Robert Gilmore Pontius
Biographic Data
| ID | 1340249 |
|---|---|
| NAME | Robert Gilmore Pontius |
| GIVEN NAMES | Robert Gilmore |
| FAMILY NAME | Pontius |
| SIGNATURE | PONTIUS R G |
| AFFILIATIONS | Clark University |
| ORCID | 0000-0001-7287-5875 |
| VERIFIED | Yes |
| TOTAL WORKS | 14 |
| TOTAL CITATIONS | 27 |
| WORKS AS AUTHOR | 14 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2004 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 3 |
Best Practices for Applying and Interpreting the Total Operating Characteristic
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 mod…
Encoding a Categorical Independent Variable for Input to TerrSet’s Multi-Layer Perceptron
The profession debates how to encode a categorical variable for input to machine learning algorithms, such as neural networks. A conventional approach is to convert a categorical variable into a collection of binary variables, which causes a burdensome number of correlated variables. TerrSet’s Land Change Modeler proposes encoding a categorical variable onto the continuous closed interval from 0 to 1 based on each category’s Population Evidence L…
Integrating a Forward Feature Selection algorithm, Random Forest, and Cellular Automata to extrapolate urban growth in the Tehran-Karaj Region of Iran
Spatial Decision Support Systems
Opportunities to improve impact, integration, and evaluation of land change models
Death to Kappa
The family of Kappa indices of agreement claim to compare a map's observed classification accuracy relative to the expected accuracy of baseline maps that can have two types of randomness: (1) random distribution of the quantity of each category and (2) random spatial allocation of the categories. Use of the Kappa indices has become part of the culture in remote sensing and other fields. This article examines five different Kappa indices, some of…
Comparison of Three Maps at Multiple Resolutions
Geographic modelers frequently compare maps of observed land transitions to maps of simulated land transitions to relate the patterns in reference maps to the output from a simulation model. Pixel-by-pixel analysis of raster maps at a single resolution is useful for this task at a single scale, but scientists often need to consider additional scales. This article presents methods to satisfy this need by proposing a multiple-resolution method to c…
Sustainable Communities on a Sustainable Planet
Uncertainty in the difference between maps of future land change scenarios
Comparing the input, output, and validation maps for several models of land change
Accuracy Assessment for a Simulation Model of Amazonian Deforestation
This article describes a quantitative assessment of the output from the Behavioral Landscape Model (BLM), which has been developed to simulate the spatial pattern of deforestation (i.e. forest fragmentation) in the Amazon basin in a manner consistent with human behavior. The assessment consists of eighteen runs for a section of the Transamazon Highway in the lower basin, where the BLM's simulated deforestation map for each run is compared to a re…
Can Error Explain Map Differences Over Time
This paper presents methods to test whether map error can explain the observed differences between two points in time among categories of land cover in maps. Such differences may be due to two reasons: error in the maps and change on the ground. Our methods use matrix algebra: (1) to determine whether error can explain specific types of observed categorical transitions between two maps, (2) to represent visually the differences between the maps t…
Detecting important categorical land changes while accounting for persistence
Calibration and validation of a model of forest disturbancein the Western Ghats, India 1920–1990
Comparison of Three Maps at Multiple Resolutions
Geographic modelers frequently compare maps of observed land transitions to maps of simulated land transitions to relate the patterns in reference maps to the output from a simulation model. Pixel-by-pixel analysis of raster maps at a single resolution is useful for this task at a single scale, but scientists often need to consider additional scales. This article presents methods to satisfy this need by proposing a multiple-resolution method to c…
Accuracy Assessment for a Simulation Model of Amazonian Deforestation
This article describes a quantitative assessment of the output from the Behavioral Landscape Model (BLM), which has been developed to simulate the spatial pattern of deforestation (i.e. forest fragmentation) in the Amazon basin in a manner consistent with human behavior. The assessment consists of eighteen runs for a section of the Transamazon Highway in the lower basin, where the BLM's simulated deforestation map for each run is compared to a re…
Opportunities to improve impact, integration, and evaluation of land change models
Can Error Explain Map Differences Over Time
This paper presents methods to test whether map error can explain the observed differences between two points in time among categories of land cover in maps. Such differences may be due to two reasons: error in the maps and change on the ground. Our methods use matrix algebra: (1) to determine whether error can explain specific types of observed categorical transitions between two maps, (2) to represent visually the differences between the maps t…
Calibration and validation of a model of forest disturbancein the Western Ghats, India 1920–1990
Uncertainty in the difference between maps of future land change scenarios
Detecting important categorical land changes while accounting for persistence
Calibration and validation of a model of forest disturbancein the Western Ghats, India 1920–1990
Can Error Explain Map Differences Over Time
This paper presents methods to test whether map error can explain the observed differences between two points in time among categories of land cover in maps. Such differences may be due to two reasons: error in the maps and change on the ground. Our methods use matrix algebra: (1) to determine whether error can explain specific types of observed categorical transitions between two maps, (2) to represent visually the differences between the maps t…
Accuracy Assessment for a Simulation Model of Amazonian Deforestation
This article describes a quantitative assessment of the output from the Behavioral Landscape Model (BLM), which has been developed to simulate the spatial pattern of deforestation (i.e. forest fragmentation) in the Amazon basin in a manner consistent with human behavior. The assessment consists of eighteen runs for a section of the Transamazon Highway in the lower basin, where the BLM's simulated deforestation map for each run is compared to a re…
Comparing the input, output, and validation maps for several models of land change
Uncertainty in the difference between maps of future land change scenarios
Sustainable Communities on a Sustainable Planet
Death to Kappa
The family of Kappa indices of agreement claim to compare a map's observed classification accuracy relative to the expected accuracy of baseline maps that can have two types of randomness: (1) random distribution of the quantity of each category and (2) random spatial allocation of the categories. Use of the Kappa indices has become part of the culture in remote sensing and other fields. This article examines five different Kappa indices, some of…
Comparison of Three Maps at Multiple Resolutions
Geographic modelers frequently compare maps of observed land transitions to maps of simulated land transitions to relate the patterns in reference maps to the output from a simulation model. Pixel-by-pixel analysis of raster maps at a single resolution is useful for this task at a single scale, but scientists often need to consider additional scales. This article presents methods to satisfy this need by proposing a multiple-resolution method to c…
Opportunities to improve impact, integration, and evaluation of land change models
Spatial Decision Support Systems
Encoding a Categorical Independent Variable for Input to TerrSet’s Multi-Layer Perceptron
The profession debates how to encode a categorical variable for input to machine learning algorithms, such as neural networks. A conventional approach is to convert a categorical variable into a collection of binary variables, which causes a burdensome number of correlated variables. TerrSet’s Land Change Modeler proposes encoding a categorical variable onto the continuous closed interval from 0 to 1 based on each category’s Population Evidence L…
Integrating a Forward Feature Selection algorithm, Random Forest, and Cellular Automata to extrapolate urban growth in the Tehran-Karaj Region of Iran
Best Practices for Applying and Interpreting the Total Operating Characteristic
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 mod…
Computer Science (14 works) · Mathematics (10 works) · Land Use and Ecosystem Services (9 works) · Statistics (8 works) · Geography (7 works) · Environmental Science (5 works) · Land use (5 works) · Conservation, Biodiversity, and Resource Management (4 works) · Ecology (4 works) · Ecology (4 works)