ABSTRACT

The adoption of remotely sensed data in forest applications has grown significantly. Whereas high spatial resolution sensors have been successful in mapping and monitoring commercial forests, their cost, accessibility, and spatial coverage remain a critical challenge. Hence, it is was necessary to investigate the value of new and improved freely available sensors in forest species mapping using the Partial Least Square-Discriminant Analysis (PLS-DA). This study evaluated the performance of new freely available and improved raw and pan-sharpened Landsat 8 Operational Land Imager (OLI) imagery in discriminating seven key plantation forest species in KwaZulu-Natal, South Africa. Accuracies achieved using the Landsat (OLI) imagery were benchmarked against the WorldView-2 imagery. Results show that raw and pan-sharpened bands successfully delineated commercial forest species, with overall classification accuracies of 79% and 77.8%, respectively. Although these accuracies were lower than the 86.5% achieved from the higher resolution Worldview-2 image data, our findings demonstrate that the Landsat 8 OLI’s lower spatial resolution (30 m) generated a plausible performance in discriminating forest species. Hence, Landsat 8 OLI could be useful in providing existing and historical preliminary forestry assessment due to its free availability, wide spatial coverage as well as its rich archive dating back to the 1970s.

摘要

遥感数据在森林应用中的采用显着增长。尽管高空间分辨率传感器在测绘和监测商品林方面取得了成功，但其成本、可达性和空间覆盖范围仍然是一个关键挑战。因此，有必要使用偏最小二乘判别分析 (PLS-DA) 研究新的和改进的免费传感器在森林物种绘图中的价值。本研究评估了新的免费可用和改进的原始和全色锐化 Landsat 8 操作土地成像仪 (OLI) 图像在区分南非夸祖鲁-纳塔尔省七种主要人工林森林物种方面的性能。使用 Landsat (OLI) 影像获得的精度与 WorldView-2 影像进行了基准测试。结果表明，原始和泛锐化带成功地描绘了商业林物种，总体分类准确率分别为 79% 和 77.8%。尽管这些精度低于更高分辨率 Worldview-2 图像数据所达到的 86.5%，但我们的研究结果表明，Landsat 8 OLI 的较低空间分辨率（30 m）在区分森林物种方面产生了合理的性能。因此，Landsat 8 OLI 可用于提供现有和历史初步林业评估，因为它可以免费使用、空间覆盖范围广以及可追溯到 1970 年代的丰富档案。我们的研究结果表明，Landsat 8 OLI 的较低空间分辨率 (30 m) 在区分森林物种方面产生了合理的性能。因此，Landsat 8 OLI 可用于提供现有和历史初步林业评估，因为它可以免费使用、空间覆盖范围广以及可追溯到 1970 年代的丰富档案。我们的研究结果表明，Landsat 8 OLI 的较低空间分辨率 (30 m) 在区分森林物种方面产生了合理的性能。因此，Landsat 8 OLI 可用于提供现有和历史初步林业评估，因为它可以免费使用、空间覆盖范围广以及可追溯到 1970 年代的丰富档案。