Canopy Spectra and Remote Sensing of Ashe Juniper and Associated Vegetation

A study was conducted in central Texas to determine the potential of using remote sensing technology to distinguish Ashe juniper (Juniperus ashei Buchholz) infestations on rangelands. Plant canopy reflectance measurements showed that Ashe juniper had lower near-infrared reflectance than other associated woody plant species and lower visible reflectance than mixed herbaceous species in spring and summer. Ashe juniper could be distinguished on color-infrared aerial photographs acquired in March, April, June, and August and on QuickBird false color satellite imagery obtained in June, where it had a distinct dark reddish-brown tonal response. Unsupervised classification techniques were used to classify aerial photographic and satellite imagery of study sites. An accuracy assessment performed on a computer classified map of a photographic image showed that Ashe juniper had producer's and user's accuracies of 100% and 92.9%, respectively, whereas an accuracy assessment performed on a classified map of a satellite image of the same site showed that Ashe juniper had producer's and user's accuracies of 94.1% and 88.1%, respectively. Accuracy assessments performed on classified maps of satellite images of two additional study sites showed that Ashe juniper had producer's and user's accuracies that ranged from 87.1% to 96.4%. These results indicate that both color-infrared photography and false color satellite imagery can be used successfully for distinguishing Ashe juniper infestations.     

Hyperspectral Characteristics of Canopy Components and Structure for Phenological Assessment of an Invasive Weed

Spectral reflectance values of four canopy components (stems, buds, opening flowers, and postflowers of yellow starthistle (Centaurea solstitialis)) were measured to describe their spectral characteristics. We then physically combined these canopy components to simulate the flowering stage indicated by accumulated flower ratios (AFR) 10%, 40%, 70%, and 90%, respectively. Spectral dissimilarity and spectral angles were calculated to quantitatively identify spectral differences among canopy components and characteristic patterns of these flowering stages. This study demonstrated the ability of hyperspectral data to characterize canopy components, and identify different flowering stages. Stems had a typical spectral profile of green vegetation, which produced a spectral dissimilarity with three reproduction organs (buds, opening flowers, and postflowers). Quantitative differences between simulated flower stages depended on spectral regions and phenological stages examined. Using full-range canopy spectra, the initial flowering stage could be separated from the early peak, peak, and late flowering stages by three spectral regions, i.e. the blue absorption (around 480 nm) and red absorption (around 650 nm) regions and NIR plateau from 730 nm to 950 nm. For airborne CASI data, only the red absorption region and NIR plateau could be used to identify the flowering stages in the field. This study also revealed that the peak flowering stage was more easily recognized than any of the other three stages.     

A mass transfer model of ammonia volatilisation from anaerobic digestate

Anaerobic digestion (AD) is becoming increasingly popular for treating organic waste. The methane produced can be burned to generate electricity and the digestate, which is high in mineral nitrogen, can be used as a fertiliser. In this paper we evaluate potential losses of ammonia via volatilisation from food waste anaerobic digestate using a closed chamber system equipped with a sulphuric acid trap. Ammonia losses represent a pollution source and, over long periods could reduce the agronomic value of the digestate. Observed ammonia losses from the experimental system were linear with time. A simple non-steady-state partitioning model was developed to represent the process. After calibration, the model was able to describe the behaviour of ammonia in the digestate and in the trap very well. The average rate of volatilisation was approximately 5.2 g N m^?2 week^?1. The model was used to extrapolate the findings of the laboratory study to a number of AD storage scenarios. The simulations highlight that open storage of digestate could result in significant losses of ammonia to the atmosphere. Losses are predicted to be relatively minor from covered facilities, particularly if depth to surface area ratio is high.     

Spatial and temporal variation of resource limitation in Chesapeake Bay

We report nutrient addition bioassays at 18 stations in Chesapeake Bay (USA) to assess resources limiting phytoplankton growth. Data were pooled from several sampling programs conducted from 1989 to 1994. Spatially, light and P limitation declined from low salinity regions to high salinity regions, as N limitation increased. This spatial pattern was driven primarily by freshwater inflows with high N/P and seawater inflows with low N/P. Seasonally, there was a marked progression of winter light limitation, spring P limitation, and summer N limitation at mesohaline and polyhaline stations. The seasonal pattern appeared to be caused by temperature, mixing, river discharge, and sediment P fluxes. At high salinity stations, we also observed winter N limitation (caused by DIN depletion prior to spring nitrate delivery), and at lower salinity stations there was fall P limitation (caused by reaeration of bottom sediments). At tidal fresh stations, turbidity and nutrient concentrations resulted in continuous light limitation, except at some stations in summer. Interannual decreases in light limitation and increases in N and P limitation appear to represent improvements in water quality. Received: 31 October 1997 / Accepted: 18 December 1998     

Mapping broom snakeweed through image analysis of color-infrared photography and digital imagery

A study was conducted on a south Texas rangeland area to evaluate aerial color-infrared (CIR) photography and CIR digital imagery combined with unsupervised image analysis techniques to map broom snakeweed [Gutierrezia sarothrae (Pursh.) Britt. and Rusby]. Accuracy assessments performed on computer-classified maps of photographic images from two sites had mean producer's and user's accuracies for broom snakeweed of 98.3 and 88.3%, respectively; whereas, accuracy assessments performed on classified maps from digital images of the same two sites had mean producer's and user's accuracies for broom snakeweed of 98.3 and 92.8%, respectively. These results indicate that CIR photography and CIR digital imagery combined with image analysis techniques can be used successfully to map broom snakeweed infestations on south Texas rangelands.     

Mapping giant salvinia with satellite imagery and image analysis

QuickBird multispectral satellite imagery was evaluated for distinguishing giant salvinia (Salvinia molesta Mitchell) in a large reservoir in east Texas. The imagery had four bands (blue, green, red, and near-infrared) and contained 11-bit data. Color-infrared (green, red, and near-infrared bands), normal color (blue, green and red bands), and four-band composite (blue, green, red, and near-infrared bands) images were studied. Unsupervised image analysis was used to classify the imagery. Accuracy assessments performed on the classification maps of the three composite images had producer’s and user’s accuracies for giant salvinia ranging from 87.8 to 93.5%. Color-infrared, normal color, and four-band satellite imagery were excellent for distinguishing giant salvinia in a complex field habitat.