乐胖代购免代理版

{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,7]],"date-time":"2025-05-07T04:19:03Z","timestamp":1746591543001,"version":"3.37.3"},"reference-count":25,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2020,11,28]],"date-time":"2020-11-28T00:00:00Z","timestamp":1606521600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003981","name":"Agenzia Spaziale Italiana","doi-asserted-by":"publisher","award":["2019-5-HH.0"],"id":[{"id":"10.13039\/501100003981","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"This study introduces a first assessment of the capabilities of PRISMA (PRecursore IperSpettrale della Missione Applicativa)\u2014the new hyperspectral satellite sensor of the Italian Space Agency (ASI)\u2014for Non-Photosynthetic Vegetation (NPV) monitoring, a topic which is becoming very relevant in the field of sustainable agriculture, being an indicator of crop residue (CR) presence in the field. Data-sets collected during the mission validation phase in croplands are used for mapping the NPV presence and for modelling the diagnostic absorption band of cellulose around 2.1 \u03bcm with an Exponential Gaussian Optimization approach, in the perspective of the prediction of the abundance of crop residues. Results proved that PRISMA data are suitable for these tasks, and call for further investigation to achieve quantitative estimates of specific biophysical variables, also in the framework of other hyperspectral missions.<\/jats:p>","DOI":"10.3390\/rs12233903","type":"journal-article","created":{"date-parts":[[2020,11,30]],"date-time":"2020-11-30T02:00:57Z","timestamp":1606701657000},"page":"3903","source":"Crossref","is-referenced-by-count":46,"title":["Detection and Classification of Non-Photosynthetic Vegetation from PRISMA Hyperspectral Data in Croplands"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5473-1050","authenticated-orcid":false,"given":"Monica","family":"Pepe","sequence":"first","affiliation":[{"name":"Institute for Electromagnetic Sensing of the Environment, National Research Council of Italy, via Bassini 15, 20133 Milano, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3217-7575","authenticated-orcid":false,"given":"Loredana","family":"Pompilio","sequence":"additional","affiliation":[{"name":"Institute for Electromagnetic Sensing of the Environment, National Research Council of Italy, via Bassini 15, 20133 Milano, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7631-2623","authenticated-orcid":false,"given":"Beniamino","family":"Gioli","sequence":"additional","affiliation":[{"name":"Institute of Bioeconomy, National Research Council of Italy, via Madonna del Piano, 10-50019 Sesto Fiorentino, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9634-6038","authenticated-orcid":false,"given":"Lorenzo","family":"Busetto","sequence":"additional","affiliation":[{"name":"Institute for Electromagnetic Sensing of the Environment, National Research Council of Italy, via Bassini 15, 20133 Milano, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2156-4166","authenticated-orcid":false,"given":"Mirco","family":"Boschetti","sequence":"additional","affiliation":[{"name":"Institute for Electromagnetic Sensing of the Environment, National Research Council of Italy, via Bassini 15, 20133 Milano, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2020,11,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"276","DOI":"10.1177\/0309133315582005","article-title":"Remote sensing of terrestrial non-photosynthetic vegetation using hyperspectral, multispectral, SAR, and LiDAR data","volume":"40","author":"Li","year":"2016","journal-title":"Prog. 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