{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,3]],"date-time":"2025-12-03T17:58:13Z","timestamp":1764784693494,"version":"build-2065373602"},"reference-count":32,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2021,7,6]],"date-time":"2021-07-06T00:00:00Z","timestamp":1625529600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Cattolica Assicurazioni","award":["N\/A"],"award-info":[{"award-number":["N\/A"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Insurance agents often provide crop hail damage estimates based on their personal experience and field samples, which are not always representative of the investigated field\u2019s spatial variability. For these reasons, farmers and the insurance market ask for a reliable, objective, and less labor-intensive method to determine crop hail losses. Integrating remote sensing and crop modeling provides a unique opportunity for the crop insurance market for a reliable, objective, and less labor-intensive method to estimate hail damage. To this end, a study was conducted on eight distinct maize fields for a total of 90 hectares. Five fields were damaged by the hailstorm that occurred on 13 July 2019 and three were not damaged. Soil and plant samples were collected to characterize the experimental areas. The Surface Energy Balance Algorithm for Land (SEBAL) was deployed to determine the total aboveground biomass and obtainable yield at harvest, using Landsat 7 and 8 satellite images. Modeled hail damages (HDDSSAT1, coupling SEBAL estimates of obtainable yield and DSSAT-based potential yield; HDDSSAT2, coupling yield map at harvest and the Decision Support System for Agrotechnology Transfer (DSSAT)-based potential yield) were calculated and compared to the estimates of the insurance company (HDinsurance). SEBAL-based biomass and yield estimates agreed with in-season measurements (\u22124% and +0.5%, respectively). While some under and overestimations were observed, HDinsurance and HDDSSAT1 averaged similar values (\u22124.9% and +3.4%) compared to the reference approach (HDDSSAT2).<\/jats:p>","DOI":"10.3390\/rs13142655","type":"journal-article","created":{"date-parts":[[2021,7,6]],"date-time":"2021-07-06T11:36:44Z","timestamp":1625571404000},"page":"2655","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Estimation of Hail Damage Using Crop Models and Remote Sensing"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1354-2023","authenticated-orcid":false,"given":"Stefano","family":"Gobbo","sequence":"first","affiliation":[{"name":"Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), Universit\u00e0 degli Studi di Padova, 35020 Legnaro, Italy"}]},{"given":"Alessandro","family":"Ghiraldini","sequence":"additional","affiliation":[{"name":"Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), Universit\u00e0 degli Studi di Padova, 35020 Legnaro, Italy"}]},{"given":"Andrea","family":"Dramis","sequence":"additional","affiliation":[{"name":"Societ\u00e0 Cattolica di Assicurazione, 37126 Verona, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7957-3212","authenticated-orcid":false,"given":"Nicola","family":"Dal Ferro","sequence":"additional","affiliation":[{"name":"Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), Universit\u00e0 degli Studi di Padova, 35020 Legnaro, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9081-868X","authenticated-orcid":false,"given":"Francesco","family":"Morari","sequence":"additional","affiliation":[{"name":"Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), Universit\u00e0 degli Studi di Padova, 35020 Legnaro, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2021,7,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"268","DOI":"10.1016\/j.atmosres.2013.11.012","article-title":"Hail occurrence in Italy: Towards a national database and climatology","volume":"138","author":"Baldi","year":"2014","journal-title":"Atmos. Res."},{"key":"ref_2","unstructured":"Politeo, M. (2008). I Danni da Grandine Sulle Colture Agrarie del Veneto dal 1990 al 2004. [Ph.D. Thesis, University of Padua]."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1002\/qj.3197","article-title":"The severe hailstorm in southwest Germany on 28 July 2013: Characteristics, impacts and meteorological conditions","volume":"144","author":"Kunz","year":"2018","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1633","DOI":"10.1002\/joc.1199","article-title":"A hail climatology of the greater Sydney area and New South Wales, Australia","volume":"25","author":"Schuster","year":"2005","journal-title":"Int. J. Climatol. A J. R. Meteorol. Soc."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1007\/s10584-009-9597-z","article-title":"Increasing major hail losses in the US","volume":"96","author":"Changnon","year":"2009","journal-title":"Clim. Chang."},{"key":"ref_6","first-page":"177","article-title":"Simulation of hail effects on crop yield losses for corn-belt states in USA","volume":"28","author":"Wang","year":"2012","journal-title":"Trans. Chin. Soc. Agric. Eng."},{"key":"ref_7","unstructured":"Young, F.R., Apan, A., and Chandler, O. (2004, January 7\u201310). Crop hail damage: Insurance loss assessment using remote sensing. Proceedings of the Annual Conference of the Remote Sensing and Photogrammetry Society, Aberdeen, UK."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"449","DOI":"10.1175\/JAMC-D-10-05012.1","article-title":"Hail in northeast Italy: Climatology and bivariate analysis with the sounding-derived indices","volume":"51","author":"Manzato","year":"2012","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1625","DOI":"10.1007\/s11069-014-1161-0","article-title":"A new physically based stochastic event catalog for hail in Europe","volume":"73","author":"Punge","year":"2014","journal-title":"Nat. Hazards"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"3939","DOI":"10.1002\/2014JD022959","article-title":"Development and application of a logistic model to estimate the past and future hail potential in Germany","volume":"120","author":"Mohr","year":"2015","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"338","DOI":"10.1175\/1520-0450(1973)012<0338:AGDOTH>2.0.CO;2","article-title":"A general description of the hail problem in the Po Valley of northern Italy","volume":"12","author":"Morgan","year":"1973","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_12","first-page":"1","article-title":"The effect of injury in imitation of hail damage on the development of the maize plant","volume":"16","author":"Eldredge","year":"1935","journal-title":"Iowa Agric. Home Econ. Exp. Stn. Res. Bull."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"585","DOI":"10.2134\/agronj1986.00021962007800040006x","article-title":"Yield Loss Due to Simulated Hail Damage on Corn: A Comparison of Actual and Predicted Values","volume":"78","author":"Shapiro","year":"1986","journal-title":"Agron. J."},{"key":"ref_14","unstructured":"Vorst, J.J. (1991). Assessing Hail Damage to Corn, Iowa State University Extension."},{"key":"ref_15","unstructured":"Towery, N.G., Eyton, J.R., Changnon, S.A., and Dailey, C.L. (1975). Remote Sensing of Crop Hail Damage, Illinois State Water Survey."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"717","DOI":"10.14358\/PERS.70.6.717","article-title":"Using remote sensing to assess stand loss and defoliation in maize","volume":"70","author":"Erickson","year":"2004","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_17","first-page":"1349","article-title":"Use of remotely sensed data for assessing crop hail damage","volume":"66","author":"Peters","year":"2000","journal-title":"PE&RS, Photogramm. Eng. Remote Sens."},{"key":"ref_18","first-page":"101","article-title":"Detection and mapping of hail damage to corn using domestic remotely sensed data in China","volume":"6","author":"Zhao","year":"2012","journal-title":"Aust. J. Crop Sci."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"406","DOI":"10.1016\/j.compag.2016.06.019","article-title":"Aerial multispectral imaging for crop hail damage assessment in potato","volume":"127","author":"Zhou","year":"2016","journal-title":"Comput. Electron. Agric."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"10888","DOI":"10.3390\/rs61110888","article-title":"The potential and uptake of remote sensing in insurance: A review","volume":"6","author":"Vrieling","year":"2014","journal-title":"Remote Sens."},{"key":"ref_21","unstructured":"Ministero delle Politiche Agricole e Forestali (1999). Metodi ufficiali di analisi chimica del suolo. Decreto Ministeriale 13 settembre 1999. Supplemento Ordinario Alla Gazzetta Ufficiale n\u00b0248 del 21 Ottobre 1999, Ministero delle Politiche Agricole e Forestali."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1030","DOI":"10.1007\/s11119-018-09632-8","article-title":"Protocol for automating error removal from yield maps","volume":"20","author":"Vega","year":"2019","journal-title":"Precis. Agric."},{"key":"ref_23","unstructured":"Nicoli, L. (2019). Procedure per la Stima dei Danni da Avversit\u00e0 Atmosferiche, Veneto Agricoltura."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1016\/S0022-1694(98)00253-4","article-title":"A remote sensing surface energy balance algorithm for land (SEBAL). 1. Formulation","volume":"212","author":"Bastiaanssen","year":"1998","journal-title":"J. Hydrol."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"675","DOI":"10.1109\/36.581987","article-title":"Second simulation of the satellite signal in the solar spectrum, 6S: An overview","volume":"35","author":"Vermote","year":"1997","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Grosso, C., Manoli, G., Martello, M., Chemin, Y.H., Pons, D.H., Teatini, P., Piccoli, I., and Morari, F. (2018). Mapping maize evapotranspiration at field scale using SEBAL: A comparison with the FAO method and soil-plant model simulations. Remote Sens., 10.","DOI":"10.3390\/rs10091452"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Gobbo, S., Lo Presti, S., Martello, M., Panunzi, L., Berti, A., and Morari, F. (2019). Integrating SEBAL with in-Field Crop Water Status Measurement for Precision Irrigation Applications\u2014A Case Study. Remote Sens., 11.","DOI":"10.3390\/rs11172069"},{"key":"ref_28","unstructured":"Jones, C.A. (1986). CERES-Maize: A Simulation Model of Maize Growth and Development (No. 04; SB91. M2, J6.), Texas A&M University Press."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1016\/S1161-0301(02)00107-7","article-title":"The DSSAT cropping system model","volume":"18","author":"Jones","year":"2003","journal-title":"Eur. J. Agron."},{"key":"ref_30","unstructured":"Hoogenboom, G., Jones, J., Wilkens, P., Porter, C., Boote, K., Hunt, L.D., Singh, U., Lizaso, J.I., White, J.M., and Uryasev, O. (2010). Decision Support System for Agrotechnology Transfer (DSSAT) Version 4.5, Honolulu University."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1016\/j.agwat.2007.02.002","article-title":"SEBAL for detecting spatial variation of water productivity and scope for improvement in eight irrigated wheat systems","volume":"89","author":"Zwart","year":"2007","journal-title":"Agric. Water Manag."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"2163","DOI":"10.2134\/agronj14.0102","article-title":"Spatiotemporal response of maize yield to edaphic and meteorological conditions in a saline farmland","volume":"106","author":"Scudiero","year":"2014","journal-title":"Agron. J."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/14\/2655\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:26:42Z","timestamp":1760164002000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/14\/2655"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,6]]},"references-count":32,"journal-issue":{"issue":"14","published-online":{"date-parts":[[2021,7]]}},"alternative-id":["rs13142655"],"URL":"https:\/\/doi.org\/10.3390\/rs13142655","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2021,7,6]]}}}