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Estimating the Biomass of Waterhyacinth (Eichhornia crassipes) Using the Normalized Difference Vegetation Index Derived from Simulated Landsat 5 TM

机译:使用模拟Landsat 5 TM归一化差异植被指数估算凤眼兰(Eichhornia crassipes)的生物量

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摘要

Waterhyacinth is a free-floating aquatic weed that is considered a nuisance worldwide. Excessive growth of waterhyacinth limits recreational use of water bodies as well as interferes with many ecological processes. Accurate estimates of biomass are useful to assess the effectiveness of control methods to manage this aquatic weed. While large water bodies require significant labor inputs with respect to ground-truth surveys, available technology like remote sensing could be capable of providing temporal and spatial information from a target area at a much reduced cost. Studies were conducted at Lakes Columbus and Aberdeen (Mississippi) during the growing seasons of 2005 and 2006 over established populations of waterhyacinth. The objective was to estimate biomass based on nondestructive methods using the normalized difference vegetation index (NDVI) derived from Landsat 5 TM simulated data. Biomass was collected monthly using a 0.10m(2) quadrat at 25 randomly-located locations at each site. Morphometric plant parameters were also collected to enhance the use of NDVI for biomass estimation. Reflectance measurements using a hyperspectral sensor were taken every month at each site during biomass collection. These spectral signatures were then transformed into a Landsat 5 TM simulated data set using MatLab (R) software. A positive linear relationship (r(2) = 0.28) was found between measured biomass of waterhyacinth and NDVI values from the simulated dataset. While this relationship appears weak, the addition of morphological parameters such as leaf area index (LAI) and leaf length enhanced the relationship yielding an r(2) = 0.66. Empirically, NDVI saturates at high LAI, which may limit its use to estimate the biomass in very dense vegetation. Further studies using NDVI calculated from narrower spectral bands than those contained in Landsat 5 TM are recommended.
机译:凤眼兰是一种自由漂浮的水生杂草,在世界范围内被认为是令人讨厌的事情。凤眼兰的过度生长限制了水体的娱乐利用,并干扰了许多生态过程。准确估算生物量有助于评估控制方法来管理这种水生杂草的有效性。尽管大型水体在实地调查方面需要大量的劳动力投入,但是诸如遥感之类的可用技术可能能够以大大降低的成本提供目标区域的时空信息。在2005年和2006年的生长季节中,对哥伦布湖和阿伯丁(密西西比州)的水葫芦种群进行了研究。目的是使用从Landsat 5 TM模拟数据得出的归一化植被指数(NDVI),基于非破坏性方法估算生物量。在每个站点的25个随机位置,每月使用0.10m(2)正交收集生物量。还收集了形态学植物参数以增强NDVI在生物量估计中的使用。在生物质收集期间,每个地点每个月都要使用高光谱传感器进行反射率测量。然后使用MatLab(R)软件将这些光谱特征转换成Landsat 5 TM模拟数据集。实测风信子的生物量与模拟数据集的NDVI值之间存在正线性关系(r(2)= 0.28)。虽然这种关系似乎很弱,但是添加诸如叶面积指数(LAI)和叶长之类的形态参数会增强该关系,从而得出r(2)= 0.66。根据经验,NDVI在高LAI时会饱和,这可能会限制其在非常茂密的植被中估算生物量的用途。建议使用从比Landsat 5 TM中更窄的光谱带计算的NDVI进行进一步研究。

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