CSLE model optimization algorithm for improving T factor based on deep learning

• Main Authors: JIA TINGHUI, YANG YANPAN, TIAN PEI, CHEN YAN, PING YAODONG
• Format: Patent
• Language: Chinese; English
• Published: 19.03.2024
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; ELECTRIC DIGITAL DATA PROCESSING; IMAGE DATA PROCESSING OR GENERATION, IN GENERAL; PHYSICS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

The invention discloses a CSLE model optimization algorithm for improving a T factor based on deep learning, and the algorithm employs DEM data to generate a gradient grading graph, and employs median filtering to remove the salt and pepper noise of a neighborhood pattern spot in image fusion. On the basis, slope grading is carried out on the water and soil conservation measure cultivated land pattern spots in the verified T factor value through a processed slope grading graph, assignment is carried out in combination with a slope grading result, and the T factor value which conforms to the actual water and soil conservation measure configuration condition of the research area and is higher in precision is obtained. According to the method, the accuracy of calculating the soil erosion amount and the soil erosion space distribution by using the CSLE model can be improved and improved, large errors and mistakes possibly brought by manual visual interpretation are reduced, the T factor calculation method is refi