[ Evaluation par télédétection des changements d’un couvert forestier de la région forestière de Kisangani ]
Volume 24, Issue 2, June 2016, Pages 255–267
Jean-fiston Mikwa1, Lumbuenamo Raymond2, Anitambua Sungu3, Jean-Marie Kahindo4, and Pierre Defourny5
1 Faculté des Gestions des Ressources Naturelles Renouvelables, Université de Kisangani, BP 2012, Kisangani, RD Congo
2 Faculté des sciences agronomiques, Université de Kinshasa, Kinshasa, RD Congo
3 Unité de recherche en sol et systèmes d’informations spatiales, RUSSIS, Faculté de Gestion des Ressources Naturelles Renouvelables, Université de Kisangani, BP 2012, Kisangani, RD Congo
4 Faculté des sciences, Université de Kisangani, BP 2012, Kisangani, RD Congo
5 Research Unit in Environmental and Geomatics, Université Catholique de Louvain, ENGE, Croix du Sud 2, bte. 1348 Louvain-la-Neuve, Belgium
Original language: French
Copyright © 2016 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
This survey is based on the assessment by remote detection of the deforestation in the forest region of Masako in Kisangani (RDC), it aims to quantify the dynamics of the soil occupation while using the techniques of the cartography by remote detection as well as those of the systems of geographical information. We had used of the Landsat pictures TM p176r060 of January 1990 and March 2001, to make the cartography of the soil occupation, the method of the post-classifications has been used, six classes have been kept in order to apply a SIG under Arcgis 10, The matrix of confusion has been used to validate the results of the classification, the matrix of transition and the yearly rate of deforestation, have been used to quantify the fragmentation of the forest landscape. Of the gotten results, the methods prove that him ya had a change in the occupation of soil of it spaces it of 11 years. So while comparing the gotten results, we noted that the forest landscape is in full change in Kisangani. Fragmentation remains intense for the classes of the dense forests and the secondary drill. The dominant class is the one of the fields and fallows.
Author Keywords: deforestation, remote detection, fragmentation, geographical information system, spatial structure, Masako.
Volume 24, Issue 2, June 2016, Pages 255–267
Jean-fiston Mikwa1, Lumbuenamo Raymond2, Anitambua Sungu3, Jean-Marie Kahindo4, and Pierre Defourny5
1 Faculté des Gestions des Ressources Naturelles Renouvelables, Université de Kisangani, BP 2012, Kisangani, RD Congo
2 Faculté des sciences agronomiques, Université de Kinshasa, Kinshasa, RD Congo
3 Unité de recherche en sol et systèmes d’informations spatiales, RUSSIS, Faculté de Gestion des Ressources Naturelles Renouvelables, Université de Kisangani, BP 2012, Kisangani, RD Congo
4 Faculté des sciences, Université de Kisangani, BP 2012, Kisangani, RD Congo
5 Research Unit in Environmental and Geomatics, Université Catholique de Louvain, ENGE, Croix du Sud 2, bte. 1348 Louvain-la-Neuve, Belgium
Original language: French
Copyright © 2016 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
This survey is based on the assessment by remote detection of the deforestation in the forest region of Masako in Kisangani (RDC), it aims to quantify the dynamics of the soil occupation while using the techniques of the cartography by remote detection as well as those of the systems of geographical information. We had used of the Landsat pictures TM p176r060 of January 1990 and March 2001, to make the cartography of the soil occupation, the method of the post-classifications has been used, six classes have been kept in order to apply a SIG under Arcgis 10, The matrix of confusion has been used to validate the results of the classification, the matrix of transition and the yearly rate of deforestation, have been used to quantify the fragmentation of the forest landscape. Of the gotten results, the methods prove that him ya had a change in the occupation of soil of it spaces it of 11 years. So while comparing the gotten results, we noted that the forest landscape is in full change in Kisangani. Fragmentation remains intense for the classes of the dense forests and the secondary drill. The dominant class is the one of the fields and fallows.
Author Keywords: deforestation, remote detection, fragmentation, geographical information system, spatial structure, Masako.
Abstract: (french)
Cette étude est basée sur l'évaluation par télédétection de la déforestation dans la région forestière de Masako à Kisangani (RDC), elle vise à quantifier la dynamique de l'occupation du sol en utilisant les techniques de la cartographie par télédétection ainsi que celles des systèmes d'informations géographiques. Nous avions utilisé des images Landsat TM p176r060 de Janvier 1990 et de Mars 2001, pour faire la cartographie de l'occupation du sol, la méthode des post-classifications a été utilisée, six classes ont été retenues afin d'appliquer un SIG sous Arcgis 10, La matrice de confusion a été utilisée pour valider les résultats de la classification, la matrice de transition et le taux annuel de déforestation, ont été utilisés pour quantifier la fragmentation du paysage forestier Des résultats obtenus, les méthodes prouvent qu'il y a eu un changement dans l'occupation du sol en l'espace de 11 ans. Ainsi en comparant les résultats obtenus, nous avons constaté que le paysage forestier est en plein changement à Kisangani. La fragmentation reste intense pour les classes des forêts denses et de la forêt secondaire. La classe dominante est celle des champs et jachères.
Author Keywords: déforestation, télédétection, fragmentation, système d'information géographique, structure spatiale, Masako.
How to Cite this Article
Jean-fiston Mikwa, Lumbuenamo Raymond, Anitambua Sungu, Jean-Marie Kahindo, and Pierre Defourny, “Assessment by remote sensing of forest cover change in a forest region of Kisangani,” International Journal of Innovation and Scientific Research, vol. 24, no. 2, pp. 255–267, June 2016.
