Abstract
Time series remote sensing products with both fine spatial and dense temporal resolutions are urgently needed for many earth system studies. The development of small satellite constellations with identical sensors affords novel opportunities to provide such kind of earth observations. In this paper, a new dense time series 30-m image product was proposed respectively based on an 8-day, 16-day and monthly composition. The products were composited by the Charge Coupled Device (CCD) images from the 2-day revisit small satellite constellation for environmental monitoring and disaster mitigation of China (HJ-1A/B). Taking the Zoige plateau in China as a case area where it is covered by highly heterogeneous vegetation landscapes, a detailed methodology was introduced on how to use 183 scenes of CCD images in 2010 to create composite products. The quality of the HJ CCD composites was evaluated by inter-comparison with the monthly 30-m global Web-Enabled Landsat Data (WELD), 16-day 500-m MODIS NDVI, and 8-day 500-m MODIS surface reflectance products. Results showed that the radiometric consistency between HJ and WELD composited Top Of Atmosphere (TOA) reflectance was in good agreement except for May, June, July and August when more clouds and invalid data gaps appeared in WELD. Visual assessment and temporal profile analysis also revealed that HJ possessed better visual effects and temporal coherence than that of WELD. The comparison between HJ and MODIS products indicated that HJ composites were radiometrically consistent with MODIS products over areas consisting of large patches of homogeneous surface types, but can better reflect the detailed spatial differences in regions with heterogeneous landscapes. This paper highlights the potential of compositing HJ-1A/B CCD images, allowing for providing a cloud free, time-space consistent, 30-m spatial resolution, and dense in time series image product. Meanwhile, the proposed products could also be treated as a reference to generate regional or even global composited products for the on-going satellite constellations and even for the forthcoming satellite missions such as Sentinel-2A/B.
Highlights
IntroductionDense time series (e.g., annual, monthly, weekly) satellite datasets are crucial for monitoring land surface dynamics (e.g., intra-seasonal ecosystem variations)
Dense time series satellite datasets are crucial for monitoring land surface dynamics
The Web-Enabled Landsat Data (WELD) project provides a good framework for producing composites at 30-m spatial resolution and monthly, seasonal, annual time intervals using Landsat 7 Enhanced Thematic Mapper Plus (ETM+) data [15]
Summary
Dense time series (e.g., annual, monthly, weekly) satellite datasets are crucial for monitoring land surface dynamics (e.g., intra-seasonal ecosystem variations). Or sub-monthly satellite datasets have been developed at moderate (>250 m) or coarser spatial resolutions [1,2]. Pixels in these coarse resolution images are often a mixture of various land cover types [3,4]. Because of the frequent cloud contamination and the poor atmospheric conditions, the comparatively infrequent 16-day repeat of the current Landsat system does not provide adequate observations for producing gap free clear view composites at monthly or sub-monthly intervals
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