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
Regular grid of permanent sample plots (PSP) of ICP-Forests monitoring system was used for forest ecosystems biodiversity assessments and inventory. The supplementary features were added to the PSP structure to conduc...Regular grid of permanent sample plots (PSP) of ICP-Forests monitoring system was used for forest ecosystems biodiversity assessments and inventory. The supplementary features were added to the PSP structure to conduct biological diversity census: eight sample plots 1 × 1 m for geo-botanical description;two sample plots of 5 × 5 m each for description of the PSP’s undergrowth;one 25 × 25 m plot for coarse woody debris estimations;four soil inventory pits. The total number of PSP amounted to 248. Total data used are as following: 1) 1984 geo-botanical descriptions of vegetation belonging to ground cover layers made on 1 × 1 m sample plots;2) 496 descriptions of undergrowth on 5 × 5 m sample plots;3) 178 descriptions of woody debris on 25 × 25 m sample plots;4) 496 descriptions of soil inventory pits. General statistical indicators characterizing forest land cover diversity were calculated. Statistic indicators of α-diversity for the Karelian Isthmus forest vegetation cover have the following values: 1) m (mean number of species per PSP) = 26 species;2) σ (standard deviation) = 9.5 species;3) v (variation coefficient) = 36.5%;4) Р (deviation amplitude) = 60 – 7 = 53 species. β – diversity of forest ecosystems as well as γ – diversity also was studied on the base of information collected on the same regular grid of sample plots. It appears that sample plots distribution by species diversity gradation is well described by the standard curve of normal distribution for the entire Karelian Isthmus forest (determination coefficient of the curve being 95.2%) as well as for each type of forest. Hence, the criterion (standard) of biodiversity for forest ecosystems can be defined as the mean value of alpha diversity for each forest type group – m;and the standard deviation – σ, as a tool for assessing deviations from the standard. PSP locations are fixed using GPS technology, this allows biodiversity assessments at the same place in the next years for biodiversity trends estimations and consist the frame for systematic biodiversity inventory.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.
文摘Regular grid of permanent sample plots (PSP) of ICP-Forests monitoring system was used for forest ecosystems biodiversity assessments and inventory. The supplementary features were added to the PSP structure to conduct biological diversity census: eight sample plots 1 × 1 m for geo-botanical description;two sample plots of 5 × 5 m each for description of the PSP’s undergrowth;one 25 × 25 m plot for coarse woody debris estimations;four soil inventory pits. The total number of PSP amounted to 248. Total data used are as following: 1) 1984 geo-botanical descriptions of vegetation belonging to ground cover layers made on 1 × 1 m sample plots;2) 496 descriptions of undergrowth on 5 × 5 m sample plots;3) 178 descriptions of woody debris on 25 × 25 m sample plots;4) 496 descriptions of soil inventory pits. General statistical indicators characterizing forest land cover diversity were calculated. Statistic indicators of α-diversity for the Karelian Isthmus forest vegetation cover have the following values: 1) m (mean number of species per PSP) = 26 species;2) σ (standard deviation) = 9.5 species;3) v (variation coefficient) = 36.5%;4) Р (deviation amplitude) = 60 – 7 = 53 species. β – diversity of forest ecosystems as well as γ – diversity also was studied on the base of information collected on the same regular grid of sample plots. It appears that sample plots distribution by species diversity gradation is well described by the standard curve of normal distribution for the entire Karelian Isthmus forest (determination coefficient of the curve being 95.2%) as well as for each type of forest. Hence, the criterion (standard) of biodiversity for forest ecosystems can be defined as the mean value of alpha diversity for each forest type group – m;and the standard deviation – σ, as a tool for assessing deviations from the standard. PSP locations are fixed using GPS technology, this allows biodiversity assessments at the same place in the next years for biodiversity trends estimations and consist the frame for systematic biodiversity inventory.
