{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T21:15:13Z","timestamp":1773868513582,"version":"3.50.1"},"reference-count":123,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2022,1,6]],"date-time":"2022-01-06T00:00:00Z","timestamp":1641427200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Funds for Distinguished Young Youths","award":["No. 42025101"],"award-info":[{"award-number":["No. 42025101"]}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["No. 31770516"],"award-info":[{"award-number":["No. 31770516"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100013314","name":"111 Project","doi-asserted-by":"publisher","award":["No. B18006"],"award-info":[{"award-number":["No. B18006"]}],"id":[{"id":"10.13039\/501100013314","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Accurately identifying the phenology of summer maize is crucial for both cultivar breeding and fertilizer controlling in precision agriculture. In this study, daily RGB images covering the entire growth of summer maize were collected using phenocams at sites in Shangqiu (2018, 2019 and 2020) and Nanpi (2020) in China. Four phenological dates, including six leaves, booting, heading and maturity of summer maize, were pre-defined and extracted from the phenocam-based images. The spectral indices, textural indices and integrated spectral and textural indices were calculated using the improved adaptive feature-weighting method. The double logistic function, harmonic analysis of time series, Savitzky\u2013Golay and spline interpolation were applied to filter these indices and pre-defined phenology was identified and compared with the ground observations. The results show that the DLF achieved the highest accuracy, with the coefficient of determination (R2) and the root-mean-square error (RMSE) being 0.86 and 9.32 days, respectively. The new index performed better than the single usage of spectral and textural indices, of which the R2 and RMSE were 0.92 and 9.38 days, respectively. The phenological extraction using the new index and double logistic function based on the PhenoCam data was effective and convenient, obtaining high accuracy. Therefore, it is recommended the adoption of the new index by integrating the spectral and textural indices for extracting maize phenology using PhenoCam data.<\/jats:p>","DOI":"10.3390\/rs14020244","type":"journal-article","created":{"date-parts":[[2022,1,9]],"date-time":"2022-01-09T23:08:26Z","timestamp":1641769706000},"page":"244","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":28,"title":["Comparison of Multi-Methods for Identifying Maize Phenology Using PhenoCams"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0099-0759","authenticated-orcid":false,"given":"Yahui","family":"Guo","sequence":"first","affiliation":[{"name":"College of Water Sciences, Beijing Normal University, Beijing 100875, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shouzhi","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Water Sciences, Beijing Normal University, Beijing 100875, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9761-5292","authenticated-orcid":false,"given":"Yongshuo H.","family":"Fu","sequence":"additional","affiliation":[{"name":"College of Water Sciences, Beijing Normal University, Beijing 100875, China"},{"name":"Department of Biology, Antwerp University, 2000 Antwerp, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yi","family":"Xiao","sequence":"additional","affiliation":[{"name":"College of Water Sciences, Beijing Normal University, Beijing 100875, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenxiang","family":"Wu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4130-6981","authenticated-orcid":false,"given":"Hanxi","family":"Wang","sequence":"additional","affiliation":[{"name":"Heilongjiang Province Key Laboratory of Geographical Environment Monitoring and Spatial Information Service in Cold Regions, Heilongjiang Province Collaborative Innovation Center of Cold Region Ecological Safety, School of Geographical Sciences, Harbin Normal University, Harbin 150025, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9244-3292","authenticated-orcid":false,"given":"Kirsten de","family":"Beurs","sequence":"additional","affiliation":[{"name":"Department of Geography and Environmental Sustainability, The University of Oklahoma, 100 East Boyd Street, Norman, OK 73019, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,1,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"014010","DOI":"10.1088\/1748-9326\/5\/1\/014010","article-title":"Robust negative impacts of climate change on African agriculture","volume":"5","author":"Schlenker","year":"2010","journal-title":"Environ. 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