Integrated Management for Sustainable Development of Coastal Zones – A Gis Based Study on the Central Kerala Coast

The present study focuses on the stability of the coast, exploitation of the coastal resources, human activities within the study are that extends from Fort Cochin at north to Thottappally at south, central Kerala State and hinterlands, socio-economic problems of the coastal community and the environmental issues arising in the recent past due to human activities. The objective of the study is critically analyse the coastal zone region and prevailing situation and to propose a comprehensive management plan for the sustainable development of the region under study. The thesis covers varied aspects of coastal uses like fisheries, tourism, land use, water resources etc. To critically examine the above scenarios, the ILWIS (Integrated Land and Water Information Systems) – GIS software has been used. A satellite image of the area has been used for the coastline change detection and land use patterns. The outcome of the present study will be beneficial to the various stakeholders within the coastal region and its hinterlands. To further add, this study should find better applications to similar or near-similar situations of Southeast Asia where identical scenarios are noticeable.

A GIS-based empirical model for vegetation prediction in Lefka Ori, Crete

The aim of the study was to establish and verify a predictive vegetation model for plant community distribution in the alti-Mediterranean zone of the Lefka Ori massif, western Crete. Based on previous work three variables were identified as significant determinants of plant community distribution, namely altitude, slope angle and geomorphic landform. The response of four community types against these variables was tested using classification trees analysis in order to model community type occurrence. V-fold cross-validation plots were used to determine the length of the best fitting tree. The final 9node tree selected, classified correctly 92.5% of the samples. The results were used to provide decision rules for the construction of a spatial model for each community type. The model was implemented within a Geographical Information System (GIS) to predict the distribution of each community type in the study site. The evaluation of the model in the field using an error matrix gave an overall accuracy of 71%. The user's accuracy was higher for the Crepis-Cirsium (100%) and Telephium-Herniaria community type (66.7%) and relatively lower for the Peucedanum-Alyssum and Dianthus-Lomelosia community types (63.2% and 62.5%, respectively). Misclassification and field validation points to the need for improved geomorphological mapping and suggests the presence of transitional communities between existing community types.

A GIS-based empirical model for vegetation prediction in Lefka Ori, Crete

The aim of the study was to establish and verify a predictive vegetation model for plant community distribution in the alti-Mediterranean zone of the Lefka Ori massif, western Crete. Based on previous work three variables were identified as significant determinants of plant community distribution, namely altitude, slope angle and geomorphic landform. The response of four community types against these variables was tested using classification trees analysis in order to model community type occurrence. V-fold cross-validation plots were used to determine the length of the best fitting tree. The final 9node tree selected, classified correctly 92.5% of the samples. The results were used to provide decision rules for the construction of a spatial model for each community type. The model was implemented within a Geographical Information System (GIS) to predict the distribution of each community type in the study site. The evaluation of the model in the field using an error matrix gave an overall accuracy of 71%. The user's accuracy was higher for the Crepis-Cirsium (100%) and Telephium-Herniaria community type (66.7%) and relatively lower for the Peucedanum-Alyssum and Dianthus-Lomelosia community types (63.2% and 62.5%, respectively). Misclassification and field validation points to the need for improved geomorphological mapping and suggests the presence of transitional communities between existing community types.

Flood Risk Assessment in Coastal Drainage Basins through a Multivariate Analysis within a GIS-Based Model

This paper presents a GIS-based multicriteria flood risk assessment and mapping approach applied to coastal drainage basins where hydrological data are not available. It involves risk to different types of possible processes: coastal inundation (storm surge), river, estuarine and flash flood, either at urban or natural areas, and fords. Based on the causes of these processes, several environmental indicators were taken to build-up the risk assessment. Geoindicators include geological-geomorphologic proprieties of Quaternary sedimentary units, water table, drainage basin morphometry, coastal dynamics, beach morphodynamics and microclimatic characteristics. Bioindicators involve coastal plain and low slope native vegetation categories and two alteration states. Anthropogenic indicators encompass land use categories properties such as: type, occupation density, urban structure type and occupation consolidation degree. The selected indicators were stored within an expert Geoenvironmental Information System developed for the State of Sao Paulo Coastal Zone (SIIGAL), which attributes were mathematically classified through deterministic approaches, in order to estimate natural susceptibilities (Sn), human-induced susceptibilities (Sa), return period of rain events (Ri), potential damages (Dp) and the risk classification (R), according to the equation R=(Sn.Sa.Ri).Dp. Thematic maps were automatically processed within the SIIGAL, in which automata cells (""geoenvironmental management units"") aggregating geological-geomorphologic and land use/native vegetation categories were the units of classification. The method has been applied to the Northern Littoral of the State of Sao Paulo (Brazil) in 32 small drainage basins, demonstrating to be very useful for coastal zone public politics, civil defense programs and flood management.

City Of Toronto’S Approach On Implementing The New Federal Wastewater Effluent Regulations Using A GIS-Based Hydrologic And Hydraulic Model

Canada releases over 150 billion litres of untreated and undertreated wastewater into the water environment every year1. To clean up urban wastewater, new Federal Wastewater Systems Effluent Regulations (WSER) on establishing national baseline effluent quality standards that are achievable through secondary wastewater treatment were enacted on July 18, 2012. With respect to the wastewater from the combined sewer overflows (CSO), the Regulations require the municipalities to report the annual quantity and frequency of effluent discharges. The City of Toronto currently has about 300 CSO locations within an area of approximately 16,550 hectares. The total sewer length of the CSO area is about 3,450 km and the number of sewer manholes is about 51,100. A system-wide monitoring of all CSO locations has never been undertaken due to the cost and practicality. Instead, the City has relied on estimation methods and modelling approaches in the past to allow funds that would otherwise be used for monitoring to be applied to the reduction of the impacts of the CSOs. To fulfill the WSER requirements, the City is now undertaking a study in which GIS-based hydrologic and hydraulic modelling is the approach. Results show the usefulness of this for 1) determining the flows contributing to the combined sewer system in the local and trunk sewers for dry weather flow, wet weather flow, and snowmelt conditions; 2) assessing hydraulic grade line and surface water depth in all the local and trunk sewers under heavy rain events; 3) analysis of local and trunk sewer capacities for future growth; and 4) reporting of the annual quantity and frequency of CSOs as per the requirements in the new Regulations. This modelling approach has also allowed funds to be applied toward reducing and ultimately eliminating the adverse impacts of CSOs rather than expending resources on unnecessary and costly monitoring.

GIS-based analytical tools for transport planning: spatial regression models for transportation demand forecast

Considering the importance of spatial issues in transport planning, the main objective of this study was to analyze the results obtained from different approaches of spatial regression models. In the case of spatial autocorrelation, spatial dependence patterns should be incorporated in the models, since that dependence may affect the predictive power of these models. The results obtained with the spatial regression models were also compared with the results of a multiple linear regression model that is typically used in trips generation estimations. The findings support the hypothesis that the inclusion of spatial effects in regression models is important, since the best results were obtained with alternative models (spatial regression models or the ones with spatial variables included). This was observed in a case study carried out in the city of Porto Alegre, in the state of Rio Grande do Sul, Brazil, in the stages of specification and calibration of the models, with two distinct datasets.

Long-term effects of oil pollution in mangrove forests (Baixada Santista, Southeast Brazil) detected using a GIS-based multitemporal analysis of aerial photographs

Oil spills are potential threats to the integrity of highly productive coastal wetlands, such as mangrove forests. In October 1983, a mangrove area of nearly 300 ha located on the southeastern coast of Brazil was impacted by a 3.5 million liter crude oil spill released by a broken pipeline. In order to assess the long-term effects of oil pollution on mangrove vegetation, we carried out a GIS-based multitemporal analysis of aerial photographs of the years 1962, 1994, 2000 and 2003. Photointerpretation, visual classification, class quantification, ground-truth and vegetation structure data were combined to evaluate the oil impact. Before the spill, the mangroves exhibited a homogeneous canopy and well-developed stands. More than ten years after the spill, the mangrove vegetation exhibited three distinct zones reflecting the long-term effects of the oil pollution. The most impacted zone (10.5 ha) presented dead trees, exposed substrate and recovering stands with reduced structural development. We suggest that the distinct impact and recovery zones reflect the spatial variability of oil removal rates in the mangrove forest. This study identifies the multitemporal analysis of aerial photographs as a useful tool for assessing a system's capacity for recovery and monitoring the long-term residual effects of pollutants on vegetation dynamics, thus giving support to mangrove forest management and conservation.

Long-term effects of oil pollution in mangrove forests (Baixada Santista, Southeast Brazil) detected using a GIS-based multitemporal analysis of aerial photographs

Oil spills are potential threats to the integrity of highly productive coastal wetlands, such as mangrove forests. In October 1983, a mangrove area of nearly 300 ha located on the southeastern coast of Brazil was impacted by a 3.5 million liter crude oil spill released by a broken pipeline. In order to assess the long-term effects of oil pollution on mangrove vegetation, we carried out a GIS-based multitemporal analysis of aerial photographs of the years 1962, 1994, 2000 and 2003. Photointerpretation, visual classification, class quantification, ground-truth and vegetation structure data were combined to evaluate the oil impact. Before the spill, the mangroves exhibited a homogeneous canopy and well-developed stands. More than ten years after the spill, the mangrove vegetation exhibited three distinct zones reflecting the long-term effects of the oil pollution. The most impacted zone (10.5 ha) presented dead trees, exposed substrate and recovering stands with reduced structural development. We suggest that the distinct impact and recovery zones reflect the spatial variability of oil removal rates in the mangrove forest. This study identifies the multitemporal analysis of aerial photographs as a useful tool for assessing a system's capacity for recovery and monitoring the long-term residual effects of pollutants on vegetation dynamics, thus giving support to mangrove forest management and conservation.

A GIS based model for solving the planar Huff problem considering different demand distributions and forbidden regions

[EN] In this paper, we have used Geographical Information Systems (GIS) to solve the planar Huff problem considering different demand distributions and forbidden regions. Most of the papers connected with the competitive location problems consider that the demand is aggregated in a finite set of points. In other few cases, the models suppose that the demand is distributed along the feasible region according to a functional form, mainly a uniform distribution. In this case, in addition to the discrete and uniform demand distributions we have considered that the demand is represented by a population surface model, that is, a raster map where each pixel has associated a value corresponding to the population living in the area that it covers...

GIS based Watershed Classification in Lao PDR

Every inclined land surface has a potential for soil and water degradation, the seriousness depends on a multitude of parameters such as slope, soil type, geomorphology, rainfall, land use and natural vegetation cover. In Laos this intensified land use leads to reduced vegetation cover, to increased soil erosion, decreasing yield, and finally is likely to influence the hydrological regime. Against this background the Mekong River Commission (MRC) elaborated a spatial explicit Watershed Classification (WSC) for the Lower Mekong Basin. Based on topographic factors derived from a high-resolution Digital Terrain Model, five watershed classes are calculated, giving indication about the sensitivity to resource degradation by soil erosion. The WSC allows spatial priority setting for watershed management and generally supports informed decision making on reconnaissance level. In the conclusions focus is laid on general considerations when GIS techniques are used for spatial decision support in a development context.

Affect and cognition measures in preference-based decisions: Validity testing of the Ottawa Decisional Conflict Scale and a decision-specific anxiety measure with men eligible for prostate cancer screening

Background. At present, prostate cancer screening (PCS) guidelines require a discussion of risks, benefits, alternatives, and personal values, making decision aids an important tool to help convey information and to help clarify values. Objective: The overall goal of this study is to provide evidence of the reliability and validity of a PCS anxiety measure and the Decisional Conflict Scale (DCS). Methods. Using data from a randomized, controlled PCS decision aid trial that measured PCS anxiety at baseline and DCS at baseline (T0) and at two-weeks (T2), four psychometric properties were assessed: (1) internal consistency reliability, indicated by factor analysis intraclass correlations and Cronbach's α; (2) construct validity, indicated by patterns of Pearson correlations among subscales; (3) discriminant validity, indicated by the measure's ability to discriminate between undecided men and those with a definite screening intention; and (4) factor validity and invariance using confirmatory factor analyses (CFA). Results. The PCS anxiety measure had adequate internal consistency reliability and good construct and discriminant validity. CFAs indicated that the 3-factor model did not have adequate fit. CFAs for a general PCS anxiety measure and a PSA anxiety measure indicated adequate fit. The general PCS anxiety measure was invariant across clinics. The DCS had adequate internal consistency reliability except for the support subscale and had adequate discriminate validity. Good construct validity was found at the private clinic, but was only found for the feeling informed subscale at the public clinic. The traditional DCS did not have adequate fit at T0 or at T2. The alternative DCS had adequate fit at T0 but was not identified at T2. Factor loadings indicated that two subscales, feeling informed and feeling clear about values, were not distinct factors. Conclusions. Our general PCS anxiety measure can be used in PCS decision aid studies. The alternative DCS may be appropriate for men eligible for PCS. Implications: More emphasis needs to be placed on the development of PCS anxiety items relating to testing procedures. We recommend that the two DCS versions be validated in other samples of men eligible for PCS and in other health care decisions that involve uncertainty. ^

Assessment of "mobile mapping system": A GIS-based support methodology

In this article, the authors examine the current status of different elements that integrate the landscape of the municipality of Olias del Rey in Toledo (Spain). A methodology for the study of rural roads, activity farming and local hunting management. We used Geographic Information Technologies (GIT) in order to optimize spatial information including the design of a Geographic Information System (GIS). In the acquisition of field data we have used vehicle "mobile mapping" instrumentation equipped with GNSS, LiDAR, digital cameras and odometer. The main objective is the integration of geoinformation and geovisualization of the information to provide a fundamental tool for rural planning and management.

Testing a GIS-based methodology for optimal location of Pumped Storage power plants in Norway

Europe needs to restructure its energy system. The aim to decrease the reliance on fossil fuels to a higher dependence on renewable energy has now been imposed by The European Commission. In order to achieve this goal there is a great interest in Norway to become "The Green Battery of Europe". In the pursuit of this goal a GIS-tool was created to investigate the pump storage potential in Norway. The tool searches for possible connections between existing reservoirs and dams with the criteria selected by the user. The aim of this thesis was to test the tool and see if the results suggested were plausible, develop a cost calculation method for the PSH lines, and make suggestions for further development of the tool. During the process the tool presented many non-feasible pumped storage hydropower (PSH) connections. The area of Telemark was chosen for the more detailed study. The results were discussed and some improvements were suggested for further development of the tool. Also a sensitivity test was done to see which of the parameters set by the user are the most relevant for the PSH connection suggestion. From a range of the most promising PSH plants suggested by the tool, the one between Songavatn and Totak was chosen for a case study, where there already exists a power plant between both reservoirs. A new Pumped Storage Plant was designed with a power production of 1200 MW. There are still many topics open to discussion, such as how to deal with environmental restrictions, or how to deal with inflows and outflows of the reservoirs from the existing power plants. Consequently the GIS-tool can be a very useful tool to establish the best possible connections between existing reservoirs and dams, but it still needs a deep study and the creation of new parameters for the user.