Hydrogeological, Geophysical And Geochemical Studies In Parts Of Coastal And Midland Areas, Central Kerala - A Gis Approach

The present study deals with the different hydrogeological characteristics of the coastal region of central Kerala and a comparative analysis with corresponding hard rock terrain. The coastal regions lie in areas where the aquifer systems discharge groundwater ultimately into the sea. Groundwater development in such regions will require a precise understanding of the complex mechanism of the saline and fresh water relationship, so that the withdrawals are so regulated as to avoid situations leading to upcoming of the saline groundwater bodies as also to prevent migration of sea water ingress further inland. Coastal tracts of Kerala are formed by several drainage systems. Thick pile of semi-consolidated and consolidated sediments from Tertiary to Recent age underlies it. These sediments comprise phreatic and confined aquifer systems. The corresponding hard rock terrain is encountered with laterites and underlined by the Precambrian metamorphic rocks. Supply of water from hard rock terrain is rather limited. This may be due to the small pore size, low degree of interconnectivity and low extent of weathering of the country rocks. The groundwater storage is mostly controlled by the thickness and hydrological properties of the weathered zone and the aquifer geometry. The over exploitation of groundwater, beyond the ‘safe yield’ limit, cause undesirable effects like continuous reduction in groundwater levels, reduction in river flows, reduction in wetland surface, degradation of groundwater quality and many other environmental problems like drought, famine etc.

Environmentally-Efficient Development Management System for Greater Kochi in Kerala State

The School of Management Studies, CUSAT

Environmentally-Efficient Development Management System for Greater Kochi in Kerala State”

The base concept from which the entire research problem emerged is as follows: Lack of spatial planning and effective development management system lead to urban sprawl with non-optimal density of population to support urban infrastructure on the one side causing a lesser quality of life in urban areas. On the other side it causes loss of productivity of natural ecosystems and agricultural areas due to disturbance to the ecosystems. Planned compact high density development with compatible mixed land use can go a long way in achieving environmental efficiency of development management system.

Development of Techniques for the Automatic Extraction and Grade Detection of Glioma Tumors from Conventional Brain Magnetic Resonant Images

Cerebral glioma is the most prevalent primary brain tumor, which are classified broadly into low and high grades according to the degree of malignancy. High grade gliomas are highly malignant which possess a poor prognosis, and the patients survive less than eighteen months after diagnosis. Low grade gliomas are slow growing, least malignant and has better response to therapy. To date, histological grading is used as the standard technique for diagnosis, treatment planning and survival prediction. The main objective of this thesis is to propose novel methods for automatic extraction of low and high grade glioma and other brain tissues, grade detection techniques for glioma using conventional magnetic resonance imaging (MRI) modalities and 3D modelling of glioma from segmented tumor slices in order to assess the growth rate of tumors. Two new methods are developed for extracting tumor regions, of which the second method, named as Adaptive Gray level Algebraic set Segmentation Algorithm (AGASA) can also extract white matter and grey matter from T1 FLAIR an T2 weighted images. The methods were validated with manual Ground truth images, which showed promising results. The developed methods were compared with widely used Fuzzy c-means clustering technique and the robustness of the algorithm with respect to noise is also checked for different noise levels. Image texture can provide significant information on the (ab)normality of tissue, and this thesis expands this idea to tumour texture grading and detection. Based on the thresholds of discriminant first order and gray level cooccurrence matrix based second order statistical features three feature sets were formulated and a decision system was developed for grade detection of glioma from conventional T2 weighted MRI modality.The quantitative performance analysis using ROC curve showed 99.03% accuracy for distinguishing between advanced (aggressive) and early stage (non-aggressive) malignant glioma. The developed brain texture analysis techniques can improve the physician’s ability to detect and analyse pathologies leading to a more reliable diagnosis and treatment of disease. The segmented tumors were also used for volumetric modelling of tumors which can provide an idea of the growth rate of tumor; this can be used for assessing response to therapy and patient prognosis.