{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,11,19]],"date-time":"2024-11-19T18:10:00Z","timestamp":1732039800505},"reference-count":53,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2020,10,16]],"date-time":"2020-10-16T00:00:00Z","timestamp":1602806400000},"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":"We present a new remote sensing based method to estimate dissolved organic carbon (DOC) flux discharged from rivers into coastal waters off the Sarawak region in Borneo. This method comprises three steps. In the first step, we developed an algorithm for estimating DOC concentrations using the ratio of Landsat-8 Red to Green bands B4\/B3 (DOC (\u03bcM C) = 89.86 \u00b7e0.27\u00b7(B4\/B3)), which showed good correlation (R = 0.88) and low mean relative error (+5.71%) between measured and predicted DOC. In the second step, we used TRMM Multisatellite Precipitation Analysis (TMPA) precipitation data to estimate river discharge for the river basins. In the final step, DOC flux for each river catchment was then estimated by combining Landsat-8 derived DOC concentrations and TMPA derived river discharge. The analysis of remote sensing derived DOC flux (April 2013 to December 2018) shows that Sarawak coastal waters off the Rajang river basin, received the highest DOC flux (72% of total) with an average of 168 Gg C per year in our study area, has seasonal variability. The whole of Sarawak represents about 0.1% of the global annual riverine and estuarine DOC flux. The results presented in this study demonstrate the ability to estimate DOC flux using satellite remotely sensed observations.<\/jats:p>","DOI":"10.3390\/rs12203380","type":"journal-article","created":{"date-parts":[[2020,10,16]],"date-time":"2020-10-16T12:56:48Z","timestamp":1602853008000},"page":"3380","source":"Crossref","is-referenced-by-count":10,"title":["A New Remote Sensing Method to Estimate River to Ocean DOC Flux in Peatland Dominated Sarawak Coastal Regions, Borneo"],"prefix":"10.3390","volume":"12","author":[{"given":"Sim","family":"ChunHock","sequence":"first","affiliation":[{"name":"Faculty of Engineering, Computing and Science, Swinburne University of Technology, Kuching 93350, Sarawak, Malaysia"}]},{"given":"Nagur","family":"Cherukuru","sequence":"additional","affiliation":[{"name":"CSIRO Oceans and Atmosphere, Canberra ACT 2601, Australia"}]},{"given":"Aazani","family":"Mujahid","sequence":"additional","affiliation":[{"name":"Faculty of Resource Science & Technology, University Malaysia Sarawak, Kota Samarahan 94300, Sarawak, Malaysia"}]},{"given":"Patrick","family":"Martin","sequence":"additional","affiliation":[{"name":"Asian School of the Environment, Nanyang Technological University, Singapore 639798, Singapore"}]},{"given":"Nivedita","family":"Sanwlani","sequence":"additional","affiliation":[{"name":"Asian School of the Environment, Nanyang Technological University, Singapore 639798, Singapore"}]},{"given":"Thorsten","family":"Warneke","sequence":"additional","affiliation":[{"name":"Institute of Environmental Physics, University of Bremen, Otto-Hahn-Allee 1, 28359 Bremen, Germany"}]},{"given":"Tim","family":"Rixen","sequence":"additional","affiliation":[{"name":"Leibniz Center for Tropical Marine Research, Fahrenheitstr. 6, 28359 Bremen, Germany"},{"name":"Institute of Geology, University of Hamburg, 20146 Hamburg, Germany"}]},{"given":"Justus","family":"Notholt","sequence":"additional","affiliation":[{"name":"Institute of Environmental Physics, University of Bremen, Otto-Hahn-Allee 1, 28359 Bremen, Germany"}]},{"ORCID":"http:\/\/orcid.org\/0000-0001-8485-1598","authenticated-orcid":false,"given":"Moritz","family":"M\u00fcller","sequence":"additional","affiliation":[{"name":"Faculty of Engineering, Computing and Science, Swinburne University of Technology, Kuching 93350, Sarawak, Malaysia"}]}],"member":"1968","published-online":{"date-parts":[[2020,10,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1038\/26200","article-title":"Deep-ocean gradients in the concentration of dissolved organic carbon","volume":"395","author":"Hansell","year":"1998","journal-title":"Nature"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"170","DOI":"10.1016\/j.cosust.2012.03.003","article-title":"Spatial distribution of riverine DOC inputs to the ocean: An updated global synthesis","volume":"4","author":"Dai","year":"2012","journal-title":"Curr. Opin. Environ. Sustain."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1239","DOI":"10.1002\/2016JG003701","article-title":"Riverine carbon fluxes to the South China Sea","volume":"122","author":"Huang","year":"2017","journal-title":"J. Geophys. Res. Biogeosci."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"798","DOI":"10.1111\/j.1365-2486.2010.02279.x","article-title":"Global and regional importance of the tropical peatland carbon pool","volume":"17","author":"Page","year":"2011","journal-title":"Glob. Chang. Biol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/ncomms10155","article-title":"The impact of disturbed peatlands on river outgassing in Southeast Asia","volume":"6","author":"Wit","year":"2015","journal-title":"Nat. Commun."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"901","DOI":"10.5194\/bg-8-901-2011","article-title":"Fluvial organic carbon losses from a Bornean blackwater river","volume":"8","author":"Moore","year":"2011","journal-title":"Biogeosciences"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3389\/fmars.2017.00007","article-title":"Where Carbon Goes When Water Flows: Carbon Cycling across the Aquatic Continuum","volume":"4","author":"Ward","year":"2017","journal-title":"Front. Mar. Sci."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1223","DOI":"10.5194\/os-14-1223-2018","article-title":"An integrated open-coastal biogeochemistry, ecosystem and biodiversity observatory of the eastern Mediterranean\u2014The Cretan Sea component of the POSEIDON system","volume":"14","author":"Petihakis","year":"2018","journal-title":"Ocean Sci."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Palmer, S.C.J., Kutser, T., and Hunter, P.D. (2015). Remote sensing of inland waters: Challenges, progress and future directions. Remote Sens. Environ., 157.","DOI":"10.1016\/j.rse.2014.09.021"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"118","DOI":"10.5589\/m13-017","article-title":"Remote sensing of lake CDOM using noncontemporaneous field data","volume":"39","author":"Cardille","year":"2013","journal-title":"Can. J. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"3286","DOI":"10.1109\/TGRS.2012.2224117","article-title":"Inversion of chromophoric dissolved organic matter from EO-1 Hyperion imagery for turbid estuarine and coastal waters","volume":"51","author":"Zhu","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"496","DOI":"10.1002\/2014JC010241","article-title":"A new algorithm to retrieve chromophoric dissolved organic matter (CDOM) absorption spectra in the UV from ocean color","volume":"120","author":"Cao","year":"2014","journal-title":"J. Geophys. Res. Oceans"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1016\/j.rse.2014.04.033","article-title":"Factors affecting the measuement of CDOM by remote sensing of optically complex inland waters","volume":"157","author":"Brezonik","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"12478","DOI":"10.3390\/rs70912478","article-title":"Seasonal variation of colored dissolved organic matter in Baratarian Bay, Louisiana, using combined Landsat and field data","volume":"7","author":"Joshi","year":"2015","journal-title":"Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1016\/j.rse.2017.11.014","article-title":"Remote sensing retrievals of colored dissolved organic matter and dissolved organic carbon dynamics in North American estuaries and their margins","volume":"205","author":"Cao","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2201","DOI":"10.1109\/TGRS.2016.2638828","article-title":"Estimation of Colored Dissolved Organic Matter from Landsat-8 Imagery for Complex Inland Water: Case Study of Lake Huron","volume":"55","author":"Chen","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"514","DOI":"10.1029\/2018MS001363","article-title":"Modeling Global Riverine DOC Flux Dynamics From 1951 to 2015","volume":"11","author":"Li","year":"2019","journal-title":"J. Adv. Model. Earth Syst."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1016\/j.isprsjprs.2018.06.004","article-title":"Optical models for remote sensing of chromophoric dissolved organic matter (CDOM) absorption in Poyang Lake","volume":"142","author":"Xu","year":"2018","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_19","first-page":"149","article-title":"Estimating dissolved organic carbon concentration in turbid coastal waters using optical remote sensing observations","volume":"52","author":"Cherukuru","year":"2016","journal-title":"Int. J. Appl. Earth Observ. Geoinf."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"661","DOI":"10.1080\/2150704X.2016.1177242","article-title":"Estimating the CDOM absorption coefficient in tropical inland waters using OLI\/Landsat-8 images","volume":"7","author":"Bernardo","year":"2016","journal-title":"Remote Sens. Lett."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/j.rse.2016.01.007","article-title":"Comparison of Landsat 8 and Landsat 7 for regional measurements of CDOM and water clarity in lakes","volume":"185","author":"Olmanson","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"518","DOI":"10.1016\/j.marpolbul.2016.02.076","article-title":"The new Landsat 8 potential for remote sensing of colored dissolved organic matter (CDOM)","volume":"107","author":"Slonecker","year":"2016","journal-title":"Mar. Pollut. Bull."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Toming, K., Kutser, T., Laas, A., Sepp, M., Paavel, B., and Noges, T. (2016). First experiences in mapping lake water quality parameters with Sentinel-2 MSI Imagery. Remote Sens., 8.","DOI":"10.3390\/rs8080640"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Coelho, C., Heim, B., Foerster, S., Brosinsky, A., and Arauho, J.C. (2017). In situ and satellite observation of CDOM and chlorophyll-a dynamics in small water surface reservoir in the Brazillian semiaric region. Water, 9.","DOI":"10.20944\/preprints201711.0075.v1"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1016\/j.rse.2018.02.060","article-title":"Quantifying CDOM and DOC in major Arctic rivers during ice-free conditions using Landsat TM and ETM+ data","volume":"209","author":"Griffin","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Herrault, P.A., Gandois, L., Gascoin, S., Tanavaev, N., Dantec, T.L., and Teisserenc, R. (2016). Using high spatio-temporal optical remote sensing to monitor dissolved organic carbon in the Arctic. Remote Sens., 8.","DOI":"10.3390\/rs8100803"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"6847","DOI":"10.5194\/bg-15-6847-2018","article-title":"Distribution and cycling of terrigenous dissolved organic carbon in peatland-draining rivers and coastal waters of Sarawak, Borneo","volume":"15","author":"Martin","year":"2018","journal-title":"Biogeosciences"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1439","DOI":"10.3390\/rs5031439","article-title":"Chromophoric dissolved organic matter and dissolved organic carbon from Sea-Viewing Wide Field-of-View Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS) and MERIS Sensors: Case study for the northern Gulf of Mexico","volume":"5","author":"Tehrani","year":"2013","journal-title":"Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1364\/OE.23.000033","article-title":"CDOM-DOC relationship in contrasted coastal waters: Implication for DOC retrieval from ocean color remote sensing observation","volume":"23","author":"Vantrepotte","year":"2015","journal-title":"Opt. Express"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"320","DOI":"10.1016\/j.jhydrol.2013.11.049","article-title":"Suitability of TRMM satellite rainfall in driving a distributed hydrological model in the source region of Yellow River","volume":"509","author":"Meng","year":"2014","journal-title":"J. Hydrol."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"242","DOI":"10.1016\/j.catena.2017.01.019","article-title":"Evaluation of CFSR, TMPA 3B42 and ground-based rainfall data as input for hydrological models-scarce region: The upper Blue Nile","volume":"152","author":"Worqlul","year":"2017","journal-title":"Catena"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"2470","DOI":"10.1038\/s41598-017-02704-1","article-title":"Hydrologic evaluation of TRMM multisatellite precipitation analysis for Nanliu River basin in humid southwestern China","volume":"7","author":"Zhao","year":"2017","journal-title":"Sci. Rep."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"809","DOI":"10.1175\/1520-0426(1998)015<0809:TTRMMT>2.0.CO;2","article-title":"The Tropical Rainfall Measuring Mission (TRMM) sensor package","volume":"15","author":"Kummerow","year":"1998","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Jiang, S., Zhang, Z., Huang, Y., Chen, X., and Chen, S. (2017). Evaluating the TRMM Multisatellite Precipitation Analysis for Extreme Precipitation and Streamflow in Ganjiang River Basin, China. Adv. Meteorol.","DOI":"10.1155\/2017\/2902493"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"4092","DOI":"10.3390\/rs70404092","article-title":"Assessment of effective seasonal downscaling of TRMM precipitation data in Peninsular Malaysia","volume":"7","author":"Mahmud","year":"2015","journal-title":"Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Tan, M.L., and Duan, Z. (2017). Assessment of GPM and TRMM precipitation products over Singapore. Remote Sens., 9.","DOI":"10.3390\/rs9070720"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"2907","DOI":"10.1175\/JHM-D-17-0008.1","article-title":"Impact of tropical deforestation and forest degradation on precipitation over Borneo Island","volume":"18","author":"Takahashi","year":"2017","journal-title":"J. Hydrometeorol."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1016\/j.csr.2016.10.008","article-title":"Riverine influence on ocean color in the equatorial South China Sea","volume":"143","author":"Sun","year":"2017","journal-title":"Cont. Shelf Res."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"3825","DOI":"10.1002\/joc.3939","article-title":"Observation of spatial patterns on the rainfall response to ENSO and IOD over Indonesia using TRMM multisatellite Precipitation Analysis (TMPA)","volume":"34","author":"Adnyana","year":"2014","journal-title":"Int. J. Climatol."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"2579","DOI":"10.5194\/hess-21-2579-2017","article-title":"Hydrology of inland tropical lowland: The kapuas and Mahakam wetlands","volume":"21","author":"Hidayat","year":"2017","journal-title":"Hydrol. Earth Syst. Sci."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"10232","DOI":"10.3390\/rs61010232","article-title":"The spectral response of the Landsat-8 operational land imager","volume":"6","author":"Barsi","year":"2014","journal-title":"Remote Sens."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"2950","DOI":"10.1080\/01431161.2016.1186852","article-title":"Mapping inland water carbon content with Landsat 8 data","volume":"37","author":"Kutser","year":"2016","journal-title":"Int. J. Remote Sens."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v028.i05","article-title":"Building predictive models in R using the caret package","volume":"28","author":"Kuhn","year":"2008","journal-title":"J. Stat. Softw."},{"key":"ref_44","unstructured":"Bates, D.M., and Chamber, J.M. (1992). Statistical Model in S (Nonlinear Models), Chapman and Hall."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"7404","DOI":"10.1364\/OE.26.007404","article-title":"Performance metrics for the assessment of satellite data products: An ocean color case study","volume":"26","author":"Seegers","year":"2018","journal-title":"Opt. Express"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1016\/j.rse.2019.03.010","article-title":"Adaptation of the dark spectrum fitting atmospheric correction for aquatic applications of the Landsat and Sentinel-2 archives","volume":"225","author":"Vanhellemont","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_47","unstructured":"Whitmore, T. (1984). Tropical Rain Forests of the Far East, Oxford University Press. [2nd ed.]."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"691","DOI":"10.5194\/bg-13-691-2016","article-title":"Fate of terrestrial organic carbon and associated CO2 and CO emissions from two Southeast Asian estuaries","volume":"13","author":"Warneke","year":"2016","journal-title":"Biogeosciences"},{"key":"ref_49","first-page":"1","article-title":"Evaluation of TRMM 3B43 data over the Yangtze River Delta of China","volume":"8","author":"Cao","year":"2018","journal-title":"Sci. Rep."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1016\/S0037-0738(00)00042-7","article-title":"Seasonal sediment transport and deposition in the Rajang River delta, Sarawak, East Malaysia","volume":"133","author":"Staub","year":"2000","journal-title":"Sediment. Geol."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"17","DOI":"10.5194\/bg-16-17-2019","article-title":"Impact of peatlands on carbon dioxide emissions from the Rajang River and Estuary, Malaysia","volume":"16","author":"Warneke","year":"2019","journal-title":"Biogeosciences"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"4321","DOI":"10.5194\/bg-16-4321-2019","article-title":"Nitrous oxide (N2O) and methane (CH4) in rivers and estuaries of northwestern borneo","volume":"16","author":"Bange","year":"2019","journal-title":"Biogeosciences"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"600","DOI":"10.3390\/rs70100600","article-title":"The ground-based absolute radiometric calibration of Landsat 8 OLI","volume":"7","author":"McCorkel","year":"2015","journal-title":"Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/20\/3380\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,4]],"date-time":"2024-07-04T07:03:02Z","timestamp":1720076582000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/20\/3380"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,16]]},"references-count":53,"journal-issue":{"issue":"20","published-online":{"date-parts":[[2020,10]]}},"alternative-id":["rs12203380"],"URL":"https:\/\/doi.org\/10.3390\/rs12203380","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,10,16]]}}}