土地覆被变化对基于ndvi的卫星农业干旱指数的影响

A. Yagci, L. Di, M. Deng
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引用次数: 15

摘要

干旱是一种自然气候事件,经常导致农业产量急剧下降。近年来,基于遥感产品的干旱指数是在干旱/水分胁迫下植被光合速率减缓的前提下发展起来的,这可以通过卫星数据和方法进行准确的跟踪。归一化植被指数(Normalized Difference Vegetation Index, NDVI)是世界范围内最常用、历史最悠久的陆地植被状态监测指标。有人认为,在基于NDVI的干旱方法中,干旱引起的NDVI下降可能与非干旱相关的NDVI下降(如火灾、洪水、土地覆盖/土地利用变化、虫害)相混淆。为了研究土地覆被变化对基于ndvi的干旱指数的影响,我们选择了基于ndvi的常用干旱指数植被条件指数(VCI)。我们发现,在VCI方法中,森林砍伐(即土地覆盖变化)被错误地分类为干旱,从而在非干旱年产生错误的干旱信号。然而,这些虚假的干旱信号可以借助空间滤波器(例如中值滤波器)从干旱图中消除,因为它们相对于研究区域大小是小尺度信号。此外,在干旱指数计算中不考虑作物轮作的情况下,农作物轮作(如玉米和大豆之间的轮作)降低了干旱报告的准确性,因为在爱荷华州,作物轮作每年占农业用地的50%以上,这对基于ndi的干旱方法产生了重大影响。综上所述,土地覆被相关变化对基于ndvi的干旱指标的影响与研究区域内非干旱相关变化的大小成正比。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The influence of land cover-related changes on the NDVI-based satellite agricultural drought indices
Drought is a natural climatic event that often causes sharp declines in agricultural production. In recent years, drought indices based on remote sensing products have been developed on the premise that photosynthetic rate of vegetation slows down under drought/water stress, and this can be accurately tracked by the satellite data and methods. The Normalized Difference Vegetation Index (NDVI) is the most popular index with the long historical record to monitor terrestrial vegetation state around the world. It has been suggested that drought-induced NDVI decline can be confused with non-drought-related NDVI decline (e.g., fire, flood, land cover/land use change, pest infestation) in the NDVI-based drought method. To investigate the effect of land cover-related changes on the NDVI-based drought indices, we selected the Vegetation Condition Index (VCI), a popular NDVI-based drought index. We found that deforestation (i.e., land cover change) is falsely classified as drought in the VCI method, hence producing the false drought signals during the non-drought years. However, these false drought signals can be eliminated from drought maps with the help of spatial filters (e.g., median filter) because they are small scale signals relative to the study area size. Furthermore, the rotation of agricultural crops (e.g., crop rotation between corn and soybean) reduces the accuracy of drought reporting when crop rotation is not considered in the drought index computation because crop rotation annually accounts for over 50% agricultural land in Iowa, it has a significant impact on the NDVI-based drought methods. In conclusion, it can be said that the influence of land cover-related changes on the NDVI-based drought indicators is proportional to the size of non-drought related changes relative to the study area.
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