Qizhong Lin

Age and nature of Cryogenian diamictites at Aksu, Northwest China: implications for Sturtian tectonics and climate

The Neoproterozoic succession in the Aksu region of northwestern China forms an unconformable boundary with the lower Precambrian Aksu basement group and consists of the Qiaoenbrak, Yuermeinak, Sugetbrak, and Chigebrak Formations. The two lowermost units include distinct glaciogenic diamictites that indicate distinct episodes of glaciation. In this study, we report the LA-ICP-MS U–Pb ages of detrital zircons and geochemical data from the lower Neoproterozoic strata. The age of the detrital zircon constrains the maximum depositional age to between 769 ± 10 and 727 ± 8 Ma for the Qiaoenbrak diamictites, which are associated with the Kaigas glaciation that occurred during the early Cryogenian period. The youngest detrital zircon age of 719 ± 9 Ma corresponds to the maximum depositional age of the Yuermeinak diamictites, which are associated with the Sturtian glaciation. The detrital zircons from the lower Neoproterozoic strata in the Aksu area indicated four peak ages of 2484, 1948, 861, and 647–581 Ma, which are consistent with the major tectonic episodes in the Tarim Block. The peak age of 2484 Ma represents an Archaean basement, which participated in the worldwide continental nuclei growth event from the late Neoarchaean to the early Palaeoproterozoic. The peak age of 1948 Ma may be associated with the assembly of the Columbia supercontinent, and the 861 and 647–581 Ma are likely associated with the break-up of the Rodinia supercontinent. The combination of geological and geochemical characteristics between the Qiaoenbrak Formation and Aksu Group indicates that the Qiaoenbrak Formation may be penecontemporaneous with the Aksu Group in an active continental margin tectonic setting. Following the break-up of the Rodinia supercontinent, the margin of the Aksu evolved into a passive margin and the Yuermeinak and Sugetbrak Formations were deposited.

Implication of the chemical index of alteration as a paleoclimatic perturbation indicator: an example from the lower Neoproterozoic strata of Aksu, Xinjiang, NW China

The Neoproterozoic successions in the Aksu region, NW China, which lies unconformably on the Precambrian Aksu Group basement, comprises the Qiaoenbrak, Yuermeinak, Sugetbrak, and Chigebrak formations (from bottom to top). The two lowermost units include two distinct glacial diamictites, which indicate distinct episodes of glaciations. We report the major and trace element (including rare earth element) data for the Qiaoenbrak, Yuermeinak, and Sugetbrak formations to identify the paleoclimatic perturbations. The chemical index of alteration (CIA) values show variations from Qiaoenbrak to Yuermeinak, then Sugetbrak formations. The diamictites have relatively lower chemical index of alteration values (45.23–59.64) than inter-, post- and non-glacial sediments (48.28–66.96). This result supported the condition that the diamictites underwent relatively weak chemical weathering from a dry-cold sedimentary environment, which is associated with the sedimentary facies description. The lower Neoproterozoic successions recoded at least two glaciations, one is Qiaoenbrak glaciation and the other is Yuermeinak glaciation.

Application of remote sensing for investigating mining geological hazards

Abstract To investigate geological mining hazards using digital techniques such as high-resolution remote sensing, a semi-automatically geological mining hazards extraction method is proposed based on the case of the Shijiaying coal mine, located in Fangshan District, Beijing, China. In the method, the vegetation is first removed using the normalized difference vegetation index (NDVI) on the GeoEye-1 data. Then, geological mining hazards interpretation features are determined after color enhancement using principal component analysis (PCA) transformation. Bitmaps mainly covered by geological mining hazards are isolated by masking operation in the environment for visualizing images software. Next, each bitmap is classified into a two-valued imagery using support vector machine algorithm. In the two-valued imagery, 1 denotes the geological mining hazards, while 0 denotes none. Afterwards, the two-valued imagery is converted into a vector graph by corresponding functions in the ArcGIS software and no geological mining hazards regions in the vector graph are deleted manually. Finally, the correlation between factors (such as mining activity, lithology, geological structure, and slope) and geological mining hazards is analyzed using a logistic regression and a hazardous-area forecasting model is built. The results of field verification show that the accuracy of the geological mining hazards extraction method is 98.1% and the results of the hazardous-area forecasting indicate that the logistic regression is an effective model in assessing geological hazard risks and that mining activity is the main contributing factor to the hazards, while geological structure, slope, lithology, roughness of the surface, and aspect are the secondary.

The prediction of nitrogen concentration in soil by VNIR reflectance spectrum

In this paper, the study on predicting nitrogen concentration in soil by VNIR (visible near infrared) spectrum is introduced. First, we analyzed the relationships between absorption features and nitrogen concentration to select the absorption features significantly correlated with nitrogen. Then several parameters of spectra in the selected absorption features were calculated, including first derivative reflectance spectra (FDR), inverse-log spectra (log (1/R)) and Band Depth. All of the soil samples were split into a calibration dataset and a validation dataset. Using stepwise multiple linear regression method, we established the statistical relationships between these parameters and nitrogen concentration. The regression models were calibrated using the calibration dataset, and validated using the validation dataset. The good results indicate that soil spectrum in the VNIR range has the potential for the rapid simultaneous prediction of nitrogen concentration. Keywords-nitrogen; soil; VNIR spectrum; SMLR

A new region growing-based segmentation method for high resolution remote sensing imagery

In this article, a newsegmentation method based on traditional region growing (RG) is proposed for high resolutionremote sensing imagery. This method takes regional minima from horizontal and vertical gradient maps of the image as seeds for the following region growing processing. The new method consists of several steps as follows: (1)deriving a morphological gradient map from the input multispectral image, (2) morphologically filtering the gradient image to remove local minima with small depthand extracting regional minima of flat areas in the resulting filtered image as seeds, (3) segmenting the multispectral image using the RG approach with reference to the seeds, and (4) merge the resulting initial segments to yield asegmentation map. In a test with a WorldView-2 multispectral image, the proposed method offered segmentation maps with nearly the same accuracy as several current methods.

Rock types detection and classification through the use of orthogonal subspace projection approach

In most cases especially rock types detection, the pixels in remote sensing image are mixed, and so common methods based on pure pixels to detect target are not appropriate here. Orthogonal Subspace Projection has two important properties: one is to eliminate or suppress the undesired signals by projecting each pixel onto the space orthogonal to interfering signals, another is to detect the presence of desired signal by projecting the residuals onto the space of interesting signal and maximizing the signal-to-noise ratio (SNR). It can be used simultaneously on mixed pixels and the pure ones. Using Thematic Mapper (TM) data to classify different rock types shows OSP to perform well.

Semi-automatic mapping of large shallow landslides using high-resolution remote sensing imagery

A semi-automatic and hierarchical detection method using only post-event high-resolution (HR) remote sensing imagery for recent shallow landslides that are triggered by an earthquake or a rainfall event, were introduced in this study. Firstly, candidate landslide regions are obtained by extracting objects in light- tone using HR images. Then, shape parameters are employed elimination roads and building in light-tone, and text parameters are considered to remove farmlands from the candidate regions. The proposed method achieves average accuracies of approximately 77% and 68%, in terms of landslide number and area, respectively.

Hyperspectral Soil Dispersion Model for the Source Region of the Zhouqu Debris Flow, Gansu, China

A new hyperspectral soil dispersion model was established by using multivariable linear regression based on experimentally derived soil dispersion data and hyperspectral field spectra of soil components. The coefficient of determination for the model is 0.8084, which shows that the model effectively reproduced soil dispersion. Those bands that were relevant to soil dispersion included 370, 377, 398, 410, 570, 1918, 1933, 2392, 2401, 2444, and 2448 nm, which identified soil components and their adsorbed ions. The correlation between soil spectral bands and soil components indicates that calcite and clay minerals were the main factors that caused soil to be dispersive because they are easily dissolved in water. This result provides a scientific basis for countering soil dispersion and reducing the occurrence of debris flows. The spectral bands determined by this model may also be relevant to air- or satellite-borne hyperspectral remote sensing in the future.

A novel multi-resolution segmentation algorithm for highresolution remote sensing imagery based on minimum spanning tree and minimum heterogeneity criterion

Image segmentation is the basis of object-based information extraction from remote sensing imagery. Image segmentation based on multiple features, multi-resolution, and spatial context is one current research focus. Combining graph theory based optimization with the multi-scale image segmentation framework of the eCognition software, a multi-scale image segmentation method is proposed in this paper. In this method, a coherent enhancement anisotropic diffusion filtering approach and a minimum spanning tree segmentation algorithm are employed to initially segment the image. After that, the resulting segments are merged regarding minimum heterogeneity criteria, which are based on both the spectral characteristics and the shape parameters of segments. Two test images were used for visual and quantitative comparisons of the proposed method with the multi-scale segmentation method FNEA employed in the eCognition software. The results show that the proposed method is effective, and is more sensitive to subtle spectral differences than the FNEA.

A method for quickly extracting seismogeological hazards in Yingxiu, Sichuan Province, China

A method for seismogeological hazards extraction using high resolution remote sensing was proposed in the research taken the epicenter of Wenchuan earthquake-Yingxiu town as the study area. In which, making imagery was built according to the Digital Elevation Model (DEM) to remove interfering factors. Then, the masked imagery was diced into several small parts to reduce the large imageries’ inconsistency and they were used as the sources to be classified. After that, the vector conversion was performed on the classified images to mapping geological hazards. Finally, other interfering factors such as bare lands, lands covered by few vegetation and buildings on the top altitude were removed manually. For it can extract geological hazards in a short time, it is of great importance for the decision–makers and rescuers to know the damaged degree in the disaster area, especially within 72 hours after the earthquake. Therefore, it will play an important role in decision making, site rescue and hazards response planning.