{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T18:46:22Z","timestamp":1775760382846,"version":"3.50.1"},"reference-count":58,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2021,5,9]],"date-time":"2021-05-09T00:00:00Z","timestamp":1620518400000},"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>Agricultural runoff transports sediments and nutrients that deteriorate water quality erratically, posing a challenge to ground-based monitoring. Satellites provide data at spatial-temporal scales that can be used for water quality monitoring. PlanetScope nanosatellites have spatial (3 m) and temporal (daily) resolutions that may help improve water quality monitoring compared to coarser-resolution satellites. This work compared PlanetScope to Landsat-8 and Sentinel-2 in their ability to detect key water quality parameters. Spectral bands of each satellite were regressed against chlorophyll a, turbidity, and Secchi depth data from 13 reservoirs in Oklahoma over three years (2017\u20132020). We developed significant regression models for each satellite. Landsat-8 and Sentinel-2 explained more variation in chlorophyll a than PlanetScope, likely because they have more spectral bands. PlanetScope and Sentinel-2 explained relatively similar amounts of variations in turbidity and Secchi Disk data, while Landsat-8 explained less variation in these parameters. Since PlanetScope is a commercial satellite, its application may be limited to cases where the application of coarser-resolution satellites is not feasible. We identified scenarios where PS may be more beneficial than Landsat-8 and Sentinel-2. These include measuring water quality parameters that vary daily, in small ponds and narrow coves of reservoirs, and at reservoir edges.<\/jats:p>","DOI":"10.3390\/rs13091847","type":"journal-article","created":{"date-parts":[[2021,5,10]],"date-time":"2021-05-10T02:54:58Z","timestamp":1620615298000},"page":"1847","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":81,"title":["Comparing PlanetScope to Landsat-8 and Sentinel-2 for Sensing Water Quality in Reservoirs in Agricultural Watersheds"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1600-5837","authenticated-orcid":false,"given":"Abubakarr S.","family":"Mansaray","sequence":"first","affiliation":[{"name":"Oklahoma Water Resources Center, Division of Agricultural Sciences and Natural Resources, Ferguson College of Agriculture, Oklahoma State University, Stillwater, OK 74078, USA"}]},{"given":"Andrew R.","family":"Dzialowski","sequence":"additional","affiliation":[{"name":"Department of Integrative Biology, Oklahoma State University, Stillwater, OK 74078, USA"}]},{"given":"Meghan E.","family":"Martin","sequence":"additional","affiliation":[{"name":"Environmental Science Graduate Program, Oklahoma State University, Stillwater, OK 74078, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9307-2799","authenticated-orcid":false,"given":"Kevin L.","family":"Wagner","sequence":"additional","affiliation":[{"name":"Oklahoma Water Resources Center, Division of Agricultural Sciences and Natural Resources, Ferguson College of Agriculture, Oklahoma State University, Stillwater, OK 74078, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4770-7893","authenticated-orcid":false,"given":"Hamed","family":"Gholizadeh","sequence":"additional","affiliation":[{"name":"Department of Geography, Oklahoma State University, Stillwater, OK 74078, USA"}]},{"given":"Scott H.","family":"Stoodley","sequence":"additional","affiliation":[{"name":"Environmental Science Graduate Program, Oklahoma State University, Stillwater, OK 74078, USA"}]}],"member":"1968","published-online":{"date-parts":[[2021,5,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1080\/10641260091129198","article-title":"Effects of Sedimentation and Turbidity on Lotic Food Webs: A Concise Review for Natural Resource Managers","volume":"8","author":"Henley","year":"2010","journal-title":"Rev. Fish. Sci."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1016\/S0269-7491(02)00304-4","article-title":"N:P ratios, light limitation, and cyanobacterial dominance in a subtropical lake impacted by non-point source nutrient pollution","volume":"122","author":"Havens","year":"2003","journal-title":"Env. Pol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1016\/j.watres.2018.01.040","article-title":"Mechanisms driving phosphorus release during algal blooms based on hourly changes in iron and phosphorus concentrations in sediments","volume":"133","author":"Chen","year":"2018","journal-title":"Water Res."},{"key":"ref_4","first-page":"117","article-title":"Regional Scale Monitoring of Indicators of Trophic Conditions of Lakes","volume":"31","author":"Larsen","year":"1995","journal-title":"JAWRA"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Urquhart, N.S., Paulsen, S.G., and Larsen, D.P. (1998). Monitoring for policy-relevant regional trends over time. Ecol. Appl.","DOI":"10.2307\/2641064"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Rodr\u00edguez, J.P., Beard, T.D., Bennett, E.M., Cumming, G.S., Cork, S.J., Agard, J., Dobson, A.P., and Peterson, G.D. (2006). Trade-offs across space, time, and ecosystem services. Ecol. Soc., 11.","DOI":"10.5751\/ES-01667-110128"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1016\/j.rse.2014.11.017","article-title":"Satellite-based water quality monitoring for improved spatial and temporal retrieval of chlorophyll-a in coastal waters","volume":"158","author":"Harvey","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_8","first-page":"111","article-title":"Remote Sensing for Regional Lake Water Quality Assessment: Capabilities and Limitations of Current and Upcoming Satellite Systems","volume":"Volume 33","author":"Olmanson","year":"2015","journal-title":"The Handbook of Environmental Chemistry"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1016\/S0034-4257(97)00106-5","article-title":"Comparison of NIR\/RED ratio and first derivative of reflectance in estimating algal-chlorophyll concentration: A case study in a turbid reservoir","volume":"62","author":"Han","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"394","DOI":"10.1016\/j.rse.2011.10.016","article-title":"Normalized difference chlorophyll index: A novel model for remote estimation of chlorophyll-a concentration in turbid productive waters","volume":"117","author":"Mishra","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"238","DOI":"10.1016\/j.rse.2005.04.020","article-title":"Identifying optimal spectral bands from in situ measurements of Great Lakes coastal wetlands using second-derivative analysis","volume":"97","author":"Becker","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"523","DOI":"10.1364\/JOSAA.34.000523","article-title":"Transformation of a high-dimensional color space for material classification","volume":"34","author":"Liu","year":"2017","journal-title":"J. Opt. Soc. Am. A"},{"key":"ref_13","first-page":"667","article-title":"Testing utility of Landsat 8 for remote assessment of water quality in two subtropical African reservoirs with contrasting trophic states","volume":"33","author":"Mhosisi","year":"2017","journal-title":"Geocarto Int."},{"key":"ref_14","unstructured":"USEPA (2021, January 13). World Health Organization (WHO) 1999 Guideline Values for Cyanobacteria in Freshwater, Available online: https:\/\/www.epa.gov\/cyanohabs\/world-health-organization-who-1999-guideline-values-cyanobacteria-freshwater."},{"key":"ref_15","unstructured":"Botting, C. (2015). Introductory Digital Image Processing\u2014A Remote Sensing Perspective, Pearson Education Inc.. [4th ed.]."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"845","DOI":"10.1109\/LGRS.2009.2026657","article-title":"Satellite Estimation of Chlorophyll-a Concentration Using the Red and NIR Bands of MERIS\u2014The Azov Sea Case Study","volume":"6","author":"Moses","year":"2009","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1016\/j.rse.2013.03.024","article-title":"Remote sensing of chlorophyll-a as a measure of cyanobacterial biomass in Lake Bogoria, a hypertrophic, saline\u2013alkaline, flamingo lake, using Landsat ETM+","volume":"135","author":"Tebbs","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2428","DOI":"10.1016\/j.watres.2011.02.002","article-title":"NIR-red reflectance-based algorithms for chlorophyll-a estimation in mesotrophic inland and coastal waters: Lake Kinneret case study","volume":"45","author":"Yacobi","year":"2011","journal-title":"Water Res."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"559","DOI":"10.3394\/0380-1330(2008)34[559:MCCIWL]2.0.CO;2","article-title":"Mapping Chlorophyll-a Concentrations in West Lake, China using Landsat 7 ETM+","volume":"34","author":"Torbick","year":"2008","journal-title":"Great Lakes Res."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"7607","DOI":"10.1080\/01431161.2013.822602","article-title":"Mapping inland lake water quality across the Lower Peninsula of Michigan using Landsat TM imagery","volume":"34","author":"Torbick","year":"2013","journal-title":"Int. J. Remote Sens."},{"key":"ref_21","first-page":"158","article-title":"Atmospheric correction assessment of SPOT-6 image and its influence on models to estimate water column transparency in tropical reservoir","volume":"4","author":"Rotta","year":"2016","journal-title":"Remote Sens. Appl. Soc. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1057","DOI":"10.1080\/014311699212849","article-title":"Use of satellite imagery to estimate surface chlorophyll-a and Secchi disc depth of Bull Shoals Reservoir, Arkansas, USA","volume":"20","author":"Allee","year":"1999","journal-title":"Int. J. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Olmanson, L.G., Brezonik, P.L., Finlay, J.C., and Bauer, M.E. (2016). Comparison of Landsat 8 and Landsat 7 for regional measurements of CDOM and water clarity in lakes. Remote Sens. Environ.","DOI":"10.1016\/j.rse.2016.01.007"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Nguyen, U.N.T., Pham, L.T.H., and Dang, T.D. (2019). An automatic water detection approach using Landsat 8 OLI and Google Earth Engine cloud computing to map lakes and reservoirs in New Zealand. Environ. Monit. Assess., 191.","DOI":"10.1007\/s10661-019-7355-x"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Ansper, A., and Alikas, K. (2019). Retrieval of Chlorophyll a from Sentinel-2 MSI Data for the European Union Water Framework Directive Reporting Purposes. Remote Sens., 11.","DOI":"10.3390\/rs11010064"},{"key":"ref_26","unstructured":"ESA (2021, January 14). Sentinel-2. Available online: https:\/\/sentinel.esa.int\/web\/sentinel\/missions\/sentinel-2."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Poursanidis, D., Traganos, D., Chrysoulakis, N., and Reinartz, P. (2019). Cubesats Allow High Spatiotemporal Estimates of Satellite-Derived Bathymetry. Remote Sens., 11.","DOI":"10.3390\/rs11111299"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"2381","DOI":"10.3390\/rs12152381","article-title":"Physics-based Bathymetry and Water Quality Retrieval Using PlanetScope Imagery: Impacts of 2020 COVID-19 Lockdown and 2019 Extreme Flood in the Venice Lagoon","volume":"12","author":"Milad","year":"2020","journal-title":"Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"5739","DOI":"10.1080\/01431161.2018.1506951","article-title":"Assessment of PlanetScope images for benthic habitat and seagrass species mapping in a complex optically shallow water environment","volume":"39","author":"Pramaditya","year":"2018","journal-title":"Int. J. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Gabr, B., Ahmed, M., and Marmoush, Y. (2020). PlanetScope and Landsat 8 Imageries for Bathymetry Mapping. J. Mar. Sci. Eng., 8.","DOI":"10.3390\/jmse8020143"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1016\/j.rse.2019.01.023","article-title":"Performance of Landsat-8 and Sentinel-2 surface reflectance products for river remote sensing retrievals of chlorophyll-a and turbidity","volume":"224","author":"Kuhn","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"106876","DOI":"10.1016\/j.ecolind.2020.106876","article-title":"Improved red-edge chlorophyll-a detection for Sentinel 2","volume":"120","author":"Bramich","year":"2021","journal-title":"Ecol. Indic."},{"key":"ref_33","unstructured":"OWRB (2021, February 13). Water Facts, Available online: https:\/\/www.owrb.ok.gov\/util\/waterfact.php."},{"key":"ref_34","unstructured":"OWRB (2021, February 12). Data & Maps\u2014Surface Water, Available online: http:\/\/www.owrb.ok.gov\/maps\/PMG\/owrbdata_SW.html."},{"key":"ref_35","unstructured":"Williams, K.W. (2007). Farm Ponds. The Encyclopedia of Oklahoma History and Culture, Oklahoma Historical Society."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1139\/juvs-2019-0020","article-title":"Generation of geolocated and radiometrically corrected true reflectance surfaces in the visible portion of the electromagnetic spectrum over large bodies of water using images from a sUAS","volume":"8","author":"Arango","year":"2020","journal-title":"J. Unmanned Veh. Syst."},{"key":"ref_37","unstructured":"OWRB (2021, February 12). Lakes, Oklahoma Water Resources Board, Available online: https:\/\/www.owrb.ok.gov\/quality\/monitoring\/bumplakes.php."},{"key":"ref_38","unstructured":"OWRB (2017). Oklahoma Lakes Report\u2014Benificial Use Monitoring Program."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/S0034-4257(02)00022-6","article-title":"A procedure for regional lake water clarity assessment using Landsat multispectral data","volume":"82","author":"Kloiber","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_40","unstructured":"OWRB (2021, February 01). Standard Operating Procedure for the Collection and Processing of Chlorophyll-a Samplesin Lakes, Available online: https:\/\/www.owrb.ok.gov\/quality\/monitoring\/bump\/pdf_bump\/Lakes\/SOPs\/Chlorophyll-aCollectionSOP.pdf."},{"key":"ref_41","unstructured":"OWRB (2005). Standard Operating Procedure for the Measurement of Turbidity in Lakes."},{"key":"ref_42","unstructured":"Planet (2021, February 10). Planet Imagery Product Specifications. Available online: https:\/\/www.planet.com\/products\/planet-imagery\/."},{"key":"ref_43","unstructured":"USGS (2021, January 15). Earth Explorer, Available online: https:\/\/earthexplorer.usgs.gov\/."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1016\/j.rse.2012.03.006","article-title":"Combining lake and watershed characteristics with Landsat TM data for remote estimation of regional lake clarity","volume":"123","author":"McCullough","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Kirk, T.O. (2011). Light and Photosynthesis in Aquatic Ecosystems, Cambridge University Press. [3rd ed.].","DOI":"10.1017\/CBO9781139168212"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Salem, S.I., Higa, H., Kim, H., Kobayashi, H., Oki, K., and Oki, T. (2017). Assessment of Chlorophyll-a Algorithms Considering Different Trophic Statuses and Optimal Bands. Sensors, 17.","DOI":"10.3390\/s17081746"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"3380","DOI":"10.1039\/c1em10608b","article-title":"Iron-rich Oklahoma Clays as a Natural Source of Chromium in Monitoring Wells","volume":"13","author":"Scott","year":"2011","journal-title":"J. Environ. Monit."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/j.rse.2014.04.031","article-title":"Distinguishing surface cyanobacterial blooms and aquatic macrophytes using Landsat\/TM and ETM+ shortwave infrared bands","volume":"157","author":"Oyama","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_49","unstructured":"Minitab (2021, February 02). Minitab 19. Available online: https:\/\/www.minitab.com\/en-us\/."},{"key":"ref_50","first-page":"1089","article-title":"No Unbiased Estimator of the Variance of K-Fold Cross-Validation","volume":"5","author":"Bengio","year":"2004","journal-title":"J. Mach. Learn. Res."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Nagel, G.W., de Moraes Novo, E.M.L., and Kampel, M. (2020). Nanosatellites applied to optical Earth observation: A review. Ambiente \u00c1gua Interdiscip. J. Appl. Sci.","DOI":"10.4136\/ambi-agua.2513"},{"key":"ref_52","first-page":"243","article-title":"Monitoring water turbidity and surface suspended sediment concentration of the Bagre Reservoir (Burkina Faso) using MODIS and field reflectance data","volume":"52","author":"Robert","year":"2016","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_53","unstructured":"Rounds, S. (2021, March 02). Estimation of Secchi Depth from Turbidity Data in the Willamette River at Portland, OR (14211720), Available online: https:\/\/or.water.usgs.gov\/will_morrison\/secchi_depth_model.html."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Gitelson, A., Gurlin, D., Moses, W.J., and Barrow, T. (2009). A bio-optical algorithm for the remote estimation of the chlorophyll-a concentration in case 2 waters. Environ. Res. Lett., 4.","DOI":"10.1088\/1748-9326\/4\/4\/045003"},{"key":"ref_55","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":"2019","author":"Claverie","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Houborg, R., and McCabe, M.F. (2018). Daily Retrieval of NDVI and LAI at 3 m Resolution via the Fusion of CubeSat, Landsat, and MODIS Data. Remote Sens., 10.","DOI":"10.3390\/rs10060890"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1016\/j.rse.2018.02.067","article-title":"A Cubesat enabled Spatio-Temporal Enhancement Method (CESTEM) utilizing Planet, Landsat and MODIS data","volume":"209","author":"Houborg","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Yan, L., Roy, D.P., Zhang, H., Li, J., and Huang, H. (2016). An Automated Approach for Sub-Pixel Registration of Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) Imagery. Remote Sens., 8.","DOI":"10.3390\/rs8060520"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/9\/1847\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:58:29Z","timestamp":1760162309000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/9\/1847"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,5,9]]},"references-count":58,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2021,5]]}},"alternative-id":["rs13091847"],"URL":"https:\/\/doi.org\/10.3390\/rs13091847","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,5,9]]}}}