In polar regions, cloud and underlying ice-snow areas are difficult to distinguish in satellite images because of their high albedo in the visible band and low surface temperature of ice-snow areas in the infrared ban...In polar regions, cloud and underlying ice-snow areas are difficult to distinguish in satellite images because of their high albedo in the visible band and low surface temperature of ice-snow areas in the infrared band. A cloud detection method over ice-snow covered areas in Antarctica is presented. On account of different texture features of cloud and ice-snow areas, five texture features are extracted based on GLCM. Nonlinear SVM is then used to obtain the optimal classification hyperplane from training data. The experiment results indicate that this algorithm performs well in cloud detection in Antarctica, especially for thin cirrus detection. Furthermore, when images are resampled to a quarter or 1/16 of the full size, cloud percentages are still at the same level, while the processing time decreases exponentially.展开更多
In order to ensure the working performance of the seeder,reduce the labor intensity of manual testing,and improve the efficiency and accuracy of the detection,a real-time detection system for detecting the performance...In order to ensure the working performance of the seeder,reduce the labor intensity of manual testing,and improve the efficiency and accuracy of the detection,a real-time detection system for detecting the performance of no-till seeders was designed based on the LabVIEW software platform of virtual instrument technology and the MCC USB-231 data acquisition card.The detection system can be used to detect the seeding quality index and residue cover index.The detection of the seeding quality index included the middle detection between the metering device and the opener,the end detection between the opener and the furrow.The result of the field test showed that the detection accuracies of seed quantity,multiple index,and miss index were 94.51%,92.83%,and 91.81%,respectively.The fault position can be accurately determined,and the measurement accuracy of residue cover index was 94.54%.The working performance of the no-tillage seeder can be monitored by the detection system to avoid the occurrence of reseeding and miss-seeding and improve production efficiency.展开更多
基金Supported by the Antarctic Geography Information Acquisition and Environmental Change Research of China (No.14601402024-04-06).
文摘In polar regions, cloud and underlying ice-snow areas are difficult to distinguish in satellite images because of their high albedo in the visible band and low surface temperature of ice-snow areas in the infrared band. A cloud detection method over ice-snow covered areas in Antarctica is presented. On account of different texture features of cloud and ice-snow areas, five texture features are extracted based on GLCM. Nonlinear SVM is then used to obtain the optimal classification hyperplane from training data. The experiment results indicate that this algorithm performs well in cloud detection in Antarctica, especially for thin cirrus detection. Furthermore, when images are resampled to a quarter or 1/16 of the full size, cloud percentages are still at the same level, while the processing time decreases exponentially.
基金supported by the National Natural Science Foundation of China(Grant No.51865022)General project of Yunnan Provincial Department of science and technology(No.2015FB125).
文摘In order to ensure the working performance of the seeder,reduce the labor intensity of manual testing,and improve the efficiency and accuracy of the detection,a real-time detection system for detecting the performance of no-till seeders was designed based on the LabVIEW software platform of virtual instrument technology and the MCC USB-231 data acquisition card.The detection system can be used to detect the seeding quality index and residue cover index.The detection of the seeding quality index included the middle detection between the metering device and the opener,the end detection between the opener and the furrow.The result of the field test showed that the detection accuracies of seed quantity,multiple index,and miss index were 94.51%,92.83%,and 91.81%,respectively.The fault position can be accurately determined,and the measurement accuracy of residue cover index was 94.54%.The working performance of the no-tillage seeder can be monitored by the detection system to avoid the occurrence of reseeding and miss-seeding and improve production efficiency.
