Tesfaw Amare, Teferi Ermias, Senbeta Feyera, Alemu Dawit
Department of Agricultural Economics, College of Agriculture and Natural Resources, Debre Markos University, Debre Markos, P. O. Box 269, Ethiopia.
Center for Environment and Development Studies, Addis Ababa University, Addis Ababa, P. O. Box 1176, Ethiopia.
Heliyon. 2023 Mar 8;9(3):e14393. doi: 10.1016/j.heliyon.2023.e14393. eCollection 2023 Mar.
Fast coppicing plantations like Eucalyptus are becoming an ever increasingly important land use system globally, including the Eucalyptus hotspot highlands of Northwestern Ethiopia. However, comprehensive information regarding species composition is essential for proper planning and policy decisions. The current study mapped the spatial distribution of Eucalyptus globulus (hereafter referred to as Eucalyptus) and identified the key push factors for its expansion. The study used a mapping procedure that uses Landsat imagery together with ground truth data based on supervised training of a pixel-by-pixel classification algorithm within image regions to distinguish areas of Eucalyptus plantations from other classes. High-resolution multispectral and multi-temporal remote-sensing images were combined with ground truth data to produce robust features of Eucalyptus plantation distribution maps. Heckman's Two-Stage econometric model was also employed for determining the major driving factors of Eucalyptus expansion. The results of the mapping algorithm were Eucalyptus plantation distribution maps of 30 × 30 m resolution that showed temporal changes from 1999 to 2021. The findings revealed that Eucalyptus coverage increased by 55% during the period from 1999 to 2010 and the change expressively increased to 69% in 2021 with respect to the reference period. The study also found that a number of push factors influenced the size of land planted with Eucalyptus. The developed maps showing the spatial distribution and expansion of Eucalyptus will help policymakers properly manage the ecosystems and agricultural landscapes of Eucalyptus growing areas.
像桉树这样的速生萌生林种植园在全球范围内正成为越来越重要的土地利用系统，包括埃塞俄比亚西北部的桉树热点高地。然而，有关物种组成的全面信息对于合理规划和政策决策至关重要。本研究绘制了蓝桉（以下简称桉树）的空间分布，并确定了其扩张的关键推动因素。该研究采用了一种制图程序，该程序使用陆地卫星图像以及基于图像区域内逐像素分类算法的监督训练的地面实况数据，以区分桉树林种植区与其他类别。高分辨率多光谱和多时间遥感图像与地面实况数据相结合，以生成桉树林种植分布图的稳健特征。还采用了赫克曼两阶段计量经济模型来确定桉树扩张的主要驱动因素。制图算法的结果是分辨率为30×30米的桉树林种植分布图，显示了1999年至2021年的时间变化。研究结果显示，1999年至2010年期间，桉树覆盖面积增加了55%，与参考期相比，2021年这一变化显著增加到69%。该研究还发现，一些推动因素影响了桉树种植土地的面积。所绘制的显示桉树空间分布和扩张情况的地图将有助于政策制定者妥善管理桉树种植区的生态系统和农业景观。
