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TitleMethodology for estimating availability of cloud-free image composites: A case study for southern Canada
AuthorZhou, F; Zhang, A
SourceInternational Journal of Applied Earth Observation and Geoinformation vol. 21, no. 1, 2012 p. 17-31,
Alt SeriesNatural Resources Canada, Contribution Series 20181282
PublisherElsevier BV
Mediapaper; on-line; digital
File formatpdf
Subjectsgeophysics; remote sensing
ProgramCanada Centre for Remote Sensing Divsion
AbstractImage composites are often used for earth surface phenomena studies at regional or national level. The compromise between residual clouds and the length of compositing period is a necessary corollary to the choice of satellite optical data for monitoring earth surface phenomena dynamics. This paper introduced a methodology for estimating availability of cloud-free image composites for optical sensors with various revisiting intervals, using MODIS MOD06 L2 cloud fraction product in the period of 2000-2008. The methodology starts with downscaling of the cloud fraction product to 1 km × 1 km cloud cover binary images. The binary images are then used for the exploration of spatial and temporal characteristics of cloud dynamics, and subsequently for the simulation of cloud-free composite availability with various revisiting intervals of optical sensors. Using Canada's southern provinces as an application case, the study explored several factors important for the design of environmental monitoring system using optical sensors of earth observation, in particular, cloud dynamics and its inter-annual variability, sensors' revisiting intervals, and cloud-free threshold for targeting composites. While the cloud images used in the analysis are at 1 km×1 km resolution, our analysis suggests that the simulated availabilities of cloud-free image composites may also provide reasonable estimates for optical sensors with higher than 1 km ×1 km resolution, though the closer to 1 km × 1 km resolution the optical sensor, the more pertinent the application. Also, the methodology can be parameterised to different temporal period and different spatial region, depending on applications.

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