应用Landsat8数据改进FCD模型方法

基金项目:
河南省基础与前沿技术研究项目"缺资料地区小流域山洪灾害预警及评估研究"

河南省农业气象保障与应用技术重点实验室开放基金项目"基于多源遥感的冬小麦全生育期墒情监测"

详细信息

刊出日期: 2017-12-15

Research on the method of using Landsat8 data to improve FCD model

Publish Date: 15 December 2017

摘要: 植被覆盖度是衡量地表植被状况的重要指标,在水文、气象和生态等方面的研究中具有重要作用.以Land-sat8为数据源,采用Gram-Schmidt变换的光谱锐化融合方法提高热红外波段的空间分辨率,计算热量指数,对传统FCD模型(forest canopy density mapping model)进行改进,根据4种指数的关系计算植被覆盖度.通过与传统FCD模型方法计算结果比较,改进后的植被覆盖度计算方法具有更高的精度.
- 植被覆盖度 /
- Landsat8 /
- FCD模型 /
- 热量指数
Abstract: As an important indicator, fractional vegetation coverage plays a critical role in the study of hydrology, weather, ecology and so on. Based on the Landsat8 as the data source and using Gramm - Schmidt transform spectrum sharpening fusion method, the authors improved the spatial resolution of thermal infrared band and calculated the thermal index. The traditional forest canopy density mapping model is improved based on the utilization of four indices to calculate the fractional vegetation coverage. A comparison with the traditional method shows that the improved model has a higher precision.
- fractional vegetation coverage /
- Landsat8 /
- forest canopy density mapping model /
- thermal index

中国自然资源航空物探遥感中心	主办
地质出版社	出版