{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,18]],"date-time":"2026-01-18T21:16:34Z","timestamp":1768770994275,"version":"3.49.0"},"reference-count":59,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2023,11,30]],"date-time":"2023-11-30T00:00:00Z","timestamp":1701302400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The monitoring of crop phenology informs decisions in environmental and agricultural management at both global and farm scales. Current methodologies for crop monitoring using remote sensing data track crop growth stages over time based on single, scalar vegetative indices (e.g., NDVI). Crop growth and senescence are indistinguishable when using scalar indices without additional information (e.g., planting date). By using a pair of normalized difference (ND) metrics derived from hyperspectral data\u2014one primarily sensitive to chlorophyll concentration and the other primarily sensitive to water content\u2014it is possible to track crop characteristics based on the spectral changes only. In a two-dimensional plot of the metrics (ND-space), bare soil, full canopy, and senesced vegetation data all plot in separate, distinct locations regardless of the year. The path traced in the ND-space over the growing season repeats from year to year, with variations that can be related to weather patterns. Senescence follows a return path that is distinct from the growth path.<\/jats:p>","DOI":"10.3390\/rs15235565","type":"journal-article","created":{"date-parts":[[2023,11,30]],"date-time":"2023-11-30T09:37:54Z","timestamp":1701337074000},"page":"5565","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Full-Season Crop Phenology Monitoring Using Two-Dimensional Normalized Difference Pairs"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4761-6094","authenticated-orcid":false,"given":"Louis","family":"Longchamps","sequence":"first","affiliation":[{"name":"School of Integrative Plant Science, Cornell University, Ithaca, NY 14853, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5283-4774","authenticated-orcid":false,"given":"William","family":"Philpot","sequence":"additional","affiliation":[{"name":"School of Civil and Environmental Engineering, Cornell University, Ithaca, NY 14853, USA"}]}],"member":"1968","published-online":{"date-parts":[[2023,11,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1038\/nature13052","article-title":"A Green Illusion","volume":"506","author":"Soudani","year":"2014","journal-title":"Nature"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"111960","DOI":"10.1016\/j.rse.2020.111960","article-title":"Remote Sensing Phenological Monitoring Framework to Characterize Corn and Soybean Physiological Growing Stages","volume":"248","author":"Diao","year":"2020","journal-title":"Remote Sens. 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