关键词: 云状态, 时空特征, 湖南省, MODIS, 遥感

Abstract:

The presence of clouds hinders remote sensing of earth surface and causes information loss. Understanding the spatiotemporal patterns of different cloud states over a given region can improve the pertinence and accuracy of cloud noise elimination. In this study, the MODIS surface reflectance products, MOD09A1, were used to extract the cloud state information for each pixel of Hunan Province, spanning from 2001 to 2017. Then, geo-statistics and spatial analysis methods were used to detect Hunan's spatiotemporal patterns of the clear, cloudy, and mixed states. The examined patterns included the spatial distribution, seasonal distribution, gap length duration, and cloud interference for the different cloud states. The results show that: (1) Hunan Province in general was quite severely affected by clouds, with obvious spatial heterogeneity, i.e., the cloudy state when imagery are shadowed by clouds mainly occurred over the western and southern mountain areas of Hunan, while the mixed state when imagery are distorted by clouds existed over the gentle plains and hilly regions of the northern, central, and southern Hunan; (2) the cloudy state was dominant among the cloudy and mixed states, with the former more likely to occur between January and February, November and December, late May and early July, while the latter maintained 10% of cloud cover during the whole year and up to 18% from June to October; (3) cloud gap lengths of 8-days and 16-days were the primary situation for the cloudy and mixed states;(4) increasing the composite window size, cloud interference effects declined dramatically and could be neglected if monthly composite size (4 collections) was utilized;(5) by Principal Component Analysis (PCA) of the different cloudy state data, the first two PCA components were derived which indicated different spatial distribution patterns and divided Hunan into four sub regions with distinctive cloud characteristics; and (6) there are significant relationships between the different cloud states and elevation variation, and except for the cloudy state, they are all negatively correlated with elevation variation. This study can provide technical support for the selection of remote sensing data, the removal method of cloud noises, and the reconstruction of vegetation indices time series for Hunan Province.

Key words: cloud states, spatiotemporal patterns, Hunan Province, MODIS, remote sensing