Monitoring land use changes using geo-information : possibilities, methods and adapted techniques

Monitoring land use with geographical databases is widely used in decision-making. This report presents the possibilities, methods and adapted techniques using geo-information in monitoring land use changes. The municipality of Soest was chosen as study area and three national land use databases, viz. Top10Vector, CBS land use statistics and LGN, were used. The restrictions of geo-information for monitoring land use changes are indicated. New methods and adapted techniques improve the monitoring result considerably. Providers of geo-information, however, should coordinate on update frequencies, semantic content and spatial resolution to allow better possibilities of monitoring land use by combining data sets

Towards safer mining: the role of modelling software to find missing persons after a mine collapse

Purpose. The purpose of the study is to apply science and technology to determine the most likely location of a container in which three miners were trapped after the Lily mine disaster. Following the collapse of the Crown Pillar at Lily Mine in South Africa on the 5th of February 2016, there was a national outcry to find the three miners who were trapped in a surface container lamp room that disappeared in the sinkhole that formed during the surface col-lapse. Methods. At a visit to Lily Mine on the 9th of March, the Witwatersrand Mining Institute suggested a two-way strategy going forward to find the container in which the miners are trapped and buried. The first approach, which is the subject of this paper, is to test temporal 3D modeling software technology to locate the container, and second, to use scientific measurement and testing technologies. The overall methodology used was to first, request academia and research entities within the University to supply the WMI with ideas, which ideas list was compiled as responses came in. These were scrutinized and literature gathered for a conceptual study on which these ideas are likely to work. The software screening and preliminary testing of such software are discussed in this article. Findings. The findings are that software modeling is likely to locate the present position of the container, but accurate data and a combination of different advanced software packages will be required, but at tremendous cost. Originality. This paper presents original work on how software technology can be used to locate missing miners. Practical implications. The two approaches were not likely to recover the miners alive because of the considerable time interval, but will alert the rescue team and mine workers when they come in close proximity to them.Мета. Визначення можливого місця локалізації лампового приміщення контейнера, в якому опинилися три шахтаря після аварії на шахті Лілі (Барбертон, Мпумаланга) методом комп’ютерного моделювання. Після обвалення стельового цілика на шахті Лілі 5 лютого 2016 року почалася національна кампанія з порятунку трьох шахтарів, які залишилися у ламповому приміщенні поверхневого транспортного контейнера, що провалився в утворену після вибуху воронку. Методика. Співробітниками Гірничого Інституту (Уітуотерс) запропонована двостадійна стратегія пошуку контейнера, в якому існує ймовірність знаходження шахтарів. В рамках першого підходу (який розглядається у даній статті) для виявлення контейнера здійснювалось випробування комп’ютерної технології 3D-моделювання в часі. Другий підхід передбачав технологію проведення наукового вимірювання та експерименту. В цілому, методологія включала, насамперед, підключення викладацького та наукового складу університету до вирішення проблеми шляхом комплексної генерації ідей, які були об’єднані в загальний список, вивчені із залученням відповідних літературних джерел, і найбільш реалістичні ідеї були виділені із загального переліку. Дана стаття розглядає результати комп’ютерної експертизи цих ідей та перевірки надійності відповідного програмного забезпечення. Результати. Для зручності моделювання процес обвалення був розділений на три окремі фази: руйнування воронки, руйнування західного схилу та небезпека ковзання на південних схилах. Ідентифіковано програмні технології, які можуть імітувати рух контейнера у перших двох фазах обвалення. В результаті моделювання у програмному забезпеченні ParaView виявлено місце розташування даного контейнера. Виконано аналіз південного схилу за допомогою ArcGIS і складені карти небезпеки схилу для району, а також підземні карти порятунку з маршрутами евакуації. Встановлено, що комп’ютерне моделювання може визначити місцезнаходження контейнера, але для цього потрібні точні вихідні дані й комплекс дорогих високоефективних програмних пакетів. Наукова новизна. Вперше застосовано комплекс комп’ютерних технологій та програмного забезпечення для пошуку зниклих шахтарів після аварійних ситуацій у підземному просторі шахт. Практична значимість. При застосуванні двостадійної стратегії пошуку шахтарів, що опинилися під завалом порід, команда рятувальників отримає сигнал про наближення до їх місцезнаходження.Цель. Определение возможного места локализации лампового помещения контейнера, в котором оказались три шахтера после аварии на шахте Лили (Барбертон, Мпумаланга) методом компьютерного моделирования. После обрушения потолочного целика на шахте Лили 5 февраля 2016 года началась национальная кампания по спасению трех шахтеров, оставшихся в ламповом помещении поверхностного транспортного контейнера, который провалился в воронку, образовавшуюся после взрыва. Методика. Сотрудниками Горного Института (Уитуотерс) предложена двухстадийная стратегия поиска контейнера, в котором существует вероятность нахождения шахтеров. В рамках первого подхода (который рассматривается в данной статье) для обнаружения контейнера производилось испытание компьютерной технологии 3D-моделирования во времени. Второй подход предполагал технологию проведения научного измерения и эксперимента. В целом, методология включала, прежде всего, подключение преподавательского и научного состава университета к решению проблемы путем комплексной генерации идей, которые были объединены в общий список, изучены с привлечением соответствующих литературных источников, и наиболее реалистичные идеи были выделены из общего списка. Настоящая статья рассматривает результаты компьютерной экспертизы данных идей и проверки надежности соответствующего программного обеспечения. Результаты. Для удобства моделирования процесс обрушения был разделен на три отдельные фазы: разрушение воронки, разрушение западного склона и опасность скольжения на южных склонах. Идентифицированы программные технологии, которые могут имитировать движение контейнера в первых двух фазах обрушения. В результате моделирования в программном обеспечении ParaView выявлено местоположение данного контейнера. Выполнен анализа южного склона с помощью ArcGIS и составлены карты опасности склона для района, а также подземные карты спасения с маршрутами эвакуации. Установлено, что компьютерное моделирование может определить местонахождение контейнера, но для этого нужны точные исходные данные и комплекс дорогостоящих высокоэффективных программных пакетов. Научная новизна. Впервые применен комплекс компьютерных технологий и программного обеспечения для поиска пропавших шахтеров после аварийных ситуаций в подземном пространстве шахт. Практическая значимость. При применении двухстадийной стратегии поиска шахтеров, оказавшихся под завалом пород, команда горноспасателей получит сигнал о приближении к их местонахождению.The results of the article were obtained without the support of any of the projects or funding

Component Segmentation of Engineering Drawings Using Graph Convolutional Networks

We present a data-driven framework to automate the vectorization and machine interpretation of 2D engineering part drawings. In industrial settings, most manufacturing engineers still rely on manual reads to identify the topological and manufacturing requirements from drawings submitted by designers. The interpretation process is laborious and time-consuming, which severely inhibits the efficiency of part quotation and manufacturing tasks. While recent advances in image-based computer vision methods have demonstrated great potential in interpreting natural images through semantic segmentation approaches, the application of such methods in parsing engineering technical drawings into semantically accurate components remains a significant challenge. The severe pixel sparsity in engineering drawings also restricts the effective featurization of image-based data-driven methods. To overcome these challenges, we propose a deep learning based framework that predicts the semantic type of each vectorized component. Taking a raster image as input, we vectorize all components through thinning, stroke tracing, and cubic bezier fitting. Then a graph of such components is generated based on the connectivity between the components. Finally, a graph convolutional neural network is trained on this graph data to identify the semantic type of each component. We test our framework in the context of semantic segmentation of text, dimension and, contour components in engineering drawings. Results show that our method yields the best performance compared to recent image, and graph-based segmentation methods.Comment: Preprint accepted to Computers in Industr

Mining climate data for shire level wheat yield predictions in Western Australia

Climate change and the reduction of available agricultural land are two of the most important factors that affect global food production especially in terms of wheat stores. An ever increasing world population places a huge demand on these resources. Consequently, there is a dire need to optimise food production. Estimations of crop yield for the South West agricultural region of Western Australia have usually been based on statistical analyses by the Department of Agriculture and Food in Western Australia. Their estimations involve a system of crop planting recommendations and yield prediction tools based on crop variety trials. However, many crop failures arise from adherence to these crop recommendations by farmers that were contrary to the reported estimations. Consequently, the Department has sought to investigate new avenues for analyses that improve their estimations and recommendations. This thesis explores a new approach in the way analyses are carried out. This is done through the introduction of new methods of analyses such as data mining and online analytical processing in the strategy. Additionally, this research attempts to provide a better understanding of the effects of both gradual variation parameters such as soil type, and continuous variation parameters such as rainfall and temperature, on the wheat yields. The ultimate aim of the research is to enhance the prediction efficiency of wheat yields. The task was formidable due to the complex and dichotomous mixture of gradual and continuous variability data that required successive information transformations. It necessitated the progressive moulding of the data into useful information, practical knowledge and effective industry practices. Ultimately, this new direction is to improve the crop predictions and to thereby reduce crop failures. The research journey involved data exploration, grappling with the complexity of Geographic Information System (GIS), discovering and learning data compatible software tools, and forging an effective processing method through an iterative cycle of action research experimentation. A series of trials was conducted to determine the combined effects of rainfall and temperature variations on wheat crop yields. These experiments specifically related to the South Western Agricultural region of Western Australia. The study focused on wheat producing shires within the study area. The investigations involved a combination of macro and micro analyses techniques for visual data mining and data mining classification techniques, respectively. The research activities revealed that wheat yield was most dependent upon rainfall and temperature. In addition, it showed that rainfall cyclically affected the temperature and soil type due to the moisture retention of crop growing locations. Results from the regression analyses, showed that the statistical prediction of wheat yields from historical data, may be enhanced by data mining techniques including classification. The main contribution to knowledge as a consequence of this research was the provision of an alternate and supplementary method of wheat crop prediction within the study area. Another contribution was the division of the study area into a GIS surface grid of 100 hectare cells upon which the interpolated data was projected. Furthermore, the proposed framework within this thesis offers other researchers, with similarly structured complex data, the benefits of a general processing pathway to enable them to navigate their own investigations through variegated analytical exploration spaces. In addition, it offers insights and suggestions for future directions in other contextual research explorations

Complexity in action: Untangling latent relationships between land quality, economic structures and socio-spatial patterns in Italy

Land quality, a key economic capital supporting local development, is affected by biophysical and anthropogenic factors. Taken as a relevant attribute of economic systems, land quality has shaped the territorial organization of any given region influencing localization of agriculture, industry and settlements. In regions with long-established human-landscape interactions, such as the Mediterranean basin, land quality has determined social disparities and polarization in the use of land, reflecting the action of geographical gradients based on elevation and population density. The present study investigates latent relationships within a large set of indicators profiling local communities and land quality on a fine-grained resolution scale in Italy with the aim to assess the potential impact of land quality on the regional socioeconomic structure. The importance of land quality gradients in the socioeconomic configuration of urban and rural regions was verified analyzing the distribution of 149 socioeconomic and environmental indicators organized in 5 themes and 17 research dimensions. Agriculture, income, education and labour market variables discriminate areas with high land quality from areas with low land quality. While differential land quality in peri-urban areas may reflect conflicts between competing actors, moderate (or low) quality of land in rural districts is associated with depopulation, land abandonment, subsidence agriculture, unemployment and low educational levels. We conclude that the socioeconomic profile of local communities has been influenced by land quality in a different way along urban-rural gradients. Policies integrating environmental and socioeconomic measures are required to consider land quality as a pivotal target for sustainable development. Regional planning will benefit from an in-depth understanding of place-specific relationships between local communities and the environment