Dr. Xia Zhang Profile

Dr. Xia Zhang

Professor at Institute of Remote Sensing and Digital Earth

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Author

Publications (23)

SPIE Journal Paper | 11 January 2019 Open Access

Denoising vegetation spectra by combining mathematical-morphology and wavelet-transform-based filters

Xia Zhang, Wenchao Qi, Yi Cen, Honglei Lin, Nan Wang

JARS, Vol. 13, Issue 01, 016503, (January 2019) https://doi.org/10.1117/12.10.1117/1.JRS.13.016503

KEYWORDS: Denoising, Vegetation, Optical filters, Signal to noise ratio, Wavelets, Interference (communication), Electronic filtering, Filtering (signal processing), Image filtering, Signal detection

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Proceedings Article | 24 October 2016 Presentation + Paper

A new semi-supervised classification strategy combining active learning and spectral unmixing of hyperspectral data

Yanli Sun, Xia Zhang, Antonio Plaza, Jun Li, Inmaculada Dópido, Yi Liu

Proceedings Volume 10007, 1000708 (2016) https://doi.org/10.1117/12.2241635

KEYWORDS: Hyperspectral imaging, Image classification, Remote sensing, Analytical research, Image analysis, Statistical analysis, Visible radiation, Data communications, Sun, Lithium

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Hyperspectral remote sensing allows for the detailed analysis of the surface of the Earth by providing high-dimensional images with hundreds of spectral bands. Hyperspectral image classification plays a significant role in hyperspectral image analysis and has been a very active research area in the last few years. In the context of hyperspectral image classification, supervised techniques (which have achieved wide acceptance) must address a difficult task due to the unbalance between the high dimensionality of the data and the limited availability of labeled training samples in real analysis scenarios. While the collection of labeled samples is generally difficult, expensive, and time-consuming, unlabeled samples can be generated in a much easier way. Semi-supervised learning offers an effective solution that can take advantage of both unlabeled and a small amount of labeled samples. Spectral unmixing is another widely used technique in hyperspectral image analysis, developed to retrieve pure spectral components and determine their abundance fractions in mixed pixels. In this work, we propose a method to perform semi-supervised hyperspectral image classification by combining the information retrieved with spectral unmixing and classification. Two kinds of samples that are highly mixed in nature are automatically selected, aiming at finding the most informative unlabeled samples. One kind is given by the samples minimizing the distance between the first two most probable classes by calculating the difference between the two highest abundances. Another kind is given by the samples minimizing the distance between the most probable class and the least probable class, obtained by calculating the difference between the highest and lowest abundances. The effectiveness of the proposed method is evaluated using a real hyperspectral data set collected by the airborne visible infrared imaging spectrometer (AVIRIS) over the Indian Pines region in Northwestern Indiana. In the paper, techniques for efficient implementation of the considered technique in high performance computing architectures are also discussed.

Proceedings Article | 19 May 2016 Paper

A nonlinear spectral unmixing method for abundance retrieval of mineral mixtures

Xia Zhang, Honglei Lin, Yi Cen, Hang Yang

Proceedings Volume 9874, 98740Z (2016) https://doi.org/10.1117/12.2225567

KEYWORDS: Quartz, Refractive index, Atmospheric particles

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Proceedings Article | 19 May 2016 Paper

Semi-supervised hyperspectral unmixing approach based on nonnegative matrix factorization

Lifu Zhang, Nan Wang, Xia Zhang, Zhengfu Chen, Min Gao

Proceedings Volume 9874, 987408 (2016) https://doi.org/10.1117/12.2225465

KEYWORDS: Remote sensing, Signal to noise ratio, Atrial fibrillation, Hyperspectral imaging, Clouds, Data modeling, Information technology, Spatial resolution, Spectroscopy, Image analysis

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Proceedings Article | 8 November 2014 Paper

Comparison of the sensor dependence of vegetation indices and vegetation water indices based on radiative transfer model

Xiaoping Chen, Shudong Wang, Hailing Jiang, Xia Zhang

Proceedings Volume 9260, 92603G (2014) https://doi.org/10.1117/12.2069033

KEYWORDS: Vegetation, Reflectivity, Atmospheric sensing, Sensors, Radiative transfer, Atmospheric modeling, Absorption, Satellites, Multispectral imaging, Remote sensing

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Proceedings Article | 24 October 2013 Paper

Estimate ecological indicators of karst rocky desertification by spectral unmixing algorithm

Xia Zhang, Tong Shuai, Banghui Yang, Zhi Zhuang

Proceedings Volume 8893, 889313 (2013) https://doi.org/10.1117/12.2028077

KEYWORDS: Vegetation, Remote sensing, Hyperspectral imaging, Absorption, Reflectivity, Digital photography, Evolutionary algorithms, Image analysis, Photography, Spectroscopy

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Proceedings Article | 26 October 2010 Paper

Band selection method for retrieving soil lead content with hyperspectral remote sensing data

Xia Zhang, Jianting Wen, Dong Zhao

Proceedings Volume 7831, 78311K (2010) https://doi.org/10.1117/12.864425

KEYWORDS: Genetic algorithms, Lead, Remote sensing, Metals, Soil science, Soil contamination, Data modeling, Reflectivity, Spectral resolution, Absorption

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Proceedings Article | 10 November 2008 Paper

Ontology-based geographic information semantic metadata integration

Qin Zhan, Deren Li, Xia Zhang, Yu Xia

Proceedings Volume 7146, 71460M (2008) https://doi.org/10.1117/12.813113

KEYWORDS: Information fusion, Chemical elements, Associative arrays, Standards development, Data modeling, Roads, Remote sensing, Geographic information systems, Artificial intelligence, Telecommunications

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Proceedings Article | 19 February 2008 Paper

Investigation of atmospheric aerosol optical properties over Lake Taihu using MODIS and CE318 data

Fang-chao Hu, Bing Zhang, Zheng-chao Chen, Xia Zhang, Jun-sheng Li, Qian Shen, Qing-xi Tong

Proceedings Volume 6625, 66251F (2008) https://doi.org/10.1117/12.791215

KEYWORDS: Aerosols, Atmospheric modeling, Atmospheric particles, Reflectivity, Optical properties, MODIS, Scattering, Atmospheric optics, Remote sensing, Data modeling

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Aerosol model is a major obstacle for passive remote sensing of aerosol properties. For the continent or urban aerosol model does not fit the needs for more accurate retrieval, and the user defined aerosol model may be more near to the realistic condition in Taihu region. A method has been developed for retrieving the aerosol model and optical properties including polarization, i.e., scattering coefficient, asymmetry factor, single scattering albedo, scattering phase function and polar phase function. In Lake Taihu, the study area of our two combined remote sensing observations in the winter and summer 2006, we got water surface spectral data of ASD (Analytical Spectral Devices) by the ship, atmospheric data of CE318 sunphotometer on the shore, and the MODIS (Moderate Resolution Imaging Spcectroradiometer) image data on the TERRA Satellite. By using the nearly synchronous measurements of the data from surface spectrum and the sunphotometer with the image, and by use of the radiative transfer model 6S(Second Simulation of a Satellite Signal in the Solar Spectrum), varying the components of the aerosol type, a LUT (look up table) is made for the radiance on the satellite. When the total relative error of the new defined parameter for relative error is getting to the least, the aerosol type will be decided. Then, based on the determination of aerosol model, the atmospheric aerosol properties over Lake Taihu have been computed by using Mie theory and analyzed with the typical continental and urban aerosol models available in 6S. These results show that the user-defined aerosol model is a mix model of continent and urban which corresponds with previous studies. Moreover, they may be useful for resolving the vector RTE (radiative transfer equation). In this paper we tried to provide a method with the combination of remote sensing data to obtain the optical properties of atmospheric aerosol over inland water in different seasons. We respect it will be helpful for accurate atmospheric correction in the future.

Proceedings Article | 15 November 2007 Paper

Estimating foliar water content of winter wheat with hyperspectral image

Xia Zhang, Quanjun Jiao, Di Wu, Bing Zhang, Lianru Gao

Proceedings Volume 6787, 678718 (2007) https://doi.org/10.1117/12.749316

KEYWORDS: Absorption, Reflectivity, Short wave infrared radiation, Near infrared, Hyperspectral imaging, Agriculture, Vegetation, Infrared radiation, Spectroscopy, Infrared imaging

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Proceedings Article | 12 November 2007 Paper

Geospatial data and services semantic share based on ebXML registry

Xu Chen, Xinyan Zhu, Xia Zhang, Daosheng Du

Proceedings Volume 6795, 679526 (2007) https://doi.org/10.1117/12.774199

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Proceedings Article | 28 October 2006 Paper

Study on geographic information service combination

Xia Zhang, Deren Li, Xinyan Zhu, Zhanwu Yu

Proceedings Volume 6421, 64210H (2006) https://doi.org/10.1117/12.712674

KEYWORDS: Geographic information systems, Taxonomy, Web services, Data conversion, Composites, Network security, Process modeling, Roads, Data processing, Spatial analysis

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Proceedings Article | 9 June 2006 Paper

A new architecture for hyperspectral image compression based on wavelets transformation and fractal composition

Xingtang Hu, Bing Zhang, Xia Zhang, Fangchao Hu, Zheng Wei

Proceedings Volume 6200, 62000L (2006) https://doi.org/10.1117/12.681725

KEYWORDS: Image compression, Fractal analysis, Hyperspectral imaging, Wavelets, Image processing, Remote sensing, Computer programming, Wavelet transforms, Iterated function systems, Sensors

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Proceedings Article | 9 June 2006 Paper

Calibration evaluation of the spaceborne hyperspectral CHRIS image

Xia Zhang, Bing Zhang, Fangchao Hu, Qingxi Tong

Proceedings Volume 6200, 62000B (2006) https://doi.org/10.1117/12.681242

KEYWORDS: Reflectivity, Calibration, Vegetation, Atmospheric corrections, Hyperspectral imaging, Atmospheric modeling, Spectral calibration, Model-based design, Soil science, Sensors

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Proceedings Article | 1 November 2005 Paper

A hyperspectral-environmental database in China

Xing Li, Xingtang Hu, Bing Zhang, Xia Zhang, Junsheng Li, Xiaoying Li

Proceedings Volume 5983, 59831O (2005) https://doi.org/10.1117/12.627356

KEYWORDS: Databases, Environmental monitoring, Remote sensing, Water contamination, Environmental sensing, Water, Image processing, Lithium, Data processing, Data storage

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Proceedings Article | 25 September 2003 Paper

Preliminary research in using the technology of data mining to analyze remote sensing data

Xiongfei Zhang, Xing Li, Xia Zhang, Qingxi Tong, Wei Liu, Lanfen Zheng

Proceedings Volume 5286, (2003) https://doi.org/10.1117/12.539951

KEYWORDS: Databases, Data mining, Analytical research, Remote sensing, Biological research, Mining, Relativity, Data conversion, Data processing, Data integration

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Proceedings Article | 25 September 2003 Paper

Image classification supported by digital geomorphology model

Bing Zhang, Xing Li, Xia Zhang, Qingxi Tong, Lanfen Zheng

Proceedings Volume 5286, (2003) https://doi.org/10.1117/12.538653

KEYWORDS: Image classification, Mathematical modeling, Spatial resolution, Remote sensing, Fuzzy logic, Mathematics, Solid modeling, Image quality, Digital imaging, Computer aided design

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Proceedings Article | 25 September 2003 Paper

Automatic flat field algorithm for hyperspectral image calibration

Xia Zhang, Bing Zhang, Xiurui Geng, Qingxi Tong, Lanfen Zheng

Proceedings Volume 5286, (2003) https://doi.org/10.1117/12.539070

KEYWORDS: Calibration, Reflectivity, Hyperspectral imaging, Remote sensing, Image processing, Image sensors, Electroluminescence, Spectral calibration, Feature extraction, Radiative transfer

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Proceedings Article | 16 June 2003 Paper

Estimating foliar nitrogen concentration with hyperspectral remote sensing image

Xia Zhang, Bing Zhang, Liangyun Liu, Jihua Wang

Proceedings Volume 4897, (2003) https://doi.org/10.1117/12.466736

KEYWORDS: Nitrogen, Absorption, Reflectivity, Hyperspectral imaging, Remote sensing, Proteins, Feature extraction, Spectroscopy, Image retrieval, Biological research

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Proceedings Article | 16 June 2003 Paper

Spectral unmixing and image classification supported by spatial knowledge

Bing Zhang, Xia Zhang, Liangyun Liu, Lanfen Zheng, Qingxi Tong

Proceedings Volume 4897, (2003) https://doi.org/10.1117/12.467408

KEYWORDS: Remote sensing, Image classification, Hyperspectral imaging, Data acquisition, Digital photography, Spatial resolution, Geographic information systems, Associative arrays, Photography, Visualization

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Proceedings Article | 25 September 2001 Paper

Dynamic analysis of hyperspectral vegetation indices

Bing Zhang, Xia Zhang, Tuanjie Liu, Genxing Xu, Lanfen Zheng, Qingxi Tong

Proceedings Volume 4548, (2001) https://doi.org/10.1117/12.441363

KEYWORDS: Vegetation, Nitrogen, Remote sensing, Reflectivity, Agriculture, Meteorological satellites, CCD cameras, Temporal resolution, Visible radiation, Sensors

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Proceedings Article | 20 September 2001 Paper

Kernel adaptive filter (SRSSHF) and quality improvement method for hyperspectral imaging based on spectral dimension recognition and spatial dimension smoothing according to CSAM

Yongchao Zhao, Qingxi Tong, Lanfen Zheng, Bing Zhang, Xia Zhang, Jiwei Bai, Chuanqing Wu, Tuanjie Liu

Proceedings Volume 4552, (2001) https://doi.org/10.1117/12.441522

KEYWORDS: Image filtering, Digital filtering, Hyperspectral imaging, Image quality, Optical filters, Speckle, Linear filtering, Image processing, Convolution, Reflectivity

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Proceedings Article | 8 February 2001 Paper

New progress in study on vegetation models for hyperspectral remote sensing

Qingxi Tong, Yongchao Zhao, Xia Zhang, Bing Zhang, Lanfen Zheng

Proceedings Volume 4151, (2001) https://doi.org/10.1117/12.417002

KEYWORDS: Vegetation, Reflectivity, Remote sensing, Hyperspectral imaging, Image processing, Agriculture, Spectral models, Algorithm development, Sensors, Spectral resolution

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Showing 5 of 23 publications

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