Genç Çiğdem Özer, Altunel Arif Oğuz
Forest Engineering, Faculty of Forestry, Kastamonu University, Kastamonu, Türkiye.
Environ Monit Assess. 2025 Jan 2;197(1):120. doi: 10.1007/s10661-024-13526-w.
Revealing the status of forests is important for sustainable forest management. The basis of the concept lies in meeting the needs of future generations and today's generations in the management of forests. The use of remote-sensing (RS) technologies and geographic information systems (GIS) techniques in revealing the current forest structure and in long-term planning of forest areas with multipurpose planning techniques is increasing day by day. Significant technological advances are in allowing programmers to modernize how they manage data. Sentinel-2, which is a relatively new addition to Earth observing satellites, is a new-generation satellite that has enabled classification and monitoring of land cover change with high precision at ease. Visible R, G, B, and near-infrared (NIR) bands have offered exceptional 10-m spatial reasolution, making them suitable for vegetation monitoring along with the additional 20-m bands to spare especially in chlorophyll content analyses. On the contrary, Landsat-8 and ASTER which have been longer lasting in Earth observation were rougher results especially in forestry studies. In this study, Landsat-8 and ASTER satellite images were compared against the Sentinel-2 images as a reference in conjunction with GIS techniques to monitor and assess the impact of various logging procedures, including selective logging and regeneration silviculture. The investigation employed a range of plant vegetation indices, including NDVI, GNDVI, and SAVI, to evaluate the efficacy of image resolution in detecting forest cover changes in the Kastamonu region, where the timber production is the hightest in Turkey. For selective and regeneration activities, satellite images were taken pre-harvesting and immediately post-harvesting, and index maps were produced. NDVI, GNDVI, and SAVI indices were the most accurate indicators of green vegetation change in the Sentinel-2A imagery. Similarly, for the Landsat-8 imagery, the SAVI, NDVI, and GNDVI indices were found to be satisfactory indicators. As for ASTER imagery, the success sequance was like SAVI, GNDVI, and NDVI. Based on the findings of this study, it has been noted that the ASTER imagery closeness to Sentinel-2A was more remarkable in detecting changes in green vegetation in forested areas. The data derived from ASTER imageries demonstrated superior efficacy compared to Landsat-8 in generating forest cover maps, owing to their proximity to those produced by Sentinel-2. The findings also indicated that ASTER imagery, with suitable spatial and spectral resolution, could still be utilized as efficienly as Landsats to generate forest cover density maps and monitor long-term forest conservation practices, particularly in professionally managed forests. Thus, this methodology demonstrated the capacity for efficient worldwide forest management.
揭示森林状况对于可持续森林管理至关重要。这一概念的基础在于在森林管理中满足子孙后代和当代人的需求。遥感（RS）技术和地理信息系统（GIS）技术在揭示当前森林结构以及运用多用途规划技术对林区进行长期规划方面的应用日益增加。重大的技术进步使程序员能够实现数据管理的现代化。哨兵 - 2号是地球观测卫星中的相对新成员，是一颗新一代卫星，能够轻松高精度地对土地覆盖变化进行分类和监测。可见光R、G、B以及近红外（NIR）波段提供了出色的10米空间分辨率，使其适合植被监测，另外还有20米波段，尤其适用于叶绿素含量分析。相反，在地球观测中持续时间更长的陆地卫星8号和高级星载热辐射与反射辐射仪（ASTER）在林业研究中得到的结果更粗糙。在本研究中，结合GIS技术，将陆地卫星8号和ASTER卫星图像与哨兵 - 2号图像作为参考进行比较，以监测和评估包括择伐和更新造林等各种采伐作业的影响。该调查采用了一系列植物植被指数，包括归一化植被指数（NDVI）、绿度归一化植被指数（GNDVI）和土壤调整植被指数（SAVI），以评估图像分辨率在检测土耳其木材产量最高的卡斯塔莫努地区森林覆盖变化方面的效果。对于择伐和更新活动，在采伐前和采伐后立即拍摄卫星图像，并制作指数地图。在哨兵 - 2A图像中，NDVI、GNDVI和SAVI指数是绿色植被变化最准确的指标。同样，对于陆地卫星8号图像，发现SAVI、NDVI和GNDVI指数是令人满意的指标。至于ASTER图像，成功顺序为SAVI、GNDVI和NDVI。基于本研究的结果，已注意到在检测林区绿色植被变化方面，ASTER图像与哨兵 - 2A的相似度更为显著。由于ASTER图像与哨兵 - 2号生成的图像接近，其获取的数据在生成森林覆盖图方面比陆地卫星8号表现出更高的效能。研究结果还表明，具有合适空间和光谱分辨率的ASTER图像在生成森林覆盖密度图和监测长期森林保护实践方面，仍可与陆地卫星一样有效地利用，特别是在专业管理的森林中。因此，这种方法展示了在全球范围内进行高效森林管理的能力。
