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Detail map with Navarino Island Navarino Island (Spanish: Isla Navarino ) is a large Chilean island, with an area of 2,514 km 2 (971 sq mi) and a coastline of 510 km (320 mi). [ 2 ] It is located between Isla Grande de Tierra del Fuego , to the north, and Cape Horn , to the south.
A major drumlin field extends on both sides of the Strait of Magellan covering the surroundings of Punta Arenas' Carlos Ibáñez del Campo Airport, Isabel Island and an area south of Gente Grande Bay in Tierra del Fuego Island. [39] Land areas around Beagle Channel host also drumlin fields; for example Gable Island and northern Navarino Island.
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Puerto Williams (Spanish: [ˈpweɾto ˈ(ɣ)wiljams]; Spanish for "Port Williams") is a city, port and naval base on Navarino Island in Chile.It faces the Beagle Channel.It is the capital of the Chilean Antarctic Province, one of four provinces in the Magellan and Chilean Antarctica Region, and administers the communes of Chilean Antarctic Territory and Cabo de Hornos.
The tree line is the edge of a habitat at which trees are capable of growing and beyond which they are not. It is found at high elevations and high latitudes. Beyond the tree line, trees cannot tolerate the environmental conditions (usually low temperatures, extreme snowpack, or associated lack of available moisture).
The channel separates the larger main island of Isla Grande de Tierra del Fuego from various smaller islands including the islands of Picton, Lennox and Nueva; Navarino; Hoste; Londonderry; and Stewart. The channel's eastern area forms part of the border between Chile and Argentina and the western area is entirely within Chile.
Flora and Vegetation on the Small Uninhabited Islands of the Marquesas Archipelago (French Polynesia): Relics of Dry Biota Threatened by Biological Invasions" in Larrue, Sébastien , ed. (in English) Biodiversity and Societies in the Pacific Islands (PDF), Aix-Marseille: Presses Universitaires de Provence, p. 150 Retrieved on 24 January 2022.
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.