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Papers by Robert Gilmore Pontius Jr.
Scientists and policymakers have realised that localities are central to addressing the causes an... more Scientists and policymakers have realised that localities are central to addressing the causes and consequences of global environmental change. The goal of the Human-Environment Regional Observatory project (HERO) was to develop the infrastructure necessary to monitor and understand the local dimensions of global change. This book presents the philosophy behind HERO, the methods used to put that philosophy into action, its results, and the lessons learned from the project. HERO used three strategies: it developed research protocols and data standards for collecting data; it built a web-based networking environment to help investigators share data, analyses and ideas from remote locations; and investigators field-tested these concepts by applying them in diverse biophysical and socioeconomic settings - central Massachusetts, central Pennsylvania, southwestern Kansas, and the US-Mexico border region of Arizona. The book highlights the unique focus of HERO regarding thinking and acting...
Agriculture, Ecosystems & Environment, Jun 1, 2001
The Biological Bulletin, Oct 1, 2002
ISPRS Journal of Photogrammetry and Remote Sensing, 2018
International Journal of Applied Earth Observation and Geoinformation, 2018
Journal of Spatial Science, 2016
Abstract Land change in Kigali, Rwanda, is examined using Intensity Analysis, which measures the ... more Abstract Land change in Kigali, Rwanda, is examined using Intensity Analysis, which measures the temporal stationarity of changes among categories. Maps for 1981, 2002 and 2014 were produced that show the land categories Built, Vegetated and Other, which is composed mainly of croplands and bare surfaces. Land change accelerated from the first time interval (1981–2002) to the second time interval (2002–2014), as increased human and economic activities drove land transformation. During the first interval, Vegetated showed net loss whereas Built showed net gain, in spite of a small transition directly from Vegetated to Built. During the second interval, Vegetated showed net gain whereas Built showed nearly equal amounts of gross loss and gross gain. The gain of Built targeted Other during both time intervals. A substantial portion of overall change during both time intervals consisted of simultaneous transitions from Vegetated to Other in some locations and from Other to Vegetated in other locations.
Biological Bulletin, 2003
Sustainable Communities on a Sustainable Planet, 2009
Conservation Biology, 2001
Photogrammetric Engineering and Remote Sensing, 2000
... hyperspectral sensing, the large number of new governmental and commercial satellite systems,... more ... hyperspectral sensing, the large number of new governmental and commercial satellite systems, digital ... GIS fields, with a particular emphasis on mathematical techniques and their application. ... The range of applications includes land-cover and land-use mapping, cloud tracking ...
The Biological Bulletin, Oct 1, 2004
Land
The Flow matrix is a novel method to describe and extrapolate transitions among categories. The F... more The Flow matrix is a novel method to describe and extrapolate transitions among categories. The Flow matrix extrapolates a constant transition size per unit of time on a time continuum with a maximum of one incident per observation during the extrapolation. The Flow matrix extrapolates linearly until the persistence of a category shrinks to zero. The Flow matrix has concepts and mathematics that are more straightforward than the Markov matrix. However, many scientists apply the Markov matrix by default because popular software packages offer no alternative to the Markov matrix, despite the conceptual and mathematical challenges that the Markov matrix poses. The Markov matrix extrapolates a constant transition proportion per time interval during whole-number multiples of the duration of the calibration time interval. The Markov extrapolation allows at most one incident per observation during each time interval but allows repeated incidents per observation through sequential time inte...
This paper gives a technique to extrapolate the anticipated accuracy of a prediction of land-use ... more This paper gives a technique to extrapolate the anticipated accuracy of a prediction of land-use and land-cover change (LUCC) to any point in the future. The method calibrates a LUCC model with information from the past in order to simulate a map of the present, so that it can compute an objective measure of validation with empirical data. Then it uses that observed measurement of predictive accuracy to anticipate how accurately the model will predict a future landscape. The technique assumes that the accuracy of the model will decay to randomness as the model predicts farther into the future and estimates how fast the decay in accuracy will occur based on prior model performance. Results are presented graphically in terms of percentage of pixels classified correctly so that nonexperts can interpret the accuracy visually. The percentage correct is budgeted by three components: agreement due to chance, agreement due to the predicted quantity of each land category, and agreement due t...
Advances in geographic information science, 2022
This paper explores the use of spatial interpolative methods in conjunction with object based ima... more This paper explores the use of spatial interpolative methods in conjunction with object based image analysis to estimate turf grass land cover quantity and allocation in Greater Boston, Massachusetts, USA. The goal is to learn how accurately turf grass can be estimated if only a limited portion of the study area is mapped. First, turf grass land cover is mapped at the 0.5 m resolution across the entire Plum Island Ecosystems (PIE) Long Term Ecological Research (LTER) site, a 1143-km 2 area. Second, the turf grass map is aggregated into 120 m cells (N = 84,661). Third, a random sample of these 120 m cells are selected to generate an estimate of the unselected cells using four estimation methods-Inverse Distance Weighting, Kriging, Polygonal Interpolation, and Mean Estimation. The difference between known and estimated values is recorded using 120 m cell and census block group stratifications. This process is repeated 500 times for sample sizes of 2.5%, 5.0%, 7.5% and 10.0% of the stu...
Scientists and policymakers have realised that localities are central to addressing the causes an... more Scientists and policymakers have realised that localities are central to addressing the causes and consequences of global environmental change. The goal of the Human-Environment Regional Observatory project (HERO) was to develop the infrastructure necessary to monitor and understand the local dimensions of global change. This book presents the philosophy behind HERO, the methods used to put that philosophy into action, its results, and the lessons learned from the project. HERO used three strategies: it developed research protocols and data standards for collecting data; it built a web-based networking environment to help investigators share data, analyses and ideas from remote locations; and investigators field-tested these concepts by applying them in diverse biophysical and socioeconomic settings - central Massachusetts, central Pennsylvania, southwestern Kansas, and the US-Mexico border region of Arizona. The book highlights the unique focus of HERO regarding thinking and acting...
Agriculture, Ecosystems & Environment, Jun 1, 2001
The Biological Bulletin, Oct 1, 2002
ISPRS Journal of Photogrammetry and Remote Sensing, 2018
International Journal of Applied Earth Observation and Geoinformation, 2018
Journal of Spatial Science, 2016
Abstract Land change in Kigali, Rwanda, is examined using Intensity Analysis, which measures the ... more Abstract Land change in Kigali, Rwanda, is examined using Intensity Analysis, which measures the temporal stationarity of changes among categories. Maps for 1981, 2002 and 2014 were produced that show the land categories Built, Vegetated and Other, which is composed mainly of croplands and bare surfaces. Land change accelerated from the first time interval (1981–2002) to the second time interval (2002–2014), as increased human and economic activities drove land transformation. During the first interval, Vegetated showed net loss whereas Built showed net gain, in spite of a small transition directly from Vegetated to Built. During the second interval, Vegetated showed net gain whereas Built showed nearly equal amounts of gross loss and gross gain. The gain of Built targeted Other during both time intervals. A substantial portion of overall change during both time intervals consisted of simultaneous transitions from Vegetated to Other in some locations and from Other to Vegetated in other locations.
Biological Bulletin, 2003
Sustainable Communities on a Sustainable Planet, 2009
Conservation Biology, 2001
Photogrammetric Engineering and Remote Sensing, 2000
... hyperspectral sensing, the large number of new governmental and commercial satellite systems,... more ... hyperspectral sensing, the large number of new governmental and commercial satellite systems, digital ... GIS fields, with a particular emphasis on mathematical techniques and their application. ... The range of applications includes land-cover and land-use mapping, cloud tracking ...
The Biological Bulletin, Oct 1, 2004
Land
The Flow matrix is a novel method to describe and extrapolate transitions among categories. The F... more The Flow matrix is a novel method to describe and extrapolate transitions among categories. The Flow matrix extrapolates a constant transition size per unit of time on a time continuum with a maximum of one incident per observation during the extrapolation. The Flow matrix extrapolates linearly until the persistence of a category shrinks to zero. The Flow matrix has concepts and mathematics that are more straightforward than the Markov matrix. However, many scientists apply the Markov matrix by default because popular software packages offer no alternative to the Markov matrix, despite the conceptual and mathematical challenges that the Markov matrix poses. The Markov matrix extrapolates a constant transition proportion per time interval during whole-number multiples of the duration of the calibration time interval. The Markov extrapolation allows at most one incident per observation during each time interval but allows repeated incidents per observation through sequential time inte...
This paper gives a technique to extrapolate the anticipated accuracy of a prediction of land-use ... more This paper gives a technique to extrapolate the anticipated accuracy of a prediction of land-use and land-cover change (LUCC) to any point in the future. The method calibrates a LUCC model with information from the past in order to simulate a map of the present, so that it can compute an objective measure of validation with empirical data. Then it uses that observed measurement of predictive accuracy to anticipate how accurately the model will predict a future landscape. The technique assumes that the accuracy of the model will decay to randomness as the model predicts farther into the future and estimates how fast the decay in accuracy will occur based on prior model performance. Results are presented graphically in terms of percentage of pixels classified correctly so that nonexperts can interpret the accuracy visually. The percentage correct is budgeted by three components: agreement due to chance, agreement due to the predicted quantity of each land category, and agreement due t...
Advances in geographic information science, 2022
This paper explores the use of spatial interpolative methods in conjunction with object based ima... more This paper explores the use of spatial interpolative methods in conjunction with object based image analysis to estimate turf grass land cover quantity and allocation in Greater Boston, Massachusetts, USA. The goal is to learn how accurately turf grass can be estimated if only a limited portion of the study area is mapped. First, turf grass land cover is mapped at the 0.5 m resolution across the entire Plum Island Ecosystems (PIE) Long Term Ecological Research (LTER) site, a 1143-km 2 area. Second, the turf grass map is aggregated into 120 m cells (N = 84,661). Third, a random sample of these 120 m cells are selected to generate an estimate of the unselected cells using four estimation methods-Inverse Distance Weighting, Kriging, Polygonal Interpolation, and Mean Estimation. The difference between known and estimated values is recorded using 120 m cell and census block group stratifications. This process is repeated 500 times for sample sizes of 2.5%, 5.0%, 7.5% and 10.0% of the stu...