{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T21:09:20Z","timestamp":1787951360852,"version":"build-2784847793"},"reference-count":42,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2019,11,18]],"date-time":"2019-11-18T00:00:00Z","timestamp":1574035200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002322","name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","doi-asserted-by":"publisher","award":["001"],"award-info":[{"award-number":["001"]}],"id":[{"id":"10.13039\/501100002322","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003593","name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","doi-asserted-by":"publisher","award":["305054\/2016-3. 95\/5000"],"award-info":[{"award-number":["305054\/2016-3. 95\/5000"]}],"id":[{"id":"10.13039\/501100003593","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001807","name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo","doi-asserted-by":"publisher","award":["2016\/19806-3"],"award-info":[{"award-number":["2016\/19806-3"]}],"id":[{"id":"10.13039\/501100001807","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Open global forest cover data can be a critical component for Reducing Emissions from Deforestation and Forest Degradation (REDD+) policies. In this work, we determine the best threshold, compatible with the official Brazilian dataset, for establishing a forest mask cover within the Amazon basin for the year 2000 using the Tree Canopy Cover 2000 GFC product. We compared forest cover maps produced using several thresholds (10%, 30%, 50%, 80%, 85%, 90%, and 95%) with a forest cover map for the same year from the Brazilian Amazon Deforestation Monitoring Project (PRODES) data, produced by the National Institute for Space Research (INPE). We also compared the forest cover classifications indicated by each of these maps to 2550 independently assessed Landsat pixels for the year 2000, providing an accuracy assessment for each of these map products. We found that thresholds of 80% and 85% best matched with the PRODES data. Consequently, we recommend using an 80% threshold for the Tree Canopy Cover 2000 data for assessing forest cover in the Amazon basin.<\/jats:p>","DOI":"10.3390\/s19225020","type":"journal-article","created":{"date-parts":[[2019,11,18]],"date-time":"2019-11-18T04:31:10Z","timestamp":1574051470000},"page":"5020","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Determining a Threshold to Delimit the Amazonian Forests from the Tree Canopy Cover 2000 GFC Data"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8380-8272","authenticated-orcid":false,"given":"Kaio Allan Cruz","family":"Gasparini","sequence":"first","affiliation":[{"name":"Divis\u00e3o de Sensoriamento Remoto, Instituto Nacional de Pesquisas Espaciais, S\u00e3o Jos\u00e9 dos Campos \u2013 SP, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1052-5551","authenticated-orcid":false,"given":"Celso Henrique Leite","family":"Silva Junior","sequence":"additional","affiliation":[{"name":"Divis\u00e3o de Sensoriamento Remoto, Instituto Nacional de Pesquisas Espaciais, S\u00e3o Jos\u00e9 dos Campos \u2013 SP, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yosio Edemir","family":"Shimabukuro","sequence":"additional","affiliation":[{"name":"Divis\u00e3o de Sensoriamento Remoto, Instituto Nacional de Pesquisas Espaciais, S\u00e3o Jos\u00e9 dos Campos \u2013 SP, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Egidio","family":"Arai","sequence":"additional","affiliation":[{"name":"Divis\u00e3o de Sensoriamento Remoto, Instituto Nacional de Pesquisas Espaciais, S\u00e3o Jos\u00e9 dos Campos \u2013 SP, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4134-6708","authenticated-orcid":false,"given":"Luiz Eduardo Oliveira Cruz e","family":"Arag\u00e3o","sequence":"additional","affiliation":[{"name":"Divis\u00e3o de Sensoriamento Remoto, Instituto Nacional de Pesquisas Espaciais, S\u00e3o Jos\u00e9 dos Campos \u2013 SP, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7844-3560","authenticated-orcid":false,"given":"Carlos Alberto","family":"Silva","sequence":"additional","affiliation":[{"name":"Department of Geographical Sciences, University of Maryland, College Park, Maryland, MD 20740, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5479-557X","authenticated-orcid":false,"given":"Peter L.","family":"Marshall","sequence":"additional","affiliation":[{"name":"Department of Forest Resources Management, The University of British Columbia, 2424 Main Mall, Vancouver, BC V6T 1Z4, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2019,11,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"831","DOI":"10.1038\/ngeo689","article-title":"Trends in the sources and sinks of carbon dioxide","volume":"2","author":"Raupach","year":"2009","journal-title":"Nat. Geosci."},{"key":"ref_2","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_3","doi-asserted-by":"crossref","first-page":"5125","DOI":"10.5194\/bg-9-5125-2012","article-title":"Carbon emissions from land use and land-cover change","volume":"9","author":"Houghton","year":"2012","journal-title":"Biogeosciences"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1573","DOI":"10.1126\/science.1217962","article-title":"Baseline Map of Carbon Emissions from Deforestation in Tropical Regions","volume":"336","author":"Harris","year":"2012","journal-title":"Science"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1038\/nclimate1354","article-title":"Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps","volume":"2","author":"Baccini","year":"2012","journal-title":"Nat. Clim. Chang."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"536","DOI":"10.1038\/s41467-017-02771-y","article-title":"21st Century drought-related fires counteract the decline of Amazon deforestation carbon emissions","volume":"9","author":"Anderson","year":"2018","journal-title":"Nat. Commun."},{"key":"ref_7","unstructured":"(2019, January 01). Monitoramento do Desmatamento da Floresta Amaz\u00f4nica Brasileira por Sat\u00e9lite. Available online: http:\/\/www.obt.inpe.br\/OBT\/assuntos\/programas\/amazonia\/prodes."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"913","DOI":"10.1111\/brv.12088","article-title":"Environmental change and the carbon balance of Amazonian forests","volume":"89","author":"Poulter","year":"2014","journal-title":"Biol. Rev."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"340","DOI":"10.1016\/j.landusepol.2015.08.027","article-title":"Brazil submitted the first REDD+ reference level to the UNFCCC-Implications regarding climate effectiveness and cost-efficiency","volume":"55","author":"Hargita","year":"2015","journal-title":"Land Use Policy"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"5475","DOI":"10.1080\/01431161.2019.1579943","article-title":"Monitoring deforestation and forest degradation using multi-temporal fraction images derived from Landsat sensor data in the Brazilian Amazon","volume":"40","author":"Shimabukuro","year":"2019","journal-title":"Int. J. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1016\/j.rse.2011.08.027","article-title":"Quantifying forest cover loss in Democratic Republic of the Congo, 2000\u20132010, with Landsat ETM+ data","volume":"122","author":"Potapov","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"8650","DOI":"10.1073\/pnas.0912668107","article-title":"Quantification of global gross forest cover loss","volume":"107","author":"Hansen","year":"2010","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_13","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_14","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.rse.2017.06.031","article-title":"Google Earth Engine: Planetary-scale geospatial analysis for everyone","volume":"202","author":"Gorelick","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"421","DOI":"10.1186\/1475-2875-13-421","article-title":"Fine-scale malaria risk mapping from routine aggregated case data","volume":"13","author":"Sturrock","year":"2014","journal-title":"Malar. J."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"418","DOI":"10.1038\/nature20584","article-title":"High-resolution mapping of global surface water and its long-term changes","volume":"540","author":"Pekel","year":"2016","journal-title":"Nature"},{"key":"ref_17","first-page":"199","article-title":"Multitemporal settlement and population mapping from Landsat using Google Earth Engine","volume":"35","author":"Patel","year":"2015","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"11887","DOI":"10.3390\/rs70911887","article-title":"Building a better Urban picture: Combining day and night remote sensing imagery","volume":"7","author":"Zhang","year":"2015","journal-title":"Remote Sens."},{"key":"ref_19","unstructured":"(2019, January 01). GFC\u2014Global Forest Change. Available online: https:\/\/earthenginepartners.appspot.com\/science-2013-global-forest\/download_v1.6.html."},{"key":"ref_20","unstructured":"(2019, January 01). GFW\u2014Global Forest Watch Tree Cover 2000. Available online: http:\/\/data.globalforestwatch.org\/datasets\/tree-cover-2000."},{"key":"ref_21","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_22","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1080\/01431161.2010.519002","article-title":"Continuous fields of land cover for the conterminous United States using Landsat data: First results from the Web-Enabled Landsat Data (WELD) project","volume":"2","author":"Hansen","year":"2011","journal-title":"Remote Sens. Lett."},{"key":"ref_23","first-page":"70","article-title":"An integrated remote sensing and GIS approach for monitoring areas affected by selective logging: A case study in northern Mato Grosso, Brazilian Amazon","volume":"61","author":"Grecchi","year":"2017","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"519","DOI":"10.1038\/nature25508","article-title":"Global patterns of tropical forest fragmentation","volume":"554","author":"Taubert","year":"2018","journal-title":"Nature"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"14855","DOI":"10.1038\/ncomms14855","article-title":"High resolution analysis of tropical forest fragmentation and its impact on the global carbon cycle","volume":"8","author":"Brinck","year":"2017","journal-title":"Nat. Commun."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Esquivel-Muelbert, A., Bennett, A.C., Sullivan, M.J.P., Baker, J.C.A., Gavish, Y., Johnson, M.O., Wang, Y., Chambers-Ostler, A., Lisli Giannichi, M., and Gomes, L. (2019). A Spatial and Temporal Risk Assessment of the Impacts of El Ni\u00f1o on the Tropical Forest Carbon Cycle: Theoretical Framework, Scenarios, and Implications. Atmosphere, 10.","DOI":"10.3390\/atmos10100588"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"23","DOI":"10.14393\/rbcv69n1-44029","article-title":"Mapping Degraded Forest Areas Caused By Fires During the Year 2010 in Mato Grosso State, Brazilian Legal Amazon Using Landsat-5 Tm Fraction Images","volume":"69","author":"Shimabukuro","year":"2017","journal-title":"Rev. Bras. Cartogr."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Wagner, F.H., H\u00e9rault, B., Rossi, V., Hilker, T., Maeda, E.E., Sanchez, A., Lyapustin, A.I., Galv\u00e3o, L.S., Wang, Y., and Arag\u00e3o, L.E.O.C. (2017). Climate drivers of the Amazon forest greening. PLoS ONE, 12.","DOI":"10.1371\/journal.pone.0180932"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1126\/sciadv.1601047","article-title":"Types and rates of forest disturbance in Brazilian Legal Amazon, 2000\u20132013","volume":"3","author":"Tyukavina","year":"2017","journal-title":"Sci. Adv."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"4502","DOI":"10.1109\/JSTARS.2015.2464097","article-title":"Estimating Burned Area in Mato Grosso, Brazil, Using an Object-Based Classification Method on a Systematic Sample of Medium Resolution Satellite Images","volume":"8","author":"Shimabukuro","year":"2015","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_31","unstructured":"(2019, September 14). Monitoramento da cobertura florestal da Amaz\u00f4nia por sat\u00e9lites: Sistemas PRODES, DETER, DEGRAD e Queimadas 2007\u20132008. Available online: https:\/\/www.google.com.hk\/url?sa=t&rct=j&q=&esrc=s&source=web&cd=8&ved=2ahUKEwisou2mjenlAhVmG6YKHYfqC_kQFjAHegQIAxAC&url=http%3A%2F%2Fwww.obt.inpe.br%2Fprodes%2FRelatorio_Prodes2008.pdf&usg=AOvVaw2mYp1hD-ekxUCilvrALCRp."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1600","DOI":"10.1038\/s41598-018-19358-2","article-title":"Pervasive Rise of Small-scale Deforestation in Amazonia","volume":"8","author":"Kalamandeen","year":"2018","journal-title":"Sci. Rep."},{"key":"ref_33","unstructured":"Eva, H., Huber, O., Achard, F., Balslev, H., Beck, S., Behling, H., Belward, A., Beuchle, R., Cleef, A., and Colchester, M. (2005). A Proposal for Defining the Geographical Boundaries of Amazonia, Publications Office."},{"key":"ref_34","unstructured":"(2019, January 01). Projeto PRODES Monitoramento da Floresta Amaz\u00f4nica Brasileira por Sat\u00e9lite. Available online: http:\/\/terrabrasilis.dpi.inpe.br\/downloads."},{"key":"ref_35","unstructured":"(2019, January 01). Sample interpretation results, Brazilian Legal Amazon. Available online: https:\/\/glad.umd.edu\/brazil\/index.php."},{"key":"ref_36","unstructured":"R Core Team (2019). R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1648","DOI":"10.1111\/ecog.04617","article-title":"Landscapemetrics: An open-source R tool to calculate landscape metrics","volume":"42","author":"Hesselbarth","year":"2019","journal-title":"Ecography"},{"key":"ref_38","unstructured":"FAO (2016). Map Accuracy Assessment and Area Estimation Map Accuracy Assessment and Area Estimation: A Practical Guide, FAO."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1016\/j.rse.2014.02.015","article-title":"Good practices for estimating area and assessing accuracy of land change","volume":"148","author":"Olofsson","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"328","DOI":"10.1016\/j.isprsjprs.2018.08.007","article-title":"Big earth observation time series analysis for monitoring Brazilian agriculture","volume":"145","author":"Picoli","year":"2018","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_41","unstructured":"UNFCCC (2010). FCCC\/CP\/2009\/11\/Add.1, Decision 4\/CP.15: Methodological Guidance for Activities Relating to Reducing Emissions from Deforestation and Forest Degradation and the Role of Conservation, Sustainable Management of Forests and Enhancement of Forest Carbon Stock, UN."},{"key":"ref_42","unstructured":"(2019, January 01). Reducing Emission From Deforestation And Forest Degradation in Develping Countries - Web Platform. Available online: https:\/\/redd.unfccc.int\/submissions.html."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/22\/5020\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:35:17Z","timestamp":1760189717000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/22\/5020"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,11,18]]},"references-count":42,"journal-issue":{"issue":"22","published-online":{"date-parts":[[2019,11]]}},"alternative-id":["s19225020"],"URL":"https:\/\/doi.org\/10.3390\/s19225020","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,11,18]]}}}