{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T05:29:34Z","timestamp":1768282174414,"version":"3.49.0"},"reference-count":100,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2019,5,20]],"date-time":"2019-05-20T00:00:00Z","timestamp":1558310400000},"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>Whiting events in seas and lakes are a natural phenomenon caused by suspended calcium carbonate (CaCO3) particles. The Arabian Gulf, which is a semi-enclosed sea, is prone to extensive whiting that covers tens of thousands of square kilometres. Despite the extent and frequency of whiting events in the Gulf, studies documenting the whiting phenomenon are lacking. Therefore, the primary objective of this study was to detect, map and document the spatial and temporal distributions of whiting events in the Gulf using daily images acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA\u2019s Terra and Aqua satellites from 2002 to 2018. A method integrating a geographic object-based image analysis, the correlation-based feature selection technique (CFS), the adaptive boosting decision tree (AdaBoost DT) and the rule-based classification were used in the study to detect, quantify and assess whiting events in the Gulf from the MODIS data. Firstly, a multiresolution segmentation was optimised using unsupervised quality measures. Secondly, a set of spectral bands and indices were investigated using the CFS to select the most relevant feature(s). Thirdly, a generic AdaBoost DT model and a rule-based classification were adopted to classify the MODIS time series data. Finally, the developed classification model was compared with various tree-based classifiers such as random forest, a single DT and gradient boosted DT. Results showed that both the combination of the mean of the green spectral band and the normalised difference index between the green and blue bands (NDGB), or the combination of the NDGB and the colour index for estimating the concentrations of calcium carbonates (CI) of the image objects, were the most significant features for detecting whiting. Moreover, the generic AdaBoost DT classification model outperformed the other tested tree-based classifiers with an overall accuracy of 97.86% and a kappa coefficient of 0.97. The whiting events during the study period (2002\u20132018) occurred exclusively during the winter season (November to March) and mostly in February. Geographically, the whiting events covered areas ranging from 12,000 km2 to 60,000 km2 and were mainly located along the southwest coast of the Gulf. The duration of most whiting events was 2 to 6 days, with some events extending as long as 8 to 11 days. The study documented the spatiotemporal distribution of whiting events in the Gulf from 2002 to 2018 and presented an effective tool for detecting and motoring whiting events.<\/jats:p>","DOI":"10.3390\/rs11101193","type":"journal-article","created":{"date-parts":[[2019,5,20]],"date-time":"2019-05-20T11:05:07Z","timestamp":1558350307000},"page":"1193","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Spatiotemporal Mapping and Monitoring of Whiting in the Semi-Enclosed Gulf Using Moderate Resolution Imaging Spectroradiometer (MODIS) Time Series Images and a Generic Ensemble Tree-Based Model"],"prefix":"10.3390","volume":"11","author":[{"given":"Abdallah","family":"Shanableh","sequence":"first","affiliation":[{"name":"Department of Civil and Environmental Engineering, University of Sharjah, Sharjah 27272, UAE"},{"name":"Research Institute of Sciences and Engineering, University of Sharjah, Sharjah 27272, UAE"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7111-0061","authenticated-orcid":false,"given":"Rami","family":"Al-Ruzouq","sequence":"additional","affiliation":[{"name":"Department of Civil and Environmental Engineering, University of Sharjah, Sharjah 27272, UAE"},{"name":"Research Institute of Sciences and Engineering, University of Sharjah, Sharjah 27272, UAE"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6465-6231","authenticated-orcid":false,"given":"Mohamed Barakat A.","family":"Gibril","sequence":"additional","affiliation":[{"name":"Research Institute of Sciences and Engineering, University of Sharjah, Sharjah 27272, UAE"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cristina","family":"Flesia","sequence":"additional","affiliation":[{"name":"Department of Earth and Environmental Sciences, University of Milano Bicocca, Piazza Della Scienza 4, 20126 Milano, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8499-2809","authenticated-orcid":false,"given":"Saeed","family":"AL-Mansoori","sequence":"additional","affiliation":[{"name":"Applications Development and Analysis Section (ADAS), Mohammed Bin Rashid Space Centre (MBRSC), Dubai 211833, UAE"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,5,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"258","DOI":"10.1016\/j.ecss.2017.07.017","article-title":"Optical and biochemical properties of a southwest Florida whiting event","volume":"196","author":"Long","year":"2017","journal-title":"Estuar. Coast. Shelf Sci."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1016\/0304-4203(93)90261-L","article-title":"Influence of T, S and PCO2 on the homogeneous nucleation of calcium carbonate from seawater. Implications for whiting formation","volume":"41","author":"Morse","year":"1993","journal-title":"Mar. Chem."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1016\/j.jglr.2013.05.007","article-title":"Is reduced benthic flux related to the Diporeia decline? Analysis of spring blooms and whiting events in Lake Ontario","volume":"39","author":"Watkins","year":"2013","journal-title":"J. Great Lakes Res."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"133","DOI":"10.4319\/lo.1997.42.1.0133","article-title":"Whiting events: Biogenic origin due to the photosynthetic activity of cyanobacterial picoplankton","volume":"42","author":"Thompson","year":"1997","journal-title":"Limnol. Oceanogr."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/j.marchem.2016.09.006","article-title":"Evidence for Inorganic Precipitation of CaCO3 on Suspended Solids in the Open Water of the Red Sea","volume":"186","author":"Wurgaft","year":"2016","journal-title":"Mar. Chem."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1130\/0091-7613(1993)021<0287:BAUEFT>2.3.CO;2","article-title":"Biochemical and ultrastructural evidence for the origin of whitings: A biologically induced calcium carbonate precipitation mechanism: Comment and reply","volume":"21","author":"Friedman","year":"1993","journal-title":"Geology"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"402","DOI":"10.1038\/154402a0","article-title":"Occasional whiteness of the dead sea","volume":"154","author":"Bloch","year":"1944","journal-title":"Nature"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.marchem.2008.10.006","article-title":"The formation of whitings on the Little Bahama Bank","volume":"113","author":"Morse","year":"2009","journal-title":"Mar. Chem."},{"key":"ref_9","unstructured":"Bathurst, R.G.C. (1975). Carbonate Sediments and Their Diagenesis, Elsevier. [2nd ed.]. Developments in Sedimentology."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"906","DOI":"10.1080\/01431161.2017.1392637","article-title":"Long-term spatiotemporal variability of southwest Florida whiting events from MODIS observations","volume":"39","author":"Long","year":"2018","journal-title":"Int. J. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"464","DOI":"10.1130\/0091-7613(1992)020<0464:BAUEFT>2.3.CO;2","article-title":"Biochemical and ultrastructural evidence for the origin of whiting: A biologically induced calcium carbonate precipitation mechanism","volume":"20","author":"Robbins","year":"1992","journal-title":"Geology"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"487","DOI":"10.5194\/bg-6-487-2009","article-title":"Optics and remote sensing of Bahamian carbonate sediment whitings and potential relationship to wind-driven Langmuir circulation","volume":"6","author":"Dierssen","year":"2009","journal-title":"Biogeosciences"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1575","DOI":"10.1029\/JZ071i006p01575","article-title":"Calcium carbonate precipitation on the Bahama Banks","volume":"71","author":"Broecker","year":"1966","journal-title":"J. Geophys. Res."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1007\/BF03175171","article-title":"Physical versus chemical processes of \u201cwhiting\u201d formation in the Bahamas","volume":"8","author":"Boss","year":"1993","journal-title":"Carbonates Evaporites"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1306\/212F8F3A-2B24-11D7-8648000102C1865D","article-title":"Whitings, a Sedimentologic Dilemma","volume":"59","author":"Shinn","year":"1989","journal-title":"J. Sediment. Petrol."},{"key":"ref_16","first-page":"170","article-title":"Environment of Calcium Carbonate Deposition West of Andros Island Bahamas","volume":"350","author":"Cloud","year":"1962","journal-title":"Geol. Surv. Prof. Pap."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Riding, R.E., and Awramik, S.M. (2000). Microbial Sediments, Springer.","DOI":"10.1007\/978-3-662-04036-2"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"410","DOI":"10.1080\/15230430.2001.12003449","article-title":"Precipitation and Dissolution of Calcite in a Swiss High Alpine Lake","volume":"33","author":"Ohlendorf","year":"2001","journal-title":"Arctic Antarct. Alp. Res."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1127\/archiv-hydrobiol\/73\/1974\/14","article-title":"Calcium and total alkalinity budgets and calcium carbonate precipitation of a small hard-water lake","volume":"73","author":"Otsuki","year":"1974","journal-title":"Arch. Hydrobiol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2819","DOI":"10.1016\/S0016-7037(03)00103-0","article-title":"CaCO3 precipitation kinetics in waters from the Great Bahama Bank: Implications for the relationship between Bank hydrochemistry and whitings","volume":"67","author":"Morse","year":"2003","journal-title":"Geochim. Cosmochim. Acta"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"4","DOI":"10.2110\/sedred.2011.4.4","article-title":"Back to the Future","volume":"9","author":"Shinn","year":"2011","journal-title":"Sediment. Rec."},{"key":"ref_22","unstructured":"Lidz, B., and Gibbons, H. (2018, September 30). Research on Whitings (Floating Patches of Calcium Carbonate Mud) Leads to Possible Explanation of Immense Middle East Oil Deposits, Available online: https:\/\/soundwaves.usgs.gov\/2008\/07\/research.html."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Whitton, B.A. (2012). Ecology of Cyanobacteria II: Their Diversity in Space and Time, Springer.","DOI":"10.1007\/978-94-007-3855-3"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"947","DOI":"10.1130\/0091-7613(1997)025<0947:TASDOW>2.3.CO;2","article-title":"Temporal and spatial distribution of whitings on Great Bahama Bank and a new lime mud budget","volume":"25","author":"Robbins","year":"1997","journal-title":"Geology"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"539","DOI":"10.1080\/2150704X.2014.933275","article-title":"Whiting events in SW Florida coastal waters: A case study using MODIS medium-resolution data","volume":"5","author":"Long","year":"2014","journal-title":"Remote Sens. Lett."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"877","DOI":"10.4319\/lo.1978.23.5.0877","article-title":"Satellite observations of calcium carbonate precipitation in the Great Lakes","volume":"23","author":"Strong","year":"1978","journal-title":"Limnol. Ocean."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Heine, I., Brauer, A., Heim, B., Itzerott, S., Kasprzak, P., Kienel, U., and Kleinschmit, B. (2017). Monitoring of calcite precipitation in hardwater lakes with multi-spectral remote sensing archives. Water, 9.","DOI":"10.3390\/w9010015"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"3604","DOI":"10.1029\/JC089iC03p03604","article-title":"The carbonate chemistry of grand bahama bank waters: After 18 years another look","volume":"89","author":"Millero","year":"1984","journal-title":"J. Geophys. Res."},{"key":"ref_29","unstructured":"Long, J.S. (2016). Whiting Events Off Southwest Florida: Remote Sensing and Field Observations. [Ph.D. Dissertation, University of South Florida]."},{"key":"ref_30","unstructured":"Lloyd, R.A. (2012). Remote Sensing of Whitings in the Bahamas. [Master\u2019s Thesis, University of South Florida]."},{"key":"ref_31","unstructured":"Tao, Y. (1994). Whitings on the Great Bahama Bank: Distribution in Space and Time Using Space Shuttle Photographs. [Ph.D. Dissertation, University of South Florida]."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2004JC002560","article-title":"Calcium carbonate measurements in the surface global ocean based on Moderate-Resolution Imaging Spectroradiometer data","volume":"110","author":"Balch","year":"2005","journal-title":"J. Geophys. Res. C Ocean."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1587","DOI":"10.1029\/2000GL012025","article-title":"Retrieval of Coccolithophore from SeaWiFS Imagery Calcite Concentration radiance","volume":"28","author":"Gordon","year":"2001","journal-title":"Geophys. Res. Lett."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"8707","DOI":"10.1002\/2017JC013146","article-title":"Estimating Particulate Inorganic Carbon Concentrations of the Global Ocean From Ocean Color Measurements Using a Reflectance Difference Approach","volume":"122","author":"Mitchell","year":"2017","journal-title":"J. Geophys. Res. Ocean."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"429","DOI":"10.1016\/S0070-4571(08)70517-X","article-title":"Present-day precipitation of calcium carbonate in the Persian Gulf","volume":"1","author":"Wells","year":"1964","journal-title":"Dev. Sedimentol."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"411","DOI":"10.1504\/IJGW.2017.087210","article-title":"Potential impact of global warming on whiting in a semi-enclosed gulf","volume":"13","author":"Shanableh","year":"2017","journal-title":"Int. J. Glob. Warm."},{"key":"ref_37","unstructured":"Shanableh, A., Al-Ruzouq, R., and Al-Khayyat, G. (2017, January 25\u201328). Assessing the Spatial and Temporal Capacity of a Semi-Enclosed Gulf to Absorb and Release CO2 Using GIS and Remote Sensing. Proceedings of the Global Civil Engineering Conference, Kuala Lumpur, Malaysia."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Sheppard, C., Al-Husiani, M., Al-Jamali, F., Al-Yamani, F., Baldwin, R., Bishop, J., Benzoni, F., Dutrieux, E., Dulvy, N.K., and Durvasula, S.R.V. (2012). Environmental Concerns for the Future of Gulf Coral Reefs, Springer.","DOI":"10.1007\/978-94-007-3008-3_16"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"27","DOI":"10.5194\/os-2-27-2006","article-title":"The circualtion of the Persian Gulf: A numerical study","volume":"2","author":"Kaempf","year":"2006","journal-title":"Ocean Sci."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.marpolbul.2018.02.012","article-title":"Is reduced freshwater flow in Tigris-Euphrates rivers driving fish recruitment changes in the Northwestern Arabian Gulf?","volume":"129","author":"Walters","year":"2018","journal-title":"Mar. Pollut. Bull."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1016\/j.isprsjprs.2013.09.014","article-title":"Geographic Object-Based Image Analysis\u2014Towards a new paradigm","volume":"87","author":"Blaschke","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"59","DOI":"10.14311\/gi.15.2.5","article-title":"Object Based and Pixel Based Classification Using Rapideye Satellite Imager of ETI-OSA, Lagos, Nigeria","volume":"15","author":"Makinde","year":"2016","journal-title":"Geoinform. FCE CTU"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1080\/10106049.2012.668950","article-title":"Spectral angle mapper and object-based classification combined with hyperspectral remote sensing imagery for obtaining land use\/cover mapping in a Mediterranean region","volume":"28","author":"Petropoulos","year":"2013","journal-title":"Geocarto Int."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"270","DOI":"10.1080\/17538947.2017.1421722","article-title":"Object-based image analysis supported by data mining to discriminate large areas of soybean","volume":"12","author":"Nanni","year":"2019","journal-title":"Int. J. Digit. Earth"},{"key":"ref_45","first-page":"72","article-title":"Object-based delineation of homogeneous landscape units at regional scale based on modis time series","volume":"37","author":"Bisquert","year":"2015","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1865","DOI":"10.1080\/01431161.2017.1280635","article-title":"Improved forest-cover mapping based on MODIS time series and landscape stratification","volume":"38","author":"Cano","year":"2017","journal-title":"Int. J. Remote Sens."},{"key":"ref_47","first-page":"83","article-title":"Crop area mapping in West Africa using landscape stratification of MODIS time series and comparison with existing global land products","volume":"14","author":"Vintrou","year":"2012","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"3181","DOI":"10.1016\/j.rse.2008.03.013","article-title":"An object-based change detection method accounting for temporal dependences in time series with medium to coarse spatial resolution","volume":"112","author":"Bontemps","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1080\/15481603.2016.1256861","article-title":"Environmental evaluation of MODIS-derived land units","volume":"54","author":"Bisquert","year":"2017","journal-title":"GISci. Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Bell\u00f3n, B., B\u00e9gu\u00e9, A., Lo Seen, D., de Almeida, C.A., and Sim\u00f5es, M. (2017). A remote sensing approach for regional-scale mapping of agricultural land-use systems based on NDVI time series. Remote Sens., 9.","DOI":"10.3390\/rs9060600"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"819","DOI":"10.14358\/PERS.75.7.819","article-title":"Forest Type Mapping using Object-specific Texture Measures from Multispectral Ikonos Imagery: Segmentation Quality and Image Classification Issues","volume":"75","author":"Kim","year":"2009","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_52","first-page":"239","article-title":"Multiresolution Segmentation: An optimization approach for high quality multi-scale image segmentation","volume":"58","author":"Baatz","year":"2004","journal-title":"J. Photogramm. Remote Sens."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"515","DOI":"10.1080\/15481603.2017.1287238","article-title":"A comparison of unsupervised segmentation parameter optimization approaches using moderate- and high-resolution imagery","volume":"54","author":"Grybas","year":"2017","journal-title":"GISci. Remote Sens."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"2825","DOI":"10.1080\/01431161003745608","article-title":"Multi-scale GEOBIA with very high spatial resolution digital aerial imagery: Scale, texture and image objects","volume":"32","author":"Kim","year":"2011","journal-title":"Int. J. Remote Sens."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1016\/j.isprsjprs.2013.03.006","article-title":"Change detection from remotely sensed images: From pixel-based to object-based approaches","volume":"80","author":"Hussain","year":"2013","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"3747","DOI":"10.1080\/01431161003777189","article-title":"Optimal region growing segmentation and its effect on classification accuracy","volume":"32","author":"Gao","year":"2011","journal-title":"Int. J. Remote Sens."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"2292","DOI":"10.3390\/ijgi4042292","article-title":"Image Segmentation Parameter Optimization Considering Within- and Between-Segment Heterogeneity at Multiple Scale Levels: Test Case for Mapping Residential Areas Using Landsat Imagery","volume":"4","author":"Johnson","year":"2015","journal-title":"ISPRS Int. J. Geo-Inf."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/j.isprsjprs.2013.11.018","article-title":"Automated parameterisation for multi-scale image segmentation on multiple layers","volume":"88","author":"Csillik","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1109\/LGRS.2011.2163056","article-title":"An unsupervised evaluation method for remotely sensed imagery segmentation","volume":"9","author":"Zhang","year":"2012","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"3035","DOI":"10.1080\/01431160600617194","article-title":"Parameter selection for region-growing image segmentation algorithms using spatial autocorrelation","volume":"27","author":"Espindola","year":"2006","journal-title":"Int. J. Remote Sens."},{"key":"ref_61","first-page":"70","article-title":"A comparison of three feature selection methods for object-based classification of sub-decimeter resolution UltraCam-L imagery","volume":"15","author":"Laliberte","year":"2012","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Ma, L., Cheng, L., Li, M., Liu, Y., and Ma, X. (2015). Training set size, scale, and features in Geographic Object-Based Image Analysis of very high resolution unmanned aerial vehicle imagery. ISPRS J. Photogramm. Remote Sens.","DOI":"10.1016\/j.isprsjprs.2014.12.026"},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Al-Ruzouq, R., Shanableh, A., Barakat, A., Gibril, M., and AL-Mansoori, S. (2018). Image Segmentation Parameter Selection and Ant Colony Optimization for Date Palm Tree Detection and Mapping from Very-High-Spatial-Resolution Aerial Imagery. Remote Sens., 10.","DOI":"10.3390\/rs10091413"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1080\/15481603.2017.1408892","article-title":"Less is more: Optimizing classification performance through feature selection in a very-high-resolution remote sensing object-based urban application","volume":"55","author":"Georganos","year":"2018","journal-title":"GISci. Remote Sens."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"3224","DOI":"10.1109\/JSTARS.2018.2851753","article-title":"Supervised and Adaptive Feature Weighting for Object-Based Classification on Satellite Images","volume":"11","author":"Zhou","year":"2018","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"1940","DOI":"10.1109\/TGRS.2003.814625","article-title":"Classification and feature extraction for remote sensing images from urban areas based on morphological transformations","volume":"41","author":"Benediktsson","year":"2003","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"131","DOI":"10.3233\/IDA-1997-1302","article-title":"Feature selection for classification","volume":"1","author":"Dash","year":"1997","journal-title":"Intell. Data Anal."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1016\/j.isprsjprs.2013.08.007","article-title":"Impact of feature selection on the accuracy and spatial uncertainty of per-field crop classification using Support Vector Machines","volume":"85","author":"Michel","year":"2013","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_69","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_70","doi-asserted-by":"crossref","first-page":"4502","DOI":"10.1080\/01431161.2011.649864","article-title":"Multi-scale object-based image analysis and feature selection of multi-sensor earth observation imagery using random forests","volume":"33","author":"Duro","year":"2012","journal-title":"Int. J. Remote Sens."},{"key":"ref_71","unstructured":"Hu, M., and Wu, F. (2010, January 16\u201317). Filter-wrapper hybrid method on feature selection. Proceedings of the 2010 Second WRI Global Congress on Intelligent Systems, Wuhan, China."},{"key":"ref_72","doi-asserted-by":"crossref","unstructured":"Ma, L., Fu, T., Blaschke, T., Li, M., Tiede, D., Zhou, Z., Ma, X., and Chen, D. (2017). Evaluation of Feature Selection Methods for Object-Based Land Cover Mapping of Unmanned Aerial Vehicle Imagery Using Random Forest and Support Vector Machine Classifiers. ISPRS Int. J. Geo-Inf., 6.","DOI":"10.3390\/ijgi6020051"},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1016\/j.eswa.2018.02.028","article-title":"Selection of spectral features for land cover type classification","volume":"102","author":"Gumus","year":"2018","journal-title":"Expert Syst. Appl."},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Hamedianfar, A., and Barakat, A.M. (2019). Gibril Large-scale urban mapping using integrated geographic object-based image analysis and artificial bee colony optimization from worldview-3 data. Int. J. Remote Sens.","DOI":"10.1080\/01431161.2019.1594435"},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1016\/j.catena.2018.04.038","article-title":"Catena An improved algorithm for identifying shallow and deep-seated landslides in dense tropical forest from airborne laser scanning data","volume":"167","author":"Ridha","year":"2018","journal-title":"Catena"},{"key":"ref_76","unstructured":"Hall, M.A., and Smith, L.A. (1997). Feature subset selection: A correlation based filter approach. International Conference on Neural Information Processing and Intelligent Information Systems, Springer."},{"key":"ref_77","unstructured":"Hall, M.A. (July, January 29). Correlation-based feature selection of discrete and numeric class machine learning. Proceedings of the 17th International Conference on Machine Learning, San Francisco, CA, USA."},{"key":"ref_78","unstructured":"Hall, M.A., and Smith, L.A. (1998, January 4\u20136). Practical feature subset selection for machine learning. Proceedings of the 21st Australasian Computer Science Conference ACSC\u201998, Perth, Australia."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"1437","DOI":"10.1109\/TKDE.2003.1245283","article-title":"Benchmarking Attribute Selection Techniques for Discrete Class Data Mining","volume":"15","author":"Hall","year":"2003","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"ref_80","unstructured":"Trimble, T. (2011). ECognition Developer 8.7 Reference Book, Trimble Germany GmbH."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1177\/030913338000400301","article-title":"Multispectral remote sensing of vegetation amount","volume":"4","author":"Curran","year":"1980","journal-title":"Prog. Phys. Geogr."},{"key":"ref_82","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 features","volume":"17","author":"Mcfeeters","year":"1996","journal-title":"Int. J. Remote Sens."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"3025","DOI":"10.1080\/01431160600589179","article-title":"Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery","volume":"27","author":"Xu","year":"2006","journal-title":"Int. J. Remote Sens."},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"2118","DOI":"10.1016\/j.rse.2009.05.012","article-title":"A novel ocean color index to detect floating algae in the global oceans","volume":"113","author":"Hu","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2011JC007395","article-title":"Chlorophyll a algorithms for oligotrophic oceans: A novel approach based on three-band reflectance difference","volume":"117","author":"Hu","year":"2012","journal-title":"J. Geophys. Res. Ocean."},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"14403","DOI":"10.3390\/rs71114403","article-title":"A remote sensing approach to estimate vertical profile classes of phytoplankton in a Eutrophic lake","volume":"7","author":"Xue","year":"2015","journal-title":"Remote Sens."},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/j.rse.2003.07.002","article-title":"Derivation of a shortwave infrared water stress index from MODIS near- and shortwave infrared data in a semiarid environment","volume":"87","author":"Fensholt","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"663","DOI":"10.2307\/1936256","article-title":"Derivation of Leaf-Area Index from Quality of Light on the Forest Floor","volume":"50","author":"Jordan","year":"1969","journal-title":"Ecology"},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/S0034-4257(02)00096-2","article-title":"Overview of the radiometric and biophysical performance of the MODIS vegetation indices","volume":"83","author":"Huete","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/0034-4257(79)90013-0","article-title":"Red and photographic infrared linear combinations for monitoring vegetation","volume":"8","author":"Tucker","year":"1979","journal-title":"Remote Sens. Environ."},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"271","DOI":"10.1016\/j.rse.2005.09.002","article-title":"Assessing vineyard condition with hyperspectral indices: Leaf and canopy reflectance simulation in a row-structured discontinuous canopy","volume":"99","author":"Miller","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1006\/jcss.1997.1504","article-title":"A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting","volume":"55","author":"Freund","year":"1997","journal-title":"J. Comput. Syst. Sci."},{"key":"ref_93","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1016\/S0034-4257(02)00078-0","article-title":"Global land cover mapping from MODIS: Algorithms and early results","volume":"83","author":"Friedl","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1016\/S0034-4257(00)00142-5","article-title":"Multiple Criteria for Evaluating Machine Learning Algorithms for Land Cover Classification from Satellite Data","volume":"74","author":"DeFries","year":"2000","journal-title":"Remote Sens. Environ."},{"key":"ref_95","doi-asserted-by":"crossref","unstructured":"Zhou, Z., Huang, J., Wang, J., Zhang, K., Kuang, Z., Zhong, S., and Song, X. (2015). Object-oriented classification of sugarcane using time-series middle-resolution remote sensing data based on AdaBoost. PLoS ONE, 10.","DOI":"10.1371\/journal.pone.0142069"},{"key":"ref_96","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_97","doi-asserted-by":"crossref","unstructured":"Congalton, R.G., and Green, K. (2009). Assessing the Accuracy of Remotely Sensed Data: Principles and Practices, CRC Press, Taylor & Francis Group. [2nd ed.].","DOI":"10.1201\/9781420055139"},{"key":"ref_98","unstructured":"Xu, L., Yan, P., and Chang, T. (November, January 14). Best first strategy for feature selection. Proceedings of the 9th International Conference on Pattern Recognition, Rome, Italy."},{"key":"ref_99","doi-asserted-by":"crossref","unstructured":"Cheng, Z., Zu, Z., and Lu, J. (2018). Traffic crash evolution characteristic analysis and spatiotemporal hotspot identification of urban road intersections. Sustainability, 11.","DOI":"10.3390\/su11010160"},{"key":"ref_100","doi-asserted-by":"crossref","unstructured":"Al-Ruzouq, R., Hamad, K., Abu Dabous, S., Zeiada, W., Khalil, M.A., and Voigt, T. (2019). Weighted Multi-attribute Framework to Identify Freeway Incident Hot Spots in a Spatiotemporal Context. Arab. J. Sci. Eng.","DOI":"10.1007\/s13369-019-03881-z"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/10\/1193\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:53:34Z","timestamp":1760187214000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/10\/1193"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,5,20]]},"references-count":100,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2019,5]]}},"alternative-id":["rs11101193"],"URL":"https:\/\/doi.org\/10.3390\/rs11101193","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,5,20]]}}}