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Correction: Rembold, F.; Atzberger, C.; Savin, I.; Rojas, O. Using Low Resolution Satellite Imagery for Yield Prediction and Yield Anomaly Detection. Remote Sens. 2013, 5, 1704-1733

Felix Rembold, Clement Atzberger, Igor Savin, Oscar Rojas
2013 Remote Sensing  
NDVI/yield linear regressions for cereals in North Africa (from Maselli and Rembold [46] ; modified).  ... 
doi:10.3390/rs5115572 fatcat:2jlkn7xitrhordod2jr44t2qoq

Image time series processing for agriculture monitoring

Herman Eerens, Dominique Haesen, Felix Rembold, Ferdinando Urbano, Carolien Tote, Lieven Bydekerke
2014 Environmental Modelling & Software  
A review on this evolution has been published by Rembold et al. (2013) .  ... 
doi:10.1016/j.envsoft.2013.10.021 fatcat:dw7lisfduvblzih2sbdzyxoov4

Comparison of Global Land Cover Datasets for Cropland Monitoring

Ana Pérez-Hoyos, Felix Rembold, Hervé Kerdiles, Javier Gallego
2017 Remote Sensing  
Author Contributions: Ana Pérez-Hoyos and Felix Rembold conceived and designed the research; Ana Pérez-Hoyos conducted the analysis and drafted the manuscript; Javier Gallego provided some essential suggestions  ...  Author Contributions: Ana Pérez-Hoyos and Felix Rembold conceived and designed the research; Ana Pérez-Hoyos conducted the analysis and drafted the manuscript; Javier Gallego provided some essential suggestions  ... 
doi:10.3390/rs9111118 fatcat:mewedztngfduvgajmwhu67ffm4

Using Low Resolution Satellite Imagery for Yield Prediction and Yield Anomaly Detection

Felix Rembold, Clement Atzberger, Igor Savin, Oscar Rojas
2013 Remote Sensing  
The two failed seasons in 2010 and 2011 Figure 4 . 4 NDVI/yield linear regressions for cereals in North Africa (from Maselli and Rembold Figure 7 . 7 Simplified scheme of a crop process model.  ...  For example, Maselli and Rembold [46] used the regression between historical yields and cumulated NDVI at pixel level to derive fractions of agricultural area by pixel and restrict yield estimates to  ... 
doi:10.3390/rs5041704 fatcat:oq23wwe56vbzfeobfaaadfw2jq

Nlcam modulates midline convergence during anterior neural plate morphogenesis

Katherine E. Brown, Philipp J. Keller, Mirana Ramialison, Martina Rembold, Ernst H.K. Stelzer, Felix Loosli, Joachim Wittbrodt
2010 Developmental Biology  
., 2006; Rembold et al., 2006b) .  ...  Injection and transplantation Injections were carried out essentially as described [Rembold] .  ... 
doi:10.1016/j.ydbio.2009.12.003 pmid:20005219 fatcat:fgd6sgz6fzfk7aq6sagfwrb4ny

Portability of neural nets modelling regional winter crop acreages using AVHRR time series

Clement Atzberger, Felix Rembold
2012 European Journal of Remote Sensing  
The current paper is an extension and refinement of the mentioned conference papers Rembold, 2009, 2010] .  ...  Alternative architectures with larger number of hidden nodes were evaluated [Atzberger and Rembold, 2009 ] but resulted in overfitting problems.  ... 
doi:10.5721/eujrs20124532 fatcat:mizyvljwifhv5gnse3vqmrlwru

Yield forecasting with machine learning and small data: what gains for grains? [article]

Michele Meroni, François Waldner, Lorenzo Seguini, Hervé Kerdiles, Felix Rembold
2021 arXiv   pre-print
., 2016; Rembold et al., 2013) .  ...  provided in a ready-to-use format by the Anomaly hotSpot of Agricultural Production (ASAP) early warning decision support system of the European Commission Joint Research Centre (Meroni et al., 2019b; Rembold  ... 
arXiv:2104.13246v2 fatcat:2htwmdrpojcf7m5h3gjsehgwo4

Mapping the Spatial Distribution of Winter Crops at Sub-Pixel Level Using AVHRR NDVI Time Series and Neural Nets

Clement Atzberger, Felix Rembold
2013 Remote Sensing  
In-season predictions improved compared to the work of Rembold and Maselli [20, 21] using the same dataset and linear prediction models.  ...  Several studies by Rembold and Maselli used Spectral Angular Mapping (SAM) for measuring inter-annual crop area changes based on NDVI time series from NOAA-AVHRR [20, 21] .  ... 
doi:10.3390/rs5031335 fatcat:ccl6xdizz5gwbghbz4s22ze2t4

Near real-time vegetation anomaly detection with MODIS NDVI: Timeliness vs. accuracy and effect of anomaly computation options

Michele Meroni, Dominique Fasbender, Felix Rembold, Clement Atzberger, Anja Klisch
2019 Remote Sensing of Environment  
Rojas et al., 2011; Sepulcre-Canto et al., 2012; Rembold et al., 2018) .  ...  Rembold Table 3 Ranked concordance between anomaly classes of NxHy and NfHf.  ... 
doi:10.1016/j.rse.2018.11.041 pmid:30774156 pmcid:PMC6360378 fatcat:skzxhrseyve5rbzsfsbuxtnry4

Evaluation of the Standardized Precipitation Index as an early predictor of seasonal vegetation production anomalies in the Sahel

Michele Meroni, Felix Rembold, Dominique Fasbender, Anton Vrieling
2016 Remote Sensing Letters  
Mitigating drought impacts requires timely and locationspecific information on drought occurrence to ensure appropriate responses (Rembold et al. 2016) .  ...  To keep the time frame consistent for the two RFE sources, we computed the SPI using data for the 1983-2013 period, using the SPIRITS software (Rembold et al., 2015) .  ... 
doi:10.1080/2150704x.2016.1264020 fatcat:jwldzc7sg5aqxm5piq4ftx4vru

Mapping areas invaded by Prosopis juliflora in Somaliland on Landsat 8 imagery

Felix Rembold, Ugo Leonardi, Wai-Tim Ng, Hussein Gadain, Michele Meroni, Clement Atzberger, Christopher M. U. Neale, Antonino Maltese
2015 Remote Sensing for Agriculture, Ecosystems, and Hydrology XVII  
Prosopis juliflora is a fast growing tree species originating from South and Central America with a high invasion potential in semi-arid areas around the globe. It was introduced to East Africa for the stabilization of dune systems and for providing fuel wood after prolonged droughts and deforestation in the 1970s and 1980s. In many dry lands in East Africa the species has expanded rapidly and has become challenging to control. The species generally starts its colonization on deep soils with
more » ... h water availability while in later stages or on poorer soils, its thorny thickets expand into drier grasslands and rangelands. Abandoned or low input farmland is also highly susceptible for invasion as P. juliflora has competitive advantages to native species and is extremely drought tolerant. In this work we describe a rapid approach to detect and map P. juliflora invasion at country level for the whole of Somaliland. Field observations were used to delineate training sites for a supervised classification of Landsat 8 imagery collected during the driest period of the year (i.e., from late February to early April). The choice of such a period allowed to maximise the spectral differences between P. juliflora and other species present in the area, as P. juliflora tends to maintain a higher vigour and canopy water content than native vegetation, when exposed to water stress. The results of our classification map the current status of invasion of Prosopis in Somaliland showing where the plant is invading natural vegetation or agricultural areas. These results have been verified for two spatial subsets of the whole study area with very high resolution (VHR) imagery, proving that Landsat 8 imagery is highly adequate to map P. juliflora. The produced map represents a baseline for understanding spatial distribution of P. juliflora across Somaliland but also for change detection and monitoring of long term dynamics in support to P. juliflora management and control activities.
doi:10.1117/12.2193133 fatcat:dw2pqcem3vcclewtfr2y6qlu2q

Remote sensing time series analysis for crop monitoring with the SPIRITS software: new functionalities and use examples

Felix Rembold, Michele Meroni, Ferdinando Urbano, Antoine Royer, Clement Atzberger, Guido Lemoine, Herman Eerens, Dominique Haesen
2015 Frontiers in Environmental Science  
Globally, a number of operational systems have implemented such type of analysis as recently reviewed in Rembold et al. (2013) and Atzberger (2013) .  ...  The mentioned vegetation indices and biophysical variables are mainly derived from space measurements in the visible to near infrared reflected domain (Rembold et al., 2013) .  ... 
doi:10.3389/fenvs.2015.00046 fatcat:jcvfz2q35ffihfrw4bwx3n7pm4

Historical extension of operational NDVI products for livestock insurance in Kenya

Anton Vrieling, Michele Meroni, Apurba Shee, Andrew G. Mude, Joshua Woodard, C.A.J.M. (Kees) de Bie, Felix Rembold
2014 International Journal of Applied Earth Observation and Geoinformation  
Droughts induce livestock losses that severely affect Kenyan pastoralists. Recent index insurance schemes have the potential of being a viable tool for insuring pastoralists against drought-related risk. Such schemes require as input a forage scarcity (or drought) index that can be reliably updated in near realtime, and that strongly relates to livestock mortality. Generally, a long record (>25 years) of the index is needed to correctly estimate mortality risk and calculate the related
more » ... premium. Data from current operational satellites used for large-scale vegetation monitoring span over a maximum of 15 years, a time period that is considered insufficient for accurate premium computation. This study examines how operational NDVI datasets compare to, and could be combined with the non-operational recently constructed 30-year GIMMS AVHRR record to provide a near-real time drought index with a long term archive for the arid lands of Kenya. We compared six freely available, near-real time NDVI products: five from MODIS and one from SPOT-VEGETATION. Prior to comparison, all datasets were averaged in time for the two vegetative seasons in Kenya, and aggregated spatially at the administrative division level at which the insurance is offered. The feasibility of extending the resulting aggregated drought indices back in time was assessed using jackknifed R 2 statistics (leave-one-year-out) for the overlapping period 2002-2011. We found that division-specific models were more effective than a global model for linking the division-level temporal variability of the index between NDVI products. Based on our results, good scope exists for historically extending the aggregated drought index, thus providing a longer operational record for insurance purposes. We showed that this extension may have large effects on the calculated insurance premium. Finally, we discuss several possible improvements to the drought index.
doi:10.1016/j.jag.2013.12.010 fatcat:u76musyj7baydgrf7ukgkh6fs4

Investigating the Relationship between the Inter-Annual Variability of Satellite-Derived Vegetation Phenology and a Proxy of Biomass Production in the Sahel

Michele Meroni, Felix Rembold, Michel Verstraete, Rene Gommes, Anne Schucknecht, Gora Beye
2014 Remote Sensing  
Felix Rembold and Rene Gommes supported the interpretation of the correlation analysis. Anne Schucknecht and Gora Beye assisted in the analysis of ground measurements and in the validation exercise.  ... 
doi:10.3390/rs6065868 fatcat:ubazklahjfbkdcmxoupdkebw3e

Comparing land surface phenology of major European crops as derived from SAR and multispectral data of Sentinel-1 and -2

Michele Meroni, Raphaël d'Andrimont, Anton Vrieling, Dominique Fasbender, Guido Lemoine, Felix Rembold, Lorenzo Seguini, Astrid Verhegghen
2021 Remote Sensing of Environment  
Phenology is also used to monitor the crop progress in food security monitoring applications (Rembold et al. 2019 ) and can represent a key indicator for the control of the European Common Agricultural  ... 
doi:10.1016/j.rse.2020.112232 pmid:33536689 pmcid:PMC7841528 fatcat:g2a6xd4msjblppov6yo6x4teqe
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