Arthur Schwarzschild

Retrieval of Substrate Bearing Strength from Hyperspectral Imagery during the Virginia Coast Reserve (VCR’07) Multi-Sensor Campaign

Hyperspectral imagery (HSI) derived from remote sensing can delineate surface properties of substrates such as type, moisture, and grain size. These are critical parameters that determine the substrate bearing strength. Although HSI only sees the surface layer, statistics can be derived that relate surface properties to the likely bearing strength of soils in particular regions. This information can be used to provide an initial map estimate on large scales of potential bearing strength. We describe an initial validation study at the Virginia Coast Reserve relating airborne HSI to in situ spectral and geotechnical measurements through a spectral-geotechnical lookup table (LUT).

Bathymetry Retrieval from Hyperspectral Imagery in the Very Shallow Water Limit: A Case Study from the 2007 Virginia Coast Reserve (VCR'07) Multi-Sensor Campaign

We focus on the validation of a simplified approach to bathymetry retrieval from hyperspectral imagery (HSI) in the very shallow water limit (less than 1–2 m), where many existing bathymetric LIDAR sensors perform poorly. In this depth regime, near infra-red (NIR) reflectance depends primarily on water depth (water absorption) and bottom type, with suspended constituents playing a secondary role. Our processing framework exploits two optimal regions where a simple model depending on bottom type and water depth can be applied in the very shallow limit. These two optimal spectral regions are at a local maximum in the near infra-red reflectance near 810 nm, corresponding to a local minimum in absorption, and a maximum in the first derivative of the reflectance near 720 nm. These two regions correspond to peaks in spectral correlation with bathymetry at these depths.

Very Shallow Water Bathymetry Retrieval from Hyperspectral Imagery at the Virginia Coast Reserve (VCR'07) Multi-Sensor Campaign

A number of institutions, including the Naval Research Laboratory (NRL), have developed look up tables for remote retrieval of bathymetry and in-water optical properties from hyperspectral imagery (HSI) [6]. For bathymetry retrieval, the lower limit is the very shallow water case (here defined as < 2m), a depth zone which is not well resolved by many existing bathymetric LIDAR sensors, such as SHOALS [4]. The ability to rapidly model these shallow water depths from HSI directly has potential benefits for combined HSI/LIDAR systems such as the Compact Hydrographic Airborne Rapid Total Survey (CHARTS) [10]. In this study, we focused on the validation of a near infra-red feature, corresponding to a local minimum in absorption (and therefore a local peak in reflectance), which can be correlated directly to bathymetry with a high degree of confidence. Compared to other VNIR wavelengths, this particular near-IR feature corresponds to a peak in the correlation with depth in this very shallow water regime, and this is a spectral range where reflectance depends primarily on water depth (water absorption) and bottom type, with suspended constituents playing a secondary role.

Flat-plate techniques for measuring reflectance of macro-algae (Ulva curvata)

We tested the consistency and accuracy of flat-plate spectral measurements (400–1000 nm) of the marine macrophyte Ulva curvata. With sequential addition of Ulva thallus layers, the reflectance progressively increased from 6% to 9% with six thalli in the visible (VIS) and from 5% to 19% with ten thalli in the near infrared (NIR). This progressive increase was simulated by a mathematical calculation based on an Ulva thallus diffuse reflectance weighted by a transmittance power series. Experimental and simulated reflectance differences that were particularly high in the NIR most likely resulted from residual water and layering structure unevenness in the experimental progression. High spectral overlap existed between fouled and non-fouled Ulva mats and the coexistent lagoon mud in the VIS, whereas in the NIR, spectral contrast was retained but substantially dampened by fouling.

Spectral definition of the macro-algae Ulva curvata in the back-barrier bays of the Eastern Shore of Virginia, USA

We have developed methods to determine the visible (VIS) to near-infrared (NIR) spectral properties of thalli and epiphytes of bloom-forming and green macrophyte Ulva curvata in back-barrier lagoons in Virginia, USA. A 2% increase in NIR thalli reflectance from winter to summer (ca. 9.5%) matched the drop in summer NIR transmittance (ca. 90%). In contrast, summer and winter VIS reflectance (reaching 6%) were nearly identical while winter transmittance (ca. 85%) was 10–20% higher. NIR absorption remained at 5% but VIS absorption increased by 10–20% from winter to summer. Replicate consistency substantiated the high transmittance difference indicating thallus composition changed from summer to winter. Epiphytes increased thallus reflectance (<ca. 4%) and decreased transmittance (<ca. 10%) and exhibited broadband VIS and NIR absorptions in summer and selective peaks in winter. A simulation coupling water extinction with thallus reflectance and transmittance found seven submerged thalli maximized the surface reflectance enhancement (ca. 2.5%).

Learning about Coastal Trends

Flowering plants that live underwater in marine and estuarine habitats (seagrasses) are important because they support human food sources, such as crabs and fish, as well as endangered animals, such as turtles and manatees. Seagrasses are now known to be declining globally, largely as a result of increasing pressure from human populations living along the coast and specifically increasing nutrient inputs. Using a 5e format (Engage, Explore, Explain, Extend, Evaluate) and interactive Web-based delivery for resources, the authors generated materials to cover the who, where, what, and why of seagrass. By learning about seagrasses, including their decline and current seagrass restoration efforts, students will become familiar with ecosystem interactions, global trends, current scientific research, and the decisions and policy-making processes involved in seagrass preservation and conservation. This lesson not only helps students learn about some of the environmental problems caused by the growing human population, but also urges them to become part of a solution.