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Remote Sens. 2014, 6(11), 10947-10965; doi:10.3390/rs61110947

From Remotely Sensed Vegetation Onset to Sowing Dates: Aggregating Pixel-Level Detections into Village-Level Sowing Probabilities

1
Center for International Forestry Research, Rua do Russel, 459/601 Rio de Janeiro (RJ), Brazil
2
Joint Research Center of the European Commission, Via Enrico Fermi, 2749 Ispra, Italy
3
World Food Programme, Via Viola Giulio, 68 Roma, Italy
*
Author to whom correspondence should be addressed.
Received: 3 June 2014 / Revised: 20 October 2014 / Accepted: 24 October 2014 / Published: 10 November 2014
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Abstract

Monitoring the start of the crop season in Sahel provides decision makers with valuable information for an early assessment of potential production and food security threats. Presently, the most common method for the estimation of sowing dates in West African countries consists of applying given thresholds on rainfall estimations. However, the coarse spatial resolution and the possible inaccuracy of these estimations are limiting factors. In this context, the remote sensing approach, which consists of deriving green-up onset dates from satellite remote sensing data, appears as an interesting alternative. It builds upon a novel statistic model that translates vegetation onset detections derived from MODIS time series into sowing probabilities at the village level. Results for Niger show that this approach outperforms the standard method adopted in the region based on rainfall thresholds. View Full-Text
Keywords: green-up onset; sowing probabilities; Niger; crops; statistical model; MODIS; remote sensing; phenology; food security green-up onset; sowing probabilities; Niger; crops; statistical model; MODIS; remote sensing; phenology; food security
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Marinho, E.; Vancutsem, C.; Fasbender, D.; Kayitakire, F.; Pini, G.; Pekel, J.-F. From Remotely Sensed Vegetation Onset to Sowing Dates: Aggregating Pixel-Level Detections into Village-Level Sowing Probabilities. Remote Sens. 2014, 6, 10947-10965.

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