Search for: All records

Harmful and nuisance algal blooms are becoming a greater concern to public health, riverine ecosystems, and recreational uses of inland waterways. Algal bloom proliferation has increased in the Upper Clark Fork River due to a combination of warming water temperatures, naturally high phosphorus levels, and an influx of nitrogen from various sources. To improve understanding of bloom dynamics and how they affect water quality, often measured as algal biomass measured through pigment standing crops, a UAV-based hyperspectral imaging system was deployed to monitor several locations along the Upper Clark Fork River in western Montana. Image data were collected across the spectral range of 400–1000 nm with 2.1 nm spectral resolution during two field sampling campaigns in 2021. Included are methods to estimate chl a and phycocyanin standing crops using regression analysis of salient wavelength bands, before and after separating the pigments according to their growth form. Estimates of chl a and phycocyanin standing crops generated through a linear regression analysis are compared to in situ data, resulting in a maximum R2 of 0.96 for estimating fila/epip chl-a and 0.94 when estimating epiphytic phycocyanin. Estimates of pigment standing crops from total abundance, epiphytic, and the sum of filamentous and epiphytic sources are also included, resulting in a promising method for remotely estimating algal standing crops. This method addresses the shortcomings of current monitoring techniques, which are limited in spatial and temporal scale, by proposing a method for rapid collection of high-spatial-resolution pigment abundance estimates. 

Hyperspectral imaging systems are becoming widely used due to their increasing accessibility and their ability to provide detailed spectral responses based on hundreds of spectral bands. However, the resulting hyperspectral images (HSIs) come at the cost of increased storage requirements, increased computational time to process, and highly redundant data. Thus, dimensionality reduction techniques are necessary to decrease the number of spectral bands while retaining the most useful information. Our contribution is two-fold: First, we propose a filter-based method called interband redundancy analysis (IBRA) based on a collinearity analysis between a band and its neighbors. This analysis helps to remove redundant bands and dramatically reduces the search space. Second, we apply a wrapper-based approach called greedy spectral selection (GSS) to the results of IBRA to select bands based on their information entropy values and train a compact convolutional neural network to evaluate the performance of the current selection. We also propose a feature extraction framework that consists of two main steps: first, it reduces the total number of bands using IBRA; then, it can use any feature extraction method to obtain the desired number of feature channels. We present classification results obtained from our methods and compare them to other dimensionality reduction methods on three hyperspectral image datasets. Additionally, we used the original hyperspectral data cube to simulate the process of using actual filters in a multispectral imager. 

The aurora is a beautiful night sky optical phenomenon that is readily seen at high-latitude locations, but with more effort can also be seen and enjoyed at mid-latitude locations. Guidelines for when and where to look are presented, along with a rich array of photographic examples of mid-latitude auroras exhibiting all the usual range of green, red, and purple colors. 

Solar eclipses are magnificent natural phenomena during which the sun is obscured by the moon. Besides the unique opportunity of studying the solar corona and immediate vicinity of the sun, an eclipse also leads to a darkened daytime sky with sunset colors and many other fascinating phenomena. Here we focus on how the daytime horizontal visual range changed during the duration of the solar eclipse of 21 August 2017, observed from Rexburg, Idaho, USA. Close to totality the eastern horizon for a short time period showed the contours of the Grand Teton Mountains from distances between about 80 km to 90 km. We show and discuss photographic images that show the visual range during totality being significantly extended beyond the visual range in most of the partial phase before and after totality, which was below 80 km when the mountains could not be seen by the naked eye. This phenomenon of an extended visual range can be explained in terms of a simple model for the daytime visual range. This model, which will be explained in this presentation, nicely reproduces the observations and also predicts other phenomena; for example, it predicts that similar phenomena may be observed if part of the line of sight close to the observer is in deep shade of a thick cloud cover. The presentation will tie these observations and their explanation to the teaching of optical scattering and atmospheric optics.