Time filter

Source Type

Chen J.,Ocean University of China | Chen J.,CAS Qingdao Institute of Oceanology | Yin S.,Satellite of Environment Center | Xiao R.,Satellite of Environment Center | Lin C.,Ocean University of China
Advances in Space Research | Year: 2014

The objectives of this study are to validate the applicability of a shortwave infrared atmospheric correction model (SWIR-based model) in deriving remote sensing reflectance in turbid Case II waters, and to improve that model using a proposed green-shortwave infrared model (GSWIR-based model). In a GSWIR-based model, the aerosol type is determined by a SWIR-based model and the reflectance due to aerosol scattering is calculated using spectral slope technology. In this study, field measurements collected from three independent cruises from two different Case II waters were used to compare models. The results indicate that both SWIR- and GSWIR-based models can be used to derive the remote sensing reflectance at visible wavelengths in turbid Case II waters, but GSWIR-based models are superior to SWIR-based models. Using the GSWIR-based model decreases uncertainty in remote sensing reflectance retrievals in turbid Case II waters by 2.6-12.1%. In addition, GSWIR-based model's sensitivity to user-supplied parameters was determined using the numerical method, which indicated that the GSWIR-based model is more sensitive to the uncertainty of spectral slope technology than to that of aerosol type retrieval methodology. Due to much lower noise tolerance of GSWIR-based model in the blue and near-infrared regions, the GSWIR-based model performs poorly in determining remote sensing reflectance at these wavelengths, which is consistent with the GSWIR-based model's accuracy evaluation results. © 2014 COSPAR. Published by Elsevier Ltd. All rights reserved.


Xiao R.,Satellite of Environment Center | Shen W.,Satellite of Environment Center | Fu Z.,Satellite of Environment Center | Shi Y.,Satellite of Environment Center | And 2 more authors.
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2012

As a kind of huge environmental risk source, tailings pond could cause a huge environmental disaster to the downstream area once an accident happened on it. Therefore it has become one key target of the environmental regulation in china. Especially, recently environmental emergencies caused by tailings pond are growing rapidly in China, the environmental emergency management of the tailings pond has been confronting with a severe situation. However, the regulatory agency is badly weak in the environmental regulation of tailings pond, due to the using of ground surveys and statistics which is costly, laborious and time consuming, and the lacking of strong technical and information support. Therefore, in this paper, according to the actual needs of the environmental emergency management of tailings pond, we firstly make a brief analysis of the characteristics of the tailings pond and the advantages and capability of remote sensing technology, and then proposed a comprehensive and systematic indexes system and the method of environmental risk monitoring of tailings pond based on remote sensing and GIS. The indexes system not only considers factors from the upstream area, the pond area and the downstream area in a perspective of the risk space theory, but also considers factors from risk source, risk receptor and risk control mechanism in a perspective of risk systems theory. Given that Zhangjiakou city has up to 580 tailings pond and is nearly located upstream of the water source of Beijing, so finally we apply the proposed indexes system and method in Zhangjiakou area in China to help collect environmental risk data of tailings pond in that area and find out it works well. Through the use case in Zhajiakou, the technique of using remote sensing to monitor environmental risk of tailings pond is feasible and effective, and would contribute to the establishment of 'Space-Ground' monitoring network of tailings pond in future. © 2012 SPIE.

Loading Satellite of Environment Center collaborators
Loading Satellite of Environment Center collaborators