V. Klemas

Remote sensing of submerged aquatic vegetation in lower Chesapeake Bay - A comparison of Landsat MSS to TM imagery

Abstract Landsat Multispectral Scanner and Thematic Mapper imagery, obtained simultaneously over Guinea Marsh, VA, were analyzed and compared for their ability to detect submerged aquatic vegetation (SAV). An unsupervised clustering algorithm was applied to each image, where the input classification parameters are defined as functions of apparent sensor noise. Class confidence and accuracy were computed for all water areas by comparing the classified images, pixel-by-pixel, to rasterized SAV distributions derived from color aerial photography. To illustrate the effect of water depth upon classification error, areas of depth greater than 1.9 m (6 ft) were masked and class confidence and accuracy recalculated. A single-scattering radiative transfer model is used to illustrate how percent canopy cover and water depth affect the volume reflectance from a water column containing SAV. For a submerged canopy that is morphologically and optically similar to Zostera marina inhabiting Lower Chesapeake Bay, dense canopies may be isolated by masking optically deep water. For less dense canopies, the effect of increasing water depth is to increase the apparent percent crown cover, which may result in classification error.

Relationship between aboveground and belowground biomass ofSpartina alterniflora (Smooth Cordgrass)

Aboveground and belowground biomass ofSpartina alterniflora were harvested during the period of peak aerial biomass from six sites along a latitudinal gradient ranging from Georgia to Nova Scotia. An equation relating live aboveground to live belowground biomass for short-form plants was formulated, using data collected in Delaware marshes. When data from the other sites were substituted into the equation, the mean live belowground biomass it predicted was within 15% of the value determined by harvesting at four of the five sites. At all sites, short-form plant live belowground biomass was concentrated in the upper 10 cm. Dead belowground biomass was located mostly in the top 15 cm in southern marshes, but was more evenly distributed with depth in northern marshes. Results were more ambiguous for tall-form plants, probably because of greater spatial variability in biomass distribution, and greater seasonal biomass dynamics.

Remote sensing of biomass and annual net aerial primary productivity of a salt marsh

Spectral radiance data, simulating bands, 3, 4, and 5 of the Landsat 4 thematic mapper, were collected with a hand-held radiometer in a Delaware Spartina alterniflora salt marsh. Previously developed regression models were used to estimate live and dead biomass from canopy radiance data. Spectral radiance data were expressed as vegetation or infrared index values. Biomass estimates computed from the models were in close agreement with biomass estimates determined from harvesting during most of the growing season. Both dead biomass and soil background reflectance attenuated vegetation index biomass predictions, whereas only dead biomass reflectance attenuated infrared index biomass predictions. As a result, the infrared index yielded biomass means more similar to harvest biomass means in low live biomass areas, and the vegetation index yielded mean biomass estimates more similar to harvest biomass means in high live biomass areas. Annual net aerial primary productivity (NAPP) estimates computed from spectral radiance data were generally within 10% of similar NAPP estimates computed from harvest biomass data.

Coastal and estuarine studies with ERTS-1 and Skylab

Abstract Coastal vegetation, land use, current circulation, water turbidity, and ocean waste dispersion were studied by interpreting ERTS-1 and Skylab imagery with the help of ground truth collected during overpasses. Based on high-contrast targets such as piers and roads, the ERTS-1 multispectral scanner was found to have a resolution of 70–100 m, Skylabs S190A cameras about 20–40 m, and its S190B camera about 10–20 m. Important coastal land-use details can be more readily mapped using Skylabs imagery. On the other hand, the regular 18-day cycle of ERTS-1 allows observation of important manmade and natural changes and facilitates collection of ground truth.

Remote sensing of emergent and submerged wetlands: an overview

To plan for wetland protection and responsible coastal development, scientists and managers need to monitor changes in the coastal zone, as the sea level continues to rise and the coastal population keeps expanding. Advances in sensor design and data analysis techniques are now making remote-sensing systems practical and cost-effective for monitoring natural and human-induced coastal changes. Multispectral and hyperspectral imagers, light detection and ranging (lidar), and radar systems are available for mapping coastal marshes, submerged aquatic vegetation, coral reefs, beach profiles, algal blooms, and concentrations of suspended particles and dissolved substances in coastal waters. Since coastal ecosystems have high spatial complexity and temporal variability, they should be observed with high spatial, spectral, and temporal resolutions. New satellites, carrying sensors with fine spatial (0.4–4 m) or spectral (200 narrow bands) resolution, are now more accurately detecting changes in coastal wetland extent, ecosystem health, biological productivity, and habitat quality. Using airborne lidars, one can produce topographic and bathymetric maps, even in moderately turbid coastal waters. Imaging radars are sensitive to soil moisture and inundation and can detect hydrologic features beneath the vegetation canopy. Combining these techniques and using time-series of images enables scientists to study the health of coastal ecosystems and accurately determine long-term trends and short-term changes.

Determination of winter temperature patterns, fronts, and surface currents in the Yellow Sea and East China Sea from satellite imagery

Abstract A detailed winter sea surface temperature (SST) pattern in the Yellow Sea and East China Sea is derived from meteorological satellite thermal infrared images. The isotherms in the pattern are calibrated by temperature measurements in situ. The features of SST patterns are analyzed using images taken from a variety of satellites (DMSP, NOAA-5,6, GMS-1, and TIROS-N) over the last 10 years. The winter SST pattern has a “sandwich” structure, which implies that two warm tongues sandwich one cold tongue. This pattern starts forming at the end of November, has formed by the end of January, begins to decline at the end of February, and disappears at the end of April. In the SST patterns strong coastal fronts can be discerned. They are the Shandong Peninsula coastal front, the Zhejiang-Fujian coastal front and the South Korean coastal front. Based on the features of SST patterns and these fronts, the winter surface currents are discussed.

Application of Landsat MSS, NOAA/TIROS AVHRR, and Nimbus CZCS to study the La Plata river and its interaction with the ocean

Abstract In this paper the application of Landsat MSS, NOAA/TIROS AVHRR, and NIMBUS CZCS to study the La Plata River is analyzed. To accomplish this objective, some properties of the river are described first and, second, the following characteristics of the satellite systems are analyzed, a) spectral response, b) radiometric sensitivity and dynamic range, c) spatial resolution, swath width, and coverage frequency, and, third, the characteristics of each satellite system for remote sensing of this area are determined. Results indicate that each system contributes different kinds of information that complement each other and, if used as a set, will provide a better understanding of this river and its interaction with the ocean.

Suspended sediment observations from ERTS-1

Abstract Satellite imagery from four successful ERTS-1 passes over Delaware Bay during different portions of the tidal cycle are interpreted with special emphasis on visibility of suspended sediment and its use as a natural tracer for gross circulation patterns. The MSS red band (band 5) appears to give the best contrast, although the sediment patterns are represented by only a few neighboring shades of grey. Color density slicing improves the differentiation of turbidity levels. However, color additive enhancements are of limited value since most of the information is in a single color band. The ability of ERTS-1 to present a synoptic view of the surface circulation over the entire bay is shown to be a valuable and unique contribution of ERTS-1 to coastal oceanography.

Measurement of the surface emmissivity of turbid waters

Abstract Knowledge of sea surface emissivity is an important factor in measuring valid thermal IR radiometric temperatures from viewing positions both near the sea surface and from satellite platforms. In the latter case, we find that the effect of as little as a 0.01 change in emissivity from a blackbody assumption may create an increase of as much as 1.0°C in recovered temperature in dry atmospheres where recovered temperatures are radiometric temperatures obtained by applying the Planck function to radiances received at the satellite. As atmospheric moisture increases to around 5 g/cm 2 , variations in emissivity of the same order have negligible effect on recovered sea surface temperatures. Laboratory measurements of fresh (tap) and sea water samples with a Barnes 8–14 μm PRT-5 radiometer show distinctive differences in the behavior of emissivity with changes in suspended sediment concentrations for both organic and inorganic materials. Tap water emissivity remains essentially invariant at 0.980 over a wide range of concentrations. In contrast, however, sea water emissivity values show an immediate but steady decrease from 0.975 to a value 0.970, with increasing suspended sediment loading up to around 100 mg/L, where emissivity levels off until it falls again to a value of 0.962 at concentrations of 10,000 mg/L. Consequently, emissivity variations should not be neglected in making thermal measurements of coastal waters.

A study of density fronts and their effects on coastal pollutants

Density fronts represent regions of extremely high gradient or discontinuity in various parameters of physical interest, the most important being the water velocity and density fields. Such fronts strongly influence pollutant dispersion, by capturing oil slicks and other pollutants concentrated in surface films and drawing them down into the water column. Satellites, aircraft and boats were used to study the behavior of different types of fronts in Delaware Bay and their effect on pollutants in order to provide a basis for improving an oil drift and spreading model. LANDSAT satellites provided the most effective means of determining the location and extent of frontal systems over all portions of the tidal cycle. Satellite observations of flood-associated fronts on the New Jersey side of the Bay and ebb-associated fronts on the Delaware side agreed with boat measurements and model predictions.