Ling Zeng

Ling Zeng
Chengdu University of Technology | CDUT

PHD

About

11
Publications
1,965
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79
Citations
Citations since 2017
8 Research Items
65 Citations
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201720182019202020212022202305101520
201720182019202020212022202305101520

Publications

Publications (11)
Article
Full-text available
Heavy metal concentrations of Cd, As, Pb, Cu, Cr, and Hg were investigated for 86 soil samples in Jinzhou near the Bohai Sea in China, in order to identify what anthropological activities influenced their distribution levels. Ordinary cokriging (OCK) was utilized to map six heavy-metal distributions by incorporating their main environmental influen...
Article
Full-text available
Multispectral-sensor images are advantageous in terms of discriminating major lithologies due to their high spatial resolution and intermediate spectral resolution, in addition to their low cost and high accessibility in comparison to hyperspectral images. In this study, Landsat-5 Thematic Mapper ™ and the Advanced Spaceborne Thermal Emission and R...
Article
Full-text available
The shape and the size of grains in sediments and soils have a significant influence on their engineering properties. Image analysis of grain shape and size has been increasingly applied in geotechnical engineering to provide a quantitative statistical description for grain morphologies. The statistic robustness and the era of big data in geotechni...
Data
This is Matlab version of crystals extraction and its principles and descriptions can be referenced in Zeng et al. (2018)
Article
Heavy metal contamination of soil poses a threat to food chains and human health, particularly in mining areas. This study aims to advance the accuracy of mapping heavy metals in soil by incorporating auxiliary information and to assess the soil contamination risk to local residents in a mining area. Pearson correlation coefficients of environmenta...
Article
Full-text available
The combined influence of surface soil moisture and roughness on radar backscatters has been limiting SAR’s application in soil moisture retrieval. In the past research, multi-temporal analysis and artificial neural network (ANN) inversion of physically based forward models were regarded as promising methods to decouple that combined influence. How...
Article
Full-text available
A cokriging model using three variables is developed to estimate bare-surface soil moisture content based on multi-temporal synthetic-aperture radar (SAR) data. This model utilizes cross-semivariogram function to take into account spatially varied correlation among multiple variables.
Article
Full-text available
It is nowadays common to collect large‐area backscattered electron images and X‐ray maps of entire standard petrographic thin sections. These images can be calibrated for compositions of some minerals (e.g. plagioclase) with a small number of electron microprobe analyses, and thus provide a wealth of quantitative data for hundreds of crystals. Howe...
Article
Giant plagioclase crystals carried into the Panzhihua gabbroic layered intrusion from a deeper magma chamber can help constrain the timescales of emplacement of the Panzhihua intrusion in the Emeishan large igneous province (LIP). In this study, we present the petrographic textures and chemical compositions of giant plagioclase and fine-grained gab...
Article
Full-text available
Giant plagioclase basalts (GPBs) reflect the storage of flood basalt magma in subvolcanic magma chambers at crustal depths. In this study of the Late Permian Emeishan large igneous province in southwest China, we focus on understanding the plumbing system and ascent of large-volume basaltic magma. We report a quantitative textural analysis and bulk...
Article
Full-text available
The refinement of Lange’s plagioclase-liquid hygrometer/thermometer presented in this paper is based on quadratic log-contrast models for experiments with mixtures. Lange’s plagioclase-liquid equilibrium thermodynamic model involves linear functions of components of magmatic liquid and crystalline plagioclase. Assuming a known temperature, the resp...

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Projects

Projects (2)
Project
High-Ti and Low-Ti basalt recognition based on remote sensing technologies and deep learning