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ESMF increases the interoperability of Earth-science modeling software developed at different sites and promotes code reuse.The idea is to transform distributed, specialized knowledge and resources into a collaborative, integrated modeling community that operates more efficiently, can address a wider variety of problems more effectively, and is more responsive to societal needs.
A supervised classification is a system of classification in which the user builds a series of randomly generated training datasets or spectral signatures representing different land-use and land-cover (LULC) classes and applies these datasets in machine learning models to predict and spatially classify LULC patterns and evaluate classification accuracies.
GCMs also began to incorporate more earth systems and feedback mechanisms, transforming themselves into coupled Earth Systems Models. The inclusion of elements from the cryosphere, carbon cycle and cloud feedbacks was both facilitated and constrained by growth in computing power. [1]
The Community Earth System Model (CESM) is a fully coupled numerical simulation of the Earth system consisting of atmospheric, ocean, ice, land surface, carbon cycle, and other components. CESM includes a climate model providing state-of-art simulations of the Earth's past, present, and future. [ 1 ]
Unsupervised classification (also known as clustering) is a method of partitioning remote sensor image data in multispectral feature space and extracting land-cover information. Unsupervised classification require less input information from the analyst compared to supervised classification because clustering does not require training data.
In the theory of cluster analysis, the nearest-neighbor chain algorithm is an algorithm that can speed up several methods for agglomerative hierarchical clustering.These are methods that take a collection of points as input, and create a hierarchy of clusters of points by repeatedly merging pairs of smaller clusters to form larger clusters.
In information science and ontology, a classification scheme is an arrangement of classes or groups of classes. The activity of developing the schemes bears similarity to taxonomy, but with perhaps a more theoretical bent, as a single classification scheme can be applied over a wide semantic spectrum while taxonomies tend to be devoted to a single topic.
The term "The Local Group" was introduced by Edwin Hubble in Chapter VI of his 1936 book The Realm of the Nebulae. [11] There, he described it as "a typical small group of nebulae which is isolated in the general field" and delineated, by decreasing luminosity, its members to be M31, Milky Way, M33, Large Magellanic Cloud, Small Magellanic Cloud, M32, NGC 205, NGC 6822, NGC 185, IC 1613 and ...