{"id":71,"date":"2024-12-09T10:31:52","date_gmt":"2024-12-09T15:31:52","guid":{"rendered":"https:\/\/www.golive.clarku.edu\/faculty\/profiles\/robert-pontius\/"},"modified":"2026-04-03T05:12:44","modified_gmt":"2026-04-03T09:12:44","slug":"robert-pontius","status":"publish","type":"cu_faculty","link":"https:\/\/www.clarku.edu\/faculty\/profiles\/robert-pontius\/","title":{"rendered":"Robert Pontius"},"content":{"rendered":"

Robert Gilmore Pontius Jr<\/a> is a Professor in Clark University\u2019s Graduate School of Geography<\/a>. Dr. Pontius specializes in Geographic Information Science (GIS) with particular expertise in statistics, simulation modeling, and land change science. He derives quantitative methods that are in the GIS software TerrSet<\/em><\/a>, which Clark Labs produces. Pontius works with Clark Labs to improve the methods for carbon offset projects to reduce greenhouse gas emissions from deforestation and forest degradation. The United States National Science Foundation continues to fund his research through more than two decades via the Plum Island Ecosystems<\/a> site of the Long-Term Ecological Research network. The National Aeronautics and Space Administration also funds his research in the Brazilian Cerrado Biome<\/a> via the Land-Cover and Land-Use Change program. Pontius is a member of the Scientific Advisory Board of MapBiomas<\/a> and a Fulbright Scholar of Brazil. He has summarized his novel quantitative methods in his 2022 book entitled Metrics That Make a Difference: How to Analyze Change and Error<\/a>. His publications<\/a> have received more than 19 thousand citations<\/a>. He joined Clark University as an Assistant Professor in 1998 and has been a full professor in Clark University s Graduate School of Geography since 2011. His two most popular courses are GIS & Land Change Models and GIS & Map Comparison. Students in his courses have made tutorial videos<\/a> that international audiences have found helpful to understand his quantitative methods. Pontius earned a Bachelor of Science in Mathematics at University of Pittsburgh in 1984, a Masters of Applied Statistics at The Ohio State University in 1989, and a Doctorate in Environmental Science at the State University of New York\u2019s College of Environmental Science and Forestry in 1994. Pontius has also had a career as a professional juggler, winning the People\u2019s Choice Award at the International Jugglers Association, as his stage character Doctor Stardust<\/a>.<\/p>\n","protected":false},"author":0,"featured_media":1948,"parent":0,"template":"","meta":{"cu_faculty_f180_userid":"C11301315","cu_faculty_first_name":"Robert","cu_faculty_last_name":"Pontius","cu_faculty_employment_status":"Full Time","cu_faculty_rank":"Professor","cu_faculty_position":"Professor","cu_faculty_phone":"","cu_faculty_email":"rpontius@clarku.edu","cu_faculty_location":"","cu_faculty_about":"

Robert Gilmore Pontius Jr<\/a> is a Professor in Clark University\u2019s Graduate School of Geography<\/a>. Dr. Pontius specializes in Geographic Information Science (GIS) with particular expertise in statistics, simulation modeling, and land change science. He derives quantitative methods that are in the GIS software TerrSet<\/em><\/a>, which Clark Labs produces. Pontius works with Clark Labs to improve the methods for carbon offset projects to reduce greenhouse gas emissions from deforestation and forest degradation. The United States National Science Foundation continues to fund his research through more than two decades via the Plum Island Ecosystems<\/a> site of the Long-Term Ecological Research network. The National Aeronautics and Space Administration also funds his research in the Brazilian Cerrado Biome<\/a> via the Land-Cover and Land-Use Change program. Pontius is a member of the Scientific Advisory Board of MapBiomas<\/a> and a Fulbright Scholar of Brazil. He has summarized his novel quantitative methods in his 2022 book entitled Metrics That Make a Difference: How to Analyze Change and Error<\/a>. His publications<\/a> have received more than 19 thousand citations<\/a>. He joined Clark University as an Assistant Professor in 1998 and has been a full professor in Clark University s Graduate School of Geography since 2011. His two most popular courses are GIS & Land Change Models and GIS & Map Comparison. Students in his courses have made tutorial videos<\/a> that international audiences have found helpful to understand his quantitative methods. Pontius earned a Bachelor of Science in Mathematics at University of Pittsburgh in 1984, a Masters of Applied Statistics at The Ohio State University in 1989, and a Doctorate in Environmental Science at the State University of New York\u2019s College of Environmental Science and Forestry in 1994. Pontius has also had a career as a professional juggler, winning the People\u2019s Choice Award at the International Jugglers Association, as his stage character Doctor Stardust<\/a>.<\/p>","cu_faculty_degrees":"Ph.D. in Environmental Science,<\/span> State University of New York \/ College of Environmental Science and Forestry, 1994\nMasters in Applied Statistics,<\/span> The Ohio State University, 1989\nB.S. in Mathematics and Economics,<\/span> University of Pittsburgh, 1984","cu_faculty_cv":"https:\/\/faculty180.interfolio.com\/public\/download.php?key=SDRwNCtxSUpsamxBQ213WS9ucHFuNnMwT0hzQU11b2RPQkJ2cWc3amxyUmNRdVVXTkF4MU10Q1FvdGN3MEZPOTlaN09uUUNKUlVqMGVHeWpXMmkwUTBWeHJQUXBHam5KMHY5OFBzQlZkckswcXo3WFo3R21zaE5OeW9vU29aQXQ%3D","cu_faculty_links":"{\"Professional Website URL\":\"https:\\\/\\\/wordpress.clarku.edu\\\/rpontius\\\/\",\"ORCID ID\":\"https:\\\/\\\/orcid.org\\\/0000-0001-7287-5875\",\"Google Scholar\":\"https:\\\/\\\/scholar.google.com\\\/citations?user=Lfmhbd8AAAAJ&hl=en\",\"Research Gate\":\"https:\\\/\\\/www.researchgate.net\\\/profile\\\/Robert-Pontius?ev=hdr_xprf\",\"Other\":\"https:\\\/\\\/www.linkedin.com\\\/in\\\/robert-gilmore-pontius-jr-8b213113\\\/\"}","cu_faculty_scholarly_interests":"Geographic Information Science, Land Change Science, Simulation Modeling, Statistics","cu_faculty_scholarly_works":"[{\"activityid\":12426,\"fields\":{\"Type\":\"Presentations\",\"Title of Presentation\":\"<span style="font-size:12pt;">The new method of Trajectory Analysis characterizes change in a time series of maps<\\\/span>\",\"Conference \\\/ Meeting Name\":\"Landscapes of Change: Dynamic Interactions between Nature and People\",\"Location of Conference \\\/ Meeting\":\"Raleigh, North Carolina\",\"Month \\\/ Season\":\"April\",\"Year\":2025,\"Sponsoring Organization\":\"International Association for Landscape Ecology\",\"CoAuthor\":null,\"URL\":\"https:\\\/\\\/www.ialena.org\\\/annual-meeting.html\",\"Description\":\"\",\"Include description in output citation\":0,\"Origin\":\"Manual\"},\"facultyid\":\"C11301315\",\"status\":[{\"id\":12426,\"status\":\"Completed\\\/Published\",\"term\":\"Spring\",\"year\":2024,\"termid\":\"2023\\\/03\",\"listingorder\":6,\"completionorder\":6}],\"userid\":\"C11301315\",\"attachments\":[],\"coauthors_list\":[\"Robert G. Pontius Jr.\"],\"sort_date\":\"2025-4-01\"},{\"activityid\":12427,\"fields\":{\"Type\":\"Presentations\",\"Title of Presentation\":\"Metrics That Make a Difference Workshop\",\"Conference \\\/ Meeting Name\":\"International Association for Landscape Ecology\",\"Location of Conference \\\/ Meeting\":\"Raleigh, North Carolina\",\"Month \\\/ Season\":\"April\",\"Year\":2025,\"Sponsoring Organization\":\"\",\"CoAuthor\":null,\"URL\":\"https:\\\/\\\/www.ialena.org\\\/annual-meeting.html\",\"Description\":\"\",\"Include description in output citation\":0,\"Origin\":\"Manual\"},\"facultyid\":\"C11301315\",\"status\":[{\"id\":12427,\"status\":\"Completed\\\/Published\",\"term\":\"Spring\",\"year\":2025,\"termid\":\"2024\\\/03\",\"listingorder\":6,\"completionorder\":6}],\"userid\":\"C11301315\",\"attachments\":[],\"coauthors_list\":[\"Robert G. Pontius Jr.\"],\"sort_date\":\"2025-4-01\"},{\"activityid\":12444,\"fields\":{\"Type\":\"Presentations\",\"Title of Presentation\":\"<span style="font-size:11pt;">The new method of Trajectory Analysis characterizes change in a time series of maps<\\\/span>\",\"Conference \\\/ Meeting Name\":\"International Association for Landscape Ecology\",\"Location of Conference \\\/ Meeting\":\"Raleigh, North Carolina\",\"Month \\\/ Season\":\"April\",\"Year\":2025,\"Sponsoring Organization\":\"\",\"CoAuthor\":null,\"URL\":\"\",\"Description\":\"\",\"Include description in output citation\":0,\"Origin\":\"Manual\"},\"facultyid\":\"C11301315\",\"status\":[{\"id\":12444,\"status\":\"Completed\\\/Published\",\"term\":\"Spring\",\"year\":2025,\"termid\":\"2024\\\/03\",\"listingorder\":6,\"completionorder\":6}],\"userid\":\"C11301315\",\"attachments\":[],\"coauthors_list\":[\"Robert G. Pontius Jr.\"],\"sort_date\":\"2025-4-01\"},{\"activityid\":12411,\"fields\":{\"Type\":\"Articles in Refereed Journals\",\"Title\":\"<span style="font-size:12pt;">A call to interpret disagreement components during classification assessment<\\\/span>\",\"Journal Title\":\"International Journal of Geographical Information Science\",\"Series Title\":\"\",\"Month \\\/ Season\":\"March\",\"Year\":2025,\"Publisher\":\"\",\"Publisher City and State\":\"\",\"Publisher Country\":\"\",\"Volume\":\"\",\"Issue Number \\\/ Edition\":\"\",\"Page Number(s) or Number of Pages\":\"18\",\"ISSN\":\"\",\"DOI\":\"10.1080\\\/13658816.2025.2469830\",\"CoAuthor\":null,\"URL\":\"https:\\\/\\\/www.tandfonline.com\\\/doi\\\/full\\\/10.1080\\\/13658816.2025.2469830\",\"Description\":\"This foresight manuscript proposes several ideas concerning how to conduct insightful classification assessment. Authors should report disagreement components that relate to the research question, without anointing results as acceptable or good. This manuscript reviews the citations of the 2011 manuscript entitled \\u2018Death to Kappa: Birth of Quantity Disagreement and Allocation Disagreement for Accuracy Assessment\\u2019, which gave two recommendations: (1) do not use Kappa and (2) use disagreement components. We analyzed 200 articles that cited the Death to Kappa manuscript. A quarter of the articles followed both recommendations, another quarter fol\\u00ad lowed only the first recommendation, another quarter followed only the second recommendation, and the last quarter followed neither recommendation. The attempt to replace Kappa with disagreement components has been partially effective, while Kappa continues to haunt several professions. We discuss misguided uses of Percent Correct and Kappa in Remote Sensing and Land Change Modeling. The concepts are general and thus relate to additional fields. Authors frequently use arbitrary thresholds of metrics to claim that results are acceptable. However, the notion that results can be acceptable or not is inherently unscientific. Scientists must use a metric that addresses a clear research question in which the scien\\u00adtists have no vested interest in the results.\",\"Include description in output citation\":1,\"Origin\":\"Manual\"},\"facultyid\":\"C11301315\",\"status\":[{\"id\":12411,\"status\":\"Completed\\\/Published\",\"term\":\"Spring\",\"year\":2025,\"termid\":\"2024\\\/03\",\"listingorder\":6,\"completionorder\":6}],\"userid\":\"C11301315\",\"attachments\":[{\"attachmentid\":10926,\"mimetype\":\"application\\\/pdf\",\"filename\":\"Pontius Jr et al. - 2025 - A call to interpret disagreement components during.pdf\",\"filesize\":1929516,\"downloadurl\":\"https:\\\/\\\/faculty180.interfolio.com\\\/public\\\/download.php?key=SDRwNCtxSUpsamxBQ213WS9ucHFuNnMwT0hzQU11b2RPQkJ2cWc3amxyUmNRdVVXTkF4MU10Q1FvdGN3MEZPOUNHVURvZmMzUmM4MitaQnZwaFYrVTFtMTY0N21pRUZCVHFUb2FUaEY4d0RoYktONFd4RVdtT01DUkZvUVBnSnlTdHZUYnk0dmNDRC85ZFFaaGloTUlzVW5iQnVIU0s4UDNUclZCc0dQOGV2RjFIRnB2MHhvS2toSC81NnhUN21ZSTJNYy9MWG80cTg9\"}],\"coauthors_list\":[\"Robert G. Pontius Jr.\",\"Thomas Francis\",\"Marco Millones\"],\"sort_date\":\"2025-3-01\"},{\"activityid\":12412,\"fields\":{\"Type\":\"Articles in Refereed Journals\",\"Title\":\"<span style="font-size:12pt;">Best Practices for Applying and Interpreting the Total Operating Characteristic<\\\/span>\",\"Journal Title\":\"ISPRS International Journal of Geo-Information\",\"Series Title\":\"\",\"Month \\\/ Season\":\"March\",\"Year\":2025,\"Publisher\":\"\",\"Publisher City and State\":\"\",\"Publisher Country\":\"\",\"Volume\":\"14\",\"Issue Number \\\/ Edition\":\"\",\"Page Number(s) or Number of Pages\":\"17\",\"ISSN\":\"\",\"DOI\":\"10.3390\\\/ijgi14040134\",\"CoAuthor\":null,\"URL\":\"https:\\\/\\\/www.mdpi.com\\\/2220-9964\\\/14\\\/4\\\/134\",\"Description\":\"The Total Operating Characteristic (TOC) is an improvement on the quantitative method called the Relative Operating Characteristic (ROC), both of which plot the association between a binary variable and a rank variable. TOC curves reveal the sizes of the four entries in the confusion matrix at each threshold, which make TOC curves more easily interpretable than ROC curves. The TOC has become popular, especially to assess the fit of simulation models to predict land change. However, the literature has shown variation in how authors apply and interpret the TOC, creating some misleading conclusions. Our manuscript lists best practices when applying and interpreting the TOC to help scientists learn from TOC curves. An example illustrates these practices by applying the TOC to measure the ability to predict the gain of crop in Western Bahia, Brazil. The application compares four ways to design the rank variable based on the distance to either pixels or patches of either the presence or change of crop. The results show that the gain of crop during the validation time interval is more strongly associated with the distance to patches rather than pixels of crop. The Discussion Section reveals that if authors show the TOC curves, then readers can interpret the results in ways that the authors might have missed. The Conclusion encourages scientists to follow best practices to learn the wealth of information that the TOC reveals.\",\"Include description in output citation\":1,\"Origin\":\"Manual\"},\"facultyid\":\"C11301315\",\"status\":[{\"id\":12412,\"status\":\"Completed\\\/Published\",\"term\":\"Spring\",\"year\":2025,\"termid\":\"2024\\\/03\",\"listingorder\":6,\"completionorder\":6}],\"userid\":\"C11301315\",\"attachments\":[{\"attachmentid\":10927,\"mimetype\":\"application\\\/pdf\",\"filename\":\"Honnef and Pontius Jr - 2025 - Best Practices for Applying and Interpreting the T.pdf\",\"filesize\":4503809,\"downloadurl\":\"https:\\\/\\\/faculty180.interfolio.com\\\/public\\\/download.php?key=SDRwNCtxSUpsamxBQ213WS9ucHFuNnMwT0hzQU11b2RPQkJ2cWc3amxyUmNRdVVXTkF4MU10Q1FvdGN3MEZPOUNHVURvZmMzUmMvdENrL1RmZStsM3gvMHR4dVJGRWRwb1VlZENKdXVwNEErUDkvcDQ0THloRUIyT2N0NDgwNC9OY3lUQWxhcDJGRk8wVmZ0S0NVNUZhRzV1enYxZ0tUdGJwVUF4eXk2K0JBR00xYWovTkVOSFpyVnJXWVJna0FpYkdaS0ZjWjZTaVk9\"}],\"coauthors_list\":[\"Tanner Honnef\",\"Robert G. Pontius Jr.\"],\"sort_date\":\"2025-3-01\"},{\"activityid\":12410,\"fields\":{\"Type\":\"Articles in Refereed Journals\",\"Title\":\"<span style="font-size:12pt;">Analyzing the Losses and Gains of a Land Category: Insights from the Total Operating Characteristic<\\\/span>\",\"Journal Title\":\"Land\",\"Series Title\":\"\",\"Month \\\/ Season\":\"July\",\"Year\":2024,\"Publisher\":\"\",\"Publisher City and State\":\"\",\"Publisher Country\":\"\",\"Volume\":\"13\",\"Issue Number \\\/ Edition\":\"8\",\"Page Number(s) or Number of Pages\":\"11\",\"ISSN\":\"\",\"DOI\":\"10.3390\\\/land13081177\",\"CoAuthor\":null,\"URL\":\"https:\\\/\\\/www.mdpi.com\\\/2073-445X\\\/13\\\/8\\\/1177\",\"Description\":\"This manuscript provides guidance concerning how to use the Total Operating Characteristic (TOC) when (1) analyzing change through time, (2) ranking a categorical independent variable, and (3) constraining the extent for a gaining category. The illustrative variable is the marsh landcover category in the Plum Island Ecosystems of northeastern Massachusetts, USA. The data are an elevation map and maps showing the land categories of water, marsh, and upland in 1938, 1971, and 2013. There were losses and gains near the edge of the marsh between 1938 and 1972 and between 1972 and 2013. The TOC curves show that marsh gained most intensively at intermediate elevations during the first time interval and then had a weaker association with elevation during the second time interval. Marsh gains more intensively from water than from upland during both time intervals. The TOC curves also demonstrate that the marsh gains occurred where marsh was previously lost, a phenomenon called Alternation. Furthermore, eliminating far distances and extreme elevations from the spatial extent decreased the area under the curve (AUC) for distance and increased the AUC for elevation. We invite scientists to use the TOC because the TOC is easier to interpret and shows more information than the Relative Operative Characteristic.\",\"Include description in output citation\":1,\"Origin\":\"Manual\"},\"facultyid\":\"C11301315\",\"status\":[{\"id\":12410,\"status\":\"Completed\\\/Published\",\"term\":\"Summer\",\"year\":2024,\"termid\":\"2023\\\/05\",\"listingorder\":6,\"completionorder\":6}],\"userid\":\"C11301315\",\"attachments\":[{\"attachmentid\":10925,\"mimetype\":\"application\\\/pdf\",\"filename\":\"Bilintoh et al. - 2024 - Analyzing the Losses and Gains of a Land Category.pdf\",\"filesize\":7168508,\"downloadurl\":\"https:\\\/\\\/faculty180.interfolio.com\\\/public\\\/download.php?key=SDRwNCtxSUpsamxBQ213WS9ucHFuNnMwT0hzQU11b2RPQkJ2cWc3amxyUmNRdVVXTkF4MU10Q1FvdGN3MEZPOUNHVURvZmMzUmMvdFpSU3Uva2s2K3YrNHFxa1oyZ2poU2hvaGJlZnBxbkw5U1R3UVNCVHN6VnpNV0lpZkFmb25ZMklicWw0QnFIZEFONWl3MFBhZThXVzNkZDMzQitvUkZuUndidlBDY0pBeEYwRkQ5c0RjallTb1dURmZQMEpi\"}],\"coauthors_list\":[\"Thomas Mumuni Bilintoh\",\"Robert G. Pontius Jr.\",\"Zhen Liu\"],\"sort_date\":\"2024-7-01\"},{\"activityid\":12423,\"fields\":{\"Type\":\"Presentations\",\"Title of Presentation\":\"<span style="font-size:12pt;color:#323131;">How and why do some authors claim their data and models are good?<\\\/span>\",\"Conference \\\/ Meeting Name\":\"3rd MOPT Conference: Advanced Spatial Modeling and Analysis\",\"Location of Conference \\\/ Meeting\":\"Lisbon, Portugal\",\"Month \\\/ Season\":\"May\",\"Year\":2024,\"Sponsoring Organization\":\"Modelling, Urban, and Regional Planning (MOPT) research group\",\"CoAuthor\":null,\"URL\":\"\",\"Description\":\"\",\"Include description in output citation\":0,\"Origin\":\"Manual\"},\"facultyid\":\"C11301315\",\"status\":[{\"id\":12423,\"status\":\"Completed\\\/Published\",\"term\":\"Summer\",\"year\":2024,\"termid\":\"2023\\\/05\",\"listingorder\":6,\"completionorder\":6}],\"userid\":\"C11301315\",\"attachments\":[{\"attachmentid\":10933,\"mimetype\":\"application\\\/pdf\",\"filename\":\"Pontius2024Lisbon2.pdf\",\"filesize\":4846747,\"downloadurl\":\"https:\\\/\\\/faculty180.interfolio.com\\\/public\\\/download.php?key=SDRwNCtxSUpsamxBQ213WS9ucHFuNnMwT0hzQU11b2RPQkJ2cWc3amxyUmNRdVVXTkF4MU10Q1FvdGN3MEZPOUNHVURvZmMzUmMva3JIN2tFNlJZTU1WMEdiekhVR0hRaytrWWhBcXhROTVxN2FEbnV4Yjd3Zz09\"}],\"coauthors_list\":[\"Robert G. Pontius Jr.\"],\"sort_date\":\"2024-5-01\"},{\"activityid\":12425,\"fields\":{\"Type\":\"Presentations\",\"Title of Presentation\":\"<span style="font-size:12pt;">Metrics That Make a Difference Workshop<\\\/span>\",\"Conference \\\/ Meeting Name\":\"5th Open Science Meeting\",\"Location of Conference \\\/ Meeting\":\"Oaxaca, Mexico\",\"Month \\\/ Season\":\"November\",\"Year\":2024,\"Sponsoring Organization\":\"Global Land Programme\",\"CoAuthor\":null,\"URL\":\"\",\"Description\":\"\",\"Include description in output citation\":0,\"Origin\":\"Manual\"},\"facultyid\":\"C11301315\",\"status\":[{\"id\":12425,\"status\":\"Completed\\\/Published\",\"term\":\"Fall\",\"year\":2024,\"termid\":\"2024\\\/01\",\"listingorder\":6,\"completionorder\":6}],\"userid\":\"C11301315\",\"attachments\":[],\"coauthors_list\":[\"Robert G. Pontius Jr.\"],\"sort_date\":\"2024-11-01\"},{\"activityid\":12409,\"fields\":{\"Type\":\"Articles in Refereed Journals\",\"Title\":\"<span style="font-size:12pt;">Methods to compare sites concerning a category\\u2019s change during various time intervals<\\\/span>\",\"Journal Title\":\"GIScience and Remote Sensing\",\"Series Title\":\"\",\"Month \\\/ Season\":\"October\",\"Year\":2024,\"Publisher\":\"\",\"Publisher City and State\":\"\",\"Publisher Country\":\"\",\"Volume\":\"61\",\"Issue Number \\\/ Edition\":\"1\",\"Page Number(s) or Number of Pages\":\"14\",\"ISSN\":\"\",\"DOI\":\"10.1080\\\/15481603.2024.2409484\",\"CoAuthor\":null,\"URL\":\"https:\\\/\\\/www.tandfonline.com\\\/doi\\\/full\\\/10.1080\\\/15481603.2024.2409484\",\"Description\":\"This paper presents new methods to analyze a category\\u2019s change through a time series of maps, even when the time intervals have inconsistent durations. The methods include an option to facilitate comparison among sites by expressing results as an annual percentage of each site\\u2019s unified size. A site\\u2019s unified size is the union of where the category exists at any of the site\\u2019s time points. The methods also specify gross losses, gross gains, eight trajectories, and three compo\\u00ad nents: Quantity, Exchange, and Alternation. The illustrative application compares maps of the marsh category for three Long-Term Ecological Research sites: Plum Island Ecosystems (PIE), Georgia Coastal Ecosystems (GCE), and the Virginia Coast Reserve (VCR). The application analyzes marsh\\u2019s changes during two time intervals that have unequal durations within each site\\u2019s distinct temporal extent. Results show that PIE has the fastest change during each site\\u2019s temporal extent. Gross change is more than double the quantity change for all sites. Exchange accounts for most of the change in GCE, while Alternation accounts for most of the change in PIE and VCR. The methods provide more information than popular methods that quantify annual net change. Our timeseriesTrajectories R package performs the analysis and is available for free at https:\\\/\\\/github. com\\\/bilintoh\\\/timeseriesTrajectories.\",\"Include description in output citation\":1,\"Origin\":\"Manual\"},\"facultyid\":\"C11301315\",\"status\":[{\"id\":12409,\"status\":\"Completed\\\/Published\",\"term\":\"Fall\",\"year\":2024,\"termid\":\"2024\\\/01\",\"listingorder\":6,\"completionorder\":6}],\"userid\":\"C11301315\",\"attachments\":[{\"attachmentid\":10924,\"mimetype\":\"application\\\/pdf\",\"filename\":\"Bilintoh et al. - 2024 - Methods to compare sites concerning a category\\u2019s c.pdf\",\"filesize\":8716037,\"downloadurl\":\"https:\\\/\\\/faculty180.interfolio.com\\\/public\\\/download.php?key=SDRwNCtxSUpsamxBQ213WS9ucHFuNnMwT0hzQU11b2RPQkJ2cWc3amxyUmNRdVVXTkF4MU10Q1FvdGN3MEZPOUNHVURvZmMzUmM5VXZVdTBUdk5EOGYrNHFxa1oyZ2poU2hvaGJlZnBxbkw5U1R3UVNCVHN6VmxNMUdwN2x3eWkrTGwxNk95ZG9saWg0QkZoT05DUGdIbkpNK0hlbGF0b1haS2xOVlFLZTQzNHBSUVkrcVR2MVI5M0Uxcmc4UWF0L0c2RytLcE1veHVpQkxpUzJMUFZWQT09\"}],\"coauthors_list\":[\"Thomas Mumuni Bilintoh\",\"Robert G. Pontius Jr.\",\"Aiyin Zhang\"],\"sort_date\":\"2024-10-01\"},{\"activityid\":10042,\"fields\":{\"Type\":\"Articles in Refereed Journals\",\"Title\":\"<span style="font-size:12pt;color:#000000;">Performance of CA_Markov and DINAMICA EGO models<\\\/span><span style="font-size:12pt;"> <span style="color:#000000;">to evaluate urban risk in Antofagasta and Mejillones, Chile<\\\/span><\\\/span>\",\"Journal Title\":\"Natural Hazards\",\"Series Title\":\"\",\"Month \\\/ Season\":\"\",\"Year\":2024,\"Publisher\":\"\",\"Publisher City and State\":\"\",\"Publisher Country\":\"\",\"Volume\":\"120\",\"Issue Number \\\/ Edition\":\"\",\"Page Number(s) or Number of Pages\":\"\",\"ISSN\":\"\",\"DOI\":\"https:\\\/\\\/doi.org\\\/10.1007\\\/s11069-024-06512-5\",\"CoAuthor\":null,\"URL\":\"https:\\\/\\\/doi.org\\\/10.1007\\\/s11069-024-06512-5\",\"Description\":\"\",\"Include description in output citation\":0,\"Origin\":\"Manual\"},\"facultyid\":\"C11301315\",\"status\":[{\"id\":10042,\"status\":\"Completed\\\/Published\",\"term\":\"Spring\",\"year\":2024,\"termid\":\"2023\\\/03\",\"listingorder\":6,\"completionorder\":6}],\"userid\":\"C11301315\",\"attachments\":[{\"attachmentid\":8451,\"mimetype\":\"application\\\/pdf\",\"filename\":\"Henr\\u00edquez et al. - 2024 - Performance of CA_Markov and DINAMICA EGO models t.pdf\",\"filesize\":3780411,\"downloadurl\":\"https:\\\/\\\/faculty180.interfolio.com\\\/public\\\/download.php?key=SDRwNCtxSUpsamxBQ213WS9ucHFuNnMwT0hzQU11b2RPQkJ2cWc3amxyUmNRdVVXTkF4MU10Q1FvdGN3MEZPOXE0SEhVVkJ3R3IyaHRpQmszSHRlOWl5Q3JnT0U3TUZUSnlURHVBazI3NU9HQmN6dWdqYmpMTHNsVUp3cXRFbFlXS0VkczFSakZOei9EVndEdk1wYit2RlljejNMam9uRmVURHlreWJ5WjRlb3RGK21BZXRZQktra1h6Ym5saWRJS2lHL2dNSy9VN1E9\"}],\"coauthors_list\":[\"Cristian Henr\\u00edquez\",\"Robert G. 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We perform pairwise map overlays between PRODES and each of GFC and MapBiomas. Each overlay generates a square contingency table, which reveals Misses, Hits, and False Alarms. GFC shows more deforestation than PRODES while MapBiomas shows less deforestation between 2008 and 2020. Both MapBiomas and GFC have more disagreement than agreement with PRODES. False Alarms constitute 64% of GFC\\u2019s deforestation and 27% of MapBiomas\\u2019s deforestation with respect to PRODES. GFC missed 8% of PRODES deforestation while MapBiomas missed 33% between 2008 and 2020. We report Misses, Hits, and False Alarms for each of the 13 years.\",\"Include description in output citation\":1,\"Origin\":\"Manual\"},\"facultyid\":\"C11301315\",\"status\":[{\"id\":12418,\"status\":\"Completed\\\/Published\",\"term\":\"Fall\",\"year\":2024,\"termid\":\"2024\\\/01\",\"listingorder\":6,\"completionorder\":6}],\"userid\":\"C11301315\",\"attachments\":[{\"attachmentid\":10928,\"mimetype\":\"custom\\\/url\",\"filename\":\"https:\\\/\\\/api.conhecimentolivre.org\\\/ecl-api\\\/storage\\\/app\\\/public\\\/L.964-2024.pdf\",\"filesize\":452448,\"downloadurl\":\"https:\\\/\\\/faculty180.interfolio.com\\\/public\\\/download.php?key=SDRwNCtxSUpsamxBQ213WS9ucHFuNnMwT0hzQU11b2RPQkJ2cWc3amxyUmNRdVVXTkF4MU10Q1FvdGN3MEZPOWxLQytxSXV3YUNZTmNTR0tYR29Id1crNS9XV2tLdDlTOUJ4blVLM2xVcDBIek9JNDcyaWMxV0VqUzBCRWp5ak5iZzV2WlE1NkZBYWwwUnpuc3l2NmhpVDFScHRnN2VTZit1WDlKRkUvOHJ1cDEwa3MvY2k2Z1JwZlNiQnpVWlZIV0g0SnJOZSt4UE91aFlCSm1Zak12dz09\"}],\"coauthors_list\":[\"Antonio Victor Galvao da Fonseca\",\"Robert G. Pontius Jr.\"],\"sort_date\":\"2024-08-15\"},{\"activityid\":12421,\"fields\":{\"Type\":\"Other Media (social media, blogs, podcasts, etc)\",\"Title\":\"<span style="font-size:12pt;">Kappa the Undead and <span>the Inconsistent Adoption of Insightful Error Metrics<\\\/span><\\\/span>\",\"Episode Title\":\"\",\"Date Published\":\"2024-08-15\",\"Year\":2024,\"Platform\":\"International Society for Photogrammetry and Remote Sensing\",\"CoAuthor\":null,\"URL\":\"https:\\\/\\\/www.youtube.com\\\/watch?v=mAPwR1bkElY\",\"Description\":\"<span><span style="color:#131313;">This webinar is organized by the ISPRS WG II\\\/2 on 13th August, 2024<\\\/span><span style="color:#131313;"> with the technical support of the ISPRS Student Consortium (ISPRS SC). <br>Speaker: Professor Robert Gilmore Pontius Jr Abstract: This webinar is a follow-up to the 2011 paper by Pontius and Millones entitled Death to Kappa: Birth of Quantity Disagreement and Allocation Disagreement for Accuracy Assessment. The paper\\u2019s title indicates its two recommendations: 1 do not use kappa and 2 use components of disagreement to assess errors. We analyzed 200 articles to see how authors cited the Death to Kappa paper, which has more than 2000 citations. Results show that a quarter of the articles followed both recommendations, another quarter of the articles followed only the first recommendation, another quarter of the articles followed only the second recommendation, and the last quarter of the articles followed neither recommendation. Thus, the attempt to kill kappa and to replace kappa with more enlightening metrics has been partially effective, but kappa continues to haunt our profession. This webinar discusses and illustrates persistent bad habits concerning how authors use metrics in Remote Sensing and Land Change Modeling that were not covered in the 2011 paper. These habits include the use of kappa to assess thematic map accuracy at time points when the research question concerns change during time intervals and to assess the validation of land change predictions. We speculate on some reasons why some scientists use flawed methods and cite literature erroneously. We urge all scientists to pay attention to at least the titles of articles that they cite<\\\/span><\\\/span>\",\"Include description in output citation\":1,\"Origin\":\"Manual\"},\"facultyid\":\"C11301315\",\"status\":[{\"id\":12421,\"status\":\"Completed\\\/Published\",\"term\":\"Summer\",\"year\":2024,\"termid\":\"2023\\\/05\",\"listingorder\":6,\"completionorder\":6}],\"userid\":\"C11301315\",\"attachments\":[{\"attachmentid\":10931,\"mimetype\":\"custom\\\/url\",\"filename\":\"https:\\\/\\\/www.youtube.com\\\/watch?v=mAPwR1bkElY\",\"filesize\":452448,\"downloadurl\":\"https:\\\/\\\/faculty180.interfolio.com\\\/public\\\/download.php?key=SDRwNCtxSUpsamxBQ213WS9ucHFuNnMwT0hzQU11b2RPQkJ2cWc3amxyUmNRdVVXTkF4MU10Q1FvdGN3MEZPOWxLQytxSXV3YUNZTmNTR0tYR29Id1crNS9XV2tLdDlTNGc1dno0aVlWMW9Ra1VYaWpDWGs1UXRrQ0wzdm91bkxnU3VDckV2NzBEejBMQW93Nk91S2pFYnVodkZXSi82c29nUzRrdGl6MVZRPQ%3D%3D\"}],\"coauthors_list\":[\"Robert G. 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Dr. Pontius discussed his journey into the field of geography, highlighting his passion for mathematics and maps. He emphasized the importance of simplicity in modeling and the need to eliminate distractions to focus on the essence of the problem\",\"Include description in output citation\":1,\"Origin\":\"Manual\"},\"facultyid\":\"C11301315\",\"status\":[{\"id\":12419,\"status\":\"Completed\\\/Published\",\"term\":\"Summer\",\"year\":2024,\"termid\":\"2023\\\/05\",\"listingorder\":6,\"completionorder\":6}],\"userid\":\"C11301315\",\"attachments\":[{\"attachmentid\":10929,\"mimetype\":\"custom\\\/url\",\"filename\":\"https:\\\/\\\/podcasts.apple.com\\\/ae\\\/podcast\\\/understanding-science-and-communicating-uncertainty\\\/id1106739747?i=1000656342606\",\"filesize\":452448,\"downloadurl\":\"https:\\\/\\\/faculty180.interfolio.com\\\/public\\\/download.php?key=SDRwNCtxSUpsamxBQ213WS9ucHFuNnMwT0hzQU11b2RPQkJ2cWc3amxyUmNRdVVXTkF4MU10Q1FvdGN3MEZPOWxLQytxSXV3YUNZTmNTR0tYR29Id1crNS9XV2tLdDlTMThLOFFVeXVkWExYVjJwQXhuQStUM1BzOTI1ZXVLNjd1Z2hLWjB4em5mNnlFaUd1eFRZa0Nrb29xd3F4QXdDU0QvYXJOQ2xNTzJEcmFGcFh3N3BtSGRQTEN2Y05LQ0lhZUs2VDM0SS84cVZhVnI3QlBHenV3akFRTXBFTmFiTkFlTTJqbHNZYjVCNmQyQkorSnVtUDFpQkdBd0p2dXl0bDNVdlh3bi80dC8xOHNVMzVlTjViYWc9PQ%3D%3D\"}],\"coauthors_list\":[\"Robert G. 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Pontius\",\"Thomas Bilintoh\",\"Gustavo Oliveira\",\"Julia Shimbo\"],\"sort_date\":\"2023-8-01\"},{\"activityid\":7772,\"fields\":{\"Type\":\"Papers Published - Conference Proceedings\",\"Title of Paper\":\"<span style="font-size:12pt;color:#000000;">Comparison among time series maps of deforestation in the Amazon: How independent monitoring systems relate to official data.<\\\/span>\",\"Title of Published Proceedings\":\"Anais do XX Simp\\u00f3sio Brasileiro de Sensoriamento Remoto\",\"Title of Conference\":\"\",\"Conference Location\":\"Florian\\u00f3polis, Brazil\",\"Month \\\/ Season\":\"April\",\"Year\":2023,\"Publisher\":\"INPE\",\"Publisher City and State\":\"\",\"Volume\":\"20\",\"Issue Number \\\/ Edition\":\"\",\"Page Numbers\":\"1057-1060\",\"DOI\":\"\",\"CoAuthor\":null,\"URL\":\"https:\\\/\\\/proceedings.science\\\/p\\\/164339?lang=pt-br\",\"Description\":\"<p style="text-align:justify;"><span style="font-size:10pt;">This study compares raster maps of Amazon deforestation during annual time intervals from 2008 to 2020 that derive from three sources: Global Forest Change (GFC), MapBiomas, and PRODES. We perform pairwise map overlays between PRODES and each of GFC and MapBiomas. Each overlay generates a square contingency table, which reveals Misses, Hits, and False Alarms. GFC shows more deforestation than PRODES while MapBiomas shows less deforestation between 2008 and 2020. Both MapBiomas and GFC have more disagreement than agreement with PRODES. False Alarms constitute 64% of GFC\\u2019s deforestation and 27% of MapBiomas\\u2019s deforestation with respect to PRODES. GFC missed 8% of PRODES deforestation while MapBiomas missed 33% between 2008 and 2020. We report Misses, Hits, and False Alarms for each of the 13 years.<\\\/span><\\\/p>\",\"Include description in output citation\":0,\"Origin\":\"Manual\"},\"facultyid\":\"C11301315\",\"status\":[{\"id\":7772,\"status\":\"Completed\\\/Published\",\"term\":\"Spring\",\"year\":2023,\"termid\":\"2022\\\/03\",\"listingorder\":6,\"completionorder\":6}],\"userid\":\"C11301315\",\"attachments\":[{\"attachmentid\":6370,\"mimetype\":\"custom\\\/url\",\"filename\":\"https:\\\/\\\/proceedings.science\\\/p\\\/164339?lang=pt-br\",\"filesize\":452448,\"downloadurl\":\"https:\\\/\\\/faculty180.interfolio.com\\\/public\\\/download.php?key=SDRwNCtxSUpsamxBQ213WS9ucHFuNnMwT0hzQU11b2RPQkJ2cWc3amxyUmNRdVVXTkF4MU10Q1FvdGN3MEZPOWxLQytxSXV3YUNZTmNTR0tYR29Id1crNS9XV2tLdDlTWFZkdUxRbHZpM0RseHVZWHhJLzVTRE5XRm1BRm11ZGNsVWNUMVZIK0lJVXhXbWFVM2JKMklTSGdqZjZweVl4azRhY3J5YXJyQk5FPQ%3D%3D\"}],\"coauthors_list\":[\"Antonio Victor Galv\\u00e3o da Fonseca\",\"Robert G. Pontius Jr.\"],\"sort_date\":\"2023-4-01\"},{\"activityid\":7773,\"fields\":{\"Type\":\"Articles in Refereed Journals\",\"Title\":\"Four fundamental questions to evaluate land change models with an illustration of a Cellular Automata \\u2013 Markov model\",\"Journal Title\":\"Annals of the Association of American Geographers\",\"Series Title\":\"\",\"Month \\\/ Season\":\"\",\"Year\":2023,\"Publisher\":\"\",\"Publisher City and State\":\"\",\"Publisher Country\":\"\",\"Volume\":\"113\",\"Issue Number \\\/ Edition\":\"10\",\"Page Number(s) or Number of Pages\":\"2497-2511\",\"ISSN\":\"\",\"DOI\":\"https:\\\/\\\/doi.org\\\/10.1080\\\/24694452.2023.2232435\",\"CoAuthor\":null,\"URL\":\"https:\\\/\\\/www.tandfonline.com\\\/doi\\\/full\\\/10.1080\\\/24694452.2023.2232435\",\"Description\":\"<p>Numerous models exist for users to simulate land change to communicate with an audience concerning future land change. <span>This <\\\/span>manuscript raises four fundamental questions to help model users decide whether to use any model: 1) Can the user understand the model? 2) Can the audience understand the model? 3) Can the user control the model? and 4) Does the model address the goals of the specific application? <span>This <\\\/span>manuscript applies these questions to the popular Cellular Automata - Markov model as the IDRISI\\u2019s CA-Markov module expresses. <span>S<\\\/span>ensitivity analysis examine<span>s<\\\/span> 120 ways to set the module\\u2019s parameters. <span>V<\\\/span>erification compare<span>s<\\\/span> the module\\u2019s behaviour to the software\\u2019s documentation. Results show that the Cellular Automata\\u2019s allocation fails to follow the quantity of change that the Markov module computes. The module\\u2019s behaviour is likely to cause users to misinterpret the validation metrics and to miscommunicate with audiences. 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