Dr. Huan Li Profile

Dr. Huan Li

at Hohai Univ

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SPIE Journal Paper | 8 July 2013

Predicting water content using linear spectral mixture model on soil spectra

Huan Li, Changkuan Zhang, Ying Zhang, Dong Zhang, Jay Gao, Zheng Gong

JARS, Vol. 7, Issue 01, 073539, (July 2013) https://doi.org/10.1117/12.10.1117/1.JRS.7.073539

KEYWORDS: Soil science, Reflectivity, Spectral models, Particles, Statistical modeling, Data modeling, Remote sensing, Statistical analysis, Spectroscopy, Error analysis

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Remote sensing has been widely applied for soil moisture estimation. However, such estimates become difficult to obtain and can be inaccurate when applied to complex earth surfaces with more than one soil type because of the interference of spectral signals from different soil components. This study aims to develop a moisture prediction method that is insensitive to soil types; this is based on in situ samples collected from an intertidal zone in Jiangsu Province in China and on laboratory measurements of soil spectra. The results demonstrate that for a reflectance-based method, moisture content is closely related to reflectance on the three wavebands centered at 2143, 1760, and 742 nm for four types of soil (sand, silty sand, sandy silt, and silt) considered separately; the relationship is not close if all soil types are mixed together (R 2 =0.77 ). To develop the desired model, a linear spectral mixture model (LSMM) was employed to extract parameter water abundance (Wa: information on soil water content) in advance, while eliminating redundant information from other soil components. Wa has a relatively higher correlation (R 2 =0.82 ) than reflectance with moisture content for a mixed soil type. Thus, employing the LSMM helps realize a practical water content estimation model for predicting moisture over complex earth surfaces, because it has the potential of eliminating spectral effects from soil components.

Proceedings Article | 21 November 2012 Paper

A compound method for automatically extracting plateau wetlands from satellite imagery

Huan Li, Jay Gao

Proceedings Volume 8524, 852409 (2012) https://doi.org/10.1117/12.977286

KEYWORDS: Satellites, Composites, Satellite imaging, Earth observing sensors, Vegetation, Remote sensing, Environmental sensing, Landsat, Spatial resolution, Roads

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Timely information on wetland distribution can be effectively acquired by means of remote sensing. A Landsat TM image recorded on 17 July 2009 (row: 36; column: 134) at a spatial resolution of 30 m was used to map wetlands in Maduo County of northwestern Qinghai Province with a combined method of thresholding, tassled cap transformation and vegetation indexing. The wetlands found in the study area fall into two broad types, I and II. Type I wetlands are characterized by a close proximity to water bodies. Type II wetlands are characterized by a higher vegetative component that obscures their morphology. Thresholding was used to map type I wetlands from TM5. Tasseled Cap transformation was used to map type II wetlands. With the assistance of NDVI, snow was then removed, leaving only grassland and type II wetland to be separate. Type 1 wetland was mapped at 832 km². The second type of wetland was mapped at 422.97 km². A total of 1254.97 km² wetlands were mapped. Comparison with the raw color composite of the same image reveals that the mapping has been accomplished quite accuracy. More research will be undertaken to compare the classified results with those obtained with supervised and unsupervised results. Both thresholding and Tassled cap transformation are found to be effective at detecting different types of wetlands in the plateau environment

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