Response of underwater light transmittance in the Rhode River estuary to changes in water-quality parameters

A year-long study of incident and underwater light transmittance (400–800 nm) in the Rhode River, Maryland, a tidal tributary to Chesapeake Bay, indicated that light transmittance responded in both intensity and spectral quality to changes in the amount and type of dissolved and suspended materials in the water. At times of relatively clear water, transmittance was similar to that previously reported in the literature for coastal waters. With high concentrations of suspended and dissolved materials in the water, attenuation of irradiance was high in the upper part of the water column and different for the various wave bands, depending on the type of material present. At such times, attenuation was higher in the upper part of the water column under sunny, clear skies than on cloudy days. We believe this to be due to higher concentrations of pigments and suspended particles in the water on sunny days, increasing the scattering and adsorption. A second factor was a lower average cosine on cloudy days, decreasing the effect of scattering on the average path length per meter of depth. High attenuation coefficients in the middle of the spectrum are attributed to accessory pigments. Regression of the diffuse attenuation coefficient on eight water-quality parameters explained up to 93% of the variance in the attenuation coefficient. Chlorophylls a and c and mineral suspensates were the three most important variables for data taken under clear skies. In contrast, under cloudy skies, the three most important variables were different for different wavelengths. Models of irradiance attenuation in turbid estuarine waters require the use of more variables than models for open ocean waters.     

Kernel Eigenspace Separation Transform for Subspace Anomaly Detection in Hyperspectral Imagery

This letter proposes a nonlinear version of the eigenspace separation transform (EST) for subspace anomaly detection in hyperspectral imaging. The EST is defined in terms of the eigenvectors of the difference correlation matrix (DCOR) obtained using the data from the two classes. Using ideas found in the machine learning literature (i.e., the kernel trick), a nonlinear version-kernel EST (KEST)-is achieved by expressing the DCOR in terms of dot products in feature space and replacing all dot products with a Mercer kernel function that is defined in terms of input data space. Experimental results indicate that KEST outperforms many other commonly used subspace anomaly detection algorithms.     

Improving Geocode Accuracy with Candidate Selection Criteria

Geocoding systems typically use more than one geographic reference dataset to improve match rates and spatial accuracy, resulting in multiple candidate geocodes from which the single “best” result must be selected. Little scientific evidence exists for formalizing this selection process or comparing one strategy to another, leading to the approach used in existing systems which we term the hierarchy‐based criterion: place the available reference data layers into qualitative, static, and in many cases, arbitrary hierarchies and attempt a match in each layer, in order. The first non‐ambiguous match with suitable confidence is selected and returned as output. This approach assumes global relationships of relative accuracy between reference data layers, ignoring local variations that could be exploited to return more precise geocodes. We propose a formalization of the selection criteria and present three alternative strategies which we term the uncertainty‐, gravitationally‐, and topologically‐based strategies. The performance of each method is evaluated against two ground truth datasets of nationwide GPS points to determine any resulting spatial improvements. We find that any of the three new methods improves on current practice in the majority of cases. The gravitationally‐ and topologically‐based approaches offer improvement over a simple uncertainty‐based approach in cases with specific characteristics.     

Short-term temporal dynamics of algal species in a subtidal kelp bed in relation to changes in environmental conditions and canopy biomass

Understanding temporal variation at the scale of weeks to months is critical to understanding broad temporal patterns in diversity in the same way as understanding diversity across landscapes relies on understanding variation at the scale of meters. However, whereas small-scale spatial variation in temperate reef algal assemblages has been extensively studied, fine-scale temporal changes have not been well addressed. By sampling the macroalgae of a subtidal reef near Perth (Australia), dominated by the small kelp Ecklonia radiata, every ∼40 days over a 2-year period, we were able to test whether temporal changes in species richness, assemblage structure and species turn-over were related to seasonal changes in surface temperature, solar radiation and wave height. A total of 93 macroalgal taxa were identified, and species richness per sampling time ranged from 25 to 64 taxa 1.25 m⁻². Biomass of E. radiata was positively correlated with changes in sea surface temperature and light, and negatively correlated with wave height. Species richness, assemblage structure and turn-over of other macroalgae were more associated with seasonal changes in kelp biomass than environmental variables per se. We conclude that seasonal changes in environmental conditions drive changes in the kelp canopy, which in turn drive changes in species richness and assemblage structure. This suggests that habitat-formers such as kelps can exert a strong temporal influence on associated communities, analogous to well-described spatial influences. Thus, as kelp canopy biomass expands and retracts over time-scales of weeks to months, so does available space for colonization and growth, resulting in a high species turn-over. Species richness is therefore increased and maintained through time, in the same way as canopy-gap mosaics increase and maintain species richness across spatial landscapes.     

Ozone Profile Retrieval from Satellite Observation Using High Spectral Resolution Infrared Sounding Instrument

I. IntroductionOzone p1ays a very 1mportant ro1e in globa1 climate change. This is particularly true inthe stratosphere, where ultra--v1olet solar radiation is strongly absorbed by ozone, leading tosubstantlal change in the earths atmospheric thermal, physical and chemical structure. Al-though the troposphere contains only about l0% of the total atmospheric ozone, the varia-tlon of tropospheric ozone may have more significant cllmatic effect than stratospheric ozoneon the earth's surface temP…