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Pham, H. N. A., & Triantaphyllou, E. (2008). The Impact of Overfitting and Overgeneraliza-tion on the Classification Accuracy in Data Mining. In O. Maimon, & L. Rokach (Eds.), Soft Computing for Knowledge Discovery and Data Mining (pp. 391-431). Springer.
https://doi.org/10.1007/978-0-387-69935-6_16

has been cited by the following article:

• TITLE: Anthropogenic Threats to Degraded Forest Land in the Savannahs’ Region of Togo from 1984 to 2020, West Africa

  AUTHORS: Kossi Senyo Ehlui, Wouyo Atakpama, Henrik von Wehrden, Alagie Bah, Edinam Kola, Christian Anthony-Krueger, Hodabalo Egbelou, Kokouvi Bruno Kokou, Tchaa Boukpessi

  KEYWORDS: Forest, Degradation, Land Use, Land Cover, Savannahs Region, Togo

  JOURNAL NAME: Journal of Geoscience and Environment Protection, Vol.12 No.1, January 29, 2024

  ABSTRACT: This study focuses on the landscape dynamics of the savannahs’ region in the far north of Togo. Based on a literature review and satellite images analysis using GIS and remote sensing, the study aims to ascertain the effects of anthropogenic threats on the forest coverage of the Savannahs’ Region between 1984 to 2020. The objective is to clarify the dynamics of land use in the region from 1984 to 2000 and from 2000 to 2020. The findings indicate a significant decline in forest coverage within the region from 1984 to 2020, a trend attributed to land use patterns. Dry forests in the Savannah region are largely converted to farmlands, housing, dry savannahs or agroforestry parks, leading to a steady reduction in forest areas.