Publications

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. Spatial rice yield estimation based on MODIS and Sentinel-1 SAR data and ORYZA crop growth model. Remote Sensing, (10), 2, https://doi.org/10.3390/rs10020293, 2018.

. Early season weed mapping in rice crops using multi-spectral UAV data. International Journal of Remote Sensing, pp. 1-21, https://doi.org/10.1080/01431161.2018.1441569, 2018.

. PhenoRice: A method for automatic extraction of spatio-temporal information on rice crops using satellite data time series. Remote Sensing of Environment, (194), pp. 347-365, https://doi.org/10.1016/j.rse.2017.03.029, 2017.

. Exploitation of SAR and optical sentinel data to detect rice crop and estimate seasonal dynamics of leaf area index. Remote Sensing, (9), 3, https://doi.org/10.3390/rs9030248, 2017.

. Estimating inter-annual variability in winter wheat sowing dates from satellite time series in Camargue, France. International Journal of Applied Earth Observation and Geoinformation, (57), pp. 190-201, https://doi.org/10.1016/j.jag.2017.01.001, 2017.

. Downstream Services for Rice Crop Monitoring in Europe: From Regional to Local Scale. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, (10), 12, pp. 5423-5441, https://doi.org/10.1109/JSTARS.2017.2679159, 2017.

. Conceptual architecture and service-oriented implementation of a regional geoportal for rice monitoring. ISPRS International Journal of Geo-Information, (6), 7, https://doi.org/10.3390/ijgi6070191, 2017.

. A weekly indicator of surface moisture status from satellite data for operational monitoring of crop conditions. Sensors (Switzerland), (17), 6, https://doi.org/10.3390/s17061338, 2017.

. Testing estimation of water surface in Italian rice district from MODIS satellite data. International Journal of Applied Earth Observation and Geoinformation, (52), pp. 284-295, https://doi.org/10.1016/j.jag.2016.06.018, 2016.

. Multitemporal monitoring of plant area index in the valencia rice district with PocketLAI. Remote Sensing, (8), 3, https://doi.org/10.3390/rs8030202, 2016.

. The fourth phase of the radiative transfer model intercomparison (RAMI) exercise: Actual canopy scenarios and conformity testing. Remote Sensing of Environment, (169), pp. 418-437, https://doi.org/10.1016/j.rse.2015.08.016, 2015.

. Rice monitoring using SAR and optical data in Northern Italy. International Geoscience and Remote Sensing Symposium (IGARSS), (2015-November), pp. 1527-1530, https://doi.org/10.1109/IGARSS.2015.7326071, 2015.

. Rapid assessment of crop status: An application of MODIS and SAR data to rice areas in Leyte, Philippines affected by Typhoon Haiyan. Remote Sensing, (7), 6, pp. 6535-6557, https://doi.org/10.3390/rs70606535, 2015.

. Models to predict the start of the airborne pollen season. International Journal of Biometeorology, (59), 7, pp. 837-848, https://doi.org/10.1007/s00484-014-0901-x, 2015.

. Intercomparison of instruments for measuring leaf area index over rice. International Geoscience and Remote Sensing Symposium (IGARSS), (2015-November), pp. 3389-3392, https://doi.org/10.1109/IGARSS.2015.7326546, 2015.

. Discriminating irrigated and rainfed maize with diurnal fluorescence and canopy temperature airborne maps. ISPRS International Journal of Geo-Information, (4), 2, pp. 626-646, https://doi.org/10.3390/ijgi4020626, 2015.

. Assimilating seasonality information derived from satellite data time series in crop modelling for rice yield estimation. International Geoscience and Remote Sensing Symposium (IGARSS), (2015-November), pp. 157-160, https://doi.org/10.1109/IGARSS.2015.7325723, 2015.

. Post-fire resilience in the Alpine region estimated from MODIS satellite multispectral data. International Journal of Applied Earth Observation and Geoinformation, (32), 1, pp. 163-172, 2014.

. Nitrogen status assessment for variable rate fertilization in maize through hyperspectral imagery. Remote Sensing, (6), 7, pp. 6549-6565, https://doi.org/10.3390/rs6076549, 2014.

. Fluorescence, PRI and canopy temperature for water stress detection in cereal crops. International Journal of Applied Earth Observation and Geoinformation, (30), 1, pp. 167-178, https://doi.org/10.1016/j.jag.2014.02.002, 2014.

. Continental-Scale Living Forest Biomass and Carbon Stock: A Robust Fuzzy Ensemble of IPCC Tier 1 Maps for Europe. IFIP Advances in Information and Communication Technology, (413), pp. 271-284, https://doi.org/10.1007/978-3-642-41151-9_26, 2013.

. Assessing canopy PRI from airborne imagery to map water stress in maize. ISPRS Journal of Photogrammetry and Remote Sensing, (86), pp. 168-177, https://doi.org/10.1016/j.isprsjprs.2013.10.002, 2013.

. Remote sensing-based estimation of gross primary production in a subalpine grassland. Biogeosciences, (9), 7, pp. 2565-2584, https://doi.org/10.5194/bg-9-2565-2012, 2012.

. Using digital repeat photography and eddy covariance data to model grassland phenology and photosynthetic CO2 uptake. Agricultural and Forest Meteorology, (151), 10, pp. 1325-1337, https://doi.org/10.1016/j.agrformet.2011.05.012, 2011.

. The hyperspectral irradiometer, a new instrument for long-term and unattended field spectroscopy measurements. Review of Scientific Instruments, (82), 4, https://doi.org/10.1063/1.3574360, 2011.

. SpecCal: Novel software for in-field spectral characterization of high-resolution spectrometers. Computers and Geosciences, (37), 10, pp. 1685-1691, https://doi.org/10.1016/j.cageo.2010.12.005, 2011.

. Phenological monitoring of grassland and larch in the Alps from Terra and Aqua MODIS images. Italian Journal of Remote Sensing / Rivista Italiana di Telerilevamento, (43), 3, pp. 83-96, https://doi.org/10.5721/ItJRS20114336, 2011.

. Remote sensing of larch phenological cycle and analysis of relationships with climate in the Alpine region. Global Change Biology, (16), 9, pp. 2504-2517, https://doi.org/10.1111/j.1365-2486.2010.02189.x, 2010.

. Performance of Spectral Fitting Methods for vegetation fluorescence quantification. Remote Sensing of Environment, (114), 2, pp. 363-374, https://doi.org/10.1016/j.rse.2009.09.010, 2010.

. High resolution field spectroscopy measurements for estimating gross ecosystem production in a rice field. Agricultural and Forest Meteorology, (150), 9, pp. 1283-1296, https://doi.org/10.1016/j.agrformet.2010.05.011, 2010.

. Chlorophyll concentration mapping with MIVIS data to assess crown discoloration in the Ticino park oak forest. International Journal of Remote Sensing, (31), 12, pp. 3307-3332, https://doi.org/10.1080/01431160903193497, 2010.

. Characterization of fine resolution field spectrometers using solar Fraunhofer lines and atmospheric absorption features. Applied Optics, (49), 15, pp. 2858-2871, https://doi.org/10.1364/AO.49.002858, 2010.

. On the spatial and temporal variability of Larch phenological cycle in mountainous areas [Analisi della variabilità spazio-temporale del ciclo fenologico del Larice in ambiente alpino]. Italian Journal of Remote Sensing / Rivista Italiana di Telerilevamento, (41), 2, pp. 79-96, 2009.

. Modeling gross primary production of agro-forestry ecosystems by assimilation of satellite-derived information in a process-based model. Sensors, (9), 2, pp. 922-942, https://doi.org/10.3390/s90200922, 2009.

. Mapping Mediterranean rangeland condition using MODIS NDVI time series. Proceedings, 33rd International Symposium on Remote Sensing of Environment, ISRSE 2009, pp. 115-118, 2009.

. Detection of water stress in maize with hyperspectral imagery. Proceedings, 33rd International Symposium on Remote Sensing of Environment, ISRSE 2009, pp. 1321-1324, 2009.

. European larch phenology in the Alps: Can we grasp the role of ecological factors by combining field observations and inverse modelling?. International Journal of Biometeorology, (52), 7, pp. 587-605, https://doi.org/10.1007/s00484-008-0152-9, 2008.

. Estimation of leaf and canopy water content in poplar plantations by means of hyperspectral indices and inverse modeling. Remote Sensing of Environment, (112), 4, pp. 1820-1834, https://doi.org/10.1016/j.rse.2007.09.005, 2008.

. A physically based method for chlorophyll estimation in forest canopies from MIVIS hyperspectral data [Un metodo fisicamente basato per la stima della clorofilla in canopy forestali da dati iperspettrali MIVIS]. Italian Journal of Remote Sensing / Rivista Italiana di Telerilevamento, (40), 3, pp. 3-15, 2008.

. Validation of global moderate-resolution LAI products: A framework proposed within the CEOS land product validation subgroup. IEEE Transactions on Geoscience and Remote Sensing, (44), 7, pp. 1804-1814, https://doi.org/10.1109/TGRS.2006.872529, 2006.

. Estimating canopy water content of poplar plantation from MIVIS data. AIP Conference Proceedings, (852), pp. 242-249, https://doi.org/10.1063/1.2349350, 2006.

. Monitoring paddy rice crops through remote sensing: Productivity estimation by light use efficiency model. Proceedings of SPIE - The International Society for Optical Engineering, (5568), pp. 46-56, https://doi.org/10.1117/12.568106, 2004.

. Use of semi-empirical and radiative transfer models to estimate biophysical parameters in a sparse canopy forest. Proceedings of SPIE - The International Society for Optical Engineering, (4879), pp. 133-144, https://doi.org/10.1117/12.463081, 2002.

. Airborne hyperspectral remote sensing applications in urban areas: Asbestos concrete sheeting identification and mapping. IEEE/ISPRS Joint Workshop on Remote Sensing and Data Fusion over Urban Areas, DFUA 2001, pp. 212-216, https://doi.org/10.1109/DFUA.2001.985882, 2001.