{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T14:03:56Z","timestamp":1773669836365,"version":"3.50.1"},"reference-count":61,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2016,5,20]],"date-time":"2016-05-20T00:00:00Z","timestamp":1463702400000},"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>Achieving more timely, accurate and transparent information on the distribution and dynamics of the world\u2019s land cover is essential to understanding the fundamental characteristics, processes and threats associated with human-nature-climate interactions. Higher resolution (~30\u201350 m) land cover mapping is expected to advance the understanding of the multi-dimensional interactions of the human-nature-climate system with the potentiality of representing most of the biophysical processes and characteristics of the land surface. However, mapping at 30-m resolution is complicated with existing manual techniques, due to the laborious procedures involved with the analysis and interpretation of huge volumes of satellite data. To cope with this problem, an automated technique was explored for the production of a high resolution land cover map at a national scale. The automated technique consists of the construction of a reference library by the optimum combination of the spectral, textural and topographic features and predicting the results using the optimum random forests model. The feature-rich reference library-driven automated technique was used to produce the Japan 30-m resolution land cover (JpLC-30) map of 2013\u20132015. The JpLC-30 map consists of seven major land cover types: water bodies, deciduous forests, evergreen forests, croplands, bare lands, built-up areas and herbaceous. The resultant JpLC-30 map was compared to the existing 50-m resolution JAXA High Resolution Land-Use and Land-Cover (JHR LULC) map with reference to Google Earth\u2122 images. The JpLC-30 map provides more accurate and up-to-date land cover information than the JHR LULC map. This research recommends an effective utilization of the spectral, textural and topographic information to increase the accuracy of automated land cover mapping.<\/jats:p>","DOI":"10.3390\/rs8050429","type":"journal-article","created":{"date-parts":[[2016,5,21]],"date-time":"2016-05-21T19:24:37Z","timestamp":1463858677000},"page":"429","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["Production of the Japan 30-m Land Cover Map of 2013\u20132015 Using a Random Forests-Based Feature Optimization Approach"],"prefix":"10.3390","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5706-4417","authenticated-orcid":false,"given":"Ram","family":"Sharma","sequence":"first","affiliation":[{"name":"Center for Environmental Remote Sensing (CEReS), Chiba University, 1-33 Yayoi-cho, Inage-ku, Chiba 263-8522, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ryutaro","family":"Tateishi","sequence":"additional","affiliation":[{"name":"Center for Environmental Remote Sensing (CEReS), Chiba University, 1-33 Yayoi-cho, Inage-ku, Chiba 263-8522, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8072-7562","authenticated-orcid":false,"given":"Keitarou","family":"Hara","sequence":"additional","affiliation":[{"name":"Department of Informatics, Tokyo University of Information Sciences, 4-1 Onaridai, Wakaba-ku, Chiba 265-8501, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kotaro","family":"Iizuka","sequence":"additional","affiliation":[{"name":"Research Institute for Sustainable Humanosphere, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2016,5,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"494","DOI":"10.1126\/science.277.5325.494","article-title":"Human domination of earth\u2019s ecosystems","volume":"277","author":"Vitousek","year":"1997","journal-title":"Science"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"574","DOI":"10.1126\/science.285.5427.574","article-title":"The U.S. carbon budget: Contributions from land-use change","volume":"285","author":"Houghton","year":"1999","journal-title":"Science"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"570","DOI":"10.1126\/science.1111772","article-title":"Global consequences of land use","volume":"309","author":"Foley","year":"2005","journal-title":"Science"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"20666","DOI":"10.1073\/pnas.0704119104","article-title":"The emergence of land change science for global environmental change and sustainability","volume":"104","author":"Turner","year":"2007","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"369","DOI":"10.1146\/annurev.environ.33.020107.113339","article-title":"Terrestrial vegetation in the coupled human-earth system: Contributions of remote sensing","volume":"33","author":"DeFries","year":"2008","journal-title":"Annu. Rev. Environ. Resour."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"4476","DOI":"10.1021\/cr500446g","article-title":"Land use change impacts on air quality and climate","volume":"115","author":"Heald","year":"2015","journal-title":"Chem. Rev."},{"key":"ref_7","first-page":"20150294","article-title":"The impact of over 80 years of land cover changes on bee and wasp pollinator communities in England","volume":"282","author":"Senapathi","year":"2015","journal-title":"Proc. R. Soc. Lond. B Biol. Sci."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1023\/A:1013051420309","article-title":"Effects of land cover conversion on surface climate","volume":"52","author":"Bounoua","year":"2002","journal-title":"Clim. Chang."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Ge, J., Qi, J., Lofgren, B.M., Moore, N., Torbick, N., and Olson, J.M. (2007). Impacts of land use\/cover classification accuracy on regional climate simulations. J. Geophys. Res. Atmos., 112.","DOI":"10.1029\/2006JD007404"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2118","DOI":"10.1002\/joc.2150","article-title":"Research priorities in land use and land-cover change for the earth system and integrated assessment modelling","volume":"30","author":"Hibbard","year":"2010","journal-title":"Int. J. Climatol."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Ganzeveld, L., Bouwman, L., Stehfest, E., van Vuuren, D.P., Eickhout, B., and Lelieveld, J. (2010). Impact of future land use and land cover changes on atmospheric chemistry-climate interactions. J. Geophys. Res. Atmos., 115.","DOI":"10.1029\/2010JD014041"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"14256","DOI":"10.1073\/pnas.182560099","article-title":"Carbon emissions from tropical deforestation and regrowth based on satellite observations for the 1980s and 1990s","volume":"99","author":"DeFries","year":"2002","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"534","DOI":"10.1016\/j.rse.2006.01.020","article-title":"Exploiting synergies of global land cover products for carbon cycle modeling","volume":"101","author":"Jung","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2333","DOI":"10.1016\/j.ecolmodel.2011.03.042","article-title":"Estimating California ecosystem carbon change using process model and land cover disturbance data: 1951\u20132000","volume":"222","author":"Liu","year":"2011","journal-title":"Ecol. Model."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2027","DOI":"10.5194\/bg-8-2027-2011","article-title":"Impacts of land cover and climate data selection on understanding terrestrial carbon dynamics and the CO2 airborne fraction","volume":"8","author":"Poulter","year":"2011","journal-title":"Biogeosciences"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"499","DOI":"10.1111\/j.1523-1739.2008.01083.x","article-title":"Delivering a global, terrestrial, biodiversity observation system through remote sensing","volume":"23","author":"Buchanan","year":"2009","journal-title":"Conserv. Biol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"2237","DOI":"10.1021\/es504380t","article-title":"High-resolution assessment of land use impacts on biodiversity in life cycle assessment using species habitat suitability models","volume":"49","author":"Curran","year":"2015","journal-title":"Environ. Sci. Technol."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Liang, L., Xu, B., Chen, Y., Liu, Y., Cao, W., Fang, L., Feng, L., Goodchild, M.F., Gong, P., and Li, W. (2010). Combining spatial-temporal and phylogenetic analysis approaches for improved understanding on global H5N1 transmission. PLoS ONE, 5.","DOI":"10.1371\/journal.pone.0013575"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/S0034-4257(01)00295-4","article-title":"Status of land cover classification accuracy assessment","volume":"80","author":"Foody","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"168","DOI":"10.1016\/j.rse.2009.08.016","article-title":"MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets","volume":"114","author":"Friedl","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_21","first-page":"99","article-title":"Production of global land cover data\u2013GLCNMO2008","volume":"6","author":"Tateishi","year":"2014","journal-title":"J. Geogr. Geol."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"3679","DOI":"10.1080\/01431160802698919","article-title":"Global irrigated area map (GIAM), derived from remote sensing, for the end of the last millennium","volume":"30","author":"Thenkabail","year":"2009","journal-title":"Int. J. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1016\/j.jag.2015.01.014","article-title":"Global rain-fed, irrigated, and paddy croplands: A new high resolution map derived from remote sensing, crop inventories and climate data","volume":"38","author":"Salmon","year":"2015","journal-title":"Int. J. Appl. Earth Observ. Geoinform."},{"key":"ref_24","first-page":"1","article-title":"A global, high-resolution (30-m) inland water body dataset for 2000: First results of a topographic\u2013spectral classification algorithm","volume":"9","author":"Feng","year":"2015","journal-title":"Int. J. Dig. Earth"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"13807","DOI":"10.3390\/rs71013807","article-title":"Developing superfine water index (SWI) for global water cover mapping using MODIS data","volume":"7","author":"Sharma","year":"2015","journal-title":"Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.isprsjprs.2014.08.004","article-title":"Spaceborne SAR data for global urban mapping at 30m resolution using a robust urban extractor","volume":"103","author":"Ban","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"054011","DOI":"10.1088\/1748-9326\/10\/5\/054011","article-title":"A global map of urban extent from nightlights","volume":"10","author":"Zhou","year":"2015","journal-title":"Environ. Res. Lett."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"348","DOI":"10.1016\/j.rse.2014.10.015","article-title":"Development of a global inundation map at high spatial resolution from topographic downscaling of coarse-scale remote sensing data","volume":"158","author":"Lehner","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"850","DOI":"10.1126\/science.1244693","article-title":"High-resolution global maps of 21st-century forest cover change","volume":"342","author":"Hansen","year":"2013","journal-title":"Science"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.rse.2014.04.014","article-title":"New global forest\/non-forest maps from ALOS PALSAR data (2007\u20132010)","volume":"155","author":"Shimada","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"2538","DOI":"10.1016\/j.rse.2007.11.013","article-title":"Some challenges in global land cover mapping: An assessment of agreement and accuracy in existing 1 km datasets","volume":"112","author":"Herold","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1016\/j.jag.2005.12.002","article-title":"A spatial comparison of four satellite derived 1 km global land cover datasets","volume":"8","author":"McCallum","year":"2006","journal-title":"Int. J. Appl. Earth Observ. Geoinform."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"12070","DOI":"10.3390\/rs61212070","article-title":"Global land cover mapping: A review and uncertainty analysis","volume":"6","author":"Congalton","year":"2014","journal-title":"Remote Sens."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"4573","DOI":"10.1080\/01431161.2014.930206","article-title":"Meta-discoveries from a synthesis of satellite-based land-cover mapping research","volume":"35","author":"Yu","year":"2014","journal-title":"Int. J. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"5309","DOI":"10.1080\/01431161.2015.1093195","article-title":"An overview of 21 global and 43 regional land-cover mapping products","volume":"36","author":"Grekousis","year":"2015","journal-title":"Int. J. Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1016\/j.jag.2013.03.005","article-title":"Next generation of global land cover characterization, mapping, and monitoring","volume":"25","author":"Giri","year":"2013","journal-title":"Int. J. Appl. Earth Observ. Geoinform."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"829","DOI":"10.14358\/PERS.70.7.829","article-title":"Development of a 2001 national land-cover database for the United States","volume":"70","author":"Homer","year":"2004","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_38","first-page":"337","article-title":"Completion of the 2001 national land cover database for the counterminous United States","volume":"73","author":"Homer","year":"2007","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_39","first-page":"345","article-title":"Completion of the 2011 national land cover database for the conterminous United States\u2013Representing a decade of land cover change information","volume":"81","author":"Homer","year":"2015","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1016\/j.isprsjprs.2014.09.002","article-title":"Global land cover mapping at 30 m resolution: A POK-based operational approach","volume":"103","author":"Chen","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"9494","DOI":"10.3390\/rs6109494","article-title":"Land cover characterization and mapping of South America for the year 2010 using Landsat 30 m satellite data","volume":"6","author":"Giri","year":"2014","journal-title":"Remote Sens."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Takahashi, M., Nasahara, K.N., Tadono, T., Watanabe, T., Dotsu, M., Sugimura, T., and Tomiyama, N. (2013, January 21\u201326). JAXA high resolution land-use and land-cover map of Japan. Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, Melbourne, Australia.","DOI":"10.1109\/IGARSS.2013.6723299"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1995","DOI":"10.1002\/(SICI)1099-1085(19981030)12:13\/14<1995::AID-HYP714>3.0.CO;2-C","article-title":"Land use\/cover changes in Japan: From the past to the future","volume":"12","author":"Himiyama","year":"1998","journal-title":"Hydrol. Process."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"23","DOI":"10.2478\/jlecol-2014-0019","article-title":"Monitoring landscape changes in Japan using classification of MODIS data combined with a landscape transformation sere (LTS) model","volume":"7","author":"Harada","year":"2015","journal-title":"J. Landsc. Ecol."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"2607","DOI":"10.1080\/01431161.2012.748992","article-title":"Finer resolution observation and monitoring of global land cover: First mapping results with Landsat TM and ETM+ data","volume":"34","author":"Gong","year":"2013","journal-title":"Int. J. Remote Sens."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.rse.2011.08.026","article-title":"The next Landsat satellite: The Landsat Data Continuity Mission","volume":"122","author":"Irons","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1016\/j.rse.2014.02.001","article-title":"Landsat-8: Science and product vision for terrestrial global change research","volume":"145","author":"Roy","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_48","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_49","doi-asserted-by":"crossref","first-page":"610","DOI":"10.1109\/TSMC.1973.4309314","article-title":"Textural features for image classification","volume":"SMC-3","author":"Haralick","year":"1973","journal-title":"IEEE Trans. Syst. Man Cybern."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1016\/0734-189X(84)90197-X","article-title":"Segmentation of a high-resolution urban scene using texture operators","volume":"25","author":"Conners","year":"1984","journal-title":"Comput. Vis. Graph. Image Process."},{"key":"ref_51","unstructured":"Bishop, C.M. (2006). Pattern Recognition and Machine Learning, Springer. Information Science and Statistics."},{"key":"ref_52","unstructured":"Breiman, L., Friedman, J.H., Olshen, R.A., and Stone, C.J. (1984). Classification and Regression Trees, Wadsworth."},{"key":"ref_53","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_54","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1080\/01431160412331269698","article-title":"Random forest classifier for remote sensing classification","volume":"26","author":"Pal","year":"2005","journal-title":"Int. J. Remote Sens."},{"key":"ref_55","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_56","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/j.rse.2011.12.003","article-title":"Random forest classification of Mediterranean land cover using multi-seasonal imagery and multi-seasonal texture","volume":"121","author":"Atkinson","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1080\/2150704X.2014.882526","article-title":"High-resolution landcover classification using Random Forest","volume":"5","author":"Hayes","year":"2014","journal-title":"Remote Sens. Lett."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1177\/001316446002000104","article-title":"A Coefficient of agreement for nominal scales","volume":"20","author":"Cohen","year":"1960","journal-title":"Educ. Psychol. Meas."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1111\/j.1469-1809.1936.tb02137.x","article-title":"The use of multiple measurements in taxonomic problems","volume":"7","author":"Fisher","year":"1936","journal-title":"Ann. Eugen."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1111\/j.2517-6161.1948.tb00008.x","article-title":"The utilization of multiple measurements in problems of biological classification","volume":"10","author":"Rao","year":"1948","journal-title":"J. R. Stat. Soc. Ser. B (Methodol.)"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"8188","DOI":"10.1080\/01431161.2014.980920","article-title":"The roles of textural images in improving land-cover classification in the Brazilian Amazon","volume":"35","author":"Lu","year":"2014","journal-title":"Int. J. Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/8\/5\/429\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T19:24:14Z","timestamp":1760210654000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/8\/5\/429"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,5,20]]},"references-count":61,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2016,5]]}},"alternative-id":["rs8050429"],"URL":"https:\/\/doi.org\/10.3390\/rs8050429","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,5,20]]}}}