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.

中文翻译：

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使用带比率物候指数法进行表面分割和环境变化分析–受监督的方面

遥感是一个不断发展的领域，有助于从不同角度监测地球，例如植被评估，海岸研究，全球变暖分析等。目前，许多卫星绕地球轨道运行以获取多光谱图像，这是遥感应用的主要原理。尽管存在用于图像分类的机制，但是仍需要创新的方法来检测和监视环境的物理特征。天气预报，生态评估和灌溉管理依靠季节变化。本研究致力于通过被称为带比率物候指数（BRPI）方法的监督图像分类对季节变化进行分析。在过去六年中，该BRPI帮助了解了对环境的季节性影响。混淆矩阵，总体准确度，