{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T05:28:19Z","timestamp":1785475699044,"version":"3.56.0"},"reference-count":52,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2021,12,30]],"date-time":"2021-12-30T00:00:00Z","timestamp":1640822400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002301","name":"Estonian Research Council","doi-asserted-by":"publisher","award":["PUT1049"],"award-info":[{"award-number":["PUT1049"]}],"id":[{"id":"10.13039\/501100002301","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002301","name":"Estonian Research Council","doi-asserted-by":"publisher","award":["PUT PRG302"],"award-info":[{"award-number":["PUT PRG302"]}],"id":[{"id":"10.13039\/501100002301","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This study investigated the potential to predict primary production in benthic ecosystems using meteorological variables and spectral indices. In situ production experiments were carried out during the vegetation season of 2020, wherein the primary production and spectral reflectance of different communities of submerged aquatic vegetation (SAV) were measured and chlorophyll (Chl a+b) concentration was quantified in the laboratory. The reflectance of SAV was measured both in air and underwater. First, in situ reflectance spectra of each SAV class were used to calculate different spectral indices, and then the indices were correlated with Chl a+b. Indices using red and blue band combinations such as 650\/450 and 650\/480 nm explained the largest part of variability in Chl a+b for datasets measured in air and underwater. Subsequently, the best-performing indices were used in boosted regression trees (BRT) models, together with meteorological data to predict the community photosynthesis of different SAV classes. The predictive power (R2) of production models were very high, estimated at the range of 0.82\u20130.87. The variable contributing the most to the model description was SAV class, followed in most cases by the water temperature. Nevertheless, the inclusion of spectral indices significantly improved BRT models, often by over 20%, and surprisingly their contribution mostly exceeded that of photosynthetically active radiation.<\/jats:p>","DOI":"10.3390\/rs14010158","type":"journal-article","created":{"date-parts":[[2021,12,30]],"date-time":"2021-12-30T23:29:07Z","timestamp":1640906947000},"page":"158","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["A Model-Based Assessment of Canopy-Scale Primary Productivity for the Baltic Sea Benthic Vegetation Using Environmental Variables and Spectral Indices"],"prefix":"10.3390","volume":"14","author":[{"given":"Ele","family":"Vahtm\u00e4e","sequence":"first","affiliation":[{"name":"Estonian Marine Institute, University of Tartu, M\u00e4ealuse 14, 12618 Tallinn, Estonia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jonne","family":"Kotta","sequence":"additional","affiliation":[{"name":"Estonian Marine Institute, University of Tartu, M\u00e4ealuse 14, 12618 Tallinn, Estonia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Laura","family":"Argus","sequence":"additional","affiliation":[{"name":"Estonian Marine Institute, University of Tartu, M\u00e4ealuse 14, 12618 Tallinn, Estonia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mihkel","family":"Kotta","sequence":"additional","affiliation":[{"name":"Estonian Marine Institute, University of Tartu, M\u00e4ealuse 14, 12618 Tallinn, Estonia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ilmar","family":"Kotta","sequence":"additional","affiliation":[{"name":"Estonian Marine Institute, University of Tartu, M\u00e4ealuse 14, 12618 Tallinn, Estonia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9679-1422","authenticated-orcid":false,"given":"Tiit","family":"Kutser","sequence":"additional","affiliation":[{"name":"Estonian Marine Institute, University of Tartu, M\u00e4ealuse 14, 12618 Tallinn, Estonia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,12,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"711","DOI":"10.1029\/96GB01667","article-title":"Change in net primary production and heterotrophic respiration: How much is necessary to sustain the terrestrial carbon sink?","volume":"10","author":"Thompson","year":"1996","journal-title":"Glob. Biogeochem. Cycles"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1126\/science.281.5374.237","article-title":"Primary Production of the Biosphere: Integrating Terrestrial and Oceanic Components","volume":"281","author":"Field","year":"1998","journal-title":"Science"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Williams, P.J.L., Thomas, D.N., and Reynolds, C.S. (2002). Phytoplankton Productivity: Carbon Assimilation in Marine and Freshwater Ecosystems. Phytoplankton Productivity: Carbon Assimilation in Marine and Freshwater Ecosystems, Blackwell.","DOI":"10.1002\/9780470995204"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"834","DOI":"10.1177\/0309133313507944","article-title":"Optical remote sensing of terrestrial ecosystem primary productivity","volume":"37","author":"Song","year":"2013","journal-title":"Prog. Phys. Geogr. Earth Environ."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"G04015","DOI":"10.1029\/2006JG000162","article-title":"On the use of MODIS EVI to assess gross primary productivity of North American ecosystems","volume":"111","author":"Sims","year":"2006","journal-title":"J. Geophys. Res. Space Phys."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"303","DOI":"10.3390\/rs4010303","article-title":"Exploring Simple Algorithms for Estimating Gross Primary Production in Forested Areas from Satellite Data","volume":"4","author":"Hashimoto","year":"2012","journal-title":"Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"D08S11","DOI":"10.1029\/2005JD006017","article-title":"Relationship between gross primary production and chlorophyll content in crops: Implications for the synoptic monitoring of vegetation productivity","volume":"111","author":"Gitelson","year":"2006","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1633","DOI":"10.1016\/j.rse.2007.08.004","article-title":"A new model of gross primary productivity for North American ecosystems based solely on the enhanced vegetation index and land surface temperature from MODIS","volume":"112","author":"Sims","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1015","DOI":"10.1016\/j.agrformet.2008.12.007","article-title":"Remote estimation of gross primary production in wheat using chlorophyll-related vegetation indices","volume":"149","author":"Wu","year":"2009","journal-title":"Agric. For. Meteorol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1081","DOI":"10.1016\/j.rse.2010.12.013","article-title":"Exploring the potential of MODIS EVI for modeling gross primary production across African ecosystems","volume":"115","author":"Arneth","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1016\/j.rse.2012.08.005","article-title":"Modeling GPP in the Nordic forest landscape with MODIS time series data\u2014Comparison with the MODIS GPP product","volume":"126","author":"Schubert","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"747","DOI":"10.2307\/2401901","article-title":"Solar Radiation and Productivity in Tropical Ecosystems","volume":"9","author":"Monteith","year":"1972","journal-title":"J. Appl. Ecol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"411","DOI":"10.1016\/j.scitotenv.2007.11.007","article-title":"The use of remote sensing in light use efficiency based models of gross primary production: A review of current status and future requirements","volume":"404","author":"Hilker","year":"2008","journal-title":"Sci. Total Environ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"D12127","DOI":"10.1029\/2009JD013023","article-title":"Gross primary production estimation from MODIS data with vegetation index and photosynthetically active radiation in maize","volume":"115","author":"Wu","year":"2010","journal-title":"J. Geophys. Res. Space Phys."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2565","DOI":"10.5194\/bg-9-2565-2012","article-title":"Remote sensing-based estimation of gross primary production in a subalpine grassland","volume":"9","author":"Rossini","year":"2012","journal-title":"Biogeosciences"},{"key":"ref_16","first-page":"L17403","article-title":"New developments in the remote estimation of the fraction of absorbed photosynthetically active radiation in crops","volume":"32","author":"Gitelson","year":"2005","journal-title":"Geophys. Res. Lett."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1080\/2150704X.2018.1547445","article-title":"Remote estimation of fraction of radiation absorbed by photosynthetically active vegetation: Generic algorithm for maize and soybean","volume":"10","author":"Gitelson","year":"2018","journal-title":"Remote Sens. Lett."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/0034-4257(92)90059-S","article-title":"A narrow-waveband spectral index that tracks diurnal changes in photosynthetic efficiency","volume":"41","author":"Gamon","year":"1992","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"492","DOI":"10.1007\/s004420050337","article-title":"The photochemical reflectance index: An optical indicator of photosynthetic radiation use efficiency across species, functional types, and nutrient levels","volume":"112","author":"Gamon","year":"1997","journal-title":"Oecologia"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1111\/j.1469-8137.1995.tb03064.x","article-title":"Assessment of photosynthetic radiation-use efficiency with spectral reflectance","volume":"131","author":"Penuelas","year":"1995","journal-title":"New Phytol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1016\/j.rse.2007.04.011","article-title":"Normalized difference spectral indices for estimating photosynthetic efficiency and capacity at a canopy scale derived from hyperspectral and CO2 flux measurements in rice","volume":"112","author":"Inoue","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1016\/j.rse.2010.08.023","article-title":"The photochemical reflectance index (PRI) and the remote sensing of leaf, canopy and ecosystem radiation use efficiencies: A review and meta-analysis","volume":"115","author":"Garbulsky","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"497","DOI":"10.4319\/lo.2003.48.1_part_2.0497","article-title":"Modeling spectral discrimination of Great Barrier Reef benthic communities by remote sensing instruments","volume":"48","author":"Kutser","year":"2003","journal-title":"Limnol. Oceanogr."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"521","DOI":"10.1016\/j.ecss.2005.12.004","article-title":"Assessing suitability of multispectral satellites for mapping benthic macroalgal cover in turbid coastal waters by means of model simulations","volume":"67","author":"Kutser","year":"2006","journal-title":"Estuarine Coast. Shelf Sci."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"51","DOI":"10.3354\/meps159051","article-title":"Measurement of seagrass standing crop using satellite and digital airborne remote sensing","volume":"159","author":"Mumby","year":"1997","journal-title":"Mar. Ecol. Prog. Ser."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"444","DOI":"10.4319\/lo.2003.48.1_part_2.0444","article-title":"Ocean color remote sensing of seagrass and bathymetry in the Bahamas Banks by high-resolution airborne imagery","volume":"48","author":"Dierssen","year":"2003","journal-title":"Limnol. Oceanogr."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"3413","DOI":"10.1016\/j.rse.2007.09.017","article-title":"Mapping seagrass species, cover and biomass in shallow waters: An assessment of satellite multi-spectral and airborne hyper-spectral imaging systems in Moreton Bay (Australia)","volume":"112","author":"Phinn","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"18","DOI":"10.5721\/EuJRS20134602","article-title":"Mapping Seagrass from Space: Addressing the Complexity of Seagrass LAI Mapping","volume":"46","author":"Wicaksono","year":"2013","journal-title":"Eur. J. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"5047","DOI":"10.1080\/01431160701258062","article-title":"Mapping the distribution of coral reefs and associated sublittoral habitats in Pacific Panama: A comparison of optical satellite sensors and classification methodologies","volume":"28","author":"Benfield","year":"2007","journal-title":"Int. J. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1016\/j.ecss.2011.07.008","article-title":"Mapping benthic macroalgal communities in the coastal zone using CHRIS-PROBA mode 2 images","volume":"94","author":"Casal","year":"2011","journal-title":"Estuarine Coast. Shelf Sci."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"2451","DOI":"10.3390\/rs5052451","article-title":"Classifying the Baltic Sea Shallow Water Habitats Using Image-Based and Spectral Library Methods","volume":"5","author":"Kutser","year":"2013","journal-title":"Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1467","DOI":"10.1007\/s12237-013-9764-3","article-title":"Evaluating Light Availability, Seagrass Biomass, and Productivity Using Hyperspectral Airborne Remote Sensing in Saint Joseph\u2019s Bay, Florida","volume":"37","author":"Hill","year":"2014","journal-title":"Estuaries Coasts"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1007\/s003380000117","article-title":"Scaling-up carbon and carbonate metabolism of coral reefs using in-situ data and remote sensing","volume":"19","author":"Payri","year":"2001","journal-title":"Coral Reefs"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"123","DOI":"10.3354\/meps312123","article-title":"Northern Florida reef tract benthic metabolism scaled by remote sensing","volume":"312","author":"Brock","year":"2006","journal-title":"Mar. Ecol. Prog. Ser."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Toro-Farmer, G., Muller-Karger, F.E., Vega-Rodr\u00edguez, M., Melo, N., Yates, K., Cerdeira-Estrada, S., and Herwitz, S.R. (2016). Characterization of Available Light for Seagrass and Patch Reef Productivity in Sugarloaf Key, Lower Florida Keys. Remote Sens., 8.","DOI":"10.3390\/rs8020086"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1007\/s00338-007-0289-8","article-title":"Coral reef benthic productivity based on optical absorptance and light-use efficiency","volume":"27","author":"Hochberg","year":"2007","journal-title":"Coral Reefs"},{"key":"ref_37","first-page":"016504","article-title":"How much benthic information can be retrieved with hyperspectral sensor from the optically complex coastal waters?","volume":"14","author":"Paavel","year":"2020","journal-title":"J. Appl. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1689","DOI":"10.4319\/lo.1994.39.7.1689","article-title":"Diffuse reflectance of oceanic shallow waters: Influence of water depth and bottom albedo","volume":"39","author":"Maritorena","year":"1994","journal-title":"Limnol. Oceanogr."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"7442","DOI":"10.1364\/AO.38.007442","article-title":"Estimation of the remote-sensing reflectance from above-surface measurements","volume":"38","author":"Mobley","year":"1999","journal-title":"Appl. Opt."},{"key":"ref_40","first-page":"5716","article-title":"Predicting macroalgal pigments (chlorophyll a, chlorophyll b, chlorophyll a + b, carotenoids) in various environmental conditions using high-resolution hyperspectral spectroradiometers","volume":"39","author":"Kotta","year":"2017","journal-title":"Int. J. Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"350","DOI":"10.1016\/0076-6879(87)48036-1","article-title":"Chlorophylls and Carotenoids: Pigments of Photosynthetic Biomembranes","volume":"148","author":"Lichtenthaler","year":"1987","journal-title":"Methods Enzymol."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1111\/j.2006.0906-7590.04596.x","article-title":"Novel methods improve prediction of species\u2019 distributions from occurrence data","volume":"29","author":"Elith","year":"2006","journal-title":"Ecography"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"267","DOI":"10.3354\/meps321267","article-title":"Variation in demersal fish species richness in the oceans surrounding New Zealand: An analysis using boosted regression trees","volume":"321","author":"Leathwick","year":"2006","journal-title":"Mar. Ecol. Prog. Ser."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"802","DOI":"10.1111\/j.1365-2656.2008.01390.x","article-title":"A working guide to boosted regression trees","volume":"77","author":"Elith","year":"2008","journal-title":"J. Anim. Ecol."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Hastie, T., Tibshirani, R., and Friedman, J. (2009). The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Springer. [2nd ed.].","DOI":"10.1007\/978-0-387-84858-7"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"421","DOI":"10.32614\/RJ-2017-016","article-title":"pdp: An R Package for Constructing Partial Dependence Plots","volume":"9","author":"Greenwell","year":"2017","journal-title":"R J."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"073590","DOI":"10.1117\/1.JRS.7.073590","article-title":"Spectral index development for mapping live coral cover","volume":"7","author":"Joyce","year":"2013","journal-title":"J. Appl. Remote Sens."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Vahtm\u00e4e, E., Kutser, T., and Paavel, B. (2020). Performance and Applicability of Water Column Correction Models in Optically Complex Coastal Waters. Remote Sens., 12.","DOI":"10.3390\/rs12111861"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"5843","DOI":"10.1080\/01431160902744837","article-title":"Mapping coloured dissolved organic matter concentration in coastal waters","volume":"30","author":"Kutser","year":"2009","journal-title":"Int. J. Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"2722","DOI":"10.4319\/lo.2006.51.6.2722","article-title":"Community photosynthesis of aquatic macrophytes","volume":"51","author":"Binzer","year":"2006","journal-title":"Limnol. Oceanogr."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1007\/BF00387606","article-title":"Photosynthetic rates of benthic marine algae in relation to light intensity and seasonal variations","volume":"37","author":"King","year":"1976","journal-title":"Mar. Biol."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"259","DOI":"10.2216\/i0031-8884-37-4-259.1","article-title":"Seasonal variation in the pigment content and photosynthesis of different thallus regions of Ascophyllum nodosum (Fucales, Phaeophyta) in relation to position in the canopy","volume":"37","author":"Stengel","year":"1998","journal-title":"Phycologia"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/1\/158\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:56:20Z","timestamp":1760169380000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/1\/158"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,30]]},"references-count":52,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2022,1]]}},"alternative-id":["rs14010158"],"URL":"https:\/\/doi.org\/10.3390\/rs14010158","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,12,30]]}}}