Vehicle movement patterns and vegetative impacts during military training exercises

The operation of off-road vehicles during military training exercises can affect the environmental conditions of training lands by removing or disturbing vegetation. The use of global positioning systems (GPS)-based vehicle tracking systems can help to characterize the movement of vehicles during training exercises for the purpose of quantifying vegetative impacts. The combination of GPS positions of vehicles in the field during a training exercise, and geographic information system (GIS) maps of the training installation can provide information about vehicle-specific vegetation impacts of a training exercise, as related to vehicle locations, turning radius and velocity. Such relationships can be used to estimate off-road vegetation impacts. Twenty GPS-based vehicle tracking systems were installed on vehicles of the US Army 3rd Brigade 1/14 Cavalry to evaluate vegetation impacts during a 10 day reconnaissance training exercise at Yakima Training Center in Yakima, WA. The vehicle tracking systems were programmed to record the position of the vehicles every second. The resulting vehicle tracking data were analyzed for quantity of travel per day of the training activity, quantity of travel on and off roads, off-road vehicle dynamic properties turning radius and velocity, and off-road vegetation removed. The vehicles were in motion an average of 8.4% (approximately 2 h per day) of the training exercise time. The average distance traveled per day on roads was 33.5 km, and the average distance traveled per day off-roads was 7.7 km. On average, the vehicles spent 16% of their off-road traveling time at turning radii less than 20 m. Vegetation impacts were compared for different missions. The zone reconnaissance mission produced the highest vegetation impact per distance traveled.     

Soil compaction and over-winter changes to tracked-vehicle ruts, Yakima Training Center, Washington

We monitored two experimental areas at the Yakima Training Center (YTC) in central Washington to measure changes to M1A2 Abrams (M1) tank-rut surface geometry and in- and out-of-rut saturated hydraulic conductivity (K_fs), soil penetration resistance (SPR) and soil bulk density (BD). Profile-meter data show that rut cross-sectional profiles smoothed significantly and that turning ruts did so more than straight ruts. Rut edges were zones of erosion and sidewall bases were zones of deposition. K_fs values were similar in and out of ruts formed on soil with 0–5% moisture by volume, but were lower in ruts formed on soil with about 15% water. Mean SPR was similar in and out of ruts from 0- to 5-cm depth, increased to 2 MPa outside ruts and 4 MPa inside ruts at 10- to 15-cm depth, and decreased by 10–38% outside ruts and by 39–48% inside ruts at the 30-cm depth. Soil BD was similar in and out of ruts from 0- to 2.5-cm depth, and below 2.5 cm, it was generally higher in ruts formed on moist soil with highest values between 10- and 20-cm depth. Conversely, BD in ruts formed on dry soil was similar to out-of-rut BD at all depths. This information is important for determining impacts of tank ruts on water infiltration and soil erosion and for modifying the Revised Universal Soil Loss Equation (RUSLE) and the Water Erosion Prediction Project (WEPP) models to more accurately predict soil losses on army training lands.     

Identification of superfluous roads in terms of sustainable military land carrying capacity and environment

A great challenge the US military land managers are often faced with is how to optimize road networks in order to maintain roads (including all roads, trails, and paths) for the purpose of military training and reducing negative impacts on environment. In this study, a methodology was developed to identify superfluous roads for being closed in terms of both sustainable military land carrying capacity and environment for Fort Riley. In this method, Geographic Information Systems (GIS), remote sensing, and landscape analysis technologies were combined to derive various spatial data layers of factors that had significant impacts on both military training and environment. The factors included maintenance cost of roads, road access area, military training intensity, soil erosion, water quality, landscape fragmentation, and noise production. The factors were quantified and normalized. A spatial multicriteria decision was then developed to obtain the weights of the factors, combine the data layers, and derive a priority map of all the roads for being closed. This map summarized the negative and positive impacts of the factors on environment and military land carrying capacity and can provide the US military land managers with useful guidelines and tools for determining superfluous roads in terms of both sustainable military training and environment. It is expected this effort can provide a method to quickly ascertain which roads are most cost-effective for being closed without hindering the mission and at the same time with benefits for environmental protection and thus provide the land managers with a comprehensive analysis and assessment of alternatives at their disposal.     

Use of military training doctrine to predict patterns of maneuver disturbance on the landscape. I. Theory and methodology

Modern-day military maneuvers, involving tactical formations of wheeled and tracked vehicles, can have significant physical and environmental impacts on the landscape. Numerous scientific studies of these impacts have been conducted, most notably the post-impact assessments of General Patton’s tank maneuvers of the early 1940s in the Mojave Desert of California and Arizona. On a smaller scale, numerous studies of military vehicle impacts have been conducted on military training lands throughout the United States, Canada and Europe. These studies have used a variety of measurement techniques, to include ground level photography and in situ measurements, aerial photography, satellite imagery and vehicle-mounted global positioning systems (GPS) data to define the footprint, patterns and magnitude of disturbances on the landscape. These disturbances are highly variable and can occur over tens of thousands of acres. Because scientists and land managers are generally not familiar with military decision-making, tactical doctrine, and vehicle–weapons systems capabilities, it is difficult for them to predict patterns of disturbance a priori. Even during post-event impact analysis, a full understanding of why and how maneuver disturbance patterns occur may not be readily apparent to them. This limitation can preclude knowledgeable planning, design and repair of damaged lands. In this case study, military tacticians and physical scientists developed an integrated methodology to predict these disturbance patterns more explicitly. The goal of the study was to provide land managers with a tool for understanding how these patterns evolve, and in turn, allow them to better plan and design mitigation efforts to sustain the landscape. The methodology combines a military terrain analysis technique, the modified combined obstacle overlay (MCOO), with an applied military tactics filter to predict where vehicle impacts would be most likely. A terrain and tactical analysis of the landscape at the Combat Maneuver Training Center-Live Fire (CMTC-LF) Area at the US Army Grafenwöhr Training Area, Germany, was conducted using maps, digital ortho-photography, spatial data and on-site reconnaissance to determine the tactical footprint and potential disturbance patterns caused by a new training mission. Part I of this study describes the background, theory and approach used to develop the methodology. Part II describes the field-based validation of the methodology, using post-maneuver ground observations and sampling to test the methodology’s predictions.     

Assessing and predicting changes in vegetation cover associated with military land use activities using field monitoring data at Fort Hood, Texas

We assessed short-term impacts of changes in military training load on vegetative cover at Fort Hood, TX. From 1989 to 1995, permanent field transects were monitored for vegetative cover and land use disturbance using standard army monitoring methods [Land Condition Trend Analysis (LCTA)]. Land use intensity (training load) was quantified and used to develop a model to predict future vegetation cover values. We found that standard Army monitoring methods detected changes in installation resources associated with changes in training load. Increased training loads were associated with increased measures of disturbance, decreased ground cover, and decreased aerial vegetative cover. We found that the spatial pattern of disturbance and vegetation cover remained relatively constant over the study period despite large variations in overall training load. Our model used the consistency in spatial cover patterns over time and the strong relationship between training load and vegetation cover to predict the impact of future training loads on vegetation.     

Maneuver analysis methodology to predict vehicle impacts on training lands

Tactical mobility analysis techniques were merged with land management strategies to assess potential impacts of vehicle operations on training areas for rangeland planning and management. A vehicle mobility analysis was performed for a suite of vehicle types using the NATO Reference Mobility Model (NRMM II). Input parameters include terrain information (soil type, slope, vegetation, surface roughness, soil strength), terrain surface condition based on climate (terrain strength, freeze–thaw, moisture content, snow cover), and vehicle specifications (tire, power train, weight on each axle, ground clearance, dimensions, ride). The vehicle performance was spatially mapped over the terrain for different seasons of the year and used to calculate the maneuverable acreage, which was compared to acreage needed for training requirements. This can be related to land capability based on expected training impact (Maneuver Impact Miles, MIM) and Land Condition Curves which link training density to land condition. This methodology can be used to determine the suitability of training lands and the degree of land management or rehabilitation expected. The methodology was applied to the transformation of the Alaska training lands to support a new brigade unit called the Stryker Brigade Combat Team (SBCT3), but is equally useful for other training areas and military units. For summer use, Alaska training lands are capable of supporting four times the projected training requirements. For winter, when the ground is frozen, more than 10 times the area needed was available.     

Assessment technique for evaluating military vehicular impacts to vegetation in the Mojave desert

A new plant-damage assessment technique was developed. The technique consists of linear transects the width of a military vehicle’s tracks located in existing tracks in the soil (usually during a prior training rotation period of 30 days or since the last rain or wind storm). Measurements of vegetation within the tracks are used to determine the area of plant parts impacted. The percent of the plant parts damaged and the percent expected to recover are estimated. The technique documents prior-damage classes based on estimates of damage that plants have apparently experienced previously (as assessed from field indicators of damage such as plant shape and height). The technique was used to evaluate different vehicle types (rubber-tire wheels vs. metal tracks) in six areas at the NTC with different soils and training intensity levels. The technique provides tabular data that can be sorted and queried to show a variety of trends related to military vehicular impacts. It also is suitable for assessing other non-military off-road traffic impacts. The study reports: (1) differences in plant sensitivity to different vehicle track types, (2) plant cover and density by species and training area after prolonged impact, (3) the degree to which rubber tire wheels have less impact than metal tracks, and (4) mean percent survival was inversely proportional to the degree of prior damage received by the vegetation (i.e., plants previously impacted have lower survival than plants not previously impacted).     

Quantifying vegetation biomass impacts on vehicle mobility

Soil impacts on vehicle mobility are well known; however, most data are for bare soil or the type and amount of vegetation is not documented. This study summarizes results from experiments to quantify the effect of above ground and below ground vegetation biomass on vehicle performance. Soil–vegetation combinations of three soils and three grasses were used. The vegetation was tested at various growth stages and was also subjected to stressors such as trafficking, burning, and cutting. Vegetation measurements included above ground (leaves and shoots) and below ground (root) biomass weights, lengths, diameters and surface area parameters. The soils were characterized for size distribution, moisture, density and terrain strength for each test condition. Vehicle traction and motion resistance were measured for each soil–grass combination using the CRREL Instrumented Vehicle. Results showed an increase in net traction biomass in sandy soils. For clay soils above ground biomass generally increased resistance while increased root diameter clearly decreased resistance. This study represents the first measurements quantifying the impacts of specific biomass parameters on vehicle mobility. The results will serve to guide new experimental methods, improve datasets, and develop physics-based models for years to come.     

Multipass coefficients for terrain impacts based on military vehicle type,size and dynamic operating properties

Quantification of multipass vehicle impacts is needed to determine terrain disturbance during military training. This study, conducted at Fort Riley, Kansas on a clay loam soil, evaluated the multipass terrain impacts of four military vehicles: the M1A1 Main Battle Tank, M998 HMMWV, M985 HEMTT, and M113 APC. Disturbed width and impact severity were assessed along 14 spirals subjected to a maximum of eight passes for a total of 696 impact points. Project goals included evaluating vegetation impacts by tracked and wheeled military vehicles across multiple passes in order to develop coefficients allowing more accurate predictive modeling of vehicle multipass impacts. Multiple passes produce increased vegetative impacts, with multipass coefficients (MPC) ranging from 0.98 to 4.44 depending on vehicle type, size and turn severity. Tracked vehicles were found to have a higher multipass coefficient than wheeled vehicles, with multipass coefficients increasing with vehicle weight and the sharpness of turns. The components of a more theoretical and universal multipass vehicle impact model are discussed. Understanding multipass dynamics will allow land managers to determine the extent and severity of terrain impacts on military training areas and quickly evaluate vehicle environmental impacts when used in conjunction with a GPS-based vehicle tracking system (VTS).     

Use of military training doctrine to predict patterns of maneuver disturbance on the landscape. II. Validation

Landscape disturbance from military training maneuvers can cause significant on-site deterioration that may impair ecosystem functioning, reduce training realism, and jeopardize the safety of soldiers and equipment. Excessive runoff and eroded sediments from within the boundaries of training areas may also affect downstream landowners. Repair of on-site and off-site damage can be very costly. Several attempts have been made to predict the spatial distribution of training-induced surface disturbance within landscapes. Techniques have used the current or historic distribution of surface disturbance to predict the future spatial distribution of disturbance. This study evaluated a new methodology to predict the spatial distribution of disturbance based on a variety of maneuver obstacles considered by military planners in the preparation of battle plans as well as applied doctrinal tactics used during cross-country maneuvers. The field validation study was conducted at Grafenwoehr Training Area, the largest US Army training area in Germany. There was a generally favorable agreement between the spatial distribution of predicted and observed high versus low maneuver disturbance, but the relationship was statistically significant only for those areas predicted to have low levels of disturbance. While the results are promising and suggest that further research may enhance the methodology, the allocation of funding for land rehabilitation on military training lands based on a priori prediction of the spatial distribution of surface disturbance is not yet practical.     

Detection of gullies in Fort Riley military installation using LiDAR derived high resolution DEM

Intensive use of military vehicles in military installations create conditions favorable for gully formation. Gullies impede the access of vehicle, restrict the continuation of training, and lead to significant damage to vehicle and risk the life of soldiers. Therefore, it is critical to correctly identify the locations of gullies for continuous training mission. In this study, Fort Riley (FR) military installation was chosen as the study area. LiDAR derived 1 m resolution digital elevation model (DEM) acquired on 2010 was used to map the gullies. A procedure that measures local topographic position, i.e., difference from mean elevation (DFME) along with its integration to the land surface having high surface curvature values was employed. Two high spatial resolution WorldView-2 images of 2010 and field gully data collected in 2010 were utilized for accuracy assessment. Results showed that: (1) A total of 237 small and 166 large gullies were detected and most of them dominated the central west and northwest parts of the installation; (2) Based on the visual interpretation in the WorldView-2 images, there was no statistically significant difference between the detected and observed numbers of gullies; (3) Gullies measured in the field were well detected with an overall accuracy of 78%.     

Analysis of vehicle use patterns during field training exercises to identify potential roads

In October of 2001, global positioning system (GPS) – based vehicle tracking systems (VTS) were placed on 20 vehicles involved in an 8-day field training exercise at Yakima Training Center, Washington. Based on the GPS data, an analysis of the potential for identifying new roads was conducted. Analysis of vehicle use patterns within selected 25-m grids was utilized to identify new formed or previously unidentified roads in the training area. The factors used to determine the existence of these new roads were (1) if a vehicle actually passed through the grid, (2) the number of vehicles following the same trail segment, (3) if the vehicles passed on different days, (4) if the vehicles were in different troops, and (5) if the vehicles traveled in both directions. A site visit was conducted and confirmed the existence of new roads along segments that met all five criteria levels. Military road class 4 and 5 roads were identified at sites meeting all five criteria.     

Analysis of vehicle platoon movement and speed-spacing relationships during military exercises

In this study a method that identifies off-road vehicle column movement was developed and evaluated. Previous studies have revealed that multiple vehicle passes produce detrimental soil and terrain impacts. Identifying the frequency and location of this type of multi-pass impact during military maneuvers is difficult. This method will aid in the assessment of environmental impacts of off-road military vehicles by allowing land managers to characterize vehicle movement patterns, especially column movement, at military training installations during maneuvers. GPS units mounted on military vehicles collected on and off-road tracking data during a reconnaissance maneuver at Fort Lewis Military Installation, Washington. A set of data utilizing a Stryker platoon of four vehicles was used to evaluate this method. The GPS coordinates, speed, and direction of travel of each vehicle was collected at each second. A criteria to identify platoon column movement was developed based on vehicle proximity, speed and direction of travel. The results of this study show that the method can correctly identify off-road column movement for the purpose of evaluating the multi-pass impacts on the terrain. In addition, using this approach the vehicle movement patterns associated with on- and off-road platoon movement (i.e. vehicle speeds and spacing) were evaluated.     

功能集成式无定形陆空粒子飞行器

为了提高无人机的灵活性与其在特殊环境中的适应能力,受细胞生物学中细胞集体聚集和迁移的启发,提出了功能集成式无定形陆空粒子飞行器,采用模块化和陆空两用设计理念,设计有飞行控制型与功能型两种粒子,各粒子之间通过电磁铁控制松散耦合.飞行控制型粒子保障飞行器在空中的稳定飞行;功能型粒子包含多种不同功能的无定形粒子,满足如摄影、...     

Validation of the GeoWATCH soil moisture model and proposed bias correction method

The US Army is required to be a good steward of the land per US Army regulation AR 200-1. Based on this regulation, Army installations need to manage lands, to reduce potential damage and impacts to water quality and habitat that may occur from training. Maneuver training does impact the vegetation and soil and this damage is directly related to soil moisture. Soil moisture is an important factor for understanding the potential for soil surface disturbance due to vehicle impacts and predicting soil resilience to vehicle traffic, however, producing accurate estimates of the spatial and temporal variation of soil moisture has historically been elusive. GeoWATCH, which stands for Geospatial Weather-Affected Terrain Conditions and Hazards (formerly DASSP), simulates soil moisture world-wide, at relatively small spatial and temporal scales. GeoWATCH uses a physics-based downscaling approach that uses weather-scale land surface model estimates of soil moisture and land surface water and energy fluxes, with high resolution geospatial data. GeoWATCH soil moisture outputs coupled with vehicle impact models, are anticipated to be useful for near-real-time estimation of ground disturbance, but will require ground validation. To validate GeoWATCH soil moisture estimates, we utilized Soil Climate Analysis Network (SCAN) gauge network soil moisture data from 127 sites across 34 states. Statistical analysis of the raw GeoWATCH output indicated the model performs statistically better in certain soil textures. Model bias is largest for sandy soils, whereas clayey soils were least biased. As a result, bias correction models were applied to the raw GeoWATCH simulated values using linear regression to predict correction factor (CF) values based on physical site characteristics. The bias correction models significantly improved the performance of the GeoWATCH soil moisture model in terms of average performance statistics and number of statistically cally unbiased sites. This process could easily be incorporated into GeoWATCH, allowing for a capability to rapidly estimate vehicle impacts and determine rehabilitation requirements by installation land managers.     

Overland transport without roads

The need for off-road vehicles as applied to commerce, warfare, and recreation is examined. Most of the developments in the mobility of off-road vehicles have had a primarily military background. The main impediments to off-road mobility are defined as major obstacles, soft ground, and rough ground. Optimization of track design for accommodating these impediments in military vehicles reveals the importance of the ratio of Mean Maximum Pressure to Mean Pressure of a traced vehicle. It appears that contemporary commercial cross-country vehicles contain limitations in their designs which culd be overcome with available knowledge. These limitations include soft ground mobility, and speed over rough ground.The role of hovercraft in providing off-road mobility is reviewed, and special attention is given to the most recent requirements for avoiding environmental disturbance when using off-road vehicles in the Canadian North.     

Modeling of terrain impact caused by tracked vehicles

Analytical models that can predict the terrain impact caused by tracked vehicles on a horizontal plane were developed and tested. The models included a disturbed width model and an impact severity model. Inputs of the terrain impact models included vehicle static properties, vehicle dynamic properties, and terrain properties. The tested vehicles included an M1A1 tank, an M577 Armored Personal Carrier (APC), and an M548 cargo carrier. The models were verified with field tests conducted in Yakima Training Center in Yakima, WA, Fort Riley, KS, and Camp Atterbury, Indiana. The average percentage errors of the disturbed width model for the M1A1, M577, and the M548 were 10.0%, 27.3%, and 8.5%, respectively. The average percentage errors of the impact severity model of the M1A1 and M577 were 25.0% and 21.4%, respectively.     

Revegetated herbaceous plant species on a compacted skid road

This study intended to determine the plant species on a skid road subjected to soil compaction due to timber skidding in a pure sessile oak (Quercus petrea L.) forest. Our previous studies show that ground based skidding destroyed the soil and ecosystem. The timber skidding limits recovery and growth of plant cover on skid roads. However, some herbaceous plant species show healthy habitat, and they can revegetate and survive after the extreme degradation in study area.The composition and cover-abundance scales of these plant species investigated in a 100 m × 3 m transect. Twelve plant species belongs to 10 plant family were determined. Compositae and Liliaceae were the most abundant families. Daphne pontica L., Smilax aspera L., Trachystemon orientalis (L.) G. Don, Carex distachya Desf. var. distachya Desf. have the highest cover-abundance scale among all of determined species on compacted skid road.     

Quantifying the intensity of vehicle impacts using vehicle tracking devices during live training exercises

The operation of off-road vehicles during military training exercises can affect the environmental conditions of training lands by removing or disturbing vegetation. To quantify the impact of vehicle based military training, global positioning system (GPS)-based vehicle tracking systems were used to characterize the movement of vehicles during live training exercises. Methods were developed to spatially estimate the tracking intensity (number of vehicle passes per area) resulting from the training exercises. This method was then combined with previous developed methods that identified off-road trail formation and vehicle dynamic properties to quantify the overall training mission impacts of specific training events on installation resources. This approach to characterizing training impacts results in mission impact profiles that more accurately quantify live training mission impacts.Search radius and output grid size are important parameters of the proposed traffic intensity approximation method. Traffic intensities estimated using a variety of search radii and grid sizes were compared. Results indicated that a 10 m search radius and a 10-by-10 m output grid size worked the best for the study dataset. Approximately, 89% accuracy was found for traffic intensity (number of passes) estimation when using a 10 m search radius and a 10-by-10 m output grid size.     

Effect of different size and orientation of rectangular rotary blades on quality of puddling

The effect of different combinations of size and orientation of rectangular blades of a wet land puddler, on puddling index, force requirement and performance index was investigated under controlled conditions in a soil-bin from the study. It was observed with the blade size of 15-cm width × 8.5-cm depth and a blade angle of 30° with respect to shaft gave better performance than other combinations in terms of minimum puddling index, minimum horizontal force, vertical force, specific energy and maximum performance index. The values are, respectively, 67.95%, 105.12 N, 33.85 N, and 9.71 kJ/m³ and 6.69. The above-mentioned parameters of the blade were found to be very close to the predicted values obtain through MREG computer programme for optimization of size and orientation of puddler blades.