Tools tagged with "Geostatistics"

This website offers a wide array of tutorials designed to help users effectively utilize QGIS, the free and open-source geographic information system. It covers fundamental GIS concepts, data manipulation, spatial analysis, and advanced mapping techniques. The resource is structured to guide users through various QGIS functionalities with clear, step-by-step instructions.

Statistics Finland offers open geographic data, mainly comprising statistical areas and associated statistical data. This page serves as a central hub for information regarding the contents, interfaces, and implementation instructions for their open geographic data resources. These datasets are an integral part of the national geographic information infrastructure of Finland.

PostGIS is a powerful open-source extension for the PostgreSQL relational database, enabling it to manage and analyze spatial and geographic objects. It provides support for various spatial data types, including points, lines, and polygons, in both 2D and 3D. Users can leverage spatial indexing for efficient data retrieval and a comprehensive suite of spatial functions for advanced analysis and manipulation.

This service provides current, historical, and projected climate data for North America, South America, Europe, and Africa. Users can download interpolated data grids at 1km and 5km resolution or utilize software packages to query specific point locations. The platform also offers numerous derived variables like drought indices and growing degree days.

This open-source software library provides highly efficient and precise capabilities for performing zonal statistics on raster data. It is designed to extract aggregated information from raster datasets based on defined polygonal zones, offering critical functionality for various geospatial analyses.

LOKSTAT is an historical databank of local statistics, offering results from general censuses conducted in Belgium around 1900. It provides consultative access to data from every Belgian municipality existing during that period, including industry, agriculture, and population statistics. This resource is part of the Queteletcentrum at Ghent University.

This online book serves as an introduction to geographic data science using the R programming language. It is designed as a companion for a university module, focusing on core programming, data wrangling, statistical analysis, and machine learning techniques for geographers. The resource emphasizes R's versatility as a free and open-source tool for spatial data processing and geographic information analysis.

Geocomputation with Python is an open-source book designed to teach reproducible geographic data analysis using Python. It provides practical guidance for solving geospatial problems and building advanced applications, emphasizing transparency and accessibility.

Apache Sedona extends existing cluster computing systems like Apache Spark, Apache Flink, and Snowflake. It provides out-of-the-box distributed Spatial Datasets and Spatial SQL for efficiently loading, processing, and analyzing large-scale spatial data across machines. The platform is designed for high-performance geospatial analytics in big data environments.

This platform offers access to statistically downscaled future climate projections, along with data related to bias correction, spatial downscaling, and weather station information. It serves as a resource for researchers and practitioners needing detailed climate data for various analyses and applications.

This resource provides a structured introduction to GIS programming, guiding users through software setup, Python fundamentals, and key geospatial libraries. It covers essential tools for data analysis, visualization, and cloud computing in a geospatial context, making complex topics accessible for learners.

SoilGrids is a comprehensive web portal offering global digital soil maps at a 250-meter resolution. It provides detailed information on various soil properties, derived from a global compilation of soil profile data and environmental layers, making it a valuable resource for environmental analysis.

Loop is an open-source platform for 3D probabilistic geological and geophysical modelling. Initiated by Geoscience Australia and OneGeology, it is funded by various Australian geological surveys, the Australian Research Council, and the MinEx CRC, supporting advanced subsurface analysis.

GeostatsPy is a robust Python package designed for spatial data analytics and geostatistics. It began as a reimplementation of GSLIB (Geostatistical Library) from Fortran to Python, making advanced geostatistical methods accessible. The package now includes numerous additional methods, supporting both 2D and 3D spatial analysis and simulation.

This online book serves as an open educational resource for applied spatial statistics at McMaster University. It was developed by Antonio Paez with support from several contributors and funded by an Open Educational Resources grant. The resource provides a structured course in spatial data analysis and statistics using the R programming language.

This resource offers global datasets quantifying spatial heterogeneity of terrestrial habitats. Utilizing textural features from MODIS Enhanced Vegetation Index (EVI) imagery, it provides 14 distinct metrics at multiple resolutions. These layers are crucial for researchers and modelers focused on biodiversity and ecosystem assessments.

The `landscapemetrics` R package provides a comprehensive collection of landscape metrics designed for analyzing categorical map patterns. It enables researchers and practitioners to quantify various aspects of landscape structure and composition within the R environment, facilitating advanced spatial ecological analysis. This tool is essential for studies in landscape ecology, conservation, and environmental management.

Geographic Information Systems Stack Exchange is a dedicated Q&A platform for professionals and enthusiasts in cartography, geography, and GIS. It serves as a community-driven resource where users can ask questions, share knowledge, and learn from peers about various aspects of geospatial technology and applications.

The Pennsylvania State Data Center (PASDC) serves as the official source of demographic and socioeconomic data for the Commonwealth of Pennsylvania. It partners with the U.S. Census Bureau to provide local access to federal statistics, assisting users with information acquisition, data evaluation, and interpretation.