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Monitoring Narrow Mangrove Stands in Baja California Sur, Mexico Using Linear Spectral Unmixing

机译:监控狭窄的红树林在Baja California Sur,墨西哥使用线性光谱脱离混件

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Small stands of mangrove trees are difficult to detect and monitor using satellite remote sensing because the width of the narrow strips of vegetation are typically much smaller than the spatial resolution of the imagery. Every mangrove pixel also contains water and bare soil reflectance. Linear spectral unmixing, which estimates the fractional presence of specific land cover types per pixel, was performed on Landsat 8 imagery to detect mangroves on the eastern shoreline of the Bay of La Paz on the Baja California Peninsula of Mexico. Low-altitude aerial imagery collected from a DJI Mavic Pro drone was used as ground-reference data in the accuracy assessment. Continuous fractional presence of mangroves was detected with 80% accuracy and 85% of mangrove area was found. Future work will use linear spectral unmixing to systematically monitor mangrove extent and health in the region relative to expected growth in tourism development.[GRAPHICS].
机译:使用卫星遥感难以检测和监测红树丛的小型,因为植被窄条的宽度通常远小于图像的空间分辨率。每个红树林像素也含有水和裸土反射率。线性光谱解密,其估计每像素的特定陆地覆盖类型的分数存在,在Landsat 8图像上进行,以检测在La Paz海湾海岸线上的美洲树木在墨西哥的Baja California半岛的东部海岸线上。从DJI Mavic Pro无人机收集的低空空中图像被用作精度评估中的地基数据。用80%的精度检测到红树林的连续小数,发现85%的红树林。未来的工作将利用线性光谱谱,系统地监测该地区的红树林范围和健康,相对于旅游开发的预期增长。[图形]。

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