{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T07:37:41Z","timestamp":1775029061951,"version":"3.50.1"},"reference-count":39,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T00:00:00Z","timestamp":1651017600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ohio Department of Natural Resources","award":["N18B 315-11"],"award-info":[{"award-number":["N18B 315-11"]}]},{"name":"Ohio Department of Natural Resources","award":["SC0022191, DE-SC0021067"],"award-info":[{"award-number":["SC0022191, DE-SC0021067"]}]},{"name":"Ohio Department of Natural Resources","award":["G16AP00076"],"award-info":[{"award-number":["G16AP00076"]}]},{"name":"Ohio Department of Natural Resources","award":["7880"],"award-info":[{"award-number":["7880"]}]},{"DOI":"10.13039\/100000015","name":"United States Department of Energy","doi-asserted-by":"publisher","award":["N18B 315-11"],"award-info":[{"award-number":["N18B 315-11"]}],"id":[{"id":"10.13039\/100000015","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000015","name":"United States Department of Energy","doi-asserted-by":"publisher","award":["SC0022191, DE-SC0021067"],"award-info":[{"award-number":["SC0022191, DE-SC0021067"]}],"id":[{"id":"10.13039\/100000015","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000015","name":"United States Department of Energy","doi-asserted-by":"publisher","award":["G16AP00076"],"award-info":[{"award-number":["G16AP00076"]}],"id":[{"id":"10.13039\/100000015","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000015","name":"United States Department of Energy","doi-asserted-by":"publisher","award":["7880"],"award-info":[{"award-number":["7880"]}],"id":[{"id":"10.13039\/100000015","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Ohio Water Resources Center","award":["N18B 315-11"],"award-info":[{"award-number":["N18B 315-11"]}]},{"name":"Ohio Water Resources Center","award":["SC0022191, DE-SC0021067"],"award-info":[{"award-number":["SC0022191, DE-SC0021067"]}]},{"name":"Ohio Water Resources Center","award":["G16AP00076"],"award-info":[{"award-number":["G16AP00076"]}]},{"name":"Ohio Water Resources Center","award":["7880"],"award-info":[{"award-number":["7880"]}]},{"name":"Ohio Water Development Authority","award":["N18B 315-11"],"award-info":[{"award-number":["N18B 315-11"]}]},{"name":"Ohio Water Development Authority","award":["SC0022191, DE-SC0021067"],"award-info":[{"award-number":["SC0022191, DE-SC0021067"]}]},{"name":"Ohio Water Development Authority","award":["G16AP00076"],"award-info":[{"award-number":["G16AP00076"]}]},{"name":"Ohio Water Development Authority","award":["7880"],"award-info":[{"award-number":["7880"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Natural wetlands are intrinsically heterogeneous and typically composed of a mosaic of ecosystem patches with different vegetation types. Hydrological and biogeochemical processes in wetlands vary strongly among these ecosystem patches. To date, most remote sensing classification approaches for wetland vegetation either rely on coarse images that cannot capture the spatial variability of wetland vegetation or rely on very-high-resolution multi-spectral images that are detailed but very sporadic in time (less than once per year). This study aimed to use NDVI time series, generated from NASA\u2019s HLS dataset, to classify vegetation patches. We demonstrate our approach at a temperate, coastal lake, estuarine marsh. To classify vegetation patches, a standard time series library of the four land-cover patch types was built from referencing specific locations that were identified as \u201cpure\u201d pixels. These were identified using a single-time high-resolution image. We calculated the distance between the HLS-NDVI time series at each pixel and the \u201cpure\u201d-pixel standards for each land-cover type. The resulting true-positive classified rate was &gt;73% for all patch types other than water lily. The classification accuracy was higher in pixels of a more uniform composition. A set of vegetation maps was created for the years 2016 to 2020 at our research site to identify the vegetation changes at the site as it is affected by rapid water elevation increases in Lake Erie. Our results reveal how changes in water elevation have changed the patch distribution in significant ways, leading to the local extinction of cattail by 2019 and a continuous increase in the area cover of water lily patches.<\/jats:p>","DOI":"10.3390\/rs14092107","type":"journal-article","created":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T22:20:20Z","timestamp":1651098020000},"page":"2107","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":37,"title":["Classification of Wetland Vegetation Based on NDVI Time Series from the HLS Dataset"],"prefix":"10.3390","volume":"14","author":[{"given":"Yang","family":"Ju","sequence":"first","affiliation":[{"name":"Environmental Science Graduate Program, Ohio State University, Columbus, OH 43210, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9209-9540","authenticated-orcid":false,"given":"Gil","family":"Bohrer","sequence":"additional","affiliation":[{"name":"Department of Civil, Environmental & Geodetic Engineering, Ohio State University, Columbus, OH 43210, USA"}]}],"member":"1968","published-online":{"date-parts":[[2022,4,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"406","DOI":"10.1016\/j.ecoleng.2017.08.040","article-title":"Solving Lake Erie\u2019s harmful algal blooms by restoring the Great Black Swamp in Ohio","volume":"108","author":"Mitsch","year":"2017","journal-title":"Ecol. Eng."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Guntenspergen, G.R., Stearns, F., and Kadlec, J. (2020). Wetland vegetation. Constructed Wetlands for Wastewater Treatment, CRC Press.","DOI":"10.1201\/9781003069850-6"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1002\/rrr.3450010303","article-title":"Hydraulic effects of aquatic weeds in UK rivers","volume":"1","author":"Watson","year":"1987","journal-title":"Regul. Rivers Res. Manag."},{"key":"ref_4","unstructured":"Boto, K.K., and Patrick, J. (1979). Role of wetlands in the removal of suspended sediments. Wetland Functions and Values: The State of Our Understanding, American Water Resources Association."},{"key":"ref_5","unstructured":"Heliotis, F.D. (1981). Wetland Systems for Wastewater Treatment: Operating Mechanisms and Implications for Design, University of Wisconsin-Madison."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"933","DOI":"10.1016\/S1001-0742(08)62364-5","article-title":"Agricultural non-point nitrogen pollution control function of different vegetation types in riparian wetlands: A case study in the Yellow River wetland in China","volume":"21","author":"Zhao","year":"2009","journal-title":"J. Environ. Sci."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"387","DOI":"10.1111\/j.1365-2427.2009.02288.x","article-title":"Effects of vegetation state on biodiversity and nitrogen retention in created wetlands: A test of the biodiversity-ecosystem functioning hypothesis","volume":"55","author":"Weisner","year":"2010","journal-title":"Freshw. Biol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2607","DOI":"10.1175\/BAMS-D-18-0268.1","article-title":"FLUXNET-CH4 Synthesis Activity: Objectives, Observations, and Future Directions","volume":"100","author":"Knox","year":"2019","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1635","DOI":"10.1002\/lno.11467","article-title":"Plant-mediated methane transport in emergent and floating-leaved species of a temperate freshwater mineral-soil wetland","volume":"65","author":"Villa","year":"2020","journal-title":"Limnol. Oceanogr."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1016\/j.ecoleng.2010.07.022","article-title":"Methane emissions from freshwater riverine wetlands","volume":"37","author":"Sha","year":"2011","journal-title":"Ecol. Eng."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1016\/j.ecoleng.2017.06.042","article-title":"Determining total emissions and environmental drivers of methane flux in a Lake Erie estuarine marsh","volume":"114","author":"Morin","year":"2018","journal-title":"Ecol. Eng."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1016\/j.rse.2006.06.006","article-title":"Mapping salt-marsh vegetation by multispectral and hyperspectral remote sensing","volume":"105","author":"Belluco","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2911","DOI":"10.1080\/01431160119174","article-title":"Vegetation mapping of a tropical freshwater swamp in the Northern Territory, Australia: A comparison of aerial photography, Landsat TM and SPOT satellite imagery","volume":"22","author":"Harvey","year":"2001","journal-title":"Int. J. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"3719","DOI":"10.1080\/014311697216577","article-title":"A comparison of Landsat Thematic Mapper and SPOT multi-spectral imagery for the classification of shrub and meadow vegetation in northern California, USA","volume":"18","author":"May","year":"1997","journal-title":"Int. J. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1016\/j.rse.2006.11.002","article-title":"Mapping an invasive plant, Phragmites australis, in coastal wetlands using the EO-1 Hyperion hyperspectral sensor","volume":"108","author":"Pengra","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"5169","DOI":"10.1080\/01431160500218770","article-title":"Mapping marshland vegetation of San Francisco Bay, California, using hyperspectral data","volume":"26","author":"Rosso","year":"2005","journal-title":"Int. J. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1016\/S0034-4257(02)00196-7","article-title":"Spectral discrimination of vegetation types in a coastal wetland","volume":"85","author":"Schmidt","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1007\/s11273-009-9169-z","article-title":"Multispectral and hyperspectral remote sensing for identification and mapping of wetland vegetation: A review","volume":"18","author":"Adam","year":"2010","journal-title":"Wetl. Ecol. Manag."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"612","DOI":"10.1016\/j.isprsjprs.2009.04.004","article-title":"Spectral discrimination of papyrus vegetation (Cyperus papyrus L.) in swamp wetlands using field spectrometry","volume":"64","author":"Adam","year":"2009","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2170","DOI":"10.1016\/j.jenvman.2007.06.028","article-title":"Building spectral libraries for wetlands land cover classification and hyperspectral remote sensing","volume":"90","author":"Zomer","year":"2009","journal-title":"J. Environ. Manag."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"317","DOI":"10.1016\/S0304-3770(97)00043-0","article-title":"Airborne remote sensing of macrophytes in Cefni Reservoir, Anglesey, UK","volume":"58","author":"Malthus","year":"1997","journal-title":"Aquat. Bot."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1005","DOI":"10.1016\/S1872-2032(06)60019-X","article-title":"Identification of the spectral characteristics of submerged plant Vallisneria spiralis","volume":"26","author":"Yuan","year":"2006","journal-title":"Acta Ecol. Sin."},{"key":"ref_23","unstructured":"Steven, M.D., and Clark, J.A. (1990). 2\u2014Optical properties of vegetation canopies. Applications of Remote Sensing in Agriculture, Butterworth-Heinemann."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"4698","DOI":"10.1080\/01431161.2014.919685","article-title":"Mapping freshwater marsh species distributions using WorldView-2 high-resolution multispectral satellite imagery","volume":"35","author":"Carle","year":"2014","journal-title":"Int. J. Remote Sens."},{"key":"ref_25","first-page":"204","article-title":"Analyzing fine-scale wetland composition using high resolution imagery and texture features","volume":"23","author":"Szantoi","year":"2013","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"559","DOI":"10.1016\/j.rse.2006.10.007","article-title":"Mapping mixed vegetation communities in salt marshes using airborne spectral data","volume":"107","author":"Wang","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2753","DOI":"10.5194\/essd-13-2753-2021","article-title":"GLC_FCS30: Global land-cover product with fine classification system at 30 m using time series Landsat imagery","volume":"13","author":"Zhang","year":"2021","journal-title":"Earth Syst. Sci. Data"},{"key":"ref_28","first-page":"16327","article-title":"An approach for land cover classification system by using NDVI data in arid and semiarid region","volume":"60","author":"Arastoo","year":"2013","journal-title":"Elixir Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.isprsjprs.2013.03.007","article-title":"Spectral discrimination of giant reed (Arundo donax L.): A seasonal study in riparian areas","volume":"80","author":"Fernandes","year":"2013","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1016\/j.ecss.2006.04.016","article-title":"Multi-seasonal spectral characteristics analysis of coastal salt marsh vegetation in Shanghai, China","volume":"69","author":"Gao","year":"2006","journal-title":"Estuar. Coast. Shelf Sci."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Ouyang, Z.T., Gao, Y., Xie, X., Guo, H.Q., Zhang, T.T., and Zhao, B. (2013). Spectral Discrimination of the Invasive Plant Spartina alterniflora at Multiple Phenological Stages in a Saltmarsh Wetland. PLoS ONE, 8.","DOI":"10.1371\/journal.pone.0067315"},{"key":"ref_32","first-page":"27","article-title":"Classification mapping and species identification of salt marshes based on a short-time interval NDVI time series from HJ-1 optical imagery","volume":"45","author":"Sun","year":"2016","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_33","unstructured":"Bohrer, G., and Kerns, J. (2018). AmeriFlux BASE US-OWC Old Woman Creek, AmeriFlux AMP."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/j.rse.2018.09.002","article-title":"The Harmonized Landsat and Sentinel-2 surface reflectance data set","volume":"219","author":"Claverie","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_35","unstructured":"Karasiak, N. (2019). Dzetsaka: v3.4.3 (Version v3.4.3), Zenodo."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1109\/TASSP.1978.1163055","article-title":"Dynamic programming algorithm optimization for spoken word recognition","volume":"26","author":"Sakoe","year":"1978","journal-title":"IEEE Trans. Acoust. Speech Signal Process."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"3729","DOI":"10.1109\/JSTARS.2016.2517118","article-title":"A time-weighted dynamic time warping method for land-use and land-cover mapping","volume":"9","author":"Maus","year":"2016","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"046509","DOI":"10.1117\/1.JRS.13.046509","article-title":"Decomposition of mixed pixels in MODIS data using Bernstein basis functions","volume":"13","author":"Qin","year":"2019","journal-title":"J. Appl. Remote Sens."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.rse.2014.03.034","article-title":"Incorporating spatial information in spectral unmixing: A review","volume":"149","author":"Shi","year":"2014","journal-title":"Remote Sens. Environ."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/9\/2107\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T23:02:14Z","timestamp":1760137334000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/9\/2107"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,4,27]]},"references-count":39,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2022,5]]}},"alternative-id":["rs14092107"],"URL":"https:\/\/doi.org\/10.3390\/rs14092107","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,4,27]]}}}