Tools for solving common geocaching puzzle types, and other
    Geocaching-related tasks.

Spatio-temporal causal inference based on point process data. 
    You provide the raw data of locations and timings of treatment and 
    outcome events, specify counterfactual scenarios, and the package 
    estimates causal effects over specified spatial and temporal windows.
    See Papadogeorgou, et  al. (2022) <doi:10.1111/rssb.12548>.

Provides functions to apply spatial fuzzy unsupervised classification, visualize and interpret results. This method is well suited when the user wants to analyze data with a fuzzy clustering algorithm and to account for the spatial dimension of the dataset. In addition, indexes for estimating the spatial consistency and classification quality are proposed.
    The methods were originally proposed in the field of brain imagery (seed Cai and al. 2007 <doi:10.1016/j.patcog.2006.07.011> and Zaho and al. 2013 <doi:10.1016/j.dsp.2012.09.016>) and recently applied in geography (see Gelb and Apparicio <doi:10.4000/cybergeo.36414>).

Stores small spatial datasets used to teach basic spatial analysis
    concepts. Datasets are based off of the 'GeoDa' software workbook and data
    site <https://geodacenter.github.io/data-and-lab/> developed by Luc Anselin
    and team at the University of Chicago. Datasets are stored as 'sf' objects.

Functions for downloading of geographic data for use in spatial analysis and mapping. The package facilitates access to climate, crops, elevation, land use, soil, species occurrence, accessibility, administrative boundaries and other data.

The geographic dimension plays a fundamental role in
    multidimensional systems. To define a geographic dimension in a star
    schema, we need a table with attributes corresponding to the levels of
    the dimension. Additionally, we will also need one or more geographic
    layers to represent the data using this dimension. The goal of this
    package is to support the definition of geographic dimensions from
    layers of geographic information related to each other. It makes it
    easy to define relationships between layers and obtain the necessary
    data from them.