Application of topo-edaphic factors and remotely sensed vegetation indices to enhance biomass estimation in a heterogeneous landscape in the Eastern Arc Mountains of Tanzania

Estimating tropical biomass is critical for establishment of conservation inventories and landscape monitoring. However, monitoring biomass in a complex and dynamic environment using traditional methods is challenging. Recently, biomass estimates based on remotely sensed data and ecological variables have shown great potential. The present study explored the utility of remotely sensed data and topo-edaphic factors to improve biomass estimation in the Eastern Arc Mountains of Tanzania. Twenty-nine vegetation indices were calculated from RapidEye data, while topo-edaphic factors were taken from field measurements. Results showed that using topo-edaphic variables or vegetation indices, biomass could be predicted with an R² of 0.4. A combination of topo-edaphic variables and vegetation indices improved the prediction accuracy to an R² of 0.6. Results further showed a decrease in biomass estimates from 1162 ton ha^?1 in 1980 to 285.38 ton ha^?1 in 2012. This study demonstrates the value of combining remotely sensed data with topo-edaphic variables in biomass estimation.     

A User‐centered Design for the Addition of Interactive Masking Capability within an existing Web GIS

This article presents a case study of how a user‐centered design (UCD) approach was utilized during the addition of interactive masking capability to an existing web‐based geographic information system (Web GIS). By analyzing and discussing specific aspects of the user‐developer dialog within the context of a Web GIS software development life cycle, this article presents a case study for similar systems. The results of the UCD methodology is a discussion that presents a shift from an initial design to a new design that, based on user feedback, furthers the utility and usability of interactive masking within the Web GIS.     

Low‐temperature concentration of tellurium and gold in continental red bed successions

There is very little understanding of tellurium (Te) distribution and behaviour in sedimentary rocks. A suite of 15 samples of reduction spheroids (centimetre‐scale pale spheroids in otherwise red rock), including samples from eight localities in Triassic red beds across the British Isles, were mapped for Te using Laser Ablation–Inductively Coupled Plasma–Mass Spectrometry. Almost all showed enrichment in Te in the cores of the spheroids relative to background red bed concentrations, by up to four orders of magnitude. Some were also enriched over background in gold and/or mercury. In one case, discrete telluride minerals were recorded. The data show that Te is mobile and can be concentrated in low‐temperature sedimentary environments, controlled by redox variations. The consistency in enrichment across widely separate localities implies that the enrichment is a normal aspect of red bed diagenesis and so likely to be controlled by a ubiquitous process, such as microbial activity.     

Beyond dual-porosity modeling for the simulation of complex flow mechanisms in shale reservoirs

The state of the art of modeling fluid flow in shale reservoirs is dominated by dual-porosity models which divide the reservoirs into matrix blocks that significantly contribute to fluid storage and fracture networks which principally control flow capacity. However, recent extensive microscopic studies reveal that there exist massive micro- and nano-pore systems in shale matrices. Because of this, the actual flow mechanisms in shale reservoirs are considerably more complex than can be simulated by the conventional dual-porosity models and Darcy’s law. Therefore, a model capturing multiple pore scales and flow can provide a better understanding of the complex flow mechanisms occurring in these reservoirs. This paper presents a micro-scale multiple-porosity model for fluid flow in shale reservoirs by capturing the dynamics occurring in three porosity systems: inorganic matter, organic matter (mainly kerogen), and natural fractures. Inorganic and organic portions of shale matrix are treated as sub-blocks with different attributes, such as wettability and pore structures. In kerogen, gas desorption and diffusion are the dominant physics. Since the flow regimes are sensitive to pore size, the effects of nano-pores and micro-pores in kerogen are incorporated into the simulator. The multiple-porosity model is built upon a unique tool for simulating general multiple-porosity systems in which several porosity systems may be tied to each other through arbitrary connectivities. This new model allows us to better understand complex flow mechanisms and eventually is extended into the reservoir scale through upscaling techniques. Sensitivity studies on the contributions of the different flow mechanisms and kerogen properties give some insight as to their importance. Results also include a comparison of the conventional dual-porosity treatment and show that significant differences in fluid distributions and dynamics are obtained with the improved multiple-porosity simulation.