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MAPPING INVASIVE AQUATIC VEGETATION IN THE SACRAMENTO-SAN JOAQUIN DELTA USING HYPERSPECTRAL IMAGERY

机译:利用高光谱成像技术在萨克拉曼多-圣华金河三角洲进行侵入性水生植被测绘

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摘要

The ecological and economic impacts associated with invasive species are of critical concern to land managers. The ability to map the extent and severity of invasions would be a valuable contribution to management decisions relating to control and monitoring efforts. We investigated the use of hyperspectral imagery for mapping invasive aquatic plant species in the Sacramento-San Joaquin Delta in the Central Valley of California, at two spatial scales. Sixty-four flightlines of HyMap hyperspectral imagery were acquired over the study region covering an area of 2,139 km~2 and field work was conducted to acquire GPS locations of target invasive species. We used spectral mixture analysis to classify two target invasive species; Brazilian waterweed (Egeria densa), a submerged invasive, and water hyacinth (Eichhornia crassipes), a floating emergent invasive. At the relatively fine spatial scale for five sites within the Delta (average size 51 ha) average classification accuracies were 93% for Brazilian waterweed and 73% for water hyacinth. However, at the coarser, Delta-wide scale (177,000 ha) these accuracy results were 29% for Brazilian waterweed and 65% for water hyacinth. The difference in accuracy is likely accounted for by the broad range in water turbidity and tide heights encountered across the Delta. These findings illustrate that hyperspectral imagery is a promising tool for discriminating target invasive species within the Sacramento-San Joaquin Delta waterways although more work is needed to develop classification tools that function under changing environmental conditions.
机译:与入侵物种有关的生态和经济影响是土地管理者极为关注的问题。绘制入侵程度和严重程度的图谱,将对与控制和监视工作有关的管理决策做出宝贵的贡献。我们调查了在两个空间尺度上利用高光谱图像在加利福尼亚州中央山谷的萨克拉曼多-圣华金河三角洲绘制入侵水生植物物种的地图。在研究区域内采集了24条HyMap高光谱图像的飞行路线,覆盖了2139 km〜2,并进行了野外工作以获取目标入侵物种的GPS位置。我们使用光谱混合分析对两个目标入侵物种进行了分类。巴西水草(Egeria densa)是一种浸润性入侵,而水葫芦(Eichhornia crassipes)是一种浮游性入侵性。在三角洲内五个地点的相对精细的空间尺度上(平均大小为51公顷),巴西水草的平均分类准确度为93%,水葫芦的平均分类准确度为73%。但是,在较粗糙的三角洲范围内(177,000公顷),巴西水草的准确度结果为29%,水葫芦的准确度结果为65%。精度上的差异很可能是由于整个三角洲的水浊度和潮汐高度范围较大所致。这些发现表明,高光谱成像是一种在萨克拉曼多-圣华金河三角洲水道内区分目标入侵物种的有前途的工具,尽管需要开展更多工作来开发在变化的环境条件下起作用的分类工具。

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