{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,14]],"date-time":"2026-04-14T15:12:39Z","timestamp":1776179559709,"version":"3.50.1"},"reference-count":54,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2016,9,28]],"date-time":"2016-09-28T00:00:00Z","timestamp":1475020800000},"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>Collect Earth is a free and open source software for land monitoring developed by the Food and Agriculture Organization of the United Nations (FAO). Built on Google desktop and cloud computing technologies, Collect Earth facilitates access to multiple freely available archives of satellite imagery, including archives with very high spatial resolution imagery (Google Earth, Bing Maps) and those with very high temporal resolution imagery (e.g., Google Earth Engine, Google Earth Engine Code Editor). Collectively, these archives offer free access to an unparalleled amount of information on current and past land dynamics for any location in the world. Collect Earth draws upon these archives and the synergies of imagery of multiple resolutions to enable an innovative method for land monitoring that we present here: augmented visual interpretation. In this study, we provide a full overview of Collect Earth\u2019s structure and functionality, and we present the methodology used to undertake land monitoring through augmented visual interpretation. To illustrate the application of the tool and its customization potential, an example of land monitoring in Papua New Guinea (PNG) is presented. The PNG example demonstrates that Collect Earth is a comprehensive and user-friendly tool for land monitoring and that it has the potential to be used to assess land use, land use change, natural disasters, sustainable management of scarce resources and ecosystem functioning. By enabling non-remote sensing experts to assess more than 100 sites per day, we believe that Collect Earth can be used to rapidly and sustainably build capacity for land monitoring and to substantively improve our collective understanding of the world\u2019s land use and land cover.<\/jats:p>","DOI":"10.3390\/rs8100807","type":"journal-article","created":{"date-parts":[[2016,9,28]],"date-time":"2016-09-28T10:56:13Z","timestamp":1475060173000},"page":"807","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":232,"title":["Collect Earth: Land Use and Land Cover Assessment through Augmented Visual Interpretation"],"prefix":"10.3390","volume":"8","author":[{"given":"Adia","family":"Bey","sequence":"first","affiliation":[{"name":"Food and Agricultural Organization of the United Nations, Forestry Department, Rome 00154, Italy"}]},{"given":"Alfonso","family":"S\u00e1nchez-Paus D\u00edaz","sequence":"additional","affiliation":[{"name":"Food and Agricultural Organization of the United Nations, Forestry Department, Rome 00154, Italy"}]},{"given":"Danae","family":"Maniatis","sequence":"additional","affiliation":[{"name":"United Nations Development Programme, Bureau for Policy and Programme Support, New York, NY 10017, USA"},{"name":"School of Geography and the Environment, University of Oxford, Oxford OX1 3QY, UK"}]},{"given":"Giulio","family":"Marchi","sequence":"additional","affiliation":[{"name":"Food and Agricultural Organization of the United Nations, Forestry Department, Rome 00154, Italy"}]},{"given":"Danilo","family":"Mollicone","sequence":"additional","affiliation":[{"name":"Food and Agricultural Organization of the United Nations, Forestry Department, Rome 00154, Italy"}]},{"given":"Stefano","family":"Ricci","sequence":"additional","affiliation":[{"name":"Food and Agricultural Organization of the United Nations, Forestry Department, Rome 00154, Italy"}]},{"given":"Jean-Fran\u00e7ois","family":"Bastin","sequence":"additional","affiliation":[{"name":"Food and Agricultural Organization of the United Nations, Forestry Department, Rome 00154, Italy"},{"name":"Landscape Ecology and Plant Production Systems Unit, Universit\u00e9 Libre de Bruxelles, Brussels 1050, Belgium"}]},{"given":"Rebecca","family":"Moore","sequence":"additional","affiliation":[{"name":"Google, Mountain View, CA 94043, USA"}]},{"given":"Sandro","family":"Federici","sequence":"additional","affiliation":[{"name":"Food and Agricultural Organization of the United Nations, Forestry Department, Rome 00154, Italy"}]},{"given":"Marcelo","family":"Rezende","sequence":"additional","affiliation":[{"name":"Food and Agricultural Organization of the United Nations, Forestry Department, Rome 00154, Italy"}]},{"given":"Chiara","family":"Patriarca","sequence":"additional","affiliation":[{"name":"Food and Agricultural Organization of the United Nations, Forestry Department, Rome 00154, Italy"}]},{"given":"Ruth","family":"Turia","sequence":"additional","affiliation":[{"name":"Papua New Guinea Forest Authority, Boroko 111, Papua New Guinea"}]},{"given":"Gewa","family":"Gamoga","sequence":"additional","affiliation":[{"name":"Papua New Guinea Forest Authority, Boroko 111, Papua New Guinea"}]},{"given":"Hitofumi","family":"Abe","sequence":"additional","affiliation":[{"name":"Food and Agricultural Organization of the United Nations, Forestry Department, Rome 00154, Italy"}]},{"given":"Elizabeth","family":"Kaidong","sequence":"additional","affiliation":[{"name":"Papua New Guinea Forest Authority, Boroko 111, Papua New Guinea"}]},{"given":"Gino","family":"Miceli","sequence":"additional","affiliation":[{"name":"Google, Mountain View, CA 94043, USA"}]}],"member":"1968","published-online":{"date-parts":[[2016,9,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"045023","DOI":"10.1088\/1748-9326\/2\/4\/045023","article-title":"Monitoring and estimating tropical forest carbon stocks: Making REDD a reality","volume":"2","author":"Gibbs","year":"2007","journal-title":"Environ. Res. Lett."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1016\/j.foreco.2015.06.003","article-title":"Assessing change in national forest monitoring capacities of 99 tropical countries","volume":"352","author":"Romijn","year":"2015","journal-title":"For. Ecol. Manag."},{"key":"ref_3","unstructured":"Martino, L., and Fritz, M. New Insight into Land Cover and Land Use in Europe. Available online: http:\/\/ec.europa.eu\/eurostat\/documents\/3433488\/5582088\/KS-SF-08-033-EN.PDF\/fc262221-5c2e-4dcf-9e7b-0c6731b3f3a4."},{"key":"ref_4","first-page":"1","article-title":"The Multi-Source National Forest Inventory of Finland\u2014Methods and Results 2011","volume":"319","author":"Tomppo","year":"2011","journal-title":"Measurement"},{"key":"ref_5","unstructured":"Tabacchi, G., de Natale, F., Floris, A., Gagliano, C., Gasparini, P., Scrinzi, G., and Tosi, V. (2005, January 3\u20136). Italian National Forest Inventory: Methods, state of the project, and future developments. Proceedings of the Seventh Annual Forest Inventory and Analysis Symposium, Portland, ME, USA."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"993","DOI":"10.1890\/11-1606.1","article-title":"Assessing aboveground tropical forest biomass using Google Earth canopy images","volume":"22","author":"Ploton","year":"2012","journal-title":"Ecol. Appl."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"2130","DOI":"10.1016\/j.rse.2009.05.021","article-title":"MODIS tree cover validation for the circumpolar taiga-tundra transition zone","volume":"113","author":"Montesano","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"208","DOI":"10.1016\/j.rse.2015.02.011","article-title":"Development of a global hybrid forest mask through the synergy of remote sensing, crowdsourcing and FAO statistics","volume":"162","author":"Schepaschenko","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_9","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_10","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1016\/j.rse.2012.01.010","article-title":"Opening the archive: How free data has enabled the science and monitoring promise of Landsat","volume":"122","author":"Wulder","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_11","unstructured":"Brotton, J. (2014). A History of the World in 12 Maps, Penguin. Kindle ed."},{"key":"ref_12","unstructured":"Official Google Blog Google Earth Downloaded More than One Billion Times. Available online: https:\/\/maps.googleblog.com\/2011\/10\/google-earth-downloaded-more-than-one.html."},{"key":"ref_13","unstructured":"Number of Internet Users Worldwide from 2005 to 2015. Available online: http:\/\/www.statista.com\/statistics\/273018\/number-of-internet-users-worldwide\/."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"345","DOI":"10.3390\/rs1030345","article-title":"Geo-Wiki.Org: The use of crowdsourcing to improve global land cover","volume":"1","author":"Fritz","year":"2009","journal-title":"Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Feng, M., Huang, C., Sexton, J.O., Channan, S., Narasimhan, R., and Townshend, J.R. (2012, January 22\u201327). An approach for quickly labeling land cover types for multiple epochs at globally selected locations. Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, Munich, Germany.","DOI":"10.1109\/IGARSS.2012.6352674"},{"key":"ref_16","unstructured":"See, L., Perger, C., Hofer, M., Weichselbaumb, J., Dresel, C., and Fritz, S. (October, January 28). LACO-Wiki: An open access online portal for land cover validation. ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information, Sciences, Proceedings of the ISPRS Geospatial Week, La Grande Motte, France."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"2911","DOI":"10.1016\/j.rse.2010.07.010","article-title":"Detecting trends in forest disturbance and recovery using yearly Landsat time series: 2. TimeSync\u2014Tools for calibration and validation","volume":"114","author":"Cohen","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"601","DOI":"10.3390\/rs3030601","article-title":"Virtual interpretation of earth web-interface tool (VIEW-IT) for collecting land-use\/land-cover reference data","volume":"3","author":"Clark","year":"2011","journal-title":"Remote Sens."},{"key":"ref_19","unstructured":"Skytruth: Mountaintop Removal Mining. Available online: http:\/\/blog.skytruth.org\/2009\/12\/measuring-mountaintop-removal-mining-in.html."},{"key":"ref_20","unstructured":"Tomnod: Nepal Earthquake Data Portal. Available online: http:\/\/blog.tomnod.com\/Nepal-Earthquake-Data-Portal."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"234","DOI":"10.1016\/j.rse.2015.01.018","article-title":"A global reference database from very high resolution commercial satellite data and methodology for application to Landsat derived 30 m continuous field tree cover data","volume":"165","author":"Pengra","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/j.rse.2003.07.006","article-title":"IKONOS spatial resolution and image interpretability characterization","volume":"88","author":"Ryan","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"521","DOI":"10.1016\/j.rse.2003.08.006","article-title":"Canopy shadow in IKONOS satellite observations of tropical forests and savannas","volume":"87","author":"Asner","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1016\/j.rse.2010.08.015","article-title":"Bidirectional texture function of high resolution optical images of tropical forest: An approach using LiDAR hillshade simulations","volume":"115","author":"Barbier","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1984","DOI":"10.1890\/13-1574.1","article-title":"Aboveground biomass mapping of African forest mosaics using canopy texture analysis: Toward a regional approach","volume":"24","author":"Bastin","year":"2014","journal-title":"Ecol. Appl."},{"key":"ref_26","unstructured":"Whitehead, T. Google Earth Imagery Suppliers. Available online: http:\/\/www.gearthblog.com\/blog\/archives\/2015\/09\/google-earth-imagery-suppliers.html."},{"key":"ref_27","unstructured":"Bing Maps Unveils Exclusive High Res Imagery with Global Ortho Project, 27 June 2011. Available online: http:\/\/blogs.bing.com\/maps\/2011\/06\/27\/bing-maps-unveils-exclusive-high-res-imagery-with-global-ortho-project\/."},{"key":"ref_28","unstructured":"Google Earth Engine Datasets. Available online: https:\/\/earthengine.google.com\/datasets\/."},{"key":"ref_29","unstructured":"Elements of Visual Interpretation. Available online: http:\/\/www.nrcan.gc.ca\/earth-sciences\/geomatics\/satellite-imagery-air-photos\/satellite-imagery-products\/educational-resources\/9291."},{"key":"ref_30","first-page":"55","article-title":"Optical remotely sensed time series data for land cover classification: A review","volume":"116","author":"Gomez","year":"2016","journal-title":"Int. Soc. Photogramm."},{"key":"ref_31","unstructured":"Open Foris Collect Earth. Available online: http:\/\/www.openforis.org\/tools\/collect-earth.html."},{"key":"ref_32","unstructured":"S\u00e1nchez-Paus D\u00edaz, A. Open Foris Collect Earth Code Repository. Available online: https:\/\/github.com\/ openforis\/collect-earth."},{"key":"ref_33","unstructured":"Google Earth. Available online: https:\/\/www.google.com\/earth\/."},{"key":"ref_34","unstructured":"Google Chrome. Available online: https:\/\/www.google.com\/chrome\/."},{"key":"ref_35","unstructured":"Mozilla Firefox. Available online: https:\/\/www.mozilla.org\/en-US\/firefox\/new\/."},{"key":"ref_36","unstructured":"Open Foris Collect. Available online: http:\/\/www.openforis.org\/tools\/collect.html."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"466","DOI":"10.1016\/j.rse.2005.04.002","article-title":"Comparing estimators of gross change derived from complete coverage mapping versus statistical sampling of remotely sensed data","volume":"96","author":"Stehman","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_38","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":"Olofson","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_39","unstructured":"Bey, A., S\u00e1nchez-Paus D\u00edaz, A., Pekkarinen, A., Patriarca, C., Maniatis, D., Weil, D., Mollicone, D., Marchi, G., Niskala, J., and Rezende, M. Collect Earth User Manual, 1st ed.. Available online: http:\/\/openforis.org\/fileadmin\/user_upload\/Collect_Earth_Tutorials\/Collect_Earth_User_Manual_20150618_highres_full.pdf."},{"key":"ref_40","unstructured":"IPCC (2006). Guidelines for National Greenhouse Gas Inventories, Institute for Global Environmental Strategies."},{"key":"ref_41","unstructured":"Google Earth Engine: A Planetary-Scale Platform for Earth Science Data & Analysis. Available online: https:\/\/earthengine.google.com\/."},{"key":"ref_42","unstructured":"Whitehead, T. Google Earth Imagery Update Mid-January 2016. Available online: http:\/\/www.gearthblog.com\/ blog\/archives\/2016\/01\/google-earth-imagery-update-mid-january-2016.html."},{"key":"ref_43","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_44","unstructured":"IPCC (2003). Good Practice Guidance for Land Use, Land-Use Change and Forestry, Institute for Global Environmental Strategies."},{"key":"ref_45","unstructured":"Google Panoramio. Available online: http:\/\/www.panoramio.com."},{"key":"ref_46","unstructured":"Food and Agriculture Organization of the United Nations (1993). Forest Resources Assessment 1990, FAO. Tropical Countries, FAO Forestry Paper 112."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"2540","DOI":"10.1111\/gcb.12605","article-title":"Determination of tropical deforestation rates and related carbon losses from 1990 to 2010","volume":"20","author":"Achard","year":"2014","journal-title":"Glob. Chang. Biol."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1080\/17538947.2010.492244","article-title":"The global Landsat imagery database for the FAO FRA remote sensing survey","volume":"4","author":"Potapov","year":"2011","journal-title":"Int. J. Digit. Earth"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1098\/rstb.2004.1590","article-title":"Tropical forest cover change in the 1990s and options for future monitoring","volume":"360","author":"Mayaux","year":"2005","journal-title":"Philos. Trans. R. Soc. Lond. B Biol. Sci."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Sexton, J.O., Song, X.-P., Feng, M., Noojipady, P., Anand, A., Huang, C., Kim, D.-H., Collins, K.M., and Channan, S. (2013). Global, 30-m resolution continuous fields of tree cover: Landsat-based rescaling of MODIS Vegetation Continuous Fields with lidar-based estimates of error. Int. J. Digit. Earth, 6.","DOI":"10.1080\/17538947.2013.786146"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"823","DOI":"10.1080\/01431160600746456","article-title":"A survey of image classification methods and techniques for improving classification performance","volume":"28","author":"Lu","year":"2007","journal-title":"Int. J. Remote Sens."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1186\/1750-0680-4-7","article-title":"An assessment of monitoring requirements and costs of Reduced Emissions from Deforestation and Degradation","volume":"4","author":"Eisbrenner","year":"2009","journal-title":"Carbon Balance Manag."},{"key":"ref_53","unstructured":"Food and Agriculture Organization of the United Nations Trees, Forests and Land Use in Drylands: The First Global Assessment, 2016. Available online: http:\/\/www.fao.org\/publications\/card\/en\/c\/01382d82-6356-478e-9f42-d85ccdfd7a7d\/."},{"key":"ref_54","unstructured":"Collect Earth Installation File for Windows Operating Systems; Collect Earth Installation File for Mac Operating Systems; Collect Earth-Papua New Guinea Customization (CEP) File. Available online: http:\/\/www.openforis.org\/tools\/collect-earth.html."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/8\/10\/807\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T19:32:01Z","timestamp":1760211121000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/8\/10\/807"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,9,28]]},"references-count":54,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2016,10]]}},"alternative-id":["rs8100807"],"URL":"https:\/\/doi.org\/10.3390\/rs8100807","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,9,28]]}}}