{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T01:08:21Z","timestamp":1769735301464,"version":"3.49.0"},"reference-count":53,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2016,11,10]],"date-time":"2016-11-10T00:00:00Z","timestamp":1478736000000},"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>Accurately mapping the spatial distribution of forests in sub-humid to semi-arid regions over time is important for forest management but a challenging task. Relatively large uncertainties still exist in the spatial distribution of forests and forest changes in the sub-humid and semi-arid regions. Numerous publications have used either optical or synthetic aperture radar (SAR) remote sensing imagery, but the resultant forest cover maps often have large errors. In this study, we propose a pixel- and rule-based algorithm to identify and map annual forests from 2007 to 2010 in Oklahoma, USA, a transitional region with various climates and landscapes, using the integration of the L-band Advanced Land Observation Satellite (ALOS) PALSAR Fine Beam Dual Polarization (FBD) mosaic dataset and Landsat images. The overall accuracy and Kappa coefficient of the PALSAR\/Landsat forest map were about 88.2% and 0.75 in 2010, with the user and producer accuracy about 93.4% and 75.7%, based on the 3270 random ground plots collected in 2012 and 2013. Compared with the forest products from Japan Aerospace Exploration Agency (JAXA), National Land Cover Database (NLCD), Oklahoma Ecological Systems Map (OKESM) and Oklahoma Forest Resource Assessment (OKFRA), the PALSAR\/Landsat forest map showed great improvement. The area of the PALSAR\/Landsat forest was about 40,149 km2 in 2010, which was close to the area from OKFRA (40,468 km2), but much larger than those from JAXA (32,403 km2) and NLCD (37,628 km2). We analyzed annual forest cover dynamics, and the results show extensive forest cover loss (2761 km2, 6.9% of the total forest area in 2010) and gain (3630 km2, 9.0%) in southeast and central Oklahoma, and the total area of forests increased by 684 km2 from 2007 to 2010. This study clearly demonstrates the potential of data fusion between PALSAR and Landsat images for mapping annual forest cover dynamics in sub-humid to semi-arid regions, and the resultant forest maps would be helpful to forest management.<\/jats:p>","DOI":"10.3390\/rs8110933","type":"journal-article","created":{"date-parts":[[2016,11,10]],"date-time":"2016-11-10T10:51:39Z","timestamp":1478775099000},"page":"933","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["Mapping Annual Forest Cover in Sub-Humid and Semi-Arid Regions through Analysis of Landsat and PALSAR Imagery"],"prefix":"10.3390","volume":"8","author":[{"given":"Yuanwei","family":"Qin","sequence":"first","affiliation":[{"name":"Department of Microbiology and Plant Biology, Center for Spatial Analysis, University of Oklahoma, Norman, OK 73019, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0956-7428","authenticated-orcid":false,"given":"Xiangming","family":"Xiao","sequence":"additional","affiliation":[{"name":"Department of Microbiology and Plant Biology, Center for Spatial Analysis, University of Oklahoma, Norman, OK 73019, USA"},{"name":"Ministry of Education Key Laboratory of Biodiversity Science and Ecological Engineering, Institute of Biodiversity Science, Fudan University, Shanghai 200433, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1866-3999","authenticated-orcid":false,"given":"Jie","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Microbiology and Plant Biology, Center for Spatial Analysis, University of Oklahoma, Norman, OK 73019, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5687-803X","authenticated-orcid":false,"given":"Jinwei","family":"Dong","sequence":"additional","affiliation":[{"name":"Department of Microbiology and Plant Biology, Center for Spatial Analysis, University of Oklahoma, Norman, OK 73019, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kayti","family":"Ewing","sequence":"additional","affiliation":[{"name":"Oklahoma Natural Heritage Inventory, Department of Geography and Environmental Sustainability, University of Oklahoma, Norman, OK 73019, USA"},{"name":"Environmental Division, Arkansas State Highway and Transportation Department, Little Rock, AR 72209, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bruce","family":"Hoagland","sequence":"additional","affiliation":[{"name":"Oklahoma Natural Heritage Inventory, Department of Geography and Environmental Sustainability, University of Oklahoma, Norman, OK 73019, USA"},{"name":"Oklahoma Biological Survey, University of Oklahoma, Norman, OK 73019, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8225-3962","authenticated-orcid":false,"given":"Daniel","family":"Hough","sequence":"additional","affiliation":[{"name":"Oklahoma Biological Survey, University of Oklahoma, Norman, OK 73019, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Todd","family":"Fagin","sequence":"additional","affiliation":[{"name":"Oklahoma Natural Heritage Inventory, Department of Geography and Environmental Sustainability, University of Oklahoma, Norman, OK 73019, USA"},{"name":"Oklahoma Biological Survey, University of Oklahoma, Norman, OK 73019, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhenhua","family":"Zou","sequence":"additional","affiliation":[{"name":"Department of Microbiology and Plant Biology, Center for Spatial Analysis, University of Oklahoma, Norman, OK 73019, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"George","family":"Geissler","sequence":"additional","affiliation":[{"name":"Oklahoma Forestry Services, Oklahoma city, OK 73105, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"George","family":"Xian","sequence":"additional","affiliation":[{"name":"U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center, Sioux Falls, SD 57198, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Thomas","family":"Loveland","sequence":"additional","affiliation":[{"name":"U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center, Sioux Falls, SD 57198, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2016,11,10]]},"reference":[{"key":"ref_1","unstructured":"United Nations Convention to Combat Desertification Redd+ and desertification. Available online: http:\/\/www.unccd.int\/Lists\/SiteDocumentLibrary\/Publications\/Factsheet%207%20redd.ENGweb.pdf."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1038\/nclimate2816","article-title":"Conservation policy and the measurement of forests","volume":"6","author":"Sexton","year":"2015","journal-title":"Nat. Clim. Chang."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"20880","DOI":"10.1038\/srep20880","article-title":"Mapping forests in monsoon Asia with ALOS PALSAR 50-m mosaic images and MODIS imagery in 2010","volume":"6","author":"Qin","year":"2016","journal-title":"Sci. Rep."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"737","DOI":"10.1038\/ngeo671","article-title":"CO2 emissions from forest loss","volume":"2","author":"Morton","year":"2009","journal-title":"Nat. Geosci."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1029\/2008EO430001","article-title":"New satellites help quantify carbon sources and sinks","volume":"89","author":"Houghton","year":"2008","journal-title":"Eos Trans. Am. Geophys. Union"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"695","DOI":"10.1007\/s10021-004-0243-3","article-title":"Detecting long-term global forest change using continuous fields of tree-cover maps from 8-km advanced very high resolution radiometer (AVHRR) data for the years 1982\u201399","volume":"7","author":"Hansen","year":"2004","journal-title":"Ecosystems"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1303","DOI":"10.1080\/014311600210191","article-title":"Development of a global land cover characteristics database and IGBP DISCover from 1 km AVHRR data","volume":"21","author":"Loveland","year":"2000","journal-title":"Int. J. Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1175\/1087-3562(2003)007<0001:GPTCAA>2.0.CO;2","article-title":"Global percent tree cover at a spatial resolution of 500 meters: First results of the MODIS vegetation continuous fields algorithm","volume":"7","author":"Hansen","year":"2003","journal-title":"Earth Interact."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"9439","DOI":"10.1073\/pnas.0804042105","article-title":"Humid tropical forest clearing from 2000 to 2005 quantified by using multitemporal and multiresolution remotely sensed data","volume":"105","author":"Hansen","year":"2008","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_10","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_11","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_12","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1016\/j.rse.2014.08.017","article-title":"Global, Landsat-based forest-cover change from 1990 to 2000","volume":"155","author":"Kim","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1080\/17538947.2012.713190","article-title":"Global characterization and monitoring of forest cover using landsat data: Opportunities and challenges","volume":"5","author":"Townshend","year":"2012","journal-title":"Int. J. Digit. Earth"},{"key":"ref_14","first-page":"345","article-title":"Completion of the 2011 national land cover database for the conterminous united states-representing a decade of land cover change information","volume":"81","author":"Homer","year":"2015","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1016\/j.rse.2013.01.012","article-title":"A comprehensive change detection method for updating the National Land Cover Database to circa 2011","volume":"132","author":"Jin","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1016\/j.isprsjprs.2013.05.004","article-title":"Applications of ALOS PALSAR for monitoring biophysical parameters of a degraded black mangrove (Avicennia germinans) forest","volume":"82","author":"Kovacs","year":"2013","journal-title":"ISPRS J. Photogramm. Renmote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"875","DOI":"10.1109\/JSTARS.2012.2212701","article-title":"Retrieval of forest biomass from ALOS PALSAR data using a lookup table method","volume":"6","author":"Ni","year":"2013","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1016\/j.rse.2005.10.019","article-title":"Empirical relationships between AIRSAR backscatter and LIDAR-derived forest biomass, Queensland, Australia","volume":"100","author":"Lucas","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"132","DOI":"10.5589\/m04-058","article-title":"Long-term stability of L-band normalized radar cross section of Amazon rainforest using the JERS-1 SAR","volume":"31","author":"Shimada","year":"2005","journal-title":"Can. J. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1329","DOI":"10.1080\/01431160110092920","article-title":"Tropical forest cover monitoring: Estimates from the GRFM JERS-1 radar mosaics using wavelet zooming techniques and validation","volume":"23","author":"Sgrenzaroli","year":"2002","journal-title":"Int. J. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"2310","DOI":"10.1109\/36.868888","article-title":"The use of decision tree and multiscale texture for classification of JERS-1 SAR data over tropical forest","volume":"38","author":"Simard","year":"2000","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1201","DOI":"10.1080\/014311600210146","article-title":"Mapping land cover types in the Amazon basin using 1 km JERS-1 mosaic","volume":"21","author":"Saatchi","year":"2000","journal-title":"Int. J. Remote Sens."},{"key":"ref_23","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_24","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.rse.2014.04.012","article-title":"Using time series PALSAR gamma nought mosaics for automatic detection of tropical deforestation: A test study in Riau, Indonesia","volume":"155","author":"Motohka","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1016\/j.rse.2013.08.050","article-title":"Change detection of boreal forest using bi-temporal ALOS PALSAR backscatter data","volume":"155","author":"Pantze","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/j.rse.2012.08.022","article-title":"A comparison of forest cover maps in mainland southeast Asia from multiple sources: PALSAR, MERIS, MODIS and FRA","volume":"127","author":"Dong","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1016\/S0034-4257(96)00154-X","article-title":"An evaluation of AIRSAR and SIR-C\/X-SAR images for mapping northern forest attributes in Maine, USA","volume":"59","author":"Ranson","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"3855","DOI":"10.1080\/01431160010006926","article-title":"Cloud cover in Landsat observations of the Brazilian Amazon","volume":"22","author":"Asner","year":"2001","journal-title":"Int. J. Remote. Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"28","DOI":"10.2307\/1942049","article-title":"Relationships between NDVI, canopy structure, and photosynthesis in 3 Californian vegetation types","volume":"5","author":"Gamon","year":"1995","journal-title":"Ecol. Appl."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1080\/01431161.2014.999167","article-title":"Phenology-based classification of vegetation cover types in Northeast China using MODIS NDVI and EVI time series","volume":"36","author":"Yan","year":"2015","journal-title":"Int. J. Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"271","DOI":"10.5589\/m02-096","article-title":"Disturbance recognition in the boreal forest using radar and Landsat-7","volume":"29","author":"Ranson","year":"2003","journal-title":"Can. J. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2007GL030980","article-title":"Larsen B Ice Shelf rheology preceding its disintegration inferred by a control method","volume":"34","author":"Khazendar","year":"2007","journal-title":"Geophys. Res. Lett."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"518","DOI":"10.5589\/m03-014","article-title":"Synergy of multitemporal ERS-1 SAR and Landsat TM data for classification of agricultural crops","volume":"29","author":"Ban","year":"2003","journal-title":"Can. J. Remote Sens."},{"key":"ref_34","first-page":"1289","article-title":"Radar and optical data comparison\/integration for urban delineation: A case study","volume":"68","author":"Haack","year":"2002","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"276","DOI":"10.1016\/j.rse.2014.10.001","article-title":"Fusing Landsat and SAR time series to detect deforestation in the tropics","volume":"156","author":"Reiche","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1016\/j.rse.2014.09.034","article-title":"SAR and optical remote sensing: Assessment of complementarity and interoperability in the context of a large-scale operational forest monitoring system","volume":"156","author":"Lehmann","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1038\/nclimate2919","article-title":"Combining satellite data for better tropical forest monitoring","volume":"6","author":"Reiche","year":"2016","journal-title":"Nat. Clim. Chang."},{"key":"ref_38","unstructured":"Diamond, D.D., and Elliott, L.F. (2015). Oklahoma Ecological Systems Mapping Interpretive Booklet: Methods, Short Type Descriptions, and Summary Results, Oklahoma Department of Wildlife Conservation."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"3915","DOI":"10.1109\/TGRS.2009.2023909","article-title":"PALSAR radiometric and geometric calibration","volume":"47","author":"Shimada","year":"2009","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_40","unstructured":"Food and Agriculture Organization of the United Nations (2012). Global Forest Resource Assessment (FRA) 2010, FAO."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.isprsjprs.2015.08.010","article-title":"Forest cover maps of China in 2010 from multiple approaches and data sources: PALSAR, Landsat, MODIS, FRA, and NFI","volume":"109","author":"Qin","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1063","DOI":"10.1002\/2013JG002493","article-title":"Mapping global seasonal forest background reflectivity with multi-angle imaging spectroradiometer data","volume":"119","author":"Jiao","year":"2014","journal-title":"J. Geophys. Res. Biogeosci."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/S0034-4257(99)00057-7","article-title":"Relationships between leaf area index and Landsat TM spectral vegetation indices across three temperate zone sites","volume":"70","author":"Turner","year":"1999","journal-title":"Remote Sens. Environ."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1016\/j.rse.2015.06.007","article-title":"A 30-year (1984\u20132013) record of annual urban dynamics of Beijing city derived from Landsat data","volume":"166","author":"Li","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_45","unstructured":"Johnson, E., Geissler, G., and Murray, D. (2010). The Oklahoma Forest Resource Assessment, 2010."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"480","DOI":"10.1126\/science.1118051","article-title":"Selective logging in the Brazilian Amazon","volume":"310","author":"Asner","year":"2005","journal-title":"Science"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"1561","DOI":"10.1016\/j.rse.2010.02.011","article-title":"Forest carbon densities and uncertainties from Lidar, quickbird, and field measurements in California","volume":"114","author":"Gonzalez","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_48","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_49","doi-asserted-by":"crossref","first-page":"709","DOI":"10.1111\/j.1461-0248.2011.01630.x","article-title":"Impacts of shrub encroachment on ecosystem structure and functioning: Towards a global synthesis","volume":"14","author":"Eldridge","year":"2011","journal-title":"Ecol. Lett."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"697","DOI":"10.1890\/11-1199.1","article-title":"Woody encroachment decreases diversity across North American grasslands and savannas","volume":"93","author":"Ratajczak","year":"2012","journal-title":"Ecology"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1029\/2010JG001506","article-title":"Woody plant proliferation in North American drylands: A synthesis of impacts on ecosystem carbon balance","volume":"116","author":"Barger","year":"2011","journal-title":"J. Geophys. Res. Biogeosci."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"308","DOI":"10.1890\/03-0583","article-title":"Ecohydrological implications of woody plant encroachment","volume":"86","author":"Huxman","year":"2005","journal-title":"Ecology"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"12948","DOI":"10.1073\/pnas.1320585111","article-title":"Effect of woody-plant encroachment on livestock production in North and South America","volume":"111","author":"Anadon","year":"2014","journal-title":"Proc. Natl. Acad. Sci. USA"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/8\/11\/933\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T19:35:16Z","timestamp":1760211316000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/8\/11\/933"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,11,10]]},"references-count":53,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2016,11]]}},"alternative-id":["rs8110933"],"URL":"https:\/\/doi.org\/10.3390\/rs8110933","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,11,10]]}}}