Tong Shuai

Derivation of a tasselled cap transformation based on Landsat 8 at-satellite reflectance

The tasselled cap transformation (TCT) is a useful tool for compressing spectral data into a few bands associated with physical scene characteristics with minimal information loss. TCT was originally evolved from the Landsat multi-spectral scanner (MSS) launched in 1972 and is widely adapted to modern sensors. In this study, we derived the TCT coefficients for the newly launched (2013) operational land imager (OLI) sensor on-board Landsat 8 for at-satellite reflectance. A newly developed standardized mechanism was used to transform the principal component analysis (PCA)-based rotated axes through Procrustes rotation (PR) conformation according to the Landsat thematic mapper (TM)-based tasselled cap space. Firstly, OLI data were transformed into TM TCT space directly and considered as a dummy target. Then, PCA was applied on the original scene. Finally, PR was applied to get the transformation results in the best conformation to the target image. New coefficients were analysed in detail to confirm Landsat 8-based TCT as a continuity of the original tasselled cap idea. Results show that newly derived set of coefficients for Landsat OLI is in continuation of its predecessors and hence provide data continuity through TCT since 1972 for remote sensing of surface features such as vegetation, albedo and water. The newly derived TCT for OLI will also be very useful for studying biomass estimation and primary production for future studies.

Estimating ecological indicators of karst rocky desertification by linear spectral unmixing method

Coverage rates of vegetation and exposed bedrock are two key indicators of karst rocky desertification. In this study, the abundances of vegetation and exposed rock were retrieved from a hyperspectral Hyperion image using linear spectral unmixing method. The results were verified using the spectral indices of karst rocky desertification (KRDSI) and an integrated LAI spectral index: modified chlorophyll absorption ratio index (MCARI2). The abundances showed significant linear correlations with KRDSI and MCARI2. The coefficients of determination (R2) were 0.93, 0.66, and 0.84 for vegetation, soil, and rock, respectively, indicating that the abundances of vegetation and bedrock can characterize their coverage rates to a certain extent. Finally, the abundances of vegetation and bedrock were graded and integrated to evaluate rocky desertification in a typical karst region. This study suggests that spectral unmixing algorithm and hyperspectral remote sensing imagery can be used to monitor and evaluate karst rocky desertification.

A Spectral Angle Distance-Weighting Reconstruction Method for Filled Pixels of the MODIS Land Surface Temperature Product

Land surface temperature (LST) is an important parameter in the physics of land surface processes, but a large number of pixels are often filled as zero due to cloud, heavy aerosols, and so on in the Moderate-resolution Imaging Spectroradiometer (MODIS) LST product. This letter presents the spectral angle distance (SAD)-weighting reconstruction (SADWER) method of reconstruction of zero-filled pixels of the MODIS LST product. It relies on the hypothesis that pixels with the same land-cover type have nearly the same LST in a localized area. SAD can measure the similarity of land-cover types of different pixels, and pixels with higher land-cover similarity can contribute more to the reconstruction using the weighting method. The result shows that the reconstruction ratio could be as high as 95% using only the SADWER method and nearly 100% after spatial filter postprocessing. The reconstruction accuracy is validated using artificially generated 20-, 50-, and 80-km-diameter concentrically filled areas in both forest and crop land-cover types. The statistical result shows that the standard deviations of the reconstruction errors are less than 2 Kelvin.

Radiometric normalization of multitemporal hyperspectral satellite images

The essay applied Multivariate alteration detection (MAD) transformation and orthogonal regression analysis for radiometric normalization of multitemporal hyperspectral satellite imagery. The evaluation results of RMSE show that the MAD-based normalization in all eighteen bands of CHRIS image is feasible and effective. And the evaluation results of DI show that the MAD-based normalization performs better in keeping the spectral-dimensional information of hyperspectral images than IR normalization.

Assessment of estimation methods for Chlorophyll-a through hyperspectral insitu data and multispectral landsat for Taihu lake

Estimating Chlorophyll-a concentration from the inland turbid water has been an important research issue for preserving and managing the ecological issues related to the lives of both flora and fauna. Hyperspectral remote sensing is being exploited to retrieve the true estimation of phytoplankton from all platforms like satellite, airborne sensors and handheld field spectroradiometers. This study was aimed to utilize both satellite sensors and field spectrometers for proper assessment of Chlorophyll-a. 4-band model with band combination [Rrs(λ<inf>1</inf>)⁻¹ − Rrs(λ<inf>2</inf>)⁻¹] × [Rrs(λ<inf>4</inf>)⁻¹ − Rrs(λ<inf>3</inf>)⁻¹]⁻¹ is found better than other models, while for Landsat ETM+, band combination b1/b2 is found better for estimating Chlorophyll-a as compared to other band combinations. It is also found that FLAASH is not suitable for atmospheric correction of ETM+ images destined to study Chlorophyll-a concentration.

Abundance retrieval of hydrous minerals around the mars science laboratory landing site

The detection of hydrous minerals on Mars is of great importance for revealing the early water environment as well as possible biotic activity. However, few studies focus on quantitatively retrieving hydrous minerals for some difficulties. In this letter, we studied the area around the Mars Science Laboratory (MSL) landing site, to identify hydrous minerals and retrieve their abundance. Firstly, the distribution of hydrous minerals was extracted using their water absorption features. Then, a sparse unmixing algorithm was applied along with the CRISM spectral library to retrieve the abundance of hydrous minerals in this area. As a result, seven hydrous minerals were quantitatively retrieved, e.g. actinolite, montmorillonite, saponite, jarosite and so forth, and the total concentration of all hydrous minerals was as high as 40 vol% near the lower reaches of Mount Sharp. Our results were consistent with results from related research and the in-situ analysis of the MSL rover Curiosity.

A preliminary research on quantitative retrieval of hydrous minerals around the Mars Science Laboratory landing site

The detection of hydrous minerals is of great importance in revealing the early water environment and even biotic activities on Mars. However, few studies focus on quantitatively retrieving hydrous minerals due to some problems. In this paper, the area around the Mars Science Laboratory (MSL) landing site is studied for quantitatively retrieving hydrous minerals. Firstly, the distribution of hydrous minerals is extracted using water absorption features. Then, sparse unmixing is employed with CRISM spectral library to retrieve the abundance of hydrous minerals in the hydrous region. The results show that seven hydrous minerals are quantitatively retrieved, e.g. actinolite, montmorillonite, saponite, jarosite and so forth, and the total concentration of all hydrous minerals can reach up to 40% near the lower reaches of Mount Sharp.

Coupling remote sensing data and eco-hydrological model to evaluate Non-point source pollution risk for water resource management

Non-point source pollution risk assessment for surface drinking water catchments is an important basis and premise for the scientific management over water environment, while remote sensing technology may timely find the spatial distribution pattern and variation of risk. Coupling the Non-point source model and remote sensing data is a potential method for the water environment risk assessment. The dual Non-point source model independently developed by China is chosen to study its practical applicability in the experimental catchment area of Hebei Yuecheng Reservoir in combination with the remote sensing and GIS data, and to study the spatial distribution pattern of the Non-point source Phosphorus (P) pollution generated by the spatial landuse. The result shows that:(1) the coupled model is well adapted to the catchment area of Hebei Yuecheng Reservoir, and the simulated Non-point source P load is strongly related to the observation data of the hydrologic stations such as Liujiazhuang, Guantai and etc.; (...

Estimate ecological indicators of karst rocky desertification by spectral unmixing algorithm

Coverage rates of vegetation and exposed bedrock are two key indicators of karst rocky desertification (KRD) envionmnents. Based on spectral unmixing algorithm, abundance of vegetation and exposed rock were retrieved from the hyperspectral Hyperion image. They were verified by the spectral indices of Karst rocky desertification (SIRD) and vegetation chlorophyll index. It showed that the abundance had significant linear correlation with SIRD. The determinate coefficients (R2) were 0.93,0.66, 0.84 for vegetation, soil and rock respectively, indicating that the abundances of vegetation and bedrock can characterize their coverage rates to a certain extent. Then, the abundances of vegetation and bedrock were graded and integrated together to evaluate the rocky desertification in typical Karst region. This study implies that spectral unmixing algorithm based on hyperspectral remote sensing image will have potential use in monitoring and evaluating KRD.