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Congo Basin Forest Types: A Detailed Cartographic Analysis

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Manage episode 474675857 series 3382423
Inhalt bereitgestellt von Florence Mak.. Alle Podcast-Inhalte, einschließlich Episoden, Grafiken und Podcast-Beschreibungen, werden direkt von Florence Mak. oder seinem Podcast-Plattformpartner hochgeladen und bereitgestellt. Wenn Sie glauben, dass jemand Ihr urheberrechtlich geschütztes Werk ohne Ihre Erlaubnis nutzt, können Sie dem hier beschriebenen Verfahren folgen https://de.player.fm/legal.

This document explores in the provided source is the detailed mapping of forest formations in the #Congo #Basin using optical remote sensing data from Sentinel-2 satellites. This research is situated within an international context where the sustainable management of #equatorial #forests is a major concern, particularly given the limited understanding of these complex ecosystems. The study focuses on the forest concessions of the Congolaise Industrielle des Bois (CIB) in the Ouesso region of the Republic of the Congo.

The methodology employed combines two main phases: a field mission and image processing to generate cartographic products. The field mission, conducted in collaboration with the CIB, aimed to describe different forest types, develop a visual interpretation key for satellite images, and acquire validation data for classification. The image processing phase involved the extraction and calculation of various metrics from atmospherically corrected Sentinel-2 images, including reflectances, vegetation indices, and textures. Different combinations of these metrics were used to perform various classifications, and the results were analyzed to highlight the relevance of each metric.

This study is relevant in the international context of forest management in the Congo Basin. The work aligns with the objectives of the Observatoire des forêts d’Afrique centrale (OFAC), which aims to provide updated and relevant data on the forests and ecosystems of the region to inform political decision-making and promote better governance and sustainability of natural resource management. The Université catholique de Louvain (#UCLouvain) is part of the scientific consortium implementing these activities. The research aims to develop a method for visual recognition of forest types using data from the Copernicus program's #Sentinel2 spatial platforms.

The thesis specifically mentions using multispectral data provided by the recently launched Sentinel-2 A and B satellites of the European Space Agency. The research area is located in the north of the Republic of the Congo, in the Ouesso region, within the forest concessions of the Congolaise Industrielle des Bois (CIB-OLAM). The study acknowledges the international importance of sustainable management of equatorial forests, which relies on a limited knowledge base of these ecosystems.

The research leverages Sentinel-2 satellite imagery and a combined field-based and digital analysis approach to achieve detailed mapping of forest types in a key area of the #CongoBasin #rainforest, addressing the critical need for improved ecological understanding to support sustainable forest management in the region.

  continue reading

49 Episoden

Artwork
iconTeilen
 
Manage episode 474675857 series 3382423
Inhalt bereitgestellt von Florence Mak.. Alle Podcast-Inhalte, einschließlich Episoden, Grafiken und Podcast-Beschreibungen, werden direkt von Florence Mak. oder seinem Podcast-Plattformpartner hochgeladen und bereitgestellt. Wenn Sie glauben, dass jemand Ihr urheberrechtlich geschütztes Werk ohne Ihre Erlaubnis nutzt, können Sie dem hier beschriebenen Verfahren folgen https://de.player.fm/legal.

This document explores in the provided source is the detailed mapping of forest formations in the #Congo #Basin using optical remote sensing data from Sentinel-2 satellites. This research is situated within an international context where the sustainable management of #equatorial #forests is a major concern, particularly given the limited understanding of these complex ecosystems. The study focuses on the forest concessions of the Congolaise Industrielle des Bois (CIB) in the Ouesso region of the Republic of the Congo.

The methodology employed combines two main phases: a field mission and image processing to generate cartographic products. The field mission, conducted in collaboration with the CIB, aimed to describe different forest types, develop a visual interpretation key for satellite images, and acquire validation data for classification. The image processing phase involved the extraction and calculation of various metrics from atmospherically corrected Sentinel-2 images, including reflectances, vegetation indices, and textures. Different combinations of these metrics were used to perform various classifications, and the results were analyzed to highlight the relevance of each metric.

This study is relevant in the international context of forest management in the Congo Basin. The work aligns with the objectives of the Observatoire des forêts d’Afrique centrale (OFAC), which aims to provide updated and relevant data on the forests and ecosystems of the region to inform political decision-making and promote better governance and sustainability of natural resource management. The Université catholique de Louvain (#UCLouvain) is part of the scientific consortium implementing these activities. The research aims to develop a method for visual recognition of forest types using data from the Copernicus program's #Sentinel2 spatial platforms.

The thesis specifically mentions using multispectral data provided by the recently launched Sentinel-2 A and B satellites of the European Space Agency. The research area is located in the north of the Republic of the Congo, in the Ouesso region, within the forest concessions of the Congolaise Industrielle des Bois (CIB-OLAM). The study acknowledges the international importance of sustainable management of equatorial forests, which relies on a limited knowledge base of these ecosystems.

The research leverages Sentinel-2 satellite imagery and a combined field-based and digital analysis approach to achieve detailed mapping of forest types in a key area of the #CongoBasin #rainforest, addressing the critical need for improved ecological understanding to support sustainable forest management in the region.

  continue reading

49 Episoden

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