研究目的
To reduce erroneous and redundant extraction of water body information by suppressing classification noise from mountain shadows, buildings, and other irrelevant features, and to solve issues of accuracy verification and inefficiency in river information extraction.
研究成果
The OSTWI method effectively extracts mountain river information with a relative accuracy of 97.52%, reducing interference from shadows and buildings. It outperforms previous methods but has limitations in handling mixed pixels and threshold calculation, with potential for application to other Landsat images in future research.
研究不足
Due to the limitation of remote sensing image resolution, some mixed pixels such as low reflectivity buildings are difficult to completely remove. In addition, the calculation of some thresholds is still in the stage of combining qualitative and quantitative, and there are still opportunities for further improvement. The method is currently only used for Landsat8 images.
1：Experimental Design and Method Selection:
The study uses an optimized spectral threshold water index (OSTWI) model for river extraction, combined with digital elevation model (DEM) data for shadow simulation and buffer zone establishment, and employs land surface temperature (LST), albedo, and normalized difference building index (NDBI) for building removal.
2：Sample Selection and Data Sources:
Data includes Landsat8 OLI imagery and 30-m resolution DEM from the geospatial data cloud (http://www.gscloud.cn), with the study area being the Chejia River watershed in Guizhou Province, China.
3：List of Experimental Equipment and Materials:
Software tools such as ENVI for band math and ArcGIS10.2 for spatial analysis are used; no specific hardware is mentioned.
4：2 for spatial analysis are used; no specific hardware is mentioned. Experimental Procedures and Operational Workflow:
4. Experimental Procedures and Operational Workflow: Steps include radiometric calibration and atmospheric correction of images, image fusion using Gram-Schmidt method, DEM processing for river network extraction and shadow simulation, threshold determination from histograms, and overlay of normalized data for final extraction.
5：Data Analysis Methods:
Area accuracy verification is used instead of confusion matrix, with relative accuracy calculated based on area ratios from sample regions compared to Google Earth imagery.
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