
    Molecular Diversity Preservation International
    Details
    Publication Date: 2020-07-10
    Description: Wheat yield variability will increase in the future due to the projected increase in extreme weather events and long-term climate change effects. Currently, regional agricultural statistics are used to monitor wheat yield. Remotely sensed vegetation indices have a higher spatio-temporal resolution and could give more insight into crop yield. In this paper, we (i) evaluate the possibility to use Normalized Difference Vegetation Index (NDVI) time series to estimate wheat yield in Latvia and (ii) determine which weather variables impact wheat yield changes using both ALARO-0 and REMO Regional Climate Models (RCM) output. The integral from NDVI series (aNDVI) for winter and spring wheat fields is used as a predictor to model regional wheat yield from 2014 to 2018. A correlation analysis between weather variables, wheat yield and aNDVI was used to elucidate which weather variables impact wheat yield changes in Latvia. Our results indicate that high temperatures in June for spring wheat and in July for winter wheat had a negative correlation with yield. A linear regression yield model explained 71% of the variability with a residual standard error of 0.55 Mg/ha. When RCM data were added as predictor variables to the wheat yield empirical model a random forest approach resulted in better results compared to a linear regression approach, the explained variance increased up to 97% and the residual standard error decreased to 0.17 Mg/ha. We conclude that NDVI time series and RCM output enabled regional crop yield and weather impact monitoring at higher spatio-temporal resolutions than regional statistics.
    Electronic ISSN: 2072-4292
    Topics: Architecture, Civil Engineering, Surveying , Geography
    Published by Molecular Diversity Preservation International
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  • 7
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    Tailored e-Health services for the dementia care setting: a pilot study of ‘eHealthMonitor’ (2015)
    BioMed Central
    Details
    Publication Date: 2015-07-28
    Electronic ISSN: 1472-6947
    Topics: Computer Science , Medicine
    Published by BioMed Central
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  • 8
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    Rainfall-runoff modelling of a humid tropical catchment: the TOPMODEL approach (2002)
    Wiley
    Details
    Publication Date: 2002-01-01
    Description: TOPMODEL, a semi-distributed, topographically based hydrological model, was applied to simulate continously the runoff hydrograph of a medium-sized (379 km2), humid tropical catchment. The objectives were to relate hydrological responses to runoff generation mechanisms operating in the catchment and to estimate the uncertainty associated with runoff prediction. Field observations indicated that water tables were not parallel to the surface topography, particularly at the start of the wet season. A reference topographic index λREF was therefore introduced into the TOPMODEL structure to increase the weighting of local storage deficits in upland areas. The model adaptation had the effect of deepening water tables with distance from the river channel. The generalized likelihood uncertainty estimation (GLUE) framework was used to assess the performance of the model with randomly selected parameter sets, and to set simulation confidence limits. The model simulated well the fast subsurface and overland flow events superimposed on the seasonal rise and fall of the baseflow. The top ranked parameter sets achieved modelling efficiencies of 0.943 and 0.849 in 1994 and 1995 respectively. The GLUE analysis showed that the exponential decay parameter m, controlling the baseflow and the local storage deficit, was the most sensitive parameter. There was increased uncertainty in the simulations of storm events during the early and late phase of the season, which was due to a combination of: errors in detecting the rainfall depths for convectional rainfall events; the treatment of rainfall as a catchment areal value; and, the strong seasonality in runoff response in the humid tropics. Copyright © 2002 John Wiley and Sons, Ltd.
    Print ISSN: 0885-6087
    Electronic ISSN: 1099-1085
    Topics: Architecture, Civil Engineering, Surveying , Geography
    Published by Wiley
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  • 9
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    Temporal and spatial rainfall analysis across a humid tropical catchment (2001)
    Wiley
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    Publication Date: 2001-01-01
    Description: Temporal and spatial rainfall patterns were analysed to describe the distribution of daily rainfall across a medium-sized (379 km2) tropical catchment. Investigations were carried out to assess whether a climatological variogram model was appropriate for mapping rainfall taking into consideration the changing rainfall characteristics through the wet season. Exploratory, frequency and moving average analyses of 30 years' daily precipitation data were used to describe the reliability and structure of the rainfall regime. Four phases in the wet season were distinguished, with the peak period (mid-August to mid-September) representing the wettest period. A low-cost rain gauge network of 36 plastic gauges with overflow reservoirs was installed and monitored to obtain spatially distributed rainfall data. Geostatistical techniques were used to develop global and wet season phase climatological variograms. The unscaled climatological variograms were cross-validated and compared using a range of rainfall events. Ordinary Kriging was used as the interpolation method. The global climatological variogram γ* = 1·2 [1 - exp - h/18 km] performed better, and was used to optimize the number and location of rain gauges in the network. The research showed that although distinct wet season phases could be established based on the temporal analysis of daily rainfall characteristics, the interpolation of daily rainfall across a medium-sized catchment based on spatial analysis was better served by using the global rather than the wet season phase climatological variogram model. Copyright © 2001 John Wiley & Sons, Ltd.
    Print ISSN: 0885-6087
    Electronic ISSN: 1099-1085
    Topics: Architecture, Civil Engineering, Surveying , Geography
    Published by Wiley
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  • 10
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    Crop Area Mapping Using 100-m Proba-V Time Series (2016)
    Molecular Diversity Preservation International
    Details
    Publication Date: 2016-07-11
    Electronic ISSN: 2072-4292
    Topics: Architecture, Civil Engineering, Surveying , Geography
    Published by Molecular Diversity Preservation International
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