Cargando…
Calculating the Wasserstein Metric-Based Boltzmann Entropy of a Landscape Mosaic
Shannon entropy is currently the most popular method for quantifying the disorder or information of a spatial data set such as a landscape pattern and a cartographic map. However, its drawback when applied to spatial data is also well documented; it is incapable of capturing configurational disorder...
Autores principales: | Zhang, Hong, Wu, Zhiwei, Lan, Tian, Chen, Yanyu, Gao, Peichao |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7516855/ https://www.ncbi.nlm.nih.gov/pubmed/33286154 http://dx.doi.org/10.3390/e22040381 |
Ejemplares similares
-
belg: A Tool for Calculating Boltzmann Entropy of Landscape Gradients
por: Nowosad, Jakub, et al.
Publicado: (2020) -
Generalizing Boltzmann Configurational Entropy to Surfaces, Point Patterns and Landscape Mosaics
por: Cushman, Samuel A.
Publicado: (2021) -
Exploring Relationships between Boltzmann Entropy of Images and Building Classification Accuracy in Land Cover Mapping
por: Li, Zhipeng, et al.
Publicado: (2023) -
Distributionally robust learning-to-rank under the Wasserstein metric
por: Sotudian, Shahabeddin, et al.
Publicado: (2023) -
Probability Forecast Combination via Entropy Regularized Wasserstein Distance
por: Cumings-Menon, Ryan, et al.
Publicado: (2020)