Development of a new cropland and rangeland Area Fraction Image at 500 m for the ASAP system
This document presents a description of the data used and the processing carried out to derive global cropland and rangeland area fraction images at 500 m used since ASAP v.8.0.
ASAP warning classification scheme v 8.0
This document illustrates the ASAP methodology for the automatic calculation of the warning levels at provincial level, including the model, the data used by the system, and the way it is implemented. Version 8.0.
Development of a national and sub-national crop calendars data set compatible with remote sensing derived land surface phenology
This document illustrates the method used to downscale the existing national level crop calendars to the sub-national level using ASAP remote sensing derived phenology.
ASAP Water Satisfaction Index - Technical Manual of WSI version 3.0
This document describes the Water Satisfaction Index model.
Climate summary report in 2018
Summary of climate variability and extremes and their main impacts on agricultural production in 2018.
Global near real-time 500 m 10 d FPAR dataset from MODIS and VIIRS for operational agricultural monitoring and crop yield forecasting
Seguini, L., Klisch, A., Meroni, M., Vrieling, A., Manfron, G., Atzberger, C., Rembold, F., 2026. Earth System Science Data, 18 (1), 309-331
From Rows to Yields: How Foundation Models for Tabular Data Simplify Crop Yield Prediction
Sabo, F., Meroni, M., Piles, M., Claverie, M., Ven Den Berg, E., Collevignarelli, F., Rembold, F., 2026. ARXIV
A new global hybrid map of annual herbaceous cropland at a 500 m resolution for the year 2019
Fritz, S., Lesiv, M., See, L., Schepaschenko, D., Pérez Guzmán, K., Laso Bayas, J.C., Schepaschenko, M., Georgieva, I., Collivignarelli, F., Meroni, M., Kerdiles, H., Rembold, F., McCallum, I., 2024. Environ. Res. Lett., 19 (2024) 084025
Increasing the prospective capacity of global crop and rangeland monitoring with phenology tailored seasonal precipitation forecasts
Meroni M., Vojnović P., Zampieri M., Materia S., Rembold F., Kipkogei O., Toreti A., 2024. Climate Services, 33, 100434
New Functionalities and Regional/National Use Cases of the Anomaly Hotspots of Agricultural Production (ASAP) Platform
Rembold F., Meroni M., Otieno V., Kipkogei O., Mwangi K., de Sousa Afonso J.M., Ihadua I.M.T.J., José A.E.A., Zoungrana L.E., Taieb A.H., Urbano F., Dimou M., Kerdiles H., Vojnović P., Zampieri M., Toreti A., 2023. Remote Sensing, 15, (17), 4284
Is deeper always better? Evaluating deep learning models for yield forecasting with small data
Szabo, F, Meroni, M., Waldner, F., Rembold, F., 2023. Environm. Monit. Asses, 1095:1153
Yield forecasting with machine learning and small data: what gains for grains?
Meroni, M., Waldner, F., Seguini, L., Kerdiles, H., Rembold, F., 2021. Agricultural and Forest Meteorology, 308-309, 108555
Integrating multiple land cover maps through a multi-criteria analysis to improve agricultural monitoring in Africa
Pérez-Hoyos A., Udías A., Rembold F., 2020. International Journal of Applied Earth Observation and Geoinformation, 88, 102064.
ASAP: A new global early warning system to detect anomaly hot spots of agricultural production for food security analysis
Rembold F., Meroni M., Urbano F., Csak G., Kerdiles H., Perez-Hoyos A., Lemoine G., Leo O., Thierry N., 2018. Agricultural Systems, 168, 247-257.
Comparison of Global Land Cover Datasets for Cropland Monitoring
Pérez-Hoyos A., Rembold F., Kerdiles H., Gallego J., 2017. Remote Sensing, 9 (11), 1118
ASAP - Anomaly hot Spots of Agricultural Production, a new early warning decision support system developed by the Joint Research Centre
Rembold F., Meroni M., Urbano F., Lemoine G., Kerdiles H., Perez-Hoyos A., Csak G., 2017. Proceedings of the 9th International Workshop on the Analysis of Multitemporal remote Sensing Images (MultiTemp), 27-29 June 2017, Bruges - Belgium
Evaluation of the Standardized Precipitation Index as an early predictor of seasonal vegetation production anomalies in the Sahel
Meroni M., Rembold F., Fasbender D., Vrieling A., 2016. Remote Sensing Letters, 8(4), 301-310
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