| Autor: |
Zekeng, Jules Christian, Sebego, Reuben, Mphinyane, Wanda N., Mpalo, Morati, Nayak, Dileswar, Fobane, Jean Louis, Onana, Jean Michel, Funwi, Forbi Preasious, Mbolo, Marguerite Marie Abada |
| Zdroj: |
Modeling Earth Systems and Environment; December 2019, Vol. 5 Issue: 4 p1801-1814, 14p |
| Abstrakt: |
Large-scale identification of land use and land cover change in a tropical forest is a challenge to landscape designers and forest ecologists. Here, Landsat images acquired during the years 2000, 2009, and 2018 were used to assess the spatial-dynamics of land use and land cover (LULC) during the last two decades (2000–2018). A classification system composed of six classes—dense forest with (high tree density and low tree density), swampy Raphia forest, swampy flooded forest and savanna were designed as LULC for this study. A maximum likelihood classification was used to classify Landsat images into thematic areas. Elsewhere, Landsat-based LULC mapping, post classification at the per-pixel scales and self-knowledge on the land cover change processes were combined to analyze LULC change, forest loss and change trajectories in Doume Communal Forest in eastern Cameroon. The results show that half of the study area changed in 2000–2009 and that the different types of LULC changes increased and involved more diverse and characteristic trajectories in 2009–2018 compared to 2000–2009. Degradation to a dense forest with low tree density and swampy Raphia forest was dominant, and the forest was mostly lost due to trajectories that involved conversion to agroforestry systems (10%), and a lesser extent due to trajectories that involved deforestation to grasslands (7%). The trajectory analyses did thus contribute to a more comprehensive analysis of LULC change and the drivers of forest loss and, therefore, is essential to improve the sustainable management and support spatial planning of the forest. |
| Databáze: |
Supplemental Index |
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