利用TDVI监测城市地区生活质量——以卡拉布拉吉市为例

Abhilasha Kumari, Bihar.
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引用次数: 0

摘要

在过去几十年中提出了许多植被指数,使专家们寻找最适合给定遥感应用的植被指数。衡量场所质量(QOP)是一项艰巨的任务,因为它涉及物理和社会经济两个方面。城市植被作为主要的土地利用类型之一,对小区QOP的判断起着重要的作用。社区公园和娱乐场所的数量和质量是社区吸引力的主要决定因素。因此,城市植被覆盖检测一直是城市图像分类技术的重要应用领域之一。Bannari等人(2002)开发的转化差异植被指数(TDVI)在之前的工作中得到了测试,该指数的表现优于NDVI和SAVI。在这项工作中,对TDVI、SAVI和NDVI进行了比较研究,以便从印度遥感卫星(IRS-1D)图像估计城市环境中的植被覆盖。根据实测结果对所得结果进行了验证,表明TDVI是城市环境下植被覆盖监测的良好工具。它不像NDVI或SAVI那样饱和,它作为植被覆盖率的函数表现出良好的线性关系。本文通过分析TDVI在城市图像分类中的性能,对前人的工作进行了补充。结果表明,TDVI在城市图像分类中的表现优于NDVI和SAVI。该指数不仅能较好地区分城市植被覆盖,还能最大限度地减少对城市类目其他未分类像元的分类误差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Monitoring the quality of life in urban area using TDVI- Case study of Kalaburagi city
Many vegetation indices have been proposed over last decades made specialists search for the most suitable vegetation index for a given remote sensing application. Measuring the Quality of Place (QOP) is a hard task since it involves both physical and socio-economic dimensions. Being one of the major land use categories, urban vegetation plays a significant role in one‟s judgment for QOP in a neighborhood. Both quantity and quality of the community parks and recreation areas are major determinants of neighborhood attraction. For these reasons, detection of urban vegetation cover has been one of the important implication areas of urban image classification techniques. “Transformed Difference Vegetation Index (TDVI) developed by Bannari et al. (2002), is tested in a previous work where the index has performed better than NDVI and SAVI. In that work, a comparative study between TDVI, SAVI and NDVI for estimating vegetation cover in urban environment from the Indian Remote Sensing Satellite (IRS-1D) imagery has been conducted. The validation of the obtained results according to the ground truth showed that the TDVI is an excellent tool for vegetation cover monitoring in urban environment. It does not saturate like NDVI or SAVI, it shows an excellent linearity as a function of the rate of vegetation cover. This paper adds on the previous work by analyzing the performance of TDVI in urban image classification. Results indicate that, the performance of TDVI in urban image classification is better than NDVI and SAVI. The new index not only differentiates the urban vegetation cover better but also helps to minimize the error in classifying other unclassified pixels of urban categories.
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