Remotely sensed estimation of forest canopy density: A comparison of the performance of four methods

In recent years, a number of alternative methods have been proposed to predict forest canopy density from remotely sensed data. To date, however, it remains difficult to decide which method to use, since their relative performance has never been evaluated. In this study the performance of: (1) an artificial neural network, (2) a multiple linear regression, (3) the forest canopy density mapper and (4) a maximum likelihood classification method was compared for prediction of forest canopy density using a Landsat ETM+ image. Comparison of confusion matrices revealed that the regression model performed significantly worse than the three other methods. These results were based on a z-test for comparison of weighted kappa statistics, which is an appropriate statistic for analysis of ranked categories. About 89% of the variance of the observed canopy density was explained by the artificial neural networks, which outperformed the other three methods in this respect. Moreover, the artificial neural networks gave an unbiased prediction, while other methods systematically under or over predicted forest canopy density. The choice of biased method could have a high impact on canopy density inventories.     

The ‘Stained Glass Procedure’, a new method to compare classification performance of images acquired with different pixel sizes

Objective comparison of classification performance of earth observation images, acquired at different spatial resolutions (e.g. NOAA-AVHRR, IRS-MOS, IRS-WiFS, Landsat-TM, IRS-LISS), is complicated because both class definition and training site selection are hampered by the inherent scale differences. This paper presents a new, generic method to compare the information content of such a set of images, the “Stained Glass Procedure”. It overcomes the stated problems by computing the scale-dependent, internal spectral variation in an image and by using this as an indicator for land cover information. The Stained Glass Procedure creates segments in the images and calculates the internal spectral variation in a high-spatial-resolution image for each segment. For each image from the set the average variance, weighted to area, is calculated. The Stained Glass Procedure can be used to predict the performance of sensors that are not available, yet, or to roughly determine the optimal spatial resolution for the classification of a specific area.The procedure was applied to images with pixel sizes ranging from 23 to 1100 m. Classification detail of Envisat-MERIS (300 m pixel size), not included in the image set, could be predicted accurately using the Stained Glass Procedure.The Stained Glass Procedure applies one procedure to all images, without any subjective decision during the analysis, thus offering a method to compare images with different pixel sizes in terms of classification detail that is truly objective.     

Prospects for gradiometric aiding of inertial survey systems

The state of current and proposed moving-base gravity gradiometer instruments is briefly reviewed. The review perspective is directed toward their deployment as a source of additional gravimetric data during inertial surveys. In such gradiometer-aided surveys, the additional gravity gradient information could be used to:

1. Improve surveyed gravity vector accuracy
2. Extend the interval between zero velocity update stops
3. Accomplish varying combinations of the above.

The paper examines potential survey improvements associated with gradiometers having noise levels observed in laboratory prototypes. The additional improvements possible with future gradiometers are also discussed. These results are interpreted in light of present and likely future inertial survey system technology.     

The flotability of very fine particles — A review

The review is in three main sections. First, the observation that overall flotation performance deteriorates for the finest particles is confirmed, but the precise effects of particle size on recovery, grade, and flotation rate are shown to be more complex. In the second section an assessment is made of theories which have been proposed to explain the slower flotation rate of ultrafines, the effects of slime coating, and the flotation of slimes with cationic collectors. The last section of the paper gives a critical evaluation of methods which are claimed to improve the flotation of ultrafine particles.     

Glaciation and ~ 770 Ma Ediacara (?) Fossils from the Lesser Karatau Microcontinent,Kazakhstan

The Cambrian explosion, c. 530–515 Ma heralded the arrival of a diverse assembly of multicellular life including the first hard-shelled organisms. Fossils found in Cambrian strata represent the ancestors of most modern animal phyla. In contrast to the apparent explosiveness seen in the Cambrian fossil record, studies of molecular biology hint that the diversification observed in Cambrian strata was rooted in ancestry extending back into the Ediacaran (635–542 Ma). Fossil evidence for this mostly cryptic phase of evolution is derived from the soft-bodied fossils of the Ediacaran biota found throughout the world and bilaterian embryos found in the Doushantuo lagerstätte in South China. The first appearance of Ediacara fauna is thought to have followed the last of the ~ 750–635 Ma Neoproterozoic glacial episodes by 20–30 million years. In this paper, we present evidence for the oldest discovery of the ‘Ediacara’ discoidal fossils Nimbia occlusa and Aspidella terranovica (?) that predate the early Cryogenian glaciations by more than fifty million years. There is considerable disagreement over the significance of discoidal Ediacaran fossils, but our findings may support earlier suggestions that metazoan life has roots extending deeper into the Proterozoic Eon. We also confirm the presence of a Late Cryogenian (e.g. “Marinoan”) glaciation on the Lesser Karatau microcontinent including dropstones and striated clasts within the glacial strata.     

By design: The architecture of microbial redox cycling

The authors’ work on mine systems, combines field and laboratory integrated microbial geochemical investigation with high-resolution techniques enabling characterization and visualization at the bacterium scale (i.e. STXM). The results indicate a repeated motif of socially organized microbial cooperation occurring within microbial consortial macrostructures (pods). The pod structure directly enables the specific geochemical processes linked to the metabolic function of the consortial members. These microbially linked geochemical processes have important ramifications for bulk system geochemistry that were previously unknown. Results from two examples: (1) microbial metal interactions within AMD biofilms and (2) sulfur redox cycling by a novel consortia within mine waters, illustrate how the ecology of the pod consortia is linked to pod biogeochemical macrostructure as well as to the resulting geochemistry associated with pod metabolism. In both instances the pod structures enabled the associated consortia to carry out reactions not predicted by classic geochemical understanding of these systems. Investigation of AMD biofilm biogeochemical architecture capturing the micro-scale linkages amongst geochemical gradients, metal dynamics and depth resolved micro-organism community structure, illustrated a novel biomineralization process driven by biofilm associated pods controlling biofilm metal capture. Similarly, the groups’ recent discovery of an environmental S redox cycling, pod-forming, consortium revealed ecologically driven S cycling with previously unknown implications for both AMD mitigation and AMD carbon flux modeling. These results highlight how microbes cooperatively orchestrate their geochemical environment, underscoring the need to consider syntrophic community activity in environmental processes and the requirement for integrated, high-resolution techniques spanning geochemistry, molecular microbiology and imaging to reveal the biogeochemistry involved.     

Mineralogical and geochemical characterization of precipitates on stream receiving acid mine water, Korea

Seasonal variations of water chemistry occurred in acid mine drainage receiving mine and leachate water. Sulfate and metal concentrations were low in winter but high in spring and summer. Mine waters were highly acidic (up to pH 3.4) in nature with high concentrations of manganese, copper and zinc but high electrical conductivity and sulfate in leachate. The blue and brownish yellow precipitates were formed under different chemical environments of acid mine drainage. Brownish yellow (Munsell color 7.5YR 8/12), blue (Munsell color 2.5B 9/7) and light blue (Munsell color 2.5B 9/3) precipitates deposited on the stream bottom receiving acid mine water. The brownish yellow precipitates formed in the acid mine water, whereas the blue and light blue precipitates formed in the leachate water. The brownish yellow precipitates consisted mainly of ferrihydrite, whereas the blue and light blue precipitates consisted of glaucocerinite and/or woodwardite.     

How well do integrated assessment models simulate climate change?

Integrated assessment models (IAMs) are regularly used to evaluate different policies of future emissions reductions. Since the global costs associated with these policies are immense, it is vital that the uncertainties in IAMs are quantified and understood. We first demonstrate the significant spread in the climate system and carbon cycle components of several contemporary IAMs. We then examine these components in more detail to understand the causes of differences, comparing the results with more complex climate models and earth system models (ESMs), where available. Our results show that in most cases the outcomes of IAMs are within the range of the outcomes of complex models, but differences are large enough to matter for policy advice. There are areas where IAMs would benefit from improvements (e.g. climate sensitivity, inertia in climate response, carbon cycle feedbacks). In some cases, additional climate model experiments are needed to be able to tune some of these improvements. This will require better communication between the IAM and ESM development communities.