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Xusheng Tang

Publications and source records attributed to Xusheng Tang.

2 recordsLinked to original sources

Using GeoAI and machine learning tools for consistent high-resolution land cover mapping based on time-series NAIP imagery

High-resolution land-cover maps support ecological monitoring, but consistent historical time series remain scarce because aerial imagery varies across years and sensors. We developed a dual-track workflow to produce temporally coherent 1-m land-cover maps from National Agricultural Imagery Program (NAIP) imagery without historical training samples. For higher-quality imagery from 2009-2017, we used a pretrained U-Net/ResNet-34 model and refined boundaries with the Segment Anything Model (SAM). For lower-quality imagery from 2004-2008, we reconstructed land cover through an NLCD-based spatiotemporal bridging and label back-casting pipeline. Evaluation across six counties in North Carolina and Pennsylvania yielded overall accuracies of 0.887 (2014), 0.886 (2017), and 0.733 (2004). Structure, Water, Wetland, and Cropland consistently achieved high F1-scores. The workflow integrates GeoAI and multiple data sources to address temporal heterogeneity in historical aerial imagery, supporting high-resolution land-change analysis and landscape planning across the conterminous United States.

cs.CV↗

Ultra-high-speed line-scan Raman imaging

Raman spectroscopic imaging has emerged as a potent tool due to its non-invasive nature and capability for chemical composition analysis. Line-scan Raman spectroscopy accelerates imaging speed by two orders of magnitude compared to point detection Raman methods. However, further enhancements in imaging speed were constrained by the readout speed of typically used charge-coupled device (CCD) spectroscopic detectors. We developed an ultra-fast line-scan Raman imaging technique based on recently available complementary metal-oxide-semiconductor (CMOS) detectors with low cost and read noise, and fast readout during exposure combined with a global shutter. Employing a high-efficiency transmissiongrating imaging spectrometer, we demonstrate imaging speeds up to two orders of magnitude faster than traditional line scan Raman imaging techniques and up to four orders of magnitude faster than point scan Raman methods, achieving Raman imaging up to 80 kHz spectral rate. We demonstrate that this technology is applicable to a variety of samples, including microplastics, biological cells, and tablets, creating images in an extremely short time frame, showcasing exceptional detection capabilities and the ability to reveal detailed information.

physics.optics↗