The research was carried out on the territory of the Karelian Isthmus of the Leningrad Region using Sentinel-2B images and data from a network of ground sample plots. The ground sample plots are located in the studied...The research was carried out on the territory of the Karelian Isthmus of the Leningrad Region using Sentinel-2B images and data from a network of ground sample plots. The ground sample plots are located in the studied territory mainly in a regular manner, laid and surveyed according to the ICP-Forests methodology with some additions. The total area of the sample plots is a small part of the entire study area. One of the objectives of the study was to determine the possibility of using the k-NN (nearest neighbor method) to assess the state of forests throughout the whole studied territory by joint statistical processing of data from ground sample plots and Sentinel-2B imagery. The data of the ground-based sample plots were divided into 2 equal parts, one for the application of the k-NN method, the second for checking the results of the method application. The systematic error in determining the mean damage class of the tree stands on sample plots by the k-NN method turned out to be zero, the random error is equal to one point. These results offer a possibility to determine the state of the forest in the entire study area. The second objective of the study was to examine the possibility of using the short-wave vegetation index (SWVI) to assess the state of forests. As a result, a close statistically reliable dependence of the average score of the state of plantations and the value of the SWVI index was established, which makes it possible to use the established relationship to determine the state of forests throughout the studied territory. The joint use and statistical processing of remotely sensed data and ground-based test areas by the two studied methods make it possible to assess the state of forests throughout the large studied area within the image. The results obtained can be used to monitor the state of forests in large areas and design appropriate forestry protective measures.展开更多
Poincare dispersed dot plot was an important method in studying heart nonlinear state and rate variability(HRV). Based on the shape of Poincare dispersed dot plot, we proposed four quantitative parameters, introduced ...Poincare dispersed dot plot was an important method in studying heart nonlinear state and rate variability(HRV). Based on the shape of Poincare dispersed dot plot, we proposed four quantitative parameters, introduced the method and algorithm how to get them, and tested them with clinical and animal experiment data. The result showed that these four parameters have certain idiosyncrasy with different heart diseases, and the animal experiment result also showed that these parameters were changed remarkably after coronary artery ligation compared with before, which indicated these parameters might be useful for clinical diagnosis. Because the algorithm we used was based only on the shape of the graph, one can apply this algorithm on any other type of graphs like Poincare dispersed dot plot.展开更多
文摘The research was carried out on the territory of the Karelian Isthmus of the Leningrad Region using Sentinel-2B images and data from a network of ground sample plots. The ground sample plots are located in the studied territory mainly in a regular manner, laid and surveyed according to the ICP-Forests methodology with some additions. The total area of the sample plots is a small part of the entire study area. One of the objectives of the study was to determine the possibility of using the k-NN (nearest neighbor method) to assess the state of forests throughout the whole studied territory by joint statistical processing of data from ground sample plots and Sentinel-2B imagery. The data of the ground-based sample plots were divided into 2 equal parts, one for the application of the k-NN method, the second for checking the results of the method application. The systematic error in determining the mean damage class of the tree stands on sample plots by the k-NN method turned out to be zero, the random error is equal to one point. These results offer a possibility to determine the state of the forest in the entire study area. The second objective of the study was to examine the possibility of using the short-wave vegetation index (SWVI) to assess the state of forests. As a result, a close statistically reliable dependence of the average score of the state of plantations and the value of the SWVI index was established, which makes it possible to use the established relationship to determine the state of forests throughout the studied territory. The joint use and statistical processing of remotely sensed data and ground-based test areas by the two studied methods make it possible to assess the state of forests throughout the large studied area within the image. The results obtained can be used to monitor the state of forests in large areas and design appropriate forestry protective measures.
基金This project is supported by the National Natural Science Foundation of China(No.3 9970 2 0 5)
文摘Poincare dispersed dot plot was an important method in studying heart nonlinear state and rate variability(HRV). Based on the shape of Poincare dispersed dot plot, we proposed four quantitative parameters, introduced the method and algorithm how to get them, and tested them with clinical and animal experiment data. The result showed that these four parameters have certain idiosyncrasy with different heart diseases, and the animal experiment result also showed that these parameters were changed remarkably after coronary artery ligation compared with before, which indicated these parameters might be useful for clinical diagnosis. Because the algorithm we used was based only on the shape of the graph, one can apply this algorithm on any other type of graphs like Poincare dispersed dot plot.
