Provides a scaling method to obtain a standardized Moran's I measure. Moran's I is a measure for the spatial autocorrelation of a data set, it gives a measure of similarity between data and its surrounding. The range of this value must be [-1,1], but this does not happen in practice. This package scale the Moran's I value and map it into the theoretical range of [-1,1]. Once the Moran's I value is rescaled, it facilitates the comparison between projects, for instance, a researcher can calculate Moran's I in a city in China, with a sample size of n1 and area of interest a1. Another researcher runs a similar experiment in a city in Mexico with different sample size, n2, and an area of interest a2. Due to the differences between the conditions, it is not possible to compare Moran's I in a straightforward way. In this version of the package, the spatial autocorrelation Moran's I is calculated as proposed in Chen(2013) <arXiv:1606.03658>.

Provides examples of code for analyzing data or accomplishing tasks that may be useful to institutional or educational researchers.

Fits a double logistic function to NDVI time series and calculates 
             instantaneous rate of green (IRG) according to methods described
             in Bischoff et al. (2012) <doi:10.1086/667590>.

Provides the dataset and an implementation of the method illustrated in Friel, N., Rastelli, R., Wyse, J. and Raftery, A.E. (2016) <DOI:10.1073/pnas.1606295113>.

Classes and functions for metrics calculation as part of the
             'IRIS DMC MUSTANG' project. The functionality in this package 
             builds upon the base classes of the 'IRISSeismic' package.
             Metrics include basic statistics as well as higher level
             'health' metrics that can help identify problematic seismometers.

Provides classes and methods for seismic data analysis. The
             base classes and methods are inspired by the python code found in
             the 'ObsPy' python toolbox <https://github.com/obspy/obspy>. Additional classes and 
             methods support data returned by web services provided by the 'IRIS DMC'
             <http://service.iris.edu/>.