Modeling structural change in spatial system dynamics: A Daisyworld example

System dynamics (SD) is an effective approach for helping reveal the temporal behavior of complex systems. Although there have been recent developments in expanding SD to include systems' spatial dependencies, most applications have been restricted to the simulation of diffusion processes; this is especially true for models on structural change (e.g. LULC modeling). To address this shortcoming, a Python program is proposed to tightly couple SD software to a Geographic Information System (GIS). The approach provides the required capacities for handling bidirectional and synchronized interactions of operations between SD and GIS. In order to illustrate the concept and the techniques proposed for simulating structural changes, a fictitious environment called Daisyworld has been recreated in a spatial system dynamics (SSD) environment. The comparison of spatial and non-spatial simulations emphasizes the importance of considering spatio-temporal feedbacks. Finally, practical applications of structural change models in agriculture and disaster management are proposed

Semantic Array Programming for Environmental Modelling: Application of the Mastrave Library

Environmental datasets grow in size and specialization while models designed for local scale are often unsuitable at regional/continental scale. At regional scale, data are usually available as georeferenced collections of spatially distributed despite semantically atomic information. Complex data intrinsically impose modellers to manipulate nontrivial information structures. For example, multi-dimensional arrays of time series may be composed by slices of raster spatial matrices for each time step, whilst heterogeneous collections of uneven arrays are common when dealing with data analogous to precipitation events, and these structures may ask for integration at several spatial scales, projections and temporal extents. Interestingly, it might be far more difficult to practically implement such a complexity rather than conceptually describe it: a subset of modelling generalizations may deal more with abstraction rather than with the explosion of lines of code. Many environmental modelling algorithms are composed by chains of data-transformations or trees of domain specific sub-algorithms. Concisely expressing them without the need for paying attention on the enormous set of spatio-temporal details, is a highly recommendable practice in both mathematical formulation and implementation. The use of semantic array programming paradigm is here exemplified as a powerful conceptual and practical (with the free software library Mastrave) tool for easing scalability and semantic integration in environmental modelling. Array programming, AP, is widely used for its computational effectiveness but often underexploited in reducing the gap between mathematical notation and algorithm implementations, i.e. by promoting arrays (vectors, matrices, tensors) as atomic quantities with extremely compact manipulating operators. Coherent array-based mathematical description of models can simplify complex algorithm prototyping while moving mathematical reasoning directly into the source code – because of its substantial size reduction – where the mathematical description is actually expressed in a completely formalized and reproducible way. The proposed paradigm suggests to complement the characteristic AP weak typing with semantics, both by composing generalized modular sub-models and via array oriented – thus concise – constraints. The Mastrave library use is exemplified with a regional scale benchmark application to local-average invariant (LAI) downscaling of climate raster data. Unnecessary errors frequently introduced by non-LAI upsampling are shown to be easily detected and removed when the scientific modelling practice is terse enough to let mathematical reasoning and model coding merge together.JRC.H.3-Forest Resources and Climat

Storage and Querying of Large Persistent Arrays

The scientic and analytical applications today are increasingly becoming data in- tensive. Many such applications deal with data that is multidimensional in nature. Traditionally, relational database systems have been used by many data intensive application, and relational paradigm has proved to be both natural and ecient. However, for multidimensional data, when the number of dimensions becomes large, relational databases are inecient both in terms of storage and query response time. In this thesis, we explore linearised storage, and indexed and skiplist based retrieval on persistent arrays. The application programs are provided with a logical view of multidimensional array. The techniques have been implemented in a home-grown database management system called MuBase

Solving the tasks of subsurface resources management in GIS RAPID environment

Purpose. Solving the tasks of subsurface resources management based on the created GIS RAPID geoinformation technology. Methods. Close spatial relationships of lineament network characteristics and earthquake epicenters were detected in 3 seismically active areas located in the mountainous regions of Central Europe. Digital elevation models (DEM) based on ASTER satellite surveys and earthquake epicenter data were used. The nature of spatial relationship of lineament network and vein ore objects was studied in the territory of Congo DR, in the Lake Kivu area using space imagery. Gold ore objects were searched and forecasted in Uzbekistan in the site of Jamansai Mountains. High- resolution imagery from QuickBird 2 satellite, geophysical field surveys, geological and geochemical data were used. Findings. It was found that a significant number of epicenters are located in areas of high concentration of “non-standard” azimuths lineaments – from 27 to 34% of the total number of lineaments. It was revealed that 59.6% of the epicenters are located within 10% of sites with the highest values of complex deformation maps; 50% of the areas with the highest values of these maps contain, on average, 89% of all earthquake epicenters. It was found that satellite image lineament concentration maps with “non-standard” azimuths reflect the spatial relationship with known deposits much better than the concentration map of all lineaments. It was detected that the total area of gold ore objects perspective sites is about 20 km2. Originality. The use of GIS RAPID in a number of earth’s crust areas has allowed to establish new regularities linking the networks of physical field and landscape lineament characteristics with ore bodies and earthquake epicenters localization. Practical implications. A new technology has been developed for solving geological forecasting and prospecting problems. The technology can be used to solve a wide range of practical problems, especially in difficult geological conditions when searching for deep objects weakly presented in external fields and landscape.Мета. Рішення задач надрокористування на базі створеної геоінформаційної технології ГІС РАПІД. Методика. Виявлення тісних просторових взаємозв’язків різноманітних характеристик мереж лінеаментів і епіцентрів землетрусів проводилося у 3 сейсмоактивних ділянках, розташованих в гірських районах Центральної Європи. Використовувалися цифрові моделі рельєфу (DEM), побудовані за зйомками зі супутника ASTER і дані по епіцентрах землетрусів. Дослідження характеру просторового взаємозв’язку мережі лінеаментів і жильних рудних об’єктів проводилися на території Демократичної Республіки Конго, в районі озера Ківу із використанням космічних зйомок. Дослідження пошуку та прогнозу золоторудних об’єктів виконувалися в Узбекистані на ділянці Джамансайскіх гір. Використовувалися високоточні космічні зйомки зі супутника QuickBird 2, зйомки геофізичних полів, геологічні та геохімічні дані. Результати. Виявлено, що значна частина епіцентрів приурочена саме до ділянок підвищеної концентрації лінеаментів “нестандартних” азимутів, складаючи від 27 до 34% загального числа лінеаментів. Встановлено, що 59.6% епіцентрів знаходяться всередині 10% території ділянок, що володіють найвищими значеннями комплексних карт деформацій; 50% території з найвищими значеннями цих карт вміщають, в середньому, 89% усіх епіцентрів землетрусів. Визначено, що карти концентрації лінеаментів космознімків з “нестанартними” азимутами значно краще відображають просторовий взаємозв’язок з відомими родовищами у порівнянні з картою концентрації всіх лінеаментів. Встановлено, що сумарна площа перспективних ділянок золоторудних об’єктів склала близько 20 км2. Наукова новизна. Застосування ГІС РАПІД на ряді ділянок земної кори дозволило встановити нові закономірності, що зв’язують характеристики мережі лінеаментів фізичних полів і ландшафту з локалізацією рудних тіл та епіцентрів землетрусів. Практична значимість. Розроблено нову технологію рішення прогнозних і пошукових геологічних завдань, яка може застосовуватися для вирішення широкого кола практичних задач, особливо у складних геологічних умовах при пошуках глибокозалягаючих об’єктів, що слабо виявляються в зовнішніх полях і ландшафті.Цель. Решения задач недропользования на базе созданной геоинформационной технологии ГИС РАПИД. Методика. Выявление тесных пространственных взаимосвязей разнообразных характеристик сетей линеаментов и эпицентров землетрясений проводилось в 3 сейсмоактивных участках, расположенных в горных районах Центральной Европы. Использовались цифровые модели рельефа (DEM), построенные по съемкам со спутника ASTER, и данные об эпицентрах землетрясений. Исследования характера пространственной взаимосвязи сети линеаментов и жильных рудных объектов проводились на территории Демократической Республики Конго, в районе озера Киву с использованием космических съемок. Исследования поиска и прогноза золоторудных объектов выполнялись в Узбекистане на участке Джамансайских гор. Использовались высокоточные космические съемки со спутника QuickBird 2, съемки геофизических полей, геологические и геохимические данные. Результаты. Выявлено, что значительная часть эпицентров приурочена именно к участкам повышенной концентрации линеаментов “нестандартных” азимутов, составляя от 27 до 34% общего числа линеаментов. Установлено, что 59.6% эпицентров находятся внутри 10% территории участков, обладающих наивысшими значениями комплексных карт деформаций; 50% территории с наивысшими значениями этих карт вмещают, в среднем, 89% всех эпицентров землетрясений. Определено, что карты концентрации линеаментов космоснимков с “нестанартными” азимутами значительно лучше отражают пространственную взаимосвязь с известными месторождениями по сравнению с картой концентрации всех линеаментов. Установлено, что суммарная площадь перспективных участков золоторудных объектов составила около 20 км2. Научная новизна. Применение ГИС РАПИД на ряде участков земной коры позволило установить новые закономерности, связывающие характеристики сети линеаментов физических полей и ландшафта с локализацией рудных тел и эпицентров землетрясений. Практическая значимость. Разработана новая технология решения прогнозных и поисковых геологических задач, которая может применяться для решения широкого круга практических задач, особенно в сложных геологических условиях при поисках глубокозалегающих объектов, слабо проявляющихся во внешних полях и ландшафте.The work is performed as a part of planned research of the geoinformation systems department of the Dnipro University of Technology. The results are obtained without any financial support of grants and research projects. The authors express appreciation to reviewers and editors for their valuable comments, recommendations, and attention to the work

Scalable analysis of multitemporal images using an array database

Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial TechnologiesMassive archives of earth observation data are now available and the size of this data is increasing at a tremendous rate. This data is a very important resource and has a variety of applications including monitoring change, forestry application, agricultural application and urban planning. At the same time, they also possess challenge of storage, management, and high computational needs. In this study SciDB, an array-based database is used to store, manage and process multitemporal satellite imagery. The major aim of this study is to investigate the performance of SciDB based scalable solution to run arithmetic operation, simple time series analysis and complex time series analysis on multitemporal satellite imagery. This study provides better insight of SciDB architecture and provides suggestions for better performance in SciDB for remote sensing jobs. The research also compared the performance of time series analysis on SciDB array with file-based analysis using multicore parallelization (Using „Parallel‟ Package of R). It is found that SciDB provides a faster solution for time series analysis. However, SciDB might not be the best solution if the data size is smaller. Also, relative immaturity of SciDB and limited inherent support of remote sensing operations increases effort for the scientist to develop SciDB based solution. Nevertheless, SciDB has the potential to meet the ever increasing storage, management and computational need of big remote sensing data

Development of Distributed Research Center for analysis of regional climatic and environmental changes

We present an approach and first results of a collaborative project being carried out by a joint team of researchers from the Institute of Monitoring of Climatic and Ecological Systems, Russia and Earth Systems Research Center UNH, USA. Its main objective is development of a hardware and software platform prototype of a Distributed Research Center (DRC) for monitoring and projecting of regional climatic and environmental changes in the Northern extratropical areas. The DRC should provide the specialists working in climate related sciences and decision-makers with accurate and detailed climatic characteristics for the selected area and reliable and affordable tools for their in-depth statistical analysis and studies of the effects of climate change. Within the framework of the project, new approaches to cloud processing and analysis of large geospatial datasets (big geospatial data) inherent to climate change studies are developed and deployed on technical platforms of both institutions. We discuss here the state of the art in this domain, describe web based information-computational systems developed by the partners, justify the methods chosen to reach the project goal, and briefly list the results obtained so far