Vulnerabilities of macrophytes distribution due to climate change

Theoretical and Applied Climatology - The rise in the earth’s surface and water temperature is part of the effect of climatic change that has been observed for the last decade. The rates of...     

Validating the use of object-based image analysis to map commonly recognized landform features in the United States

ABSTRACT

The U.S. Geological Survey (USGS) National Geospatial Program (NGP) seeks to i) create semantically accessible terrain features from the pixel-based 3D Elevation Program (3DEP) data, and ii) enhance the usability of the USGS Geographic Names Information System (GNIS) by associating boundaries with GNIS features whose spatial representation is currently limited to 2D point locations. Geographic object-based image analysis (GEOBIA) was determined to be a promising method to approach both goals. An existing GEOBIA workflow was modified and the resulting segmented objects and terrain categories tested for a strategically chosen physiographic province in the mid-western US, the Ozark Plateaus. The chi-squared test of independence confirmed that there is significant overall spatial association between terrain categories of the GEOBIA and GNIS feature classes. Contingency table analysis also suggests strong category-specific associations between select GNIS and GEOBIA classes. However, 3D visual analysis revealed that GEOBIA objects resembled segmented regions more than they did individual landform objects, with their boundaries often failing to correspond to match what people would likely perceive as landforms. Still, objects derived through GEOBIA can provide initial baseline landscape divisions that can improve the efficiency of more specialized feature extraction methods.     

The Indus flood of 2010 in Pakistan: a perspective analysis using remote sensing data

The Indus flood in 2010 was one of the greatest river disasters in recent history, which affected more than 14 million people in Pakistan. Although excessive rainfall between July and September 2010 has been cited as the major causative factor for this disaster, the human interventions in the river system over the years made this disaster a catastrophe. Geomorphic analysis suggests that the Indus River has had a very dynamic regime in the past. However, the river has now been constrained by embankments on both sides, and several barrages have been constructed along the river. As a result, the river has been aggrading rapidly during the last few decades due to its exceptionally high sediment load particularly in reaches upstream of the barrages. This in turn has caused significant increase in cross-valley gradient leading to breaches upstream of the barrages and inundation of large areas. Our flow accumulation analysis using SRTM data not only supports this interpretation but also points out that there are several reaches along the Indus River, which are still vulnerable to such breaches and flooding. Even though the Indus flood in 2010 was characterized by exceptionally high discharges, our experience in working on Himalayan rivers and similar recent events in rivers in Nepal and India suggest that such events can occur at relatively low discharges. It is therefore of utmost importance to identify such areas and plan mitigation measures as soon as possible. We emphasize the role of geomorphology in flood analysis and management and urge the river managers to take urgent steps to incorporate the geomorphic understanding of Himalayan rivers in river management plans.     

Remote Sensing and GIS Based Analysis of Geomorphic Evidences and Morphometry of Active Faults in Kachchh Area

Kachchh basin is a Mesozoic rift basin under the influence of many active faults. This in turn gives rise to marked structural complexity and associated seismicity. Remote Sensing study of geomorphic evidences of these faults has been carried out using satellite images and is validated using morphometric analysis and digital elevation model data. Satellite images not only help in identifying expression of active faults and active tectonics on a macroscopic scale, but also provide the image characteristics of active faults directly. A few faults along with nature of lateral displacement could be identified from the Kachchh area. Morphometric analysis viz., sinuosity, asymmetry factor and hypsometry indicated affected streams and drainage basins due to fault activity.     

Flood inundation mapping and hazard assessment of Baitarani River basin using hydrologic and hydraulic model

Frequent flood is a concern for most of the coastal regions of India. The importance of flood maps in governing strategies for flood risk management is of prime importance. Flood inundation maps are considered dependable output generated from simulation results from hydraulic models in evaluating flood risks. In the present work, a continuous hydrologic-hydraulic model has been implemented for mapping the flood, caused by the Baitarani River of Odisha, India. A rainfall time-series data were fed into the hydrologic model and the runoff generated from the model was given as an input into the hydraulic model. The study was performed using the HEC-HMS model and the FLO-2D model to map the extent of flooding in the area. Shuttle Radar Topographic Mission (SRTM) 90 m Digital Elevation Model (DEM) data, Land use/Land cover map (LULC), soil texture data of the basin area were used to compute the topographic and hydraulic parameters. Flood inundation was simulated using the FLO-2D model and based on the flow depth, hazard zones were specified using the MAPPER tool of the hydraulic model. Bhadrak District was found to be the most hazard-prone district affected by the flood of the Baitarani River. The result of the study exhibited the hydraulic model as a utile tool for generating inundation maps. An approach for assessing the risk of flooding and proper management could help in mitigating the flood. The automated procedure for mapping and the details of the study can be used for planning flood disaster preparedness in the worst affected area.

     

New legume fruits from the oligocene sediments of Assam

For the first time a rich assemblage of legume fruits is described from the Late Oligocene sediments of the Makum as well as Dilli-Jeypore coalfields of Assam. A new genus Buteocarpon has been instituted for the fossil fruits resembling Butea Roxb. of the family Fabaceae. In addition, six new species of the genus Leguminocarpon Goeppert are also described. Their presence indicates a warm and humid climate in the region during the deposition of the sediments.     

Measuring similarity between geospatial lifelines in studies of environmental health

Many epidemiological studies involve analysis of clusters of diseases to infer locations of environmental hazards that could be responsible for the disease. This approach is however only suitable for sedentary populations or diseases with small latency periods. For migratory populations and diseases with long latency periods, people may change their residential location between time of exposure and onset of ill health. For such situations, clusters are diffused and diluted by in- and out-migration and may become very difficult to detect. One way to address the problem of diffused clusters is to include in analyses not only current residential locations, but all past locations at which cases might have been exposed to environmental hazardous. In this paper, we assume that a persons residential history provides such information and represent it through a discrete geospatial lifeline data model. Clusters of similar geospatial lifelines represent individuals who have similar residential histories—and therefore represent people who are more likely to have had similar environmental exposure histories. We therefore introduce a lifeline distance (dissimilarity) measure to detect clusters of cases, providing a basis for revealing possible regions in space-time where environmental hazards might have existed in the past. The ability of the measure to distinguish cases from controls is tested using two sets of synthetically generated cases and controls. Results indicate that the measure is able to consistently distinguish between populations of cases and controls with statistically significant results. The lifeline distance measure consistently outperforms another measure which uses only the distance between subjects residences at time of diagnosis. However, the advantages of using the entire residential history are only partly realized, since the ability to distinguish between cases and controls is only moderately better for the lifeline distance function. Future work is needed to investigate modifications to the inter-lifeline distance measure in order to enhance the potential of this approach to detect locations of environmental hazards over the lifespan.This project is supported by grant number 1 R01 ES09816-01 from the National Institute of Environmental Health Sciences, NIH. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the NIEHS or NIH. We wish to thank Peter Rogerson for helpful discussions of the migration models, and the anonymous reviewers for pointing out areas where the paper could be improved.     

<Emphasis Type="Italic">Ficus palaeoracemosa</Emphasis> sp. nov. – A new fossil leaf from the Kasauli Formation of Himachal Pradesh and its palaeoclimatic significance

A new fossil leaf impression is described from the Early Miocene sediments of Kasauli–Kalka road section, Himachal Pradesh. The characteristic leaf venation pattern suggests that it has a close affinity with Ficus L., particularly with F. racemosa L. (= F. glomerata Roxb.). Its presence indicates a warm and humid climate in the region during the deposition of sediments, in contrast to the present day cooler and less humid climate.     

Fractal Analysis of <Emphasis Type="Italic">In Situ</Emphasis> Host Rock Nepheline Syenite Xenoliths in a Micro-Shonkinite Dyke (The Elchuru Alkaline Complex,SE India)

Formation of the fragments of the wall-rock during dyking is one of the important manifestations of instantaneous magmatic events. This process is well documented at shallower depths of Earth’s crust but not at deeper levels. In this paper the in situ xenoliths of host rock nepheline syenite within a micro-shonkinite dyke emplaced at mid-crustal depths is described and the fractal theory applied to evaluate origin of the xenoliths. The nepheline syenite xenoliths are angular to oval shaped and sub-millimetre to ~50 cm long. The xenoliths are matrix supported with clasts and matrix being in equal proportions. Partly detached wall-rock fragments indicate incipient xenolith formation, which suggested that the model fragmentation processes is solely due to dyke emplacement. Fractal analytical techniques including clast size distribution, boundary roughness fractal dimension and clast circularity was carried out. The fractal data suggests that hydraulic (tensile) fracturing is the main process of host rock brecciation. However, the clast size and shape are further affected by postfragmentation processes including shear and thermal fracturing, and chemical erosion. The study demonstrates that dyking in an isotropic medium produces fractal size distributions of host rock xenoliths; however, post-fragmentation processes modify original fractal size distributions.     

Multicriteria generalization (MCG): a decision-making framework for formalizing multiscale environmental data reduction

Environmental simulation models need automated geographic data reduction methods to optimize the use of high-resolution data in complex environmental models. Advanced map generalization methods have been developed for multiscale geographic data representation. In the case of map generalization, positional, geometric and topological constraints are focused on to improve map legibility and communication of geographic semantics. In the context of environmental modelling, in addition to the spatial criteria, domain criteria and constraints also need to be considered. Currently, due to the absence of domain-specific generalization methods, modellers resort to ad hoc methods of manual digitization or use cartographic methods available in off-the-shelf software. Such manual methods are not feasible solutions when large data sets are to be processed, thus limiting modellers to the single-scale representations. Automated map generalization methods can rarely be used with confidence because simplified data sets may violate domain semantics and may also result in suboptimal model performance. For best modelling results, it is necessary to prioritize domain criteria and constraints during data generalization. Modellers should also be able to automate the generalization techniques and explore the trade-off between model efficiency and model simulation quality for alternative versions of input geographic data at different geographic scales. Based on our long-term research with experts in the analytic element method of groundwater modelling, we developed the multicriteria generalization (MCG) framework as a constraint-based approach to automated geographic data reduction. The MCG framework is based on the spatial multicriteria decision-making paradigm since multiscale data modelling is too complex to be fully automated and should be driven by modellers at each stage. Apart from a detailed discussion of the theoretical aspects of the MCG framework, we discuss two groundwater data modelling experiments that demonstrate how MCG is not just a framework for automated data reduction, but an approach for systematically exploring model performance at multiple geographic scales. Experimental results clearly indicate the benefits of MCG-based data reduction and encourage us to continue expanding the scope of and implement MCG for multiple application domains.