Predictive mapping of aquatic ecosystems by means of support vector machines and random forests

Author:

Martínez-Santos P.,Aristizábal H.F.,Díaz-Alcaide S.,Gómez-Escalonilla V.

Funder

Government of Spain Ministry of Science and Innovation

Publisher

Elsevier BV

Subject

Water Science and Technology

Reference56 articles.

1. AETG (2012). Aquatic Ecosystems Toolkit. Module 1: Aquatic Ecosystems Toolkit Guidance Paper. Aquatic Ecosystems Task Group. Australian Government Department of Sustainability, Environment, Water, Population and Communities, Canberra.

2. Allen GH, Pavelsky TM (2018). Global extent of rivers and streams. Science 361, 585–588.

3. The use of support vectors from support vector machines for hydrometeorologic monitoring network analyses;Asquith;J. Hydrol.,2020

4. Berhane TM, Lane CR, Wu Q, Autrey BC, Anenkhonov OA, Chepinoga VV, Liu H (2018). Comparing Pixel- and Object-Based Approaches in Effectively Classifying Wetland-Dominated Landscapes. Remote Sens 10(1)46. DOI:10.3390/rs10010046.

5. Analysis of a Random Forests Model;Biau;J. Mach. Learn. Res.,2012

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