Since Professor Siwen Bi proposed quantum remote sensing (QRS) in early 2001, the first QRS imaging prototype was developed after many stages of researches. Based on the results, our group has also undertaken in-depth theoretical and algorithmic experiments on QRS image processing. It’s both a quantum system simulation algorithm, preparing for the future quantum physical devices and calculation technology, and an expansion of quantum theories to RS image processing fields. It combines quantum mechanics theory and RS image processing technology, which introduces a new research direction for RS image processing technology. Now our researches achievements include a quantum denoising algorithm theory and simulation, a quantum enhancement algorithm theory and simulation, and a quantum segmentation algorithm theory research and simulation. A RS denoising algorithm based on the quantum-inspired concept is proposed for image denoising. Key benefits of the algorithm, which include improvements in transmission and accuracy, are demonstrated experimentally. Experiments showed that the peak signal to noise ratio (PSNR) for the proposed algorithm is improved by over 2dB and the edge retention index (EPI) is 0.1 higher than that for common methods. Given the low contrast ratio and brightness as well as insufficient detail for some RS images, a quantum algorithm based on the combination of a quantum inspired and unsharp masking to enhance and segment the RS image data was proposed. Results showed that the contrast ratio and brightness of images processed by the quantum algorithm improved, the image entropy and peak signal to noise ratio is higher.
The Variable Infiltration Capacity (VIC) hydrologic model was adopted for investigating spatial and temporal variability
of hydrologic impacts of climate change over the Nenjiang River Basin (NRB) based on a set of gridded forcing dataset
at 1/12th degree resolution from 1970 to 2013. Basin-scale changes in the input forcing data and the simulated
hydrological variables of the NRB, as well as station-scale changes in discharges for three major hydrometric stations
were examined, which suggested that the model was performed fairly satisfactory in reproducing the observed
discharges, meanwhile, the snow cover and evapotranspiration in temporal and spatial patterns were simulated
reasonably corresponded to the remotely sensed ones. Wetland maps produced by multi-sources satellite images
covering the entire basin between 1978 and 2008 were also utilized for investigating the responses and feedbacks of
hydrological regimes on wetland dynamics. Results revealed that significant decreasing trends appeared in annual, spring
and autumn streamflow demonstrated strong affection of precipitation and temperature changes over the study
watershed, and the effects of climate change on the runoff reduction varied in the sub-basin area over different time
scales. The proportion of evapotranspiration to precipitation characterized several severe fluctuations in droughts and
floods took place in the region, which implied the enhanced sensitiveness and vulnerability of hydrologic regimes to
changing environment of the region. Furthermore, it was found that the different types of wetlands undergone quite
unique variation features with the varied hydro-meteorological conditions over the region, such as precipitation,
evapotranspiration and soil moisture. This study provided effective scientific basis for water resource managers to
develop effective eco-environment management plans and strategies that address the consequences of climate changes.
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