Spelling suggestions: "subject:"geographical information systems""
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Environmental justice through pollution prevention development of a quantitative method to assess community vulnerability and air emission hazard for optimal impact /Boettner, John Lewis. January 2002 (has links)
Thesis (M.S.)--West Virginia University, 2002. / Title from document title page. Document formatted into pages; contains ix, 137 p. : ill. (some col.), col. maps. Includes abstract. Includes bibliographical references (p. 104-105).
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Generation of forest stand type maps using high-resolution digital imagery /Mercier, Wilfred Jean-Baptiste, January 2009 (has links)
Thesis (M.S.) in Forest Resources--University of Maine, 2009. / Includes vita. Includes bibliographical references (leaves 77-80).
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Integrating geographic information systems and community mapping into secondary science education : a web GIS approach /O'Dea, Elizabeth K. January 1900 (has links)
Thesis (M.S.)--Oregon State University, 2003. / Typescript (photocopy). Includes bibliographical references (leaves 57-62). Also available online.
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Shake, rattle and roll hazard modeling in Indonesia using GIS /Snyder, Jacqueline K. January 2001 (has links)
Thesis (M.S.)--West Virginia University, 2001. / Title from document title page. Document formatted into pages; contains vi, 134 p. : ill., maps (some col.). Includes abstract. Includes bibliographical references (p. 128-134).
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New methods for positional quality assessment and change analysis of shoreline featuresAli, Tarig Abdelgayoum, January 2003 (has links)
Thesis (Ph. D.)--Ohio State University, 2003. / Title from first page of PDF file. Document formatted into pages; contains xiv, 142 p.; also includes graphics (some col.). Includes abstract and vita. Advisor: Ronxing Li, Dept.of Civil Engineering and Geodetic Science. Includes bibliographical references (p. 134-142).
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Remote sensing, geographical information systems, and spatial modeling for analyzing public transit servicesWu, Changshan. January 2003 (has links)
Thesis (Ph. D.)--Ohio State University, 2003. / Title from first page of PDF file. Document formatted into pages; contains xvi, 141 p.; also includes graphics (some col.). Includes abstract and vita. Advisor: Alan T. Murray, Dept. of Geography. Includes bibliographical references (p. 124-141).
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Evaluation, modeling and policy assessment for park-and-ride services as a component of public transportationFarhan, Bilal Ishaq, January 2003 (has links)
Thesis (Ph. D.)--Ohio State University, 2003. / Title from first page of PDF file. Document formatted into pages; contains xii, 139 p.; also includes graphics (some col.). Includes abstract and vita. Advisor: Mei-Po Kwan, Dept. of Geography. Includes bibliographical references (p. 132-139).
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Handling uncertainty in GIS and environmental models : An application in forest managementJoy, Michael Wilfrid 05 1900 (has links)
The study of uncertainty in Geographic Information Systems (GIS) and environmental
models has received increasing attention in recent years, due in part to the widespread use
of GIS for resource management. This study used GIS-based techniques in order to
compare several different forest inventory and forest cover datasets. These datasets pertain
to an area of the boreal mixedwood forest in northeastern Alberta which covers roughly
73,000 km2, and which has recently been approved for logging. The datasets include two
forest inventories based on aerial photographs, and a forest cover classification based on
remotely sensed satellite data.
Simple logical operations were used to transform the datasets to a form suitable for
comparison. Standard GIS overlay techniques were used to compare the agreement among
different datasets. Visualization techniques were used to display patterns of agreement in
attribute space (contingency tables), and in geographic space (maps of uncertainty).
Agreement between the two forest inventories was about 50% (Percent Correctly
Classified), with a Kappa value of 0.4, for a classification based on species composition.
In general, much of the misclassification was between ecologically similar types,
particularly between different combinations of aspen and white spruce. Comparison of the
forest inventories with the classified satellite image was done using a simplified land
cover classification with five categories. Agreement was about 55% (Percent Correctly
Classified), with a Kappa value of 0.3.
Possible sources of discrepancy among datasets include change over time, differences in
spatial scale, differences in category definitions, positional inaccuracy, boundary effects
and misclassification. Analyses were conducted to characterize the effect of each of these
sources of disagreement. The agreement was strongly affected by the distance to
boundary, indicating a boundary effect extending to more than 100 meters. Differences in
spatial scale accounted for a small proportion of discrepancy. None of the other possible
sources had a measurable effect on the discrepancy. It was therefore inferred that
misclassification accounted for a large proportion of the discrepancy.
Estimated levels of uncertainty were propagated through models including simple growth
and yield tables and a more complex harvest scheduling model. It was found that
uncertainty in model outputs was strongly affected by uncertainty in inventory data,
uncertainty in volume yield curves, and perhaps most importantly, by a poor
understanding of disturbance and forest dynamics in the region. The results of the analysis
show that these uncertainties may have significant economic and ecological implications.
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Topographic characterization for DEM error modellingXiao, Yanni 05 1900 (has links)
Digital Elevation Models have been in use for more than three decades and have become a
major component of geographic information processing. The intensive use of DEMs has
given rise to many accuracy investigations. The accuracy estimate is usually given in a form
of a global measure such as root-mean-square error (RMSE), mostly from a producer's point
of view. Seldom are the errors described in terms of their spatial distribution or how the
resolution of the DEM interacts with the variability of terrain. There is a wide range of
topographic variation present in different terrain surfaces. Thus, in defining the accuracy of
a DEM, one needs ultimately to know the global and local characteristics of the terrain and
how the resolution interacts with them.
In this thesis, DEMs of various resolutions (i.e., 10 arc-minutes, 5 arc-minutes, 2 km, 1 km,
and 50 m) in the study area (Prince George, British Columbia) were compared to each other
and their mismatches were examined. Based on the preliminary test results, some
observations were made regarding the relations among the spatial distribution of DEM errors,
DEM resolution and the roughness of terrain. A hypothesis was proposed that knowledge of
the landscape characteristics might provide some insights into the nature of the inherent error
(or uncertainty) in a DEM. To test this statistically, the global characteristics of the study
area surfaces were first examined by measures such as grain and those derived from spectral
analysis, nested analysis of variance and fractal analysis of DEMs. Some important scale
breaks were identified for each surface and this information on the surface global
characteristics was then used to guide the selection of the moving window sizes for the
extraction of the local roughness measures. The spatial variation and complexity of various
study area surfaces was characterized by means of seven local geomorphometric parameters.
The local measures were extracted from DEMs with different resolutions and using different
moving window sizes. Then the multivariate cluster analysis was used for automated terrain
classification in which relatively homogeneous terrain types at different scale levels were
identified. Several different variable groups were used in the cluster analysis and the
different classification results were compared to each other and interpreted in relation to each
roughness measure. Finally, the correlations between the DEM errors and each of the local
roughness measures were examined and the variation of DEM errors within various terrain
clusters resulting from multivariate classifications were statistically evaluated. The
effectiveness of using different moving window sizes for the extraction of the local measures
and the appropriateness of different variable groups for terrain classification were also
evaluated.
The major conclusion of this study is that knowledge of topographic characteristics does
provide some insights into the nature of the inherent error (or uncertainty) in a DEM
and can be useful for DEM error modelling. The measures of topographic complexity are
related to the observed patterns of discrepancy between DEMs of differing resolution, but
there are variations from case to case. Several patterns can be identified in terms of relation
between DEM errors and the roughness of terrain. First of all, the DEM errors (or elevation
differences) do show certain consistent correlations with each of the various local roughness
variables. With most variables, the general pattern is that the higher the roughness measure,
the more points with higher absolute elevation differences (i.e., horn-shaped scatter of points
indicating heteroscedasticity). Further statistical test results indicate that various DEM errors
in the study area do show significant variation between different clusters resulting from
terrain classifications based on different variable groups and window sizes. Cluster analysis
was considered successful in grouping the areas according to their overall roughness and
useful in DEM error modelling. In general, the rougher the cluster, the larger the DEM error
(measured with either the standard deviation of the elevation differences or the mean of the
absolute elevation differences in each cluster). However, there is still some of the total
variation of various DEM errors that could not be accounted for by the cluster structure
derived from multivariate classification. This could be attributed to the random errors
inherent in any of the DEMs and the errors introduced in the interpolation process.
Another conclusion is that the multivariate approach to the classification of topographic
surfaces for DEM error modelling is not necessarily more successful than using only a single
roughness measure in characterizing the overall roughness of terrain. When comparing the
DEM error modelling results for surfaces with different global characteristics, the size of the
moving window used in geomorphometric parameter abstraction also has certain impact on
the modelling results. It shows that some understanding of the global characteristics of the
surface is useful in the selection of appropriate/optimal window sizes for the extraction of
local measures for DEM error modelling. Finally, directions for further research are
suggested.
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Assessment and optimization of site characterization and monitoring activities using geostatistical methods within a geographic information systems environmentParsons, Robert Lee 05 1900 (has links)
No description available.
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