{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T20:55:56Z","timestamp":1774126556175,"version":"3.50.1"},"reference-count":50,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2012,9,12]],"date-time":"2012-09-12T00:00:00Z","timestamp":1347408000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In previous attempts to identify aquatic vegetation from remotely-sensed images using classification trees (CT), the images used to apply CT models to different times or locations necessarily originated from the same satellite sensor as that from which the original images used in model development came, greatly limiting the application of CT. We have developed an effective normalization method to improve the robustness of CT models when applied to images originating from different sensors and dates. A total of 965 ground-truth samples of aquatic vegetation types were obtained in 2009 and 2010 in Taihu Lake, China. Using relevant spectral indices (SI) as classifiers, we manually developed a stable CT model structure and then applied a standard CT algorithm to obtain quantitative (optimal) thresholds from 2009 ground-truth data and images from Landsat7-ETM+, HJ-1B-CCD, Landsat5-TM and ALOS-AVNIR-2 sensors. Optimal CT thresholds produced average classification accuracies of 78.1%, 84.7% and 74.0% for emergent vegetation, floating-leaf vegetation and submerged vegetation, respectively. However, the optimal CT thresholds for different sensor images differed from each other, with an average relative variation (RV) of 6.40%. We developed and evaluated three new approaches to normalizing the images. The best-performing method (Method of 0.1% index scaling) normalized the SI images using tailored percentages of extreme pixel values. Using the images normalized by Method of 0.1% index scaling, CT models for a particular sensor in which thresholds were replaced by those from the models developed for images originating from other sensors provided average classification accuracies of 76.0%, 82.8% and 68.9% for emergent vegetation, floating-leaf vegetation and submerged vegetation, respectively. Applying the CT models developed for normalized 2009 images to 2010 images resulted in high classification (78.0%\u201393.3%) and overall (92.0%\u201393.1%) accuracies. Our results suggest that Method of 0.1% index scaling provides a feasible way to apply CT models directly to images from sensors or time periods that differ from those of the images used to develop the original models.<\/jats:p>","DOI":"10.3390\/s120912437","type":"journal-article","created":{"date-parts":[[2012,9,12]],"date-time":"2012-09-12T12:11:41Z","timestamp":1347451901000},"page":"12437-12454","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["A Method for Application of Classification Tree Models to Map Aquatic Vegetation Using Remotely Sensed Images from Different Sensors and Dates"],"prefix":"10.3390","volume":"12","author":[{"given":"Hao","family":"Jiang","sequence":"first","affiliation":[{"name":"Department of Biological Science and Technology, Nanjing University, 22 Hankou Rd., Nanjing 210093, China"},{"name":"HydroChina Huadong Engineering Corporation, 22 Chaowang Rd., Hangzhou 310014, China"}]},{"given":"Dehua","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Biological Science and Technology, Nanjing University, 22 Hankou Rd., Nanjing 210093, China"}]},{"given":"Ying","family":"Cai","sequence":"additional","affiliation":[{"name":"Department of Biological Science and Technology, Nanjing University, 22 Hankou Rd., Nanjing 210093, China"}]},{"given":"Shuqing","family":"An","sequence":"additional","affiliation":[{"name":"Department of Biological Science and Technology, Nanjing University, 22 Hankou Rd., Nanjing 210093, China"}]}],"member":"1968","published-online":{"date-parts":[[2012,9,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"399","DOI":"10.1016\/j.ecss.2005.11.020","article-title":"Assessment of changes in the seagrass-dominated submerged vegetation of tropical Chwaka Bay (Zanzibar) using satellite remote sensing","volume":"67","author":"Bodin","year":"2006","journal-title":"Estuar. Coast. Shelf Sci."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1007\/s10750-007-9154-6","article-title":"Global diversity of aquatic macrophytes in freshwater","volume":"595","author":"Chambers","year":"2008","journal-title":"Hydrobiologia"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"369","DOI":"10.1016\/j.scitotenv.2008.06.018","article-title":"Flow controls on lowland river macrophytes: A review","volume":"400","author":"Franklin","year":"2008","journal-title":"Sci. Total Environ."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1017\/S0376892902000061","article-title":"Environmental threats and environmental future of estuaries","volume":"29","author":"Kennish","year":"2002","journal-title":"Environ. Conserv."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1126\/science.222.4619.51","article-title":"Chesapeake Bay: An unprecedented decline in submerged aquatic vegetation","volume":"222","author":"Orth","year":"1983","journal-title":"Science"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"629","DOI":"10.1126\/science.1059199","article-title":"Historical overfishing and the recent collapse of coastal ecosystems","volume":"293","author":"Jackson","year":"2001","journal-title":"Science"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/S0304-3770(03)00105-0","article-title":"An evaluation of approaches used to determine the distribution and biomass of emergent and submerged aquatic macrophytes over large spatial scales","volume":"77","author":"Vis","year":"2003","journal-title":"Aquat. Bot."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1007\/s10661-007-9855-3","article-title":"Remote sensing of aquatic vegetation: Theory and applications","volume":"140","author":"Silva","year":"2008","journal-title":"Environ. Monit. Assess"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1016\/j.aquabot.2010.08.001","article-title":"Two decades of macrophyte expansion on the shores of a large shallow northern temperate lake-a retrospective series of satellite images","volume":"93","author":"Liira","year":"2010","journal-title":"Aquat. Bot."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1007\/s10750-008-9675-7","article-title":"Environmental science and management of coastal lagoons in the Southern Mediterranean Region: Key issues revealed by the MELMARINA Project","volume":"622","author":"Thompson","year":"2009","journal-title":"Hydrobiologia"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1007\/s10750-010-0466-6","article-title":"High-resolution satellite remote sensing of littoral vegetation of Lake Sevan (Armenia) as a basis for monitoring and assessment","volume":"661","author":"Heblinski","year":"2011","journal-title":"Hydrobiologia"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1658","DOI":"10.1111\/j.1365-2427.2010.02400.x","article-title":"Differentiating aquatic plant communities in a eutrophic river using hyperspectral and multispectral remote sensing","volume":"55","author":"Tian","year":"2010","journal-title":"Freshw. Biol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2138","DOI":"10.1016\/j.jenvman.2007.06.022","article-title":"Identification and mapping of submerged plants in a shallow lake using quickbird satellite data","volume":"90","author":"Dogan","year":"2009","journal-title":"J. Environ. Manage"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1016\/j.rse.2005.02.017","article-title":"Retrospective seagrass change detection in a shallow coastal tidal Australian lake","volume":"97","author":"Dekker","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2130","DOI":"10.1016\/j.jenvman.2007.06.031","article-title":"Mapping wetlands in the Lower Mekong Basin for wetland resource and conservation management using Landsat ETM images and field survey data","volume":"90","author":"MacAlister","year":"2009","journal-title":"J. Environ. Manage"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"552","DOI":"10.1016\/j.rse.2009.10.009","article-title":"Wetland monitoring using classification trees and SPOT-5 seasonal time series","volume":"114","author":"Davranche","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1998","DOI":"10.1016\/j.rse.2010.04.007","article-title":"Spatial and temporal variability of macrophyte cover and productivity in the eastern Amazon floodplain: A remote sensing approach","volume":"114","author":"Silva","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"465","DOI":"10.1672\/0277-5212(2006)26[465:MWARAU]2.0.CO;2","article-title":"Mapping wetlands and riparian areas using Landsat ETM+ imagery and decision-tree-based models","volume":"26","author":"Baker","year":"2006","journal-title":"Wetlands"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1023\/A:1020887204285","article-title":"The use of remote sensing and GIS in the sustainable management of tropical coastal ecosystems","volume":"4","year":"2002","journal-title":"Environ. Dev. Sustain."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1007\/s10750-008-9682-8","article-title":"Application of remote sensing to site characterisation and environmental change analysis of North African coastal lagoons","volume":"622","author":"Ahmed","year":"2009","journal-title":"Hydrobiologia"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"469","DOI":"10.1007\/s10750-010-0537-8","article-title":"Monitoring the dynamics of an invasive emergent macrophyte community using operational remote sensing data","volume":"661","author":"Albright","year":"2011","journal-title":"Hydrobiologia"},{"key":"ref_22","first-page":"685","article-title":"Utilization of satellite data for inventorying prairie ponds and potholes","volume":"5","author":"Work","year":"1976","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"464","DOI":"10.4319\/lo.2003.48.1_part_2.0464","article-title":"Spatial and temporal variation in spectral reflectance: Are seagrass species spectrally distinct?","volume":"48","author":"Fyfe","year":"2003","journal-title":"Limnol. Oceanogr."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1016\/j.ecolind.2010.05.003","article-title":"Mapping changes to vegetation pattern in a restoring wetland: Finding pattern metrics that are consistent across spatial scale and time","volume":"11","author":"Kelly","year":"2011","journal-title":"Ecol. Indic."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"316","DOI":"10.1016\/S0034-4257(03)00010-5","article-title":"National Park vegetation mapping using multitemporal Landsat 7 data and a decision tree classifier","volume":"85","author":"Brown","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"582","DOI":"10.1016\/j.rse.2006.10.019","article-title":"Improved wetland remote sensing in Yellowstone National Park using classification trees to combine TM imagery and ancillary environmental data","volume":"107","author":"Wright","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1577\/1548-8446(2007)32[167:UOIITM]2.0.CO;2","article-title":"Use of IKONOS imagery to map coastal wetlands of Georgian Bay","volume":"32","author":"Wei","year":"2007","journal-title":"Fisheries"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s13157-010-0105-z","article-title":"Mapping floating and emergent aquatic vegetation in coastal wetlands of Eastern Georgian Bay, Lake Huron, Canada","volume":"30","author":"Midwood","year":"2010","journal-title":"Wetlands"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1016\/j.jenvman.2011.10.007","article-title":"Remote sensing of aquatic vegetation distribution in Taihu Lake using an improved classification tree with modified thresholds","volume":"95","author":"Zhao","year":"2012","journal-title":"J. Environ. Manage"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"304","DOI":"10.1016\/S0034-4257(01)00211-5","article-title":"A generalized approach to the vicarious calibration of multiple Earth observation sensors using hyperspectral data","volume":"77","author":"Teillet","year":"2001","journal-title":"Remote Sens. Environ."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1080\/014311697219286","article-title":"Multi-sensor analysis of NDVI, surface temperature and biophysical variables at a mixed grassland site","volume":"18","author":"Goetz","year":"1997","journal-title":"Int. J. Remote Sens."},{"key":"ref_32","first-page":"159","article-title":"Temporal and spatial variation of aquatic macrophytes in west Taihu Lake","volume":"27","author":"Liu","year":"2007","journal-title":"Acta Ecol. Sinica."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"790","DOI":"10.18307\/2008.0618","article-title":"Aquatic macrophytes in East Lake Taihu and its interaction with water environment","volume":"20","author":"He","year":"2008","journal-title":"J. Lake Sci."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1569","DOI":"10.1016\/j.ecoleng.2009.04.003","article-title":"Lake eutrophication: Control countermeasures and recycling exploitation","volume":"35","author":"Qin","year":"2009","journal-title":"Ecol. Eng."},{"key":"ref_35","unstructured":"Lee, X. (2009). The Human-Induced Driver on the Development of Lake Taihu, Lectures on China's Environment, Yale School of Forestry and Environmental Studies."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1016\/j.advwatres.2010.08.010","article-title":"Estimation of water clarity in Taihu Lake and surrounding rivers using Landsat imagery","volume":"34","author":"Zhao","year":"2011","journal-title":"Adv. Water Resour."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"3988","DOI":"10.3390\/s8063988","article-title":"Detecting aquatic vegetation changes in Taihu Lake, China using multi-temporal satellite imagery","volume":"8","author":"Ma","year":"2008","journal-title":"Sensors"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1023\/A:1020908432489","article-title":"Satellite remote sensing of wetlands","volume":"10","author":"Ozesmi","year":"2002","journal-title":"Wetlands Ecol. Manag."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"4330","DOI":"10.1016\/S0043-1354(02)00146-X","article-title":"Application of Landsat imagery to regional-scale assessments of lake clarity","volume":"36","author":"Kloiber","year":"2002","journal-title":"Water Res."},{"key":"ref_40","first-page":"1025","article-title":"Image-based atmospheric corrections-revisited and improved","volume":"62","author":"Chavez","year":"1996","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"3271","DOI":"10.1016\/j.watres.2007.05.018","article-title":"Concurrent monitoring of vessels and water turbidity enhances the strength of evidence in remotely sensed dredging impact assessment","volume":"41","author":"Wu","year":"2007","journal-title":"Water Res."},{"key":"ref_42","first-page":"2898","article-title":"Spatial distribution characteristics and ecological significance of alkaline phosphatase in water column of Tahihu Lake","volume":"30","author":"Lu","year":"2009","journal-title":"Environ. Sci."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"145","DOI":"10.18307\/2008.0202","article-title":"Cyanobacteria bloom monitoring with remote sensing in Lake Taihu","volume":"20","author":"Duan","year":"2008","journal-title":"J. Lake Sci."},{"key":"ref_44","unstructured":"Rouse, J.W., Haas, R.H., Schell, J.A., Deering, D.W., and Harlan, J.C. (1974). NASA\/GSFC, Type III, Final Report, Texas A & M University."},{"key":"ref_45","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_46","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1016\/S0048-9697(00)00688-4","article-title":"Detection of water quality using simulated satellite data and semi-empirical algorithms in Finland","volume":"268","author":"Hannonen","year":"2001","journal-title":"Sci. Total Environ."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"412","DOI":"10.1016\/j.rse.2003.08.010","article-title":"Intercalibration of vegetation indices from different sensor systems","volume":"88","author":"Steven","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_48","first-page":"967","article-title":"Relative radiometric normalization performance for change detection from multi-date satellite images","volume":"66","author":"Yang","year":"2000","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1016\/0924-2716(96)00018-4","article-title":"Comparison of relative radiometric normalization techniques","volume":"51","author":"Yuan","year":"1996","journal-title":"ISPRS J. Photogramm"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"2774","DOI":"10.3390\/s8042774","article-title":"Relative radiometric normalization and atmospheric correction of a SPOT 5 time series","volume":"8","author":"Lafrance","year":"2008","journal-title":"Sensors"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/12\/9\/12437\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T21:52:19Z","timestamp":1760219539000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/12\/9\/12437"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012,9,12]]},"references-count":50,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2012,9]]}},"alternative-id":["s120912437"],"URL":"https:\/\/doi.org\/10.3390\/s120912437","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2012,9,12]]}}}