{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,13]],"date-time":"2026-06-13T16:00:53Z","timestamp":1781366453065,"version":"3.54.1"},"reference-count":69,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2022,7,8]],"date-time":"2022-07-08T00:00:00Z","timestamp":1657238400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key Research and Development Program of China","award":["2021YFC3001000"],"award-info":[{"award-number":["2021YFC3001000"]}]},{"name":"National Key Research and Development Program of China","award":["2019ZT08G090"],"award-info":[{"award-number":["2019ZT08G090"]}]},{"name":"Guangdong Provincial Department of Science and Technology, China","award":["2021YFC3001000"],"award-info":[{"award-number":["2021YFC3001000"]}]},{"name":"Guangdong Provincial Department of Science and Technology, China","award":["2019ZT08G090"],"award-info":[{"award-number":["2019ZT08G090"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Coastal aquaculture is an important supply of animal proteins for human consumption, which is expanding globally. Meanwhile, extensive aquaculture may increase nutrient loadings and environmental concerns along the coast. Accurate information on aquaculture pond location is essential for coastal management. Traditional methods use morphological parameters to characterize the geometry of surface waters to differentiate artificially constructed conventional aquaculture ponds from other water bodies. However, there are other water bodies with similar morphology (e.g., saltworks, rice fields, and small reservoirs) that are difficult to distinguish from aquaculture ponds, causing a lot of omission\/commissioning errors in areas with complex land-use types. Here, we develop an extraction method with shape and water quality parameters to map aquaculture ponds, including three steps: (1) Sharpen normalized difference water index to detect and binarize water pixels by the Otsu method; (2) Connect independent water pixels into water objects through the four-neighbor connectivity algorithm; and (3) Calculate the shape features and water quality features of water objects and input them into the classifier for supervised classification. We selected eight sites along the coast of China to evaluate the accuracy and generalization of our method in an environment with heterogeneous pond morphology and landscape. The results showed that six transfer characteristics including water quality characteristics improved the accuracy of distinguishing aquaculture ponds from salt pans, rice fields, and wetland parks, which typically had F1 scores &gt; 85%. Our method significantly improved extraction efficiency on average, especially when aquaculture ponds are mixed with other morphological similar water bodies. Our identified area was in agreement with statistics data of 12 coastal provinces in China. In addition, our approach can effectively improve water objects when high-resolution remote sensing images are unavailable. This work was applied to open-source remote sensing imagery and has the potential to extract long-term series and large-scale aquaculture ponds globally.<\/jats:p>","DOI":"10.3390\/rs14143306","type":"journal-article","created":{"date-parts":[[2022,7,11]],"date-time":"2022-07-11T00:06:21Z","timestamp":1657497981000},"page":"3306","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":32,"title":["Improving Satellite Retrieval of Coastal Aquaculture Pond by Adding Water Quality Parameters"],"prefix":"10.3390","volume":"14","author":[{"given":"Yuxuan","family":"Hou","sequence":"first","affiliation":[{"name":"Center for Water Resources and Environment, School of Civil Engineering, Sun Yat-sen University, Guangzhou 510275, China"},{"name":"Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai 519082, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gang","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Global Ecology, Carnegie Institution for Science, Stanford, CA 94305, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0809-5297","authenticated-orcid":false,"given":"Xiaohong","family":"Chen","sequence":"additional","affiliation":[{"name":"Center for Water Resources and Environment, School of Civil Engineering, Sun Yat-sen University, Guangzhou 510275, China"},{"name":"Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai 519082, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xuan","family":"Yu","sequence":"additional","affiliation":[{"name":"Center for Water Resources and Environment, School of Civil Engineering, Sun Yat-sen University, Guangzhou 510275, China"},{"name":"Southern Marine Science and Engineering Guangdong Laboratory, Zhuhai 519082, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,8]]},"reference":[{"key":"ref_1","unstructured":"FAO (2018). The State of World Fisheries and Aquaculture 2018-Meeting the Sustainable Development Goals, Fisheries and Aquaculture Department, Food and Agriculture Organization of the United Nations."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"133923","DOI":"10.1016\/j.scitotenv.2019.133923","article-title":"The food-water quality nexus in periurban aquacultures downstream of Bangkok, Thailand","volume":"695","author":"Mrozik","year":"2019","journal-title":"Sci. Total Environ."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"244","DOI":"10.1016\/j.ocecoaman.2015.10.015","article-title":"Aquaculture: Relevance, distribution, impacts and spatial assessments\u2013A review","volume":"119","author":"Ottinger","year":"2016","journal-title":"Ocean. Coast. Manag."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"736210","DOI":"10.1016\/j.aquaculture.2020.736210","article-title":"Status, challenges and trends of aquaculture in Singapore","volume":"533","author":"Shen","year":"2020","journal-title":"Aquaculture"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"551","DOI":"10.1038\/s41586-021-03308-6","article-title":"A 20-year retrospective review of global aquaculture","volume":"591","author":"Naylor","year":"2021","journal-title":"Nature"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.ocecoaman.2015.06.026","article-title":"Categorizing social vulnerability patterns in Chinese coastal cities","volume":"116","author":"Su","year":"2015","journal-title":"Ocean Coast. Manag."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"737331","DOI":"10.1016\/j.aquaculture.2021.737331","article-title":"Coastal aquaculture in Zanzibar, Tanzania","volume":"546","author":"Charisiadou","year":"2022","journal-title":"Aquaculture"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1016\/j.ecss.2015.03.003","article-title":"Two faces of agricultural intensification hanging over aquatic biodiversity: The case of chironomid diversity from farm ponds vs. natural wetlands in a coastal region","volume":"157","author":"Fenoy","year":"2015","journal-title":"Estuar. Coast. Shelf Sci."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"144083","DOI":"10.1016\/j.scitotenv.2020.144083","article-title":"Pond aquaculture effluents feed an anthropogenic nitrogen loop in a SE Asian estuary","volume":"756","author":"Herbeck","year":"2021","journal-title":"Sci. Total Environ."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"115100","DOI":"10.1016\/j.jenvman.2022.115100","article-title":"Rapid expansion of coastal aquaculture ponds in Southeast Asia: Patterns, drivers and impacts","volume":"315","author":"Luo","year":"2022","journal-title":"J. Environ. Manag."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"105922","DOI":"10.1016\/j.ocecoaman.2021.105922","article-title":"Evaluating the spatio-temporal development of coastal aquaculture: An example from the coastal plains of West Bengal, India","volume":"214","author":"Mandal","year":"2021","journal-title":"Ocean. Coast. Manag."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"151712","DOI":"10.1016\/j.scitotenv.2021.151712","article-title":"Biodiversity impacts by multiple anthropogenic stressors in Mediterranean coastal wetlands","volume":"818","author":"Rico","year":"2022","journal-title":"Sci. Total Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1890\/130260","article-title":"Tracking the rapid loss of tidal wetlands in the Yellow Sea","volume":"12","author":"Murray","year":"2014","journal-title":"Front. Ecol. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"107041","DOI":"10.1016\/j.ecss.2020.107041","article-title":"Morphological characterization of ponds and tidal courses in coastal wetlands using Google Earth imagery","volume":"246","author":"Delrieux","year":"2020","journal-title":"Estuar. Coast. Shelf Sci."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"100339","DOI":"10.1016\/j.aqrep.2020.100339","article-title":"Aquaculture extension system in China: Development, challenges, and prospects","volume":"17","author":"Wang","year":"2020","journal-title":"Aquac. Rep."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1076","DOI":"10.1038\/s41893-021-00793-5","article-title":"Rebound in China\u2019s coastal wetlands following conservation and restoration","volume":"4","author":"Wang","year":"2021","journal-title":"Nat. Sustain."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Ottinger, M., Clauss, K., and Kuenzer, C. (2018). Opportunities and challenges for the estimation of aquaculture production based on earth observation data. Remote Sens., 10.","DOI":"10.3390\/rs10071076"},{"key":"ref_18","first-page":"101902","article-title":"Rapid expansion of coastal aquaculture ponds in China from Landsat observations during 1984\u20132016","volume":"82","author":"Ren","year":"2019","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Sun, Z., Luo, J., Yang, J., Yu, Q., Zhang, L., Xue, K., and Lu, L. (2020). Nation-Scale Mapping of Coastal Aquaculture Ponds with Sentinel-1 SAR Data Using Google Earth Engine. Remote Sens., 12.","DOI":"10.3390\/rs12183086"},{"key":"ref_20","first-page":"13","article-title":"Extracting aquaculture ponds from natural water surfaces around inland lakes on medium resolution multispectral imagerys","volume":"80","author":"Zeng","year":"2019","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1016\/j.isprsjprs.2009.06.004","article-title":"Object based imagery analysis for remote sensing","volume":"65","author":"Blaschke","year":"2010","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1109\/TGE.1976.294460","article-title":"Classification of multispectral image data by extraction and classification of homogeneous objects","volume":"14","author":"Kettig","year":"1976","journal-title":"IEEE Trans. Geosci. Electron."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1016\/j.apgeog.2014.12.012","article-title":"Assessment of land-use and land-cover changes from 1965 to 2014 in Tam Giang-Cau Hai Lagoon, central Vietnam","volume":"58","author":"Disperati","year":"2015","journal-title":"Appl. Geogr."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Loberternos, R.A., Porpetcho, W.P., Graciosa JC, A., Violanda, R.R., Diola, A.G., and Dy, D.T. (2016, January 12\u201319). An Object-Based Workflow Developed To Extract Aquaculture Ponds From Airborne Lidar Data: A Test Case In Central Visayas, Philippines. International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences, 41. Proceedings of the XXIII ISPRS Congress, Prague, Czech Republic.","DOI":"10.5194\/isprsarchives-XLI-B8-1147-2016"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1007\/s10661-013-3360-7","article-title":"An object-based image analysis approach for aquaculture ponds precise mapping and monitoring: A case study of Tam Giang-Cau Hai Lagoon, Vietnam","volume":"186","author":"Virdis","year":"2014","journal-title":"Environ. Monit. Assess."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Ottinger, M., Clauss, K., and Kuenzer, C. (2017). Large-scale assessment of coastal aquaculture ponds with Sentinel-1 time series data. Remote Sens., 9.","DOI":"10.3390\/rs9050440"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"734666","DOI":"10.1016\/j.aquaculture.2019.734666","article-title":"Mapping national-scale aquaculture ponds based on the Google Earth Engine in the Chinese coastal zone","volume":"520","author":"Duan","year":"2020","journal-title":"Aquaculture"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"294","DOI":"10.1016\/j.patrec.2005.08.011","article-title":"Random forests for land cover classification","volume":"27","author":"Gislason","year":"2006","journal-title":"Pattern Recognit. Lett."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1399","DOI":"10.1080\/01431161.2017.1404162","article-title":"Mapping rice areas with Sentinel-1 time series and superpixel segmentation","volume":"39","author":"Clauss","year":"2018","journal-title":"Int. J. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"112651","DOI":"10.1016\/j.rse.2021.112651","article-title":"Complementary water quality observations from high and medium resolution Sentinel sensors by aligning chlorophyll-a and turbidity algorithms","volume":"265","author":"Warren","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.rse.2014.10.032","article-title":"Using multi-temporal Landsat imagery and linear mixed models for assessing water quality parameters in R\u00edo Tercero reservoir (Argentina)","volume":"158","author":"Bonansea","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"735377","DOI":"10.1016\/j.aquaculture.2020.735377","article-title":"Synchronizing use of sophisticated wet-laboratory and in-field handheld technologies for real-time monitoring of key microalgae, bacteria and physicochemical parameters influencing efficacy of water quality in a freshwater aquaculture recirculation system: A case study from the Republic of Ireland","volume":"526","author":"Naughton","year":"2020","journal-title":"Aquaculture"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1791","DOI":"10.1007\/s11430-016-5317-5","article-title":"Characteristics of coastline changes in mainland China since the early 1940s","volume":"59","author":"Hou","year":"2016","journal-title":"Sci. China Earth Sci."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Traganos, D., Poursanidis, D., Aggarwal, B., Chrysoulakis, N., and Reinartz, P. (2018). Estimating satellite-derived bathymetry (SDB) with the google earth engine and sentinel-2. Remote Sens., 10.","DOI":"10.3390\/rs10060859"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1016\/j.rse.2018.10.027","article-title":"Sentinel-2\/Landsat-8 product consistency and implications for monitoring aquatic systems","volume":"220","author":"Pahlevan","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.rse.2017.06.031","article-title":"Google Earth Engine: Planetary-scale geospatial analysis for everyone","volume":"202","author":"Gorelick","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1425","DOI":"10.1080\/01431169608948714","article-title":"The use of the Normalized Difference Water Index (NDWI) in the delineation of open water parameters","volume":"17","author":"McFeeters","year":"1996","journal-title":"Int. J. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"886","DOI":"10.1016\/j.ijleo.2008.03.016","article-title":"Imagery enhancement by the modified high-pass filtering approach","volume":"120","author":"Yang","year":"2009","journal-title":"Optik"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1109\/TSMC.1979.4310076","article-title":"A threshold selection method from gray-level histograms","volume":"9","author":"Otsu","year":"1979","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"ref_40","unstructured":"De Smith, M.J., Goodchild, M.F., and Longley, P. (2007). Geospatial Analysis: A Comprehensive Guide to Principles, Techniques and Software Tools, Troubador publishing Ltd."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"105348","DOI":"10.1016\/j.ocecoaman.2020.105348","article-title":"Automatic extraction of aquaculture ponds based on Google Earth Engine","volume":"198","author":"Xia","year":"2020","journal-title":"Ocean. Coast. Manag."},{"key":"ref_42","unstructured":"Rutledge, D.T. (2003). Landscape Indices as Measures of the Effects of fragmentation: Can Pattern Reflect Process?."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Johansen, R.A., Reif, M.K., Emery, E.B., Nowosad, J., Beck, R.A., Xu, M., and Liu, H. (2019). Waterquality: An Open-Source R Package for the Detection and Quantification of Cyanobacterial Harmful Algal Blooms and Water Quality.","DOI":"10.21079\/11681\/35053"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"3665","DOI":"10.1080\/01431160802007640","article-title":"Relating spectral shape to cyanobacterial blooms in the Laurentian Great Lakes","volume":"29","author":"Wynne","year":"2008","journal-title":"Int. J. Remote Sens."},{"key":"ref_45","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_46","doi-asserted-by":"crossref","first-page":"1771","DOI":"10.1080\/014311699212470","article-title":"Interpretation of the 685nm peak in water-leaving radiance spectra in terms of fluorescence, absorption and scattering, and its observation by MERIS","volume":"20","author":"Gower","year":"1999","journal-title":"Int. J. Remote Sens."},{"key":"ref_47","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_48","doi-asserted-by":"crossref","first-page":"535","DOI":"10.1016\/j.rse.2004.11.009","article-title":"Mapping lake CDOM by satellite remote sensing","volume":"94","author":"Kutser","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"782506","DOI":"10.1117\/12.862096","article-title":"Detection of surface algal blooms using the newly developed algorithm surface algal bloom index (SABI)","volume":"Volume 7825","author":"Alawadi","year":"2010","journal-title":"Remote Sensing of the Ocean, Sea Ice, and Large Water Regions"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"17","DOI":"10.5589\/m03-048","article-title":"Observation of chlorophyll fluorescence in west coast waters of Canada using the MODIS satellite sensor","volume":"30","author":"Gower","year":"2004","journal-title":"Can. J. Remote Sens."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"2784","DOI":"10.1080\/01431161.2018.1433343","article-title":"Implementation of machine-learning classification in remote sensing: An applied review","volume":"39","author":"Maxwell","year":"2018","journal-title":"Int. J. Remote Sens."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1016\/j.isprsjprs.2015.03.014","article-title":"Exploring issues of training data imbalance and mislabelling on random forest performance for large area land cover classification using the ensemble margin","volume":"105","author":"Mellor","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Oshiro, T.M., Perez, P.S., and Baranauskas, J.A. (2012). How many trees in a random forest?. International Workshop on Machine Learning and Data Mining in Pattern Recognition, Springer.","DOI":"10.1007\/978-3-642-31537-4_13"},{"key":"ref_55","first-page":"1157","article-title":"An introduction to variable and feature selection","volume":"3","author":"Guyon","year":"2003","journal-title":"J. Mach. Learn. Res."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"111199","DOI":"10.1016\/j.rse.2019.05.018","article-title":"Key issues in rigorous accuracy assessment of land cover products","volume":"231","author":"Stehman","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_57","first-page":"397","article-title":"Accuracy assessment: A user\u2019s perspective","volume":"52","author":"Story","year":"1986","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"112316","DOI":"10.1016\/j.rse.2021.112316","article-title":"Improving satellite retrieval of oceanic particulate organic carbon concentrations using machine learning methods","volume":"256","author":"Liu","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_59","unstructured":"Helld\u00e9n, U. (1980). A Test of Landsat-2 Imagery and Digital Data for Thematic Mapping Illustrated by an Environmental Study in Northern Kenya, Lund University, Natural Geography Institute. Natural Geography Institute Report No. 47."},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Goutte, C., and Gaussier, E. (2005). A probabilistic interpretation of precision, recall and F-score, with implication for evaluation. European Conference on Information Retrieval, Springer.","DOI":"10.1007\/978-3-540-31865-1_25"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"881","DOI":"10.1109\/TGRS.2016.2616585","article-title":"Dense semantic labeling of subdecimeter resolution images with convolutional neural networks","volume":"55","author":"Volpi","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"659","DOI":"10.1007\/s11222-016-9646-1","article-title":"Correlation and variable importance in random forests","volume":"27","author":"Gregorutti","year":"2016","journal-title":"Stat. Comput."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1145\/3446776","article-title":"Understanding deep learning (still) requires rethinking generalization","volume":"64","author":"Zhang","year":"2021","journal-title":"Commun. ACM"},{"key":"ref_64","first-page":"589","article-title":"A study on information extraction of water body with the modified normalized difference water index (MNDWI)","volume":"5","author":"Xu","year":"2005","journal-title":"J. Remote Sens."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"9655","DOI":"10.3390\/rs70809655","article-title":"An evaluation of different training sample allocation schemes for discrete and continuous land cover classification using decision tree-based algorithms","volume":"7","author":"Colditz","year":"2015","journal-title":"Remote Sens."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"1193","DOI":"10.1007\/s10499-011-9433-0","article-title":"Effect of combined shrimp and rice farming on water and soil quality in Bangladesh","volume":"19","author":"Chowdhury","year":"2011","journal-title":"Aquac. Int."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"111302","DOI":"10.1016\/j.rse.2019.111302","article-title":"Adaptive bathymetry estimation for shallow coastal waters using Planet Dove satellites","volume":"232","author":"Li","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_68","first-page":"247","article-title":"Danis Retrieving water surface temperature from archive LANDSAT thermal infrared data: Application of the mono-channel atmospheric correction algorithm over two freshwater reservoirs","volume":"30","author":"Simon","year":"2014","journal-title":"Int. J. Appl. Earth Obs."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"112271","DOI":"10.1016\/j.jenvman.2021.112271","article-title":"Aquaculture industry: Supply and demand, best practices, effluent and its current issues and treatment technology","volume":"287","author":"Ahmad","year":"2021","journal-title":"J. Environ. Manag."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/14\/3306\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T23:46:57Z","timestamp":1760140017000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/14\/3306"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,8]]},"references-count":69,"journal-issue":{"issue":"14","published-online":{"date-parts":[[2022,7]]}},"alternative-id":["rs14143306"],"URL":"https:\/\/doi.org\/10.3390\/rs14143306","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,7,8]]}}}