Riparian systems in the western United States provide important habitat for bird communities during all times of the year. In recent decades, invasive plants, such as Russian olive (Elaeagnus angustifolia), have achieved broad distribution and local dominance in many western riparian areas, raising concerns over the loss of ecological function within these systems. In 2005 and 2006 we conducted avian point counts and surveyed vegetation cover at 95 points along the Snake and Columbia Rivers in southeastern Washington to investigate the effects of total woody vegetation cover and the relative proportion of Russian olive cover on breeding and wintering riparian bird communities. Our results indicated that riparian habitats dominated by Russian olive can support diverse and abundant bird communities, though cavity nesting species were noticeably sparse. Bird density and species richness were best explained by a quadratic relationship to total woody vegetation cover in both seasons, as was breeding bird community composition, with greatest density and richness in intermediate cover levels. We found no indication that the proportion of the woody vegetation comprised of Russian olive strongly influenced any of these bird community metrics. Given that Russian olive comprised 81.6% of the riparian vegetation in our study area, it is unclear from our results how Russian olive would affect bird communities in regions where native vegetation is more abundant. Regardless, complete eradication of Russian olive from riparian systems where the plant is a major component will reduce the overall habitat value for birds by eliminating significant structural complexity.

PURPOSE: The 2004 hurricane season significantly impacted portions of Florida's coastlines and altered shoreline habitat for a wide variety of coastal organisms (Greening et al. 2006). Remotely sensed data can help characterize and assess these habitats and provide inferences on how hurricanes and subsequent coastal engineering practices affect the distribution and abundance of these species. This technical note focuses specifically on providing a better understanding of the requirements and limitations involved for mapping coastal bird habitat with respect to hurricane impacts. Recommendations are also made for conducting surveys to effectively monitor shoreline-dependent bird communities, since the geospatial data are specifically intended to supplement this effort. BACKGROUND: On 13 October 2004, President George W. Bush signed into law the Military Construction Appropriations and Emergency Hurricane Supplemental Appropriations Act of 2005 (Public Law 108-324), which authorized the Shore Protection Project Performance Improvement Initiative (S3P2I), or simply Shore Protection Assessment (SPA), in direct response to the 2004 hurricane season that had such an impact on portions of Florida. This document is a product of the Environmental Consideration work unit funded under this Initiative. To appropriately assess the impact hurricanes have on coastal bird habitats, it is necessary to obtain suitable pre- and post-storm data on the distribution, abundance, and structure of these habitats. This allows for the establishment of baseline data (pre-conditions) that can then be compared to post-event data to assess the amount of change that occurred. It is also necessary to acquire data on the distribution and abundance of shoreline-dependent birds from discrete coastal locations that coincide with the remotely sensed data. Due to the lack of sufficient pre-storm remotely sensed data, the focus of the effort was redirected to conducting a "proof of concept" approach using only the more suitable post-event data. This research effort involved the gathering and evaluation of remotely sensed data (with assessment of post-event data) and suggests an approach for directly measuring habitat changes before and after future storm events. STUDY AREA: The study area is in Lee County, FL from just south of Captiva Pass (R661)

: Forest ecosystems, in particular forest wetlands, are very dynamic and offer many ecological benefits because of their complex floral and faunal assemblages. It is important to understand these interactions, thus improving the ability to sustain this precious resource, and as stewards, pass it on. In addition, response to various natural influences, such as severe weather events, is also a vital part of understanding ecosystem health. It is important to quantify not only the obvious, visible damage but also the ambiguous stress these systems have undergone as a result of sustained wind damage. Satellite and airborne-based remote sensing (particularly imagery) are well-established methods for monitoring and assessing large-scale forest damage and are currently used to quantify visible damage. This research establishes proof of concept techniques for fusing sensor data from multiple remote sensing platforms to better understand the requirements needed to characterize subtle damage to forest environments impacted by hurricanes, in this case Hurricane Katrina. These advanced techniques may provide an indication of such vegetation stress before becoming visibly detectable, thus essentially predicting stress induced mortality before it occurs. This information can be used in formulating mitigation practices in riparian areas and along streams to help reduce sediment intake due to erosion from loss of vegetation, thus improving water quality.

Abstract : Monitoring the success of large-scale submerged aquatic vegetation (SAV) restoration projects requires the ability to detect and map the presence or absence of SAV, as well as assess changes in SAV distributions over time. Aerial photography is generally considered to be the most widely used, versatile, and relatively economical form of remote sensing (Lillesand and Kiefer 2000), and is the most common source of SAV mapping information (McKenzie et al. 2001). More often than not, however, difficulties arise that result in an undesirable or sometimes unusable photographic product.

A high-resolution, ground-based 3D laser scanner was recently evaluated for terrestrial site characterization of variable-surface minefield sites and generation of surface and terrain models. The instrument used to conduct this research was a Leica HDS3000 3D laser scanner. Two study sites located in the mid-western United States were used for this analysis. A very dense vegetation site (Grass Site) and a bare soil site (Dirt Site) with intermittent rocks and sparse vegetation were selected for data collection to simulate both obscured and semi-obscured minefield sites. High-density scans (0.2 cm to 2.0 cm) were utilized for Cyra target acquisition and were commensurate with size and distance to target from scanner location. Medium-density scans (2.0 cm to 5.0 cm) were chosen for point cloud generation of each site with approximately 10 percent overlap between field scans. To provide equivalent, unobstructed viewing perspectives from all scan locations at each site, the scanner was positioned on a trailer-mounted, chain-driven lift and raised to a scan height of 7.62 m above the ground. Final registration to UTM projected coordinate system of the multiple scan locations for the Dirt Site and Grass Site produced mean absolute errors of 0.014 m and 0.017 m, respectively. The laser scanner adequately characterized surface roughness and vegetation height to produce contour and terrain models for the respective site locations. The detailed scans of the sites along with the inherent, natural vegetation characteristics present at each site provide real-time discrimination of site components under contrasting land surface conditions.

: The use of a high-resolution, ground-based 3D laser scanner was recently evaluated for terrestrial site characterization of variable-surface minefield sites and generation of surface and terrain models. The instrument used to conduct this research was a Leica HDS3000 3D laser scanner. The high-speed, highly accurate ranging system has a 360 deg horizontal 270 deg vertical field of view that delivers positional, range, and angular (vertical and horizontal) single point accuracies (range 1 to 50 m) of 6 mm, 4 mm, and 60 micro-radians, respectively. The laser is a class 3R and is completely eye-safe with a wavelength of 523 nm and spot size of less than or equal to 6 mm at a distance of 50 m. The pulse rate is 1,000 points/ sec with an optimal effective range up to 100 m which is capable of producing a maximum point cloud spacing of 1.2 mm in the horizontal and vertical direction. Two study sites located in the midwestern United States were used for this analysis. A very dense vegetation site (Grass Site) and a bare soil site with intermittent rocks and sparse vegetation (Dirt Site) were selected for data collection to simulate both obscured and semi-obscured minefield sites. High-density scans (range 0.2 to 2.0 cm spacing) were utilized for Cyra target acquisition and were commensurate with size and distance to target from scanner location. Medium-density scans (range 2.0 to 5.0 cm spacing) were chosen for point cloud generation of the entire site(s) with approximately 10 percent edge overlap between field scans. In order to provide equivalent, unobstructed viewing perspectives from all scan locations at each site, the scanner was positioned on a trailer-mounted, chain-driven lift and raised to an approximate scan height of 7.6 m above the ground. Final registration to UTM projected coordinate system of the multiple scan locations for the Dirt Site and Grass Site produced mean absolute errors of 0.014 and 0.017 m, respectively.

Concerns about the effects of urban encroachment occurring near military installations continue to grow.Urban encroachment impacts both the civilian population and the military installation.Urban growth and development negatively influence a military installation's ability to conduct training and maintain combat readiness, and they hinder the viability of the installation itself.The primary objective of this study was to monitor urban encroachment at Fort Benning, GA.A secondary objective was

PURPOSE: Information regarding regional land cover is a fundamental requirement to support the long- term baseline ecosystem monitoring plan under the Strategic Environmental Research and Development Program (SERDP), Ecosystem Management Project (SEMP), Ecosystem Characterization and Monitoring Initiative (ECMI). The land cover characterization phase of this plan provides the foundation needed to derive vegetation density indices and land cover patterns. These characteristics are the primary visible expressions of the underlying ecosystem structure, function, and process at all spatial scales (Kress 2000). To meet the requirement for land cover information, Landsat 7 Enhanced Thematic Mapper (ETM) data were used to classify land cover types for the Fort Benning ecoregion. This technical note describes the procedures used to extract land cover information from the satellite imagery. BACKGROUND: At a regional scale, land cover significantly affects biophysical factors such as surface albedo and sensible heat flux, and plays an important role in material cycling. Developing an accurate land cover classification is vital, since other landscape characteristics are directly linked to it. Satellite imagery has been used since the 1970's as an accurate and cost-effective tool for deriving regional vegetation and land cover information. Digital processing techniques involving the statistical analysis of image data representing various portions of the electromagnetic spectrum allow definition of areas that reflect solar radiation in a like manner (the thermal band was not used in this analysis). These areas may then be related to land cover or vegetation types through the use of ground-truth data collected in the field.