The application of data mining techniques to interrogate Western Australian water catchment data sets

Current environmental challenges such as increasing dry land salinity, waterlogging, eutrophication and high nutrient runoff in south western regions of Western Australia may have both cultural and environmental implications in the near future. Advances in computer science disciplines, more specifically, data mining techniques and geographic information services provide the means to be able to conduct longitudinal climate studies to predict changes in the Water catchment areas of Western Australia. The research proposes to utilise existing spatial data mining techniques in conjunction of modern open-source geospatial tools to interpret trends in Western Australian water catchment land use. This will be achieved through the development of a innovative data mining interrogation tool that measures and validates the effectiveness of data mining methods on a sample water catchment data set from the Peel Harvey region of WA. In doing so, the current and future statistical evaluation on potential dry land salinity trends can be eluded. The interrogation tool will incorporate different modern geospatial data mining techniques to discover meaningful and useful patterns specific to current agricultural problem domain of dry land salinity. Large GIS data sets of the water catchments on Peel-Harvey region have been collected by the state government Shared Land Information Platform in conjunction with the LandGate agency. The proposed tool will provide an interface for data analysis of water catchment data sets by benchmarking measures using the chosen data mining techniques, such as: classical statistical methods, cluster analysis and principal component analysis.The outcome of research will be to establish an innovative data mining instrument tool for interrogating salinity issues in water catchment in Western Australia, which provides a user friendly interface for use by government agencies, such as Department of Agriculture and Food of Western Australia researchers and other agricultural industry stakeholders

GIS-based approach for optimization of onshore wind park infrastructure alignment in Finland

Wind power is a rapidly developing, low-emission form of energy production. In Fin-land, the official objective is to increase wind power capacity from the current 1 005 MW up to 3 500–4 000 MW by 2025. By the end of April 2015, the total capacity of all wind power project being planned in Finland had surpassed 11 000 MW. As the amount of projects in Finland is record high, an increasing amount of infrastructure is also being planned and constructed. Traditionally, these planning operations are conducted using manual and labor-intensive work methods that are prone to subjectivity. This study introduces a GIS-based methodology for determining optimal paths to sup-port the planning of onshore wind park infrastructure alignment in Nordanå-Lövböle wind park located on the island of Kemiönsaari in Southwest Finland. The presented methodology utilizes a least-cost path (LCP) algorithm for searching of optimal paths within a high resolution real-world terrain dataset derived from airborne lidar scannings. In addition, planning data is used to provide a realistic planning framework for the anal-ysis. In order to produce realistic results, the physiographic and planning datasets are standardized and weighted according to qualitative suitability assessments by utilizing methods and practices offered by multi-criteria evaluation (MCE). The results are pre-sented as scenarios to correspond various different planning objectives. Finally, the methodology is documented by using tools of Business Process Management (BPM). The results show that the presented methodology can be effectively used to search and identify extensive, 20 to 35 kilometers long networks of paths that correspond to certain optimization objectives in the study area. The utilization of high-resolution terrain data produces a more objective and more detailed path alignment plan. This study demon-strates that the presented methodology can be practically applied to support a wind power infrastructure alignment planning process. The six-phase structure of the method-ology allows straightforward incorporation of different optimization objectives. The methodology responds well to combining quantitative and qualitative data. Additional-ly, the careful documentation presents an example of how the methodology can be eval-uated and developed as a business process. This thesis also shows that more emphasis on the research of algorithm-based, more objective methods for the planning of infrastruc-ture alignment is desirable, as technological development has only recently started to realize the potential of these computational methods.Siirretty Doriast

Ensuring health and food safety from rapidly expanding wastewater irrigation in South Asia: BMZ final report 2005-2008

Wastewater irrigation / Institutions / Public health / Health hazards / Diseases / Cropping systems / Vegetables / Fodder / Livestock / Risk assessment / Economic evaluation / Surveys / GIS / Research priorities / South Asia / India / Pakistan / Hyderabad / Faisalabad / Musi River

Wetland Habitat Studies using various Classification Techniques on Multi-Spectral Landsat Imagery: Case study: Tram chim National Park, Dong Thap Vietnam

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial TechnologiesWetland is one of the most valuable ecological systems in nature. Wetland habitat is a set of comprehensive information of wetland distribution, wetland habitat types are essential to wetland management programs. Maps of wetland should provide sufficient detail, retain an appropriate scale and be useful for further mapping and inventory work (Queensland wetland framework). Remotely sensed image classification techniques are useful to detect vegetation patterns and species combination in the inaccessible regions. Automated classification procedures are conducted to save the time of the research. The purpose of the research was to develop a hierarchical classification approach that effectively integrate ancillary information into the classification process and combines ISODATA (iterative self-organizing data analysis techniques algorithm) clustering, Maximum likelihood and rule-based classifier. The main goal was to find out the best possible combination or sequence of classifiers for typically classifying wetland habitat types yields higher accuracy than the existing classified wetland map from Landsat ETM data. Three classification schemes were introduced to delineate the wetland habitat types in the idea of comparison among the methods. The results showed the low accuracy of different classification schemes revealing the fact that image classification is still on the way toward a fine proper procedure to get high accuracy result with limited effort to make the investigation on sites. Even though the motivation of the research was to apply an appropriate procedure with acceptable accuracy of classified map image, the results did not achieve a higher accuracy on knowledge-based classification method as it was expected. The possible reasons are the limitation of the image resolution, the ground truth data requirements, and the difficulties of building the rules based on the spectral characteristics of the objects which contain high mix of spectral similarities

CIRSS vertical data integration, San Bernardino study

The creation and use of a vertically integrated data base, including LANDSAT data, for local planning purposes in a portion of San Bernardino County, California are described. The project illustrates that a vertically integrated approach can benefit local users, can be used to identify and rectify discrepancies in various data sources, and that the LANDSAT component can be effectively used to identify change, perform initial capability/suitability modeling, update existing data, and refine existing data in a geographic information system. Local analyses were developed which produced data of value to planners in the San Bernardino County Planning Department and the San Bernardino National Forest staff

Artificial neural networks to detect forest fire prone areas in the southeast fire district of Mississippi

An analysis of the fire occurrences parameters is essential to save human lives, property, timber resources and conservation of biodiversity. Data conversion formats such as raster to ASCII facilitate the integration of various GIS software’s in the context of RS and GIS modeling. This research explores fire occurrences in relation to human interaction, fuel density interaction, euclidean distance from the perennial streams and slope using artificial neural networks. The human interaction (ignition source) and density of fuels is assessed by Newton’s Gravitational theory. Euclidean distance to perennial streams and slope that do posses a significant role were derived using GIS tools. All the four non linear predictor variables were modeled using the inductive nature of neural networks. The Self organizing feature map (SOM) utilized for fire size risk classification produced an overall classification accuracy of 62% and an overall kappa coefficient of 0.52 that is moderate (fair) for annual fires

Spatial analysis of the preserved wooden architectural remains of eight late Classic Maya salt works in Punta Ycacos Lagoon, Toledo District, Belize

This dissertation examined the remains of wooden architecture at eight Late Classic Maya sites found beneath the surface of Punta Ycacos Lagoon in southern Belize. The presence of briquetage on the surface and embedded among the clusters of wooden architectural features implies association with salt production activity. This research is significant in that the preservation of wooden structures at the salt works has not previously been reported for the ancient Maya. This dissertation includes a detailed discussion of documented evidence of salt production throughout Mesoamerica from archaeological, historical and modern examples. The discussion also addressed the evidence of Maya wooden architecture from archaeological, historical and modern examples with attention to wooden features reported at salt production sites. Additional background discussion includes a description of the physical landscape of the region and study area. The methods used in this dissertation involved specialized strategies adapted from conventional research methods to overcome the challenges of gathering data in the inundated context of Punta Ycacos Lagoon. Additionally, this research involved the post-processing of a large body of survey data to build the project GIS used in the analysis of this study. The results of the study included the discovery of 372 wooden posts as well as scatters of ceramic and lithic artifacts distributed among the eight sites. Analysis of a sample collection of artifacts recovered revealed the presence of Late Classic Maya ceramic types found in association with salt production sites elsewhere. Stone tools made of non-local materials were also present. Analysis of the wooden posts recorded in the field survey, used GIS to compare patterns in the distribution of posts to modern and historical distributions of posts in Maya architectural features discussed during the background portion of the text. The comparison included the use of templates, based on the modern and historical examples, to identify similarities in the post distributions. This research found that there are patterns in post distribution, some of which compare to modern and historical examples of Maya wooden architecture. This study emphasizes that there are rectilinear patterns in the placement of posts. This research demonstrates how GIS analysis offers an effective interactive medium from which to investigate and test patterns in this archaeological dataset. The use of GIS also demonstrated effective in-the-field potential for investigative decision making. The use of GIS in fieldwork may serve to direct efforts in a more effective and efficient manner, maximizing the output of often-limited time in the field. Like many scholars before me, my research combined archaeological field methods and data, ethnographic and ethnohistoric accounts with geographic spatial analysis methods. My research examined the spatial distribution of wooden posts at Late Classic Maya salt workshops with GIS in an attempt to explain what these posts represent in the ancient Maya relationship with the coastal lagoon environment of Punta Ycacos Lagoon. In this analysis my research uses salt production examples from the pan-Maya lowlands and Mesoamerica to look for similarities with documented sources from the greater region. Following in the footsteps of a long history of anthropogeography in the Department of Geography and Anthropology at LSU my dissertation was intended to continue in this tradition under the recently formalized concentration in anthrogeography