{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T17:48:51Z","timestamp":1780595331723,"version":"3.54.1"},"reference-count":61,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2015,4,27]],"date-time":"2015-04-27T00:00:00Z","timestamp":1430092800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministry of Education, Culture, Sports, Science and Technology, Japan"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Timely and nondestructive monitoring of leaf area index (LAI) using remote sensing techniques is crucial for precise and efficient management of crops. In this paper, a new spectral index (SI) for estimating LAI of winter wheat (Triticum aestivum L.) is proposed on the basis of field hyperspectral measurements. A simple index based on the empirical relationships between LAIs and SIs of all available two-waveband combinations from hyperspectral data is developed by considering the difference between reflectance values at 760 and 739 nm (DSIR760\u2013R739 = R760 \u2013 R739). Among published and newly developed SIs, DSIR760\u2013R739 exhibited a significant and strong linear relationship with LAI and showed outstanding performance in LAI assessments. The permissible bandwidths for broad-band DSIR760\u2013R739 investigated using simulated reflectance were 5 nm for both 760 and 739 nm center wavelengths. The results indicate that the linear regression model based on the narrow-band and broad-band DSIR760\u2013R739 is a simple but accurate method for timely and nondestructive monitoring of LAI.<\/jats:p>","DOI":"10.3390\/rs70505329","type":"journal-article","created":{"date-parts":[[2015,4,27]],"date-time":"2015-04-27T12:16:51Z","timestamp":1430137011000},"page":"5329-5346","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":58,"title":["Spectral Index for Quantifying Leaf Area Index of Winter Wheat by Field Hyperspectral Measurements: A Case Study in Gifu Prefecture, Central Japan"],"prefix":"10.3390","volume":"7","author":[{"given":"Shinya","family":"Tanaka","sequence":"first","affiliation":[{"name":"Department of Forest Management, Forestry and Forest Products Research Institute, 1 Matsunosato, Tsukuba, Ibaraki 305-8687, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2824-1266","authenticated-orcid":false,"given":"Kensuke","family":"Kawamura","sequence":"additional","affiliation":[{"name":"Graduate School for International Development and Cooperation, Hiroshima University,  1-5-1 Kagamiyama, Higashi-Hiroshima 739-8529, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Masayasu","family":"Maki","sequence":"additional","affiliation":[{"name":"Faculty of Engineering, Tohoku Institute of Technology, 35-1, YagiyamaKasumi-cho, Taihaku-ku, Sendai, Miyagi 982-8577, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yasunori","family":"Muramoto","sequence":"additional","affiliation":[{"name":"Gifu Prefectural Agricultural Technology Center, 729-1 Matamaru, Gifu 501-1152, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kazuaki","family":"Yoshida","sequence":"additional","affiliation":[{"name":"Gifu Region Agriculture and Forestry Office, 5-14-53 YabutaMinami, Gifu 500-8384, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tsuyoshi","family":"Akiyama","sequence":"additional","affiliation":[{"name":"River Basin Research Center, Gifu University, 1-1 Yanagido, Gifu 501-1193, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2015,4,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1395","DOI":"10.1016\/j.rse.2007.05.023","article-title":"Assimilation of leaf area index derived from ASAR and MERIS data into CERES-Wheat model to map wheat yield","volume":"112","author":"Dente","year":"2008","journal-title":"Remote Sens. 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