卫星图像处理生物量估算

A. Mummoorthy, R. Chandrika, N. Ganesh, E. Pavithra
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引用次数: 1

摘要

在这个项目中,我们的主要目的是利用卫星图像处理技术估计生物量。首先,我们需要确定我们的研究区域,并收集地面数据。然后计算熵值,估算生物量。然后从LandSat TM或EnviSat获取卫星图像并对图像进行预处理。精确几何预处理和大气定标是图像预处理的两个重要方面。预处理完成后,对图像进行处理,建立不同的生物量模型,如异速生长方程、回归模型、地统计模型、非参数模型等。这些技术中的任何一种都可以使用。多元回归分析是最常用的方法。对于我们项目中的研究区域,我们将从Vellore区域开始,并使用该区域的遥感数据。几何校正和斑点减少可以用来改善我们所拍摄的图像。然后我们有增强ETM数据和过滤ASAR。然后,我们直观地解释给定的图像,并确定生物量含量的可能位置。然后使用上述各种模型确定体积方程。在此之后,我们可以使用我们手头的方程来计算支架体积。最后一步是计算平均生物量。一旦计算出来,我们项目的主要目标就实现了。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Satellite Image processing Biomass Estimation
In this project our main aim is the estimation of biomass using satellite image processing techniques. Firstly, we need to identify our study area and gather the ground data. After that calculate the entropy values and estimate the biomass. Then take the Satellite Images from either the LandSat TM or EnviSat and pre-process the image. Accurate Geometric Preprocessing and Atmospheric calibration are two important aspects in image pre-processing. After the preprocessing has been done then process the image and develop the different biomass models, like the allometric equations, regression models, geostatistical models, Non-parametric models, etc. Any one of these techniques can be used. The Multiple Regression Analysis is the most often used approach. For the study area in our project we shall proceed with the Vellore area and use the remote sensing data for the same. Geometric Correction and Speckle reduction can be used to improve the image we have taken. Then we have the Enhanced ETM data and filtered ASAR. Then we visually interpret the given image and identify the possible locations of biomass content. Then the volumetric equations are identified using various models as described above. After this we can calculate the Stand Volume using the equations we have at hand. The final step involves the calculation of Mean Biomass. Once this is calculated the main aim of our project is fulfilled.
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