John R. Andrews

A method for acquiring and processing ground-based lidar data in difficult-to-access outcrops for use in three-dimensional, virtual-reality models

Lidar (light detection and ranging) data provide a centimeter-scale–resolution digital outcrop model. This technology supplements and improves conventional outcrop investigations by providing ways for geoscientists to digitally visit and analyze outcrops on their computers or workstations. Our current processing workflow includes creation of an optimized, triangulated surface, onto which high-resolution photographs are rectified and draped. For optimal resolution, lidar data should be acquired along a direction perpendicular to the outcrop face. Field constraints, such as sea cliffs or exposures without a good vantage point, sometimes necessitate scanning the outcrop in an oblique direction. And yet acquiring lidar data from an oblique direction creates large shadows (zones of no data) and anomalously elongated, triangulated areas. Using a three-dimensional transformation matrix that modifies the direction of triangulation, we can correct for elongated triangles. In addition, combining multiple scans shot from different angles minimizes data shadow. This procedure lets us obtain an optimized triangulated surface as if it were shot from an inaccessible angle, without altering the position or density of the original digital data. This angle-correction method is essential to accurate photo draping and virtual-reality model creation.

Mapping coastal environments with lidar and EM on Mustang Island, Texas, U.S.

We explore whether lidar (light detection and ranging) and EM (electromagnetic induction) can improve the accuracy and resolution of wetland mapping that has historically been based chiefly on analysis of aerial photographs. Using Mustang Island on the central Texas coast as an example, we exploit (1) the known strong relationship between elevation and coastal habitat by comparing a lidar-derived digital elevation model (DEM) with existing wetland maps and detailed vegetation transects, and (2) another known strong relationship between soil and water salinity and coastal habitat by collecting and comparing EM-derived conductivity data with elevation and vegetation type across the island.

Time Series Analysis of Energy Production and Associated Landscape Fragmentation in the Eagle Ford Shale Play

Spatio-temporal trends in infrastructure footprints, energy production, and landscape alteration were assessed for the Eagle Ford Shale of Texas. The period of analysis was over four 2-year periods (2006–2014). Analyses used high-resolution imagery, as well as pipeline data to map EF infrastructure. Landscape conditions from 2006 were used as baseline. Results indicate that infrastructure footprints varied from 94.5 km2 in 2008 to 225.0 km2 in 2014. By 2014, decreased land-use intensities (ratio of land alteration to energy production) were noted play-wide. Core-area alteration by period was highest (3331.6 km2) in 2008 at the onset of play development, and increased from 582.3 to 3913.9 km2 by 2014, though substantial revegetation of localized core areas was observed throughout the study (i.e., alteration improved in some areas and worsened in others). Land-use intensity in the eastern portion of the play was consistently lower than that in the western portion, while core alteration remained relatively constant east to west. Land alteration from pipeline construction was ~65 km2 for all time periods, except in 2010 when alteration was recorded at 47 km2. Percent of total alteration from well-pad construction increased from 27.3% in 2008 to 71.5% in 2014. The average number of wells per pad across all 27 counties increased from 1.15 to 1.7. This study presents a framework for mapping landscape alteration from oil and gas infrastructure development. However, the framework could be applied to other energy development programs, such as wind or solar fields, or any other regional infrastructure development program.Graphical abstractLandscape alteration caused by hydrocarbon pipeline installation in Val Verde County, Texas

COMBINING EM AND LIDAR TO MAP COASTAL WETLANDS: AN EXAMPLE FROM MUSTANG ISLAND, TEXAS

We combined airborne lidar and ground-based EM induction measurements with vegetation surveys along two transects across Mustang Island, a barrier island on the Texas coast, to examine whether these methods can be used to map coastal wetlands and associated geomorphic environments. Conductivity varied inversely with elevation along both transects. Elevation and conductivity profiles correlated reasonably well with habitat mapped in the largely imagery-based 1992 National Wetland Inventory (NWI), but they possessed greater detail and identified misclassified habitat. Detail achievable with elevation and conductivity data was similar to that achieved in on-the-ground vegetation surveys. Lowest elevations and highest conductivities were measured in saline environments (marine and estuarine units, forebeach, salt marsh, and wind-tidal flats). Highest elevations and lowest conductivities were measured in nonsaline environments (upland and palustrine units, dunes, vegetated-barrier flats, and fresh marsh). Elevation and conductivity data allow better discrimination among coastal wetland and geomorphic environments than can be achieved from image interpretation alone. Future work should include evaluating the effect of vegetation density on lidar-beam penetration, quantifying seasonal change in ground conductivity in fresh and saline coastal environments, examining the geographic variability of elevation and conductivity statistics, and evaluating the use of airborne EM sensors to measure ground conductivity at multiple exploration depths.

Shoreline and Sand Storage Dynamics from Annual Airborne LIDAR Surveys, Texas Gulf Coast

ABSTRACT Paine, J.G.; Caudle, T.L., and Andrews, J.R., 2017. Shoreline and sand storage dynamics from annual airborne LIDAR surveys, Texas Gulf Coast. Annual airborne LIDAR surveys were conducted along the Texas Gulf of Mexico shoreline between 2010 and 2012 to map shoreline position, determine shoreline movement and its historical context, and quantify beach and dune morphology by determining elevation threshold area (ETA) relationships for Holocene barrier islands, strandplains, and fluvial and deltaic headlands and marshes. Historical (1800s to 2007) movement is erosional for all major Texas shoreline segments, averaging 1.3 m/y of retreat. Shorelines retreated between 2007 and 2010 at a higher average rate of 2.8 m/y because of erosion and partial recovery from Hurricanes Ike (2008), Humberto (2007), and Dolly (2008). Despite the erosional context, airborne LIDAR surveys show that the shoreline advanced at 75% of 11,783 monitoring sites between 2010 and 2011 and moved an average of 6.5 m seaward during storm recovery. The recovery reversed between 2011 and 2012, when the shoreline retreated at 67% of 11,811 sites and moved an average of 3.1 m landward. Movement was similar to historical trends: NE and southern coast shorelines retreated, whereas central coast shorelines were relatively stable. Retreat between 2011 and 2012 did not fully offset advance between 2010 and 2011; the shoreline advanced at 59% of 11,811 sites and moved an average of 3.4 m seaward between 2010 and 2012, resulting in a net area gain of 203 ha. LIDAR-derived beach and dune areas exceeding threshold elevations of 2–9 m above mean sea level (at 1-m increments), divided by shoreline length over which the ETAs were determined, were used to produce average profiles. These data can be used to determine sediment storage volumes and temporal change, flood susceptibility, and erosion resilience. Storage patterns evident in ETA data mimic historical shoreline movement. Low elevation and sand storage occur where retreat is highest, whereas higher elevation and storage occur where retreat is lowest.

Comparison of Recent Oil and Gas, Wind Energy, and Other Anthropogenic Landscape Alteration Factors in Texas Through 2014

Recent research assessed how hydrocarbon and wind energy expansion has altered the North American landscape. Less understood, however, is how this energy development compares to other anthropogenic land use changes. Texas leads U.S. hydrocarbon production and wind power generation and has a rapidly expanding population. Thus, for ~47% of Texas (~324,000 km2), we mapped the 2014 footprint of energy activities (~665,000 oil and gas wells, ~5700 wind turbines, ~237,000 km oil and gas pipelines, and ~2000 km electrical transmission lines). We compared the footprint of energy development to non-energy-related activities (agriculture, roads, urbanization) and found direct landscape alteration from all factors affects ~23% of the study area (~76,000 km2), led by agriculture (~16%; ~52,882 km2). Oil and gas activities altered <1% of the study area (2081 km2), with 838 km2 from pipelines and 1242 km2 from well pad construction—and that the median Eagle Ford well pad is 7.7 times larger than that in the Permian Basin (16,200 vs. 2100 m2). Wind energy occupied <0.01% (~24 km2), with ~14 km2 from turbine pads and ~10 km2 from power transmission lines. We found that edge effects of widely-distributed energy infrastructure caused more indirect landscape alteration than larger, more concentrated urbanization and agriculture. This study presents a novel technique to quantify and compare anthropogenic activities causing both direct and indirect landscape alteration. We illustrate this landscape-mapping framework in Texas for the Spot-tailed Earless Lizard (Holbrookia lacerata); however, the approach can be applied to a range of species in developing regions globally.

An Improved Approach for Forecasting Ecological Impacts from Future Drilling in Unconventional Shale Oil and Gas Plays

Directional well drilling and hydraulic fracturing has enabled energy production from previously inaccessible resources, but caused vegetation conversion and landscape fragmentation, often in relatively undisturbed habitats. We improve forecasts of future ecological impacts from unconventional oil and gas play developments using a new, more spatially-explicit approach. We applied an energy production outlook model, which used geologic and economic data from thousands of wells and three oil price scenarios, to map future drilling patterns and evaluate the spatial distribution of vegetation conversion and habitat impacts. We forecast where future well pad construction may be most intense, illustrating with an example from the Eagle Ford Shale Play of Texas. We also illustrate the ecological utility of this approach using the Spot-tailed Earless Lizard (Holbrookia lacerata) as the focal species, which historically occupied much of the Eagle Ford and awaits a federal decision for possible Endangered Species Act protection. We found that ~17,000–45,500 wells would be drilled 2017‒2045 resulting in vegetation conversion of ~26,485–70,623 ha (0.73–1.96% of pre-development vegetation), depending on price scenario (

PRECISE AIRBORNE LIDAR SURVEYING FOR COASTAL RESEARCH AND GEOHAZARDS APPLICATIONS

40–

Airborne lidar on the Alaskan North Slope: Wetlands mapping, lake volumes, and permafrost features

80/barrel). Grasslands and row crop habitats were most affected (2.30 and 2.82% areal vegetation reduction). Our approach improves forecasts of where and to what extent future energy development in unconventional plays may change land-use and ecosystem services, enabling natural resource managers to anticipate and direct on-the-ground conservation actions to places where they will most effectively mitigate ecological impacts of well pads and associated infrastructure.