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The classification of late seral forests in the Pacific Northwest, USA using Landsat ETM+ imagery

机译:利用Landsat ETM +影像对美国西北太平洋地区晚期的针叶林进行分类

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To conserve the Earth's most extraordinary expressions of temperate biodiversity in the Pacific Northwest (PNW), USA, the mapping of late seral (old and mature) conifer forests plays a critical role. For this paper, we define old conifer forests as >150 years and mature conifer forest between 50 and 150 years. We offer a new Optimal Iterative Unsupervised Classification (OIUC) procedure for mapping late seral conifer forests over an eight-ecoregion area. The key steps of the OIUC classification were: (1) fully using the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) 15m panchromatic channel merged with other 30 m bands 3 and 5 to make a pan-sharpened false color composite for high resolution image interpretation; (2) splitting the ETM+ scene by ecologically distinct areas, or ecoregions, to create relatively homologous images for classification; (3) using a procedure similar to cluster busting where multiple iterative manipulation of the ISODATA clusters was employed; and (4) edge matching of sub-scenes to form ecoregions, then later merged together to form a map for the entire PNW, Supporting data and information included ancillary spatial GIS data layers, aerial photos, Digital Ortho Quad images (DOQs), field investigations, and previously reported forest age results. Classification accuracy was assessed using 2081 stratified random locations on 105 individual DOQs covering the entire region. Approximately 4.7 million ha (~ 19%) of the PNW was classified as old conifer forest (>150 years). Another 4.8 million ha (~ 19%) was classified as mature conifer forest (50-150 years). Over 9.48 million ha (~ 38%) of the PNW was late seral conifer forest, The extent of late seral forests (old and mature conifer cover classes) varied greatly between the eight ecoregions. The Central and Southern Cascades and Klamath-Siskiyou ecoregions contained the highest amount of late seral forest in the region. The results showed high accuracy of the late seral forest classification for the PNW with an overall accuracy of 90.72% and KAPPA test K value 0.8534. Producer's (Omission) accuracy for old and mature forests were 91.36% and 80.40%, User's (Commission) accuracy were 89.42% and 80.59%, respectively. Accuracy levels differed for the different ecoregions examined. In general, mature conifer forests exhibited higher levels of confusion than did old conifer forests, due to the spectral influences of high-density young conifer stands and terrain shadow effects. The results fill an important data gap needed for ongoing conservation planning purposes throughout the region. We found that for relatively large geographic areas the OIUC method is an efficient and cost-effective alternative that yields high quality results.
机译:为了保护美国西北太平洋地区(PNW)地球上最温和的生物多样性表现形式,晚浆叶(旧的和成熟的)针叶林的制图起着至关重要的作用。在本文中,我们将旧的针叶林定义为> 150年,将成熟的针叶林定义为50至150年。我们提供了一个新的最优迭代无监督分类(OIUC)程序,用于在8个生态区域内绘制晚期针叶树针叶林。 OIUC分类的关键步骤是:(1)充分使用Landsat 7增强型主题映射器Plus(ETM +)15m全色通道与其他30 m波段3和5合并,以形成用于高分辨率图像解释的泛锐假色合成; (2)按生态上不同的区域或生态区域划分ETM +场景,以创建相对同源的图像进行分类; (3)使用类似于群集破坏的过程,其中对ISODATA群集进行了多次迭代操作; (4)子场景的边缘匹配以形成生态区,然后合并在一起以形成整个PNW的地图。支持的数据和信息包括辅助空间GIS数据层,航拍照片,数字正交四边形图像(DOQ),野外调查,以及先前报告的森林年龄结果。使用覆盖整个区域的105个独立DOQ上的2081个分层随机位置来评估分类准确性。大约470万公顷(约19%)的西北太平洋地区被归类为旧针叶林(> 150年)。另有480万公顷(〜19%)被归类为成熟的针叶林(50-150年)。西北太平洋超过948万公顷(〜38%)是晚浆叶针叶林。八个生态区之间晚浆叶林的范围(老针叶树和成熟针叶树覆盖等级)差异很大。中部和南部小瀑布以及克拉马斯-西斯基尤(Klamath-Siskiyou)生态区包含该地区晚期丝叶林数量最多。结果表明,PNW的晚浆叶林分类具有很高的准确性,总体准确性为90.72%,KAPPA测试K值为0.8534。老森林和成熟森林的生产者(遗漏)准确度分别为91.36%和80.40%,用户(委员会)准确度分别为89.42%和80.59%。所检查的不同生态区域的准确度水平有所不同。通常,由于高密度针叶林林分的光谱影响和地形阴影效应,成熟的针叶林比老针叶林表现出更高的混乱程度。结果填补了整个地区正在进行的保护规划目的所需的重要数据缺口。我们发现,对于较大的地理区域,OIUC方法是一种可产生高质量结果的有效且具有成本效益的替代方法。

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