Virginia Tech GIS and Remote Sensing Research Symposium

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2010 VT-GIS Symposium April 9, 2010: Presentations Abstracts
(Virginia Tech. Office for GIS and Remote Sensing Research, 2010-04-09)
Presentation abstracts from the Virginia Tech GIS symposium, held on April 9, 2010.
2010 VT-GIS Symposium April 9, 2010: Poster Presentations
(Virignia Tech. Office for GIS and Remote Sensing Research, 2010-04-09)
Abstracts from the poster presentations at the Virginia Tech GIS Symposium, held on April 9, 2010.
2012 OGIS Symposium Program
McGee, John; Wynne, Randolph H.; Shao, Yang (2012-04-13)
List of all proceedings from the Virginia Tech GIS Symposium, held on April 13, 2012.
2013 OGIS Symposium Program
McGee, John; Wynne, Randolph H.; Shao, Yang (2013-04-19)
List of all proceedings from the Virginia Tech GIS Symposium, held on April 19, 2013.
Analysis of Crop Phenology Using Time-Series MODIS Data and Climate Data
Ren, Jie; Campbell, James B. Jr.; Shao, Yang; Thomas, R. Quinn (2014)
Understanding crop phenology is fundamental to agricultural production, management, planning and decision-making. In the continental United States, key phenological stages are strongly influenced by meteorological and climatological conditions. This study used remote sensing satellite data and climate data to determine key phenological states of corn and soybean and evaluated estimates of these phenological parameters. A time series of Moderate Resolution Imaging Spectrometer (MODIS) Normalized Difference Vegetation Index (NDVI) 16-day composites from 2001 to 2013 was analyzed with the TIMESAT program to automatically retrieve key phenological stages such as the start of season (emergence), peak (heading) and end of season (maturity). These stages were simulated with 6 hourly temperature data from 1980 to 2013 on the basis of crop model under the Community Land Model (CLM) (version 4.5). With these two methods, planting date, heading date, harvesting date, and length of growing season from 2001 to 2013 were determined and compared. There should be a good correlation between estimates derived from satellites and estimates produced with the climate data based on the crop model.
Waldo Canyon Fire
Garza, Mario; Freeman, Sam (2014)
The Waldo Canyon fire was the most destructive wildfire in Colorado history (until the Black Forest Fire in 2013). The fire torched more than 340 houses and claimed at least two lives. It started on June 23, 2012 while the biggest spread of the fire occurred on June 26, 2012 when the meteorological conditions for fire risk peaked. The fire was 100% contained on July 10, 2012. Research Questions: How did this fire happen? What were the Meteorological and Climatological conditions before the fire started and also during the fire? How did it spread? What was the vegetation factor in the cause of this fire? Techniques: Using GIS and Remote Sensing data collected from GLOVIS and NOAA websites with information of the wildfires to analyze the physical geography and the vegetation to calculate the risk and analyze the spread of the fire. In addition, data from satellite imagery will help investigate these wildfires along with other supporting images from LANSAT, Aerial Photographs, and thermal imagery. A big component of any fire is how dry and windy the area was. Data from the National Weather Service and other weather websites will be necessary to gather the resources to study the Meteorological and Climatological conditions leading up to this event.
Automated Landsat Classification of Tropical Forest Disturbances for Large Scale Identification in the Amazon
Derwin, Jill (2014)
Under-reporting of selective logging and forest disturbance has posed an issue for forest health and deforestation estimations in the tropics due to difficulty of detection by satellite data. Several studies have proposed methods for the delineation of these areas using a variety of data and models. In the interest of supporting the study of large-scale ecosystem and climate dynamics in this region for the purposes of prioritization of critical focal points in climate mitigation policy and incentive programs, I hope to test one such methodology over different regions across Amazonia. Landsat-derived Multiple Soil Adjusted Vegetation Index (MSAVI) and alternately Multiple Soil Adjusted Vegetation Index with Aerosol Resistance (MSAVIaf) have been shown to be relatively successful in obtaining green fractional percentage (fc) when incorporated into a linear mixture model. I plan to replicate this technique, followed by a multi-temporal comparison of fc to locate disturbed and degraded areas, and then expand the analysis over an extended study area to review the potential for automation to a state-wide or national scale.
Investigating Forest Conversion Across Several Scales of Urbanization in the Eastern United States
Wu, Yi-Jei; Thomas, Valerie A.; Oliver, Robert D. (2014)
Urbanization in the United States has clearly impacted land cover, and land use and land cover change (LULCC) patterns. A great body of literature has addressed the negative results of increased sprawl and a supporting literature has catalogued the story of forest loss—to grassland/ shrub, to agricultural land, to developed land and other land use categories. The Micropolitan Statistical Area (μSA) is a new geographic entity created in 2003 by the Office of Management and Budget (OMB) to depict the transitional area between Metropolitan Statistics Areas (MSAs) and non-designated areas (i.e., rural regions). Our prior work has demonstrated that μSAs are unique with regards to the dynamics of land conversion for development, and that there is a clear need to investigate the regional drivers of specific types of land-cover change at this scale. This research seeks to (1) tabulate the amount difference of forest conversion among MSAs, μSAs, and non-designated areas in select megaregions; and (2) highlight/ depict the change in key μSAs (computed as a percentage of forest cover change) across east coast. By combining μSA boundaries with the National Land Cover Database (NLCD) change product and change detection results from Google Earth Engine platform to examine forest cover change patterns across four East-Coast megaregions (as defined by America 2050 [Florida, Piedmont Atlantic, Great Lakes and the North East megaregion]). We have an opportunity to illustrate that in rare circumstances there are μSAs that have witnessed an irregularities in forest conversion between 2001 and 2006.
Spatial Data for Agent-Based Wood Supply Chain Modeling
Kauffman, Joby; Prisley, Stephen P.; Yao, Xiaozheng; Crescenti, Neil; Braff, Pamela (2014)
The Center for Natural Resources Assessment and Decision Support (CeNRADS) in the College of Natural Resources and Environment at Virginia Tech has been tasked with developing tools, data, and knowledge for analyzing questions about sustainable supplies of wood fiber in Virginia and beyond. An agent-based design provides an appropriate computational model for simulating the actions and interactions of paper mills, saw mills, and energy companies in the procurement of timber resources. The spatial location of timber resources plays a vital role in the decision making process of these wood consuming agents. Distance from the timber stand to the mill relates directly to transportation cost. Other variables that depend on the location of the timber stand, including slope and distance to a road, affect the operations costs of harvesting the resource. Future growth of the resources is related to spatial environmental and human factors such as soils and land use. Precise data is also needed to account for the spatial heterogeneity of the abundance of the wood resources. When modeling there is always a balance between simplicity and realism which is interrelated with the availability of data. This, in turn, creates the need for decisions on what data to use, how to obtain it, and how to use it in the model. The focus will include data requirements and options for the model, analysis tools needed to prepare the data, rationale that have influenced decisions, and factors for making future decisions as the model continues to develop.
Ecosystem Service Benefits from Public and Private Conservation Lands
Scott, L.; Gillespie, J.; Villamagna, A. (2014)
Research Objective: To quantify and compare ecosystem services (ES) capacity for Publicly Protected Areas (PPAs) and private conservation easements. Method: The study area was state and federal PPAs and private conservation easements in NC and VA. We developed and used existing ES capacity models to quantify ES capacity using GIS. Focal ES were surface water regulation, groundwater protection, water quality regulation, erosion control, recreational fishing, carbon storage, and biodiversity support. National Conservation Easement Database was used to map private conservation easements with environmental systems, recreation and education, open forest, and open farm purposes with a gap status of 1, 2, or unknown. USGS National Inventory of Protected Areas (PAD-US) was used to map State and Federal PPAs with a gap status 1 or 2. All ES capacities were standardized on a scale of 0-1 for comparison. Results: Biodiversity support was significantly greater in federal PPAs, especially throughout VA. Surface water regulation was the only ES where federal and state PPA capacity was significantly greater than private conservation easements. Ecosystem service capacity for private conservation easements was equal or greater to federal and state PPAs for all services except surface water regulation. Private land conservation protects ES and may have positive regional impacts where PPAs are not present. Although smaller, private easements can protect ES in more diffuse areas throughout the region. Existing ES capacity can be used to identify conservation areas with potential to enhance ES protection. Riparian filtration, erosion control, carbon storage, and surface water regulation capacity are the most practical services to incentivize ES protection on private lands.
A Climatology of Precipitation Efficiency for the Central Appalachian Mountains Region
Morrow, James; Luchetti, Nick (2014)
Precipitation efficiency is commonly defined as the ratio of the amount of precipitation at ground level to the amount of precipitable water in the column of the atmosphere above. The value represents the fraction of available water vapor in the atmosphere that is translated into precipitation reaching the surface. Although relatively under-studied, precipitation efficiency is an important element of any hydroclimate, and variability or change in precipitation efficiency spatially or temporally has significant consequences to physical and social systems. Daily data were used to construct a spring season climatology of precipitation efficiency for the central Appalachian Mountains region of the eastern United States for the period 1982 Through 2012. The spatial variability in mean precipitation efficiency across the region is presented and related to the region’s physiography. Time series analyses of precipitation efficiency are presented to highlight both (1) the inter-annual variability for the purpose of identifying any large scale climate system controllers and (2) any trends that may signal a recent change in the regional climate for the purpose of engaging concerns over both future drought and increasingly extreme precipitation events.
Mapping Congress
Vaughan, Matthew; Rouzer, Sarah (2014)
Historians are increasingly coming to believe that space matters. From claims that "geography is destiny" to the long-held belief that "all politics is local," understanding the implications of space--the spatial turn--is becoming central to the study of history. Understanding the changing nature of politics in this country since the eighteenth century has involved detailed temporal analysis of voting patterns, demographics, etc. at various scales. In order to efficiently conduct such research, relevant and readily available historical resources are a necessity. Through the use of GIS resources, we are making the transition from analog data to digital data. This research allows us to analyze large amounts of historical data from a spatial perspective. The purpose of this project is to make available user-friendly U.S. Congressional historical data and create resources that advance the understanding of the interaction between space and politics in American history. Methods involved creating GIS resources, including shapefiles and formatted data sets of elections results, roll call votes, and district and state demographics. This project is part of an ongoing effort to assess the impact of region, local economies, demographics and local politics on national politics and policy making. The transformation of historical, analog sources and scattered digital data (some from the punch card era) into an integrated base involves surmounting numerous intellectual and information management challenges. This poster will help illustrate the power of GIS and the implications of digital data analysis to the study of American political history, while examining conventional wisdom about realigning elections and changes in the American electorate.
Accuracy Assessment of the NLCD 2006 Impervious Surface for Roanoke and Blacksburg
Zhao, Suwen; Feng, Leyang; Shao, Yang; Dymond, Randel L. (2014)
Impervious surface map products are important for the study of urbanization, urban heat island effects, watershed hydrology, water pollution, and ecosystem services in general. At the conterminous US scale, impervious surfaces are mapped for 2001 and 2006. The accuracy of the 2006 NLCD impervious surface, however, has not been thoroughly examined, especially for small and intermediate size cities (e.g., regional city). In this study, we selected two transects in two cities and visually interpreted aerial photo to develop impervious surface reference maps. We then compared percent impervious surface of the NLCD and aerial photo-interpreted reference maps. The comparison was conducted at 90m resolution to minimize the errors in image registration. Overall, we found that the 2006 NLCD impervious surface matched well with our reference data, although slight skewness at two extremes is present. The R² and RMSE statistics improved when the two datasets are compared at coarse aggregation levels (e.g. 180m).
Spatial Methods for Broad-Scale Assessment of Deer Browse Impacts in Virginia
Kniowski, Andrew B.; Ford, W. Mark (2014)
Biodiversity has become a central focus of conservation effort and research over the past several decades. Ungulates are important modifiers in many ecosystems and can significantly alter biodiversity. Throughout the eastern United States, white-tailed deer (Odocoileus virginianus) are the forefront of research and discussion due to chronically high densities in many regions and the resultant impact to ecosystems and human land use activities. Although ecological benchmarks or measures of herbivory impact have become increasingly important metrics to consider in deer population management, current limitations in understanding impede their application across landscapes. For example, few data describe the local and regional spatial variation in impact measures due to inherent geologic and topographic characteristics. Further, little is known regarding the extent anthropogenically altered landscape elements, such as roadways, agriculture, and urban areas influence deer browse impact or how vegetation species respond to herbivory in different landscape contexts. We propose a method to examine deer spatial browse patterns and factors influencing browse intensity and impact measurement across Virginia by implementing a spatially explicit and stratified study design. By examining distinct, spatial aspects of deer herbivory across landscapes, the information gathered may provide critical insight and aid the widespread application of deer impact measurements.
Floodplain Hydraulics: LiDAR Applications
Jones, C. Nathan; Scott, Durelle T. (2014)
As climate becomes increasingly variable, the costs to infrastructure and our society as a whole are going to rise drastically. Since the year 2000, damages due to hurricanes are estimated to be ~$260 Billion in the United States alone. This has led to changes in the national flood insurance program and could place more emphasis on flood modelling in the coming years. Here, we present a case study where remotely sensed data was used to increase the accuracy of a two-dimensional hydrodynamic flood model. The study site is a 14 km reach of the Tangipahoa River in Southern Louisiana. The reach has extensive floodplains with complex microtopography, making flowpath characterization difficult. Utilizing Light Detection and Ranging (LiDAR) data freely available from the state of Louisiana, a surface model was developed and storage zones within the floodplain were delineated. Further, information about the forest structure derived from the LiDAR was used to estimate each storage zone’s resistance to flow in the form of the Manning’s N coefficient. This produced a roughness estimation that more closely resembles the spatial heterogeneity of roughness experienced in the floodplain, thus increasing the predictive capability of the flood model.
Lyme disease and the wilderness-urban interface in North Carolina and Virginia
Zajic, Katherine (2014)
Lyme, a tick-borne disease, has been endemic in Northeastern America for decades. However, with changing development patterns it is becoming a concern in areas where it was not previously endemic. Areas with high herbaceous- forest edges are a perfect environment for the white-footed mouse, a reservoir for the pathogen, and deer which carry ticks. As more suburban neighborhoods are developed around wooded areas, the environment becomes ideal for Lyme transmission. Abandoned development projects resulting from the housing decline also create this environment. In this project, I will use land cover data to identify the wilderness- urban interface and layer it with climate data as well as current Lyme incidence in order to determine areas at risk of increased Lyme incidence in Virginia and North Carolina based on the intersection of factors that are hospitable to Lyme. This information could be used to determine which areas need education programs and where doctors should be watchful of the variety of symptoms that Lyme can present by bringing attention to emerging high-risk areas.
Optimizing Measurement of 4G LTE Broadband Access in Virginia
Adams, Erica (2014)
Wireless coverage is not confined to jurisdictional boundaries and populations are not distributed evenly within jurisdictions. However both population and coverage statistics are often reported at the jurisdictional scale. Using census-based data to measure a population’s wireless broadband coverage can be a challenge, as census population values are aggregated into jurisdictional boundaries instead of associated with the actual location of individuals. Furthermore, Census data accounts for population by household, essentially capturing, at a jurisdictional level, where people sleep, and not necessarily where they are all day. Alternatively, Oak Ridge National Laboratory developed the LandScanTM dataset, a 1km resolution raster surface that attempts to represent ambient population (or the average over 24 hours) through spatial data and imagery analysis, and by disaggregating census counts using multi-variable dasymmetric modeling. This analysis compared the use of U.S. Census population data at the block level and LandScan’s ambient population model to calculate the percent of population with 4G LTE broadband access in Virginia. 2013 4g-LTE coverage data was provider-reported and accessed through the Virginia Geographic Information Network. The results of this study show that only 4% of census blocks covered by 4G LTE differed by more than 5% when measuring population using LandScan and Census data, for the most part, at the census block level these data sets are comparable for use in analysis of broadband coverage, in Virginia.
Multi-temporal Multi-sensor Data Fusion
Ghannam, Sherin; Abbott, A. Lynn (2014)
Landsat data offered a great help in mapping a lot of vegetation parameters at 30 m spatial resolution but unfortunately does not provide daily coverage (it has a 16 day revisit cycle). This is a major obstacle for monitoring short term disturbances and changes in vegetation characteristics through time. MODIS, on the other hand, offers daily coverage but with a coarser resolution; 250m or coarser. The development of data fusion techniques has helped to improve the temporal resolution of fine spatial resolution data by blending observations from sensors with differing spatial and temporal characteristics. This would be helpful for many purposes including crop monitoring and investigating landscape disturbances. This study tries to make benefit of the multi-resolution analysis offered by data transforms to adopt a fusion technique for estimating missing Landsat data with the help of MODIS data. Results should be compared to the known STARFM algorithm.
Spatial Analysis of Region Where FBI Headquarters May be Relocated
Kebede, Mussie (2014)
The Federal Bureau of Investigation (FBI) recently shortened their list for relocation of their operational headquarters in Washington DC to two venues. The location currently in favor is an area in Springfield, Virginia. Located between two GSA (General Services Administration) requirements, which are that this new FBI location be within 2 miles of a metro station and within 2.5 miles of the Capital Beltway (I-495). The Springfield location meets both of these requirements plus more. The relocation of the J. Edgar Hoover building to Springfield would mean a sure increase in revenue for businesses in the area, along with the obvious bump in population. Where exactly this Building would be placed is the big question, with most of the land already developed on, the FBI may have to purchase a plot of land adequate in size (50 acres) to house the building. For my project, I will produce a map showing average traffic congestion from 2012 (Annual Average Daily Traffic shapefile) in the area of interest (Springfield, VA), including where the proposed FBI facility could be located, and where traffic improvements can be made to alleviate pressure. I will use census data to highlight residential areas along with locations where new residential neighborhoods may be constructed.
Application of GIS and RS in Abandoned Land Surveying: A Case Study in Shandong, China
Li, Jing; Liu, Zishang; Li, Wenyu (2014)
For the acute contradiction between land and people, cherishing and reasonable using per inch land is a persistent national policy in China, whereas land damage is unavoidable in mining, construction and other activity. There is still a lot of abandoned land unused and with no obligator in China, which will have to be the government’s responsibility to survey, plan how to use them and to complete recovering them. For the abandoned land damage always occurred minimally 25 years ago, it is hard to find their information which is truly needed to make clear how much, when and where to reclaim them. Focus on that problem, we proposed a method to find and capture the abandoned land information, which is based on social surveying methods, but featured with GIS and RS. The method was used in Shandong Province. Result showed there are totally 15,751 units and 76,088 ha abandoned land, distributed in 15 cities. Among that, subsided land, digging land and occupied land are 23,981ha, 4154ha and 4,471ha respectively. The conclusion is that based on social survey data, GIS overlapping analysis function and RS method are effective to identified the location, specific damaged time, land use status and so on. As the project is just on the beginning stage, there are still further study on the monitoring and evaluation of self-rehabilitation status of abandoned land.

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