Scott A. Tweddale

Correlation of rangeland cover measures to satellite‐imagery‐derived vegetation indices

Abstract Using field data from the U.S. Armys land inventory and monitoring program, a study was conducted to examine the utility in estimating the quantity of vegetation cover with satellite imagery across a large and complex rangeland. The study area used for this investigation was the U.S. Armys Yakima Training Center in central Washington. The Land Condition‐Trend Analysis (LCTA) program at Yakima Training Center has 202 permanent plots located in a randomly stratified manner across the installation. The principle measures taken along the transects were canopy cover and ground cover. Landsat Thematic Mapper imagery collected in May and August of 1992 was used in the analyses. The satellite data coincided with the beginning and end of the field data collection period and were used to derive various vegetation indices including Ratio, TVI, SAVI, and MSAVI. Analysis of correlation of rangeland cover measures and satellite imagery derived vegetation indices were performed. Correlation between the vegeta...

A dynamic simulation/optimization model for scheduling restoration of degraded military training lands

Intensive use of military vehicles on Department of Defense training installations causes deterioration in ground surface quality. Degraded lands restrict the scheduled training activities and jeopardize personnel and equipment safety. We present a simulation-optimization approach and develop a discrete dynamic optimization model to determine an optimum land restoration for a given training schedule and availability of financial resources to minimize the adverse effects of training on military lands. The model considers weather forecasts, scheduled maneuver exercises, and unique qualities and importance of the maneuver areas. An application of this approach to Fort Riley, Kansas, shows that: i) starting with natural conditions, the total amount of training damages would increase almost linearly and exceed a quarter of the training area and 228 gullies would be formed (mostly in the intensive training areas) if no restoration is carried out over 10 years; ii) assuming an initial state that resembles the present conditions, sustaining the landscape requires an annual restoration budget of

Obstruction detection comparison of small-footprint full-waveform and discrete return lidar

957 thousand; iii) targeting a uniform distribution of maneuver damages would increase the total damages and adversely affect the overall landscape quality, therefore a selective restoration strategy may be preferred; and iv) a proactive restoration strategy would be optimal where land degradations are repaired before they turn into more severe damages that are more expensive to repair and may pose a higher training risk. The last finding can be used as a rule-of-thumb for land restoration efforts in other installations with similar characteristics.

Quantifying Impacts of Urban Growth Potential on Army Training Capabilities

Laser Radar, also referred to as lidar, has become widely available and is an established contributor to the military and intelligence community by providing precise elevation data using 3-dimensional measurements. The utilization of customized algorithms designed for lidar data exploitation provides the capability to determine corridors or gaps in areas of vegetation cover. These capabilities lend themselves as geospatial tools for mobility applications and tactical planning. This effort uses elevations derived from small-footprint (airborne) lidar surveys to create accurate surface models and corresponding canopy characterization maps. The canopy height models are based on elevation voxels above ground level and are used as input into a tree finding algorithm. Corridors under the canopy are then predicted using the obstruction identification technique and neighboring point characteristics. Path determination can also be performed using the obstruction maps and a modified A-star algorithm. A lidar survey over Camp Shelby, MS was chosen as the test case for the obstruction detection utilities as it provides fairly dense vegetation cover and interesting topographic features. The survey was completed using both a full-waveform lidar and a discrete return system which offers a coincident comparison of the obstruction methodology for differing data types. It is determined that the fullwaveform data provides a more complete and accurate assessment of the surface, the canopy and potential obstruction detection than the discrete return system.

Fundamental relationships inherent to lidar waveforms for classification

Building on previous studies of urban growth and population effects on U.S. military installations and training activities (e.g., Wilhoit et al. 2016), this report describes methodology and applies a methodology for quantifying urban development and encroachment impacts. The authors propose a distance-weighted assessment of population growth around the training areas to include both current population and projected urban growth. The results of this study demonstrate improvement over the previous methodology. DISCLAIMER: The contents of this report are not to be used for advertising, publication, or promotional purposes. Citation of trade names does not constitute an official endorsement or approval of the use of such commercial products. All product names and trademarks cited are the property of their respective owners. The findings of this report are not to be construed as an official Department of the Army position unless so designated by other authorized documents. DESTROY THIS REPORT WHEN NO LONGER NEEDED. DO NOT RETURN IT TO THE ORIGINATOR. ERDC/CERL TR-17-34 iii

A Procedure to Extrapolate Vegetation Cover Estimates Over Large Arid and Semi‐arid Regions Using Multiple Spatial Resolution Imagery

Full-waveform laser altimetry has been used in the research community since the mid-1990s and this technology holds great potential for the science and defense communities. Laser waveforms are a digital recording of the entire temporal profile from the reflected laser energy. The shape of the returned laser waveform is a function of both laser and surface properties. Waveform metrics were extracted for each waveform and include peak amplitude, peak standard deviation, integrated canopy energy, integrated ground energy, total waveform energy, ratio between canopy and ground energy, rise time to the first peak, fall time of the last peak, and vegetation height. The utilization of such metrics provides a potential for discriminating and identifying discrete targets on a per-shot basis. Analysis of the entire reflected laser energy profile provides a detailed description of distributed targets/features along the laser line-of-sight. Waveform data collected over Camp Shelby, Mississippi reveal separation of conifer from broadleaf vegetation. Metrics such as integrated canopy energy and fall time were found to be higher in hardwood forest than pine forest. Other landscape features such as the presence of a burn are also detected with full-waveform data, which would otherwise be missed with discrete return elevation data. With new full-waveform systems entering the commercial sector, new possibilities emerge to utilize the lidar data to classify land cover as well as quantify surface parameters.

Correlation of Land Condition Trend Analysis (LCTA) Rangeland Cover Measures to Satellite-Imagery-Derived Vegetation Indices.

Abstract Typically, land degradation on arid and semi‐arid military training and testing lands in the desert Southwestern United States is associated with a decrease in total vegetative cover. Long‐term field surveys have been established by the military to measure and monitor total vegetative cover over time. However, field methods are not cost effective due to the large area of training lands, nearly 3 million acres in the California deserts alone, that must be sampled. Measurements recorded at individual transects must still be spatially extrapolated to produce a complete census of the installation. Remote sensing has been used to spatially extrapolate such field measurements over larger areas, but in the past, imagery has lacked sufficient spatial resolution to accurately estimate total vegetative cover. In this study, nested, high resolution imagery was collected at different spatial resolutions for study sites at the Marine Corps Air Ground Combat Center in the south‐central Mojave Desert of southern California. Vegetation cover estimates derived from these multiple resolution images were examined as a possible surrogate for sampling total vegetative cover in the field. Results indicate that a high correlation exits between field measurements of cover and estimates of cover derived from imagery. However, similar to field measurements, if the intent is to estimate total vegetative cover across large geographic areas, high resolution imagery is also costly in terms of collection, processing, and interpretation because a single image generally covers a small geographic area. Therefore, a protocol to scale detailed observations of total cover from high resolution imagery to lower resolution imagery that covers a larger geographic area was developed and tested. The results of this study indicate that a relatively high correlation exists between vegetation cover estimates derived from high resolution imagery and image brightness derived from a nested, lower resolution image. This protocol now allows military land managers to sample site‐specific areas with high resolution imagery and extrapolate absolute estimates of vegetation cover across training and testing lands with more cost effective, lower resolution imagery that provides complete coverage of an installation.