В современных условиях экономического развития страны важным фактором является привлечение инвестиций в различные секторы экономики. Одним из таких секторов является земельный рынок, который представляет собой значительный потенциал для инвестирования.

В учебно-методическом пособии описываются основные функции геоинформационной системы Golden Software Surfer 8. Читателям предлагается изучить теоретические моменты, положенные в основу этой системы, и самостоятельно применить их на практике. С помощью этого пособия можно научиться осуществлять переход от неравномерно распределённых данных к цифровым моделям поверхности, производить построение разного вида карт и извлекать из данных дополнительную информацию, не вполне очевидную при визуальном анализе изображений.

The fourth edition of the European Conference on Geostatistics for Environmental Applications (geoENV IV) took place in Barcelona, November 27-29, 2002. As a proof that there is an increasing interest in environmental issues in the geostatistical community, the conference attracted over 100 participants, mostly Europeans (up to 10 European countries were represented), but also from other countries in the world. Only 46 contributions, selected out of around 100 submitted papers, were invited to be presented orally during the conference. Additionally 30 authors were invited to present their work in poster format during a special session.

Modelling and prediction of spatially distributed data such as the secondary cassiterite mineral distributions are often affected by spatial autocorrelation (SAC); a phenomenon that violates attributes data independence in space, which leads to type1 errors in classical statistics and overfitting or underfitting in machine learning (ML) classification respectively. The concept of overfitting and underfitting of spatially distributed datasets in an ML classification has not been properly addressed by the traditional random holdout technique of model validation, and this is a challenge to the assessment of predictive spatial model performance in spatially distributed datasets.

The integration of geology with data science disciplines, such as spatial statistics, remote sensing, and geographic information systems (GIS), has given rise to a shift in many natural sciences schools, pushing the boundaries of knowledge and enabling new discoveries in geological processes and earth systems.

When computers were frst invented in the middle of the last century, nobody ever anticipated that the instruction sets to program them would ultimately evolve to the point where many of them could be accessed freely, without charge, in ways that would become widely available to nonexpert communities. Nor did we ever consider that computers would penetrate every corner of social life, revolutionizing our social behavior, our science, and our politics.

Современные методы 3D моделирования рудных месторождений, дающие количественную оценку пространственной изменчивости границ рудных тел и содержания металлов, необходимы как для принятия решений при освоении и разработке месторождений, так и для технико-экономического обоснования кондиций и утверждения запасов в ГКЗ. Подсчеты запасов, выполненные с помощью традиционных методов оценки, очень трудозатратны и как правило трудно проверяемы. Рассмотренные в статье современные методы компьютерного моделирования, используемые российскими геологами и экспертами ГКЗ, позволяют эффективно и менее трудозатратно получать более достоверные результаты оценки запасов месторождений <...>

QGIS is a crossing point of the free and open source geospatial world. While there are a great many tools in QGIS, it is not one massive application that does everything, and it was never really designed to be that from the beginning. It is rather a visual interface to much of the open source geospatial world. You can load data from proprietary and open formats into spatial databases of various flavors and then analyze the data with well-known analytical backends before creating a printed or web-based map to display and interact with your results. What’s QGIS’s role in all this? It’s the place where you check your data along the way, build and queue the analysis, visualize the results, and develop cartographic end products. This learning path will teach you all that and more, in a hands-on learn-by-doing manner. Become an expert in QGIS with this useful companion. <...>