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Surface segmentation and environment change analysis using band ratio phenology index method – supervised aspect

机译：利用频率比吩咐方法 - 监督方面的表面分割与环境变化分析

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摘要

Remote sensing is an escalating field that helps to monitor the earth in different perspectives like vegetation assessment, coastal studies, global warming analysis etc. Presently many satellites are orbiting the earth for taking multispectral imagery, which is working behind the principle remote sensing applications. Though there are mechanisms for image classification still innovative method is required to detect and monitor the physical characteristics of the environment. Weather forecasting, ecology assessment and irrigation management are relying upon the seasonal changes. This research study concentrates on seasonal change analysis by supervised image classification called Band Ratio Phenology Index (BRPI) method. This BRPI has helped to learn seasonal impact on the environment for the last six years. Confusion Matrix, Overall Accuracy, and Kappa Coefficient are the quality measures used to legitimise the classification exactness.
机译：遥感是一个不断升级的领域，有助于在不同的角度下监视地球，如植被评估，沿海研究，全球变暖分析等。目前，许多卫星是用于采用多光谱图像的地球，这在原理遥感应用后面工作。虽然存在图像分类机制仍然需要创新的方法来检测和监控环境的物理特征。天气预报，生态评估和灌溉管理依赖于季节性变化。本研究研究通过监督图像分类来集中在季节性变化分析，称为带比候选指数（BRPI）方法。该BRPI有助于为过去六年来学习对环境的季节性影响。困惑矩阵，总体精度和κ系数是用于合法化分类精确性的质量措施。

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