Papers by Suzanne Wechsler
Review November 30, 2006 US EPA Funding No. 05-101-180-0
Small commercial aerial platforms for the generation of systematic, high-resolution, multi-spectral imagery and photogrammetry: Trimble UX5 and X100
The contents of this report reflect the views of the authors, who are responsible for the facts a... more The contents of this report reflect the views of the authors, who are responsible for the facts and the accuracy of the information presented herein. This document is disseminated under the sponsorship of the Department of Transportation, University Transportation Centers Program, and California Department of Transportation in the interest of information exchange. The U.S. Government and California Department of Transportation assume no liability for the contents or use thereof. The contents do not necessarily reflect the official views or policies of the State of California or the Department of Transportation. This report does not constitute a standard, specification, or regulation.
Journal of Environmental Management, 2018
Savanna fires are a critical earth-system process that alter vegetation regionally and contribute... more Savanna fires are a critical earth-system process that alter vegetation regionally and contribute to changes in atmospheric composition globally. The fire regime in savannas has shifted over time resulting in a large reduction in burned area. Savanna fires, which are human caused and set for a plethora of reasons, produce complex mosaic burned area patterns that tend to result in lower overall burned area. Mosaic fire regimes are difficult to detect and map accurately using available satellite data. Imagery-induced low-resolution bias makes it difficult to link fires with relevant environmental and anthropogenic factors, while higher resolution imagery is temporally less frequent. We explore how landscape pattern affects the fire regime in a mesic savanna by quantifying relationships between the spatial patterns of vegetation, which are shaped by natural and human factors, widely used ecological indices, and the seasonality and frequency of fires. The study finds that landscape pattern influences the fire regime; fire seasonality and frequency varied by landscape index at both the vegetation class and landscape scales. Percent cover, shape index and largest patch landscape ecological indices demonstrated the most consistency in burn date trends across scales. The study finds that landscape fragmentation-specifically a reduction in the size of patches and an increase in their number-results in an earlier fire regime. We conclude that fire intensity and severity will continue to decline as agriculture expands and landscapes fragment from agriculture in savannas. Our methods also demonstrate the ability to integrate landscape indices with coarse-resolution fire data.
Buffering the savanna: fire regimes and disequilibrium ecology in West Africa
Plant Ecology, 2016
According to contemporary ecological theory, the mechanisms governing tree cover in savannas vary... more According to contemporary ecological theory, the mechanisms governing tree cover in savannas vary by precipitation level. In tropical areas with mesic rainfall levels, savannas are unstable systems in which disturbances, such as fire, determine the ratio of trees to grasses. Precipitation in these so-called “disturbance-driven savannas” is sufficient to support forest but frequent disturbances prevent transition to a closed canopy state. Building on a savanna buffering model we argue that a consistent fire regime is required to maintain savannas in mesic areas. We hypothesize that the spatiotemporal pattern of fires is highly regular and stable in these areas. Furthermore, because tree growth rates in savannas are a function of precipitation, we hypothesize that savannas with the highest rainfall levels will have the most consistent fire pattern and the most intense fires—thus the strongest buffering mechanisms. We analyzed the spatiotemporal pattern of burning over 11 years for a large subset of the West African savanna using a moderate resolution imaging spectroradiometer active fire product to document the fire regime for three savanna belts with different precipitation levels. We used LISA analysis to quantify the spatiotemporal patterns of fires, coefficient of variance to quantify differences in peak fire dates, and center or gravity pathways to characterize the spatiotemporal patterns of the fires for each area. Our analysis confirms that spatiotemporal regularity of the fire regime is greater for mesic areas that for areas where precipitation is lower and that areas with more precipitation have more regular fire regimes.
Hydrology and Earth System Sciences, 2007
Digital elevation models (DEMs) represent the topography that drives surface flow and are arguabl... more Digital elevation models (DEMs) represent the topography that drives surface flow and are arguably one of the more important data sources for deriving variables used by numerous hydrologic models. A considerable amount of research has been conducted to address uncertainty associated with error in digital elevation models (DEMs) and the propagation of error to derived terrain parameters. This review brings together a discussion of research in fundamental topical areas related to DEM uncertainty that affect the use of DEMs for hydrologic applications. These areas include: (a) DEM error; (b) topographic parameters frequently derived from DEMs and the associated algorithms used to derive these parameters; (c) the influence of DEM scale as imposed by grid cell resolution; (d) DEM interpolation; and (e) terrain surface modification used to generate hydrologicallyviable DEM surfaces. Each of these topical areas contributes to DEM uncertainty and may potentially influence results of distributed parameter hydrologic models that rely on DEMs for the derivation of input parameters. The current state of research on methods developed to quantify DEM uncertainty is reviewed. Based on this review, implications of DEM uncertainty and suggestions for the GIS research and user communities are offered.
Spatial Data Uncertainty
Reference Module in Earth Systems and Environmental Sciences, 2018
Uncertainty is an attendant characteristic of all spatial data. Spatial data are complex, as are ... more Uncertainty is an attendant characteristic of all spatial data. Spatial data are complex, as are the phenomena and processes we use these data to represent, model, and understand. Although not exhaustive, this article reviews fundamental concepts related to spatial data uncertainty and methods the geospatial research communities have developed to understand and represent uncertainty. Addressing uncertainty is an ongoing creative exploration and challenge. Especially in the era of big geospatial data, spatial analyses and spatial datasets evolve with technological advances; therefore, new methods for studying uncertainty will be required. In the meantime, existing methods reviewed here should be more widely integrated into standard geospatial practice.
The Geoscience Diversity Enhancement Program (GDEP): A Model for Faculty and Student Engagement in Urban Geoscience Research
For the past three years (2002-2004) faculty in the departments of geological sciences, geography... more For the past three years (2002-2004) faculty in the departments of geological sciences, geography, and anthropology at California State University, Long Beach have joined to offer an NSF-funded (GEO-0119891) eight-week summer research experience to faculty and students at Long Beach area high schools and community colleges. GDEP's goal is to increase the numbers of students from underrepresented groups (African-American, Hispanic,
Landscape-scale geospatial research utilizing low elevation aerial photography generated with commercial unmanned aerial systems
The Pervasive Challenge of Error and Uncertainty in Geospatial Data
Key Challenges in Geography
Error-based Uncertainty
Geographic Information Science & Technology Body of Knowledge
Digital elevation models (DEMs) represent the topography that drives surface flow and are arguabl... more Digital elevation models (DEMs) represent the topography that drives surface flow and are arguably one of the more important data sources for deriving variables used by numerous hydrologic models. A considerable amount of research has been conducted to address uncertainty associated with error in digital elevation models (DEMs) and the propagation of error to derived terrain parameters. This review brings together a discussion of research in fundamental topical areas related to DEM uncertainty that affect the use of DEMs for hydrologic applications. These areas include: (a) DEM error; (b) topographic parameters frequently derived from DEMs and the associated algorithms used to derive these parameters; (c) the influence of DEM scale as imposed by grid cell resolution; (d) DEM interpolation; and (e) terrain surface modification used to generate hydrologically-viable DEM surfaces. Each of these topical areas contributes to DEM uncertainty and may potentially influence results of distributed parameter hydrologic models that rely on DEMs for the derivation of input parameters. The current state of research on methods developed to quantify DEM uncertainty is reviewed. Based on this review, implications of DEM uncertainty and suggestions for the GIS research and user communities are offered.
Health effects associated with goods movement in the Los Angeles basin
M.S., Water Resources Management, SUNY-ESF, Syracuse, NY. Research: Integration of GIS data with the Agricultural Nonpoint Source Pollution Model: Effect of Cell Size Resolution and Scale of Soils Data on Model Output
An Alternative Approach to Geospatial Graduate Education, ArcNews, Fall 2014
Eos, Transactions American Geophysical Union, 2005
Geosciences Student Recruitment Strategies at California State University, Long Beach (CSULB): Earth System Science/Community-Research Based Education Partnerships
Collaborations among geoscience-oriented departments at California State University, Long Beach (... more Collaborations among geoscience-oriented departments at California State University, Long Beach (Geological Sciences, as well as portions of the Geography and Anthropology departments and a new, fast-growing Environmental Sciences and Policy (ES&P) program) are characterized by attention to three important elements: (1) community-based partnerships and research, (2) outreach and continuity within educational pipeline transitions from high school, to community college, to university, and, (3) sharing of resources and expertise. Three specific collaborations, (1) creation of the ES&P, (2) the NSF-funded Geoscience Diversity Enhancement Program (GDEP), and, (3) the Institute for Interdisciplinary Research on Materials, Environment, and Societies (IIRMES), are powerful illustrations of how these collaborations can work to foster geoscience student recruitment and academic development, particularly at urban, highly diverse institutions with limited resources. Through a combination of stu...
This report describes an assessment of digital elevation models (DEMs) derived from LiDAR data fo... more This report describes an assessment of digital elevation models (DEMs) derived from LiDAR data for a subset of the Ports of Los Angeles and Long Beach. A methodology based on Monte Carlo simulation was applied to investigate the accuracy of DEMs derived from the LiDAR data using different interpolation methods (inverse distance weighted, spline and Kriging) at different grid cell resolutions (0.25m 2 , and 0.50m 2 , 1m 2 and 2m 2 ). Results indicate that elevation accuracy and the accuracy of a building feature derived from the interpolated elevations are not correlated. Inverse Distance Weighed at 0.25m 2 resolution produced the most accurate surfaces and ranked second in its ability to capture the shape of the building. However, this interpolation method and grid cell resolution pair took the longest time to compute (over three weeks for the accuracy simulation). The methodology provides Port personnel and LiDAR users with an approach to determine an appropriate grid cell resolution and interpolation method for generating DEMs and extracting building features from LiDAR data. Results indicate that compromises between surface accuracy, shape representation and the time required to process the data are required.
Digital elevation models (DEMs) represent the topography that drives surface flow and are arguabl... more Digital elevation models (DEMs) represent the topography that drives surface flow and are arguably one of the more important data sources for deriving variables used by numerous hydrologic models. A considerable amount of research has been conducted to address uncertainty associated with error in digital elevation models (DEMs) and the propagation of error to derived terrain parameters. This review brings together a discussion of research in fundamental topical areas related to DEM uncertainty that affect the use of DEMs for hydrologic applications. These areas include: (a) DEM error; (b) topographic parameters frequently derived from DEMs and the associated algorithms used to derive these parameters; (c) the influence of DEM scale as imposed by grid cell resolution; (d) DEM interpolation; and (e) terrain surface modification used to generate hydrologicallyviable DEM surfaces. Each of these topical areas contributes to DEM uncertainty and may potentially influence results of distributed parameter hydrologic models that rely on DEMs for the derivation of input parameters. The current state of research on methods developed to quantify DEM uncertainty is reviewed. Based on this review, implications of DEM uncertainty and suggestions for the GIS research and user communities are offered.
Photogrammetric engineering and remote …, Jan 1, 2006
Digital elevation models (DEMs) are representations of topography with inherent errors that const... more Digital elevation models (DEMs) are representations of topography with inherent errors that constitute uncertainty. DEM data are often used in analyses without quantifying the effects of these errors. This paper describes a Monte Carlo methodology for evaluation of the effects of uncertainty on elevation and derived topographic parameters. Four methods for representing DEM uncertainty that utilize metadata and spatial characteristics of a DEM are presented. Seven statistics derived from simulation results were used to quantify the effect of DEM error. When uncertainty was quantified by the average relative absolute difference, elevation did not deviate. The range of deviation across the four methods for slope was 5 to 8 percent, 460 to 950 percent for derived catchment areas and 4 to 9 percent for the topographic index. This research demonstrates how application of this methodology can address DEM uncertainty, contributing to more responsible use of elevation and derived topographic parameters, and ultimately results obtained from their use.
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Papers by Suzanne Wechsler