It uses 'phenological' and productivity-related variables derived from time series of vegetation
indexes, such as the Normalized Difference Vegetation Index, to assess ecosystem dynamics and change, which
eventually might drive to land degradation. The final result of the Land Productivity Dynamics indicator
is a categorical map with 5 classes of land productivity dynamics, ranging from declining to increasing
productivity. See <https://eartharxiv.org/repository/view/2294/> for a description of the methods used in
the package to calculate the indicator.

Nonparametric Smoothing of Laplacian Graph Spectra
A nonparametric method to approximate Laplacian graph spectra of a network with
ordered vertices. This provides a computationally efficient algorithm for obtaining an
accurate and smooth estimate of the graph Laplacian basis. The approximation results can
then be used for tasks like change point detection, k-sample testing, and so on. The
primary reference is Mukhopadhyay, S. and Wang, K. (2018, Technical Report).

LP Nonparametric High Dimension K-Sample Comparison
LP nonparametric high-dimensional K-sample comparison method that includes (i) confirmatory test; (ii) exploratory results and (iii) options to output a data-driven LP-transformed matrix for classification. The primary reference is Mukhopadhyay, S. and Wang, K. (2017, Technical Report).

LP Nonparametric High Dimensional K-Sample Comparison
LP nonparametric high-dimensional K-sample comparison method that includes
(i) confirmatory test, (ii) exploratory analysis, and (iii) options to output a data-driven
LP-transformed matrix for classification.
The primary reference is Mukhopadhyay, S. and Wang, K. (2018, Technical Report).

LP nonparametric high-dimensional K-sample comparison method that includes
(i) confirmatory test, (ii) exploratory analysis, and (iii) options to output a
data-driven LP-transformed matrix for classification. The primary reference is
Mukhopadhyay, S. and Wang, K. (2020, Biometrika); <arXiv:1810.01724>.
R (>= 2.10), apcluster, igraph, mclust, LPGraph