Since the launch of the Google Earth Engine(GEE)cloud platform in 2010,it has been widely used,leading to a wealth of valuable information.However,the potential of GEE for forest resource management has not been fully...Since the launch of the Google Earth Engine(GEE)cloud platform in 2010,it has been widely used,leading to a wealth of valuable information.However,the potential of GEE for forest resource management has not been fully exploited.To extract dominant woody plant species,GEE combined Sen-tinel-1(S1)and Sentinel-2(S2)data with the addition of the National Forest Resources Inventory(NFRI)and topographic data,resulting in a 10 m resolution multimodal geospatial dataset for subtropical forests in southeast China.Spectral and texture features,red-edge bands,and vegetation indices of S1 and S2 data were computed.A hierarchical model obtained information on forest distribution and area and the dominant woody plant species.The results suggest that combining data sources from the S1 winter and S2 yearly ranges enhances accuracy in forest distribution and area extraction compared to using either data source independently.Similarly,for dominant woody species recognition,using S1 winter and S2 data across all four seasons was accurate.Including terrain factors and removing spatial correlation from NFRI sample points further improved the recognition accuracy.The optimal forest extraction achieved an overall accuracy(OA)of 97.4%and a maplevel image classification efficacy(MICE)of 96.7%.OA and MICE were 83.6%and 80.7%for dominant species extraction,respectively.The high accuracy and efficacy values indicate that the hierarchical recognition model based on multimodal remote sensing data performed extremely well for extracting information about dominant woody plant species.Visualizing the results using the GEE application allows for an intuitive display of forest and species distribution,offering significant convenience for forest resource monitoring.展开更多
The physiological characteristics of trees change with age,suggesting that growth-related climate signals vary over time.This study aimed to clarify the impacts of different diameter classes on the chronological chara...The physiological characteristics of trees change with age,suggesting that growth-related climate signals vary over time.This study aimed to clarify the impacts of different diameter classes on the chronological characteristics of Pinus massoniana Lamb.and its response to climatic factors.Chronologies of P inus massoniana were established in small diameter(14.1 cm),middle diameter(27.3 cm),and large diameter(34.6 cm)trees according to dendrochronology.The results show that:(1)radial growth of different diameter classes had varied characteristics and climate sensitivities;(2)radial growth of small diameter trees was affected by climatic factors of the previous and the current year,while large diameter trees were mainly affected by climatic factors of the current year;and(3)precipitation and temperature were key factors that restricted the radial growth of small and large diameter trees,respectively.展开更多
Warm-wet climatic conditions are widely regarded as conducive to remarkable tree growth,alleviating climatic pressures.However,the notable decline in tree growth observed in the southern edge of boreal forests has hei...Warm-wet climatic conditions are widely regarded as conducive to remarkable tree growth,alleviating climatic pressures.However,the notable decline in tree growth observed in the southern edge of boreal forests has heightened concerns over the spatial-temporal dynamics of forest decline.Currently,attaining a comprehensive grasp of the underlying patterns and their propelling factors remains a formidable challenge.We collected tree ring samples from a network of 50 sites across the Greater Xing'an Mountains.These samples were subsequently grouped into two distinct clusters,designated as Groups A and B.The percentage change of growth(GC,%)and the proportion of declining sites were utilized to assess forest decline.The decline in tree growth within Larix gmelinii forests exhibits significant regional variation,accompanied by temporal fluctuations even within a given region.Group A exhibited a pronounced increase in frequency(59.26%)of occurrences and encountered more severe declines(21.65%)in tree growth subsequent to the 1990s,contrasting sharply with Group B,which observed lower frequencies(20.00%)and relatively less severe declines(21.02%)prior to the 1980s.The primary impetus underlying the opposite radial growth increments observed in Larix gmelinii trees from the interplay between their differential response to temperatures and wetter climatic conditions,which is significantly influenced by varying stand densities.In cold-dry conditions,low-density forests may experience soil water freezing,exacerbating drought conditions and thereby inhibiting tree growth,in Group B.Trees growth in high-density stands is restrained by warm-wet conditions,in Group A.These results provide new insights into the variability at the southern edge of the boreal forest biome with different responses to density and climate.展开更多
Quantifying forest stand parameters is crucial in forestry research and environmental monitoring because it provides important factors for analyzing forest structure and comprehending forest resources.And the estimati...Quantifying forest stand parameters is crucial in forestry research and environmental monitoring because it provides important factors for analyzing forest structure and comprehending forest resources.And the estimation of crown density and volume has always been a prominent topic in forestry remote sensing.Based on GF-2 remote sensing data,sample plot survey data and forest resource survey data,this study used the Chinese fir(Cunninghamia lanceolata(Lamb.)Hook.)and Pinus massoniana Lamb.as research objects to tackle the key challenges in the use of remote sensing technology.The Boruta feature selection technique,together with multiple stepwise and Cubist regression models,was used to estimate crown density and volume in portions of the research area’s stands,introducing novel technological methods for estimating stand parameters.The results show that:(i)the Boruta algorithm is effective at selecting the feature set with the strongest correlation with the dependent variable,which solves the problem of data and the loss of original feature data after dimensionality reduction;(ii)using the Cubist method to build the model yields better results than using multiple stepwise regression.The Cubist regression model’s coefficient of determination(R^(2))is all more than 0.67 in the Chinese fir plots and 0.63 in the P.massoniana plots.As a result,combining the two methods can increase the estimation accuracy of stand parameters,providing a theoretical foundation and technical support for future studies.展开更多
Digital aerial photograph(DAP)data is processed based on Structure from Motion(Sf M)algorithm and regional net adjustment method to generate digital surface discrete point clouds similar to Light Detection and Ranging...Digital aerial photograph(DAP)data is processed based on Structure from Motion(Sf M)algorithm and regional net adjustment method to generate digital surface discrete point clouds similar to Light Detection and Ranging(LiDAR)and digital orthophoto mosaic(DOM)similar to optical remote sensing image.In this study,we obtained highresolution images of mature forests of Chinese fir by unmanned aerial vehicle(UAV)flying through crossroute flight,and then reconstructed the threedimensional point clouds in the UAV aerial area by SfM technique.The point cloud segmentation(PCS)algorithm was used for the individual tree segmentation,and the F-score of the three sample plots were 0.91,0.94,and 0.94,respectively.Individual tree biomass modeling was conducted using 155 mature Chinese fir forests which were correctly segmented.The relative root mean squared error(rRMSE)values of random forest(RF),bagged tree(BT)and support vector regression(SVR)were 34.48%,35.74%and 40.93%,respectively.Our study demonstrated that DAP point clouds had great potential to extract forest vertical parameters and could be applied successfully in individual tree segmentation and individual tree biomass modeling.展开更多
A peak is an important topographic feature crucial in quantitative geomorphic feature analysis,digital geomorphological mapping,and other fields.Most peak extraction methods are based on the maximum elevation in a loc...A peak is an important topographic feature crucial in quantitative geomorphic feature analysis,digital geomorphological mapping,and other fields.Most peak extraction methods are based on the maximum elevation in a local area but ignore the morphological characteristics of the peak area.This paper proposes three indices based on the morphological characteristics of peaks and their spatial relationship with ridge lines:convexity mean index(CM-index),convexity standard deviation(CSD-index),and convexity imbalance index(CIBindex).We develop computation methods to extract peaks from digital elevation model(DEM).Subsequently,the initial peaks extracted by neighborhood statistics are classified using the proposed indices.The method is evaluated in the Qinghai Tibet Plateau and the Loess Plateau in China.An ASTER Global DEM(ASTGTM2 DEM)with a grid size of 30 m is chosen to assess the suitability of the proposed mountain peak extraction and classification method in different geomorphic regions.DEM data with grid sizes of 30 m and 5 m are used for the Loess Plateau.The mountain peak extraction and classification results obtained from the different resolution DEM are compared.The experimental results show that:(1)The CM-index and the CSDindex accurately reflect the concave or convex morphology of the surface and can be used as supplements to existing surface morphological indices.(2)The three indices can identify pseudo mountain peaks and classify the remaining peaks into single ridge peak(SR-Peak)and multiple ridge intersection peak(MRI-Peak).The visual inspection results show that the classification accuracy in the different study areas exceeds 75%.(3)The number of peaks is significantly higher for the 5 m DEM than for the 30 m DEM because more peaks can be detected at a finer resolution.展开更多
Background:The relationship between climate and radial growth of trees exhibits spatial variation due to environ-mental changes.Therefore,elucidation of how the growth–climate responses of trees vary in space is esse...Background:The relationship between climate and radial growth of trees exhibits spatial variation due to environ-mental changes.Therefore,elucidation of how the growth–climate responses of trees vary in space is essential for understanding forest growth dynamics to facilitate scientific management with the ongoing global climate warming.To explore the altitudinal and slope variations of these interactions,tree-ring width chronologies of Larix olgensis A.Henry were analyzed in the southern Lesser Khingan Mountains,Northeast China.Results:The radial growth of L.olgensis exhibited significant 5-to 10-year periodic changes at three altitudes and two slopes,and the frequency change occurred mainly during the early growth stage and after 2000.The radial growth of L.olgensis was significantly negatively correlated with September precipitation only at low altitudes,but also with the mean temperature in July–August and the mean maximum temperature in June–August at high altitudes.The radial growth of L.olgensis at low and middle altitudes as well as on the sunny slope led to a higher demand for moisture,while temperature was the key limiting factor at high altitudes and on the shady slope.Conclusions:The climate–radial growth relationship of L.olgensis exhibits altitudinal and slope variability.This study quantitatively describes the spatially varying growth–climate responses of L.olgensis in the southern Lesser Khingan Mountains,which provides basic data for the management of L.olgensis forests and the prediction of future climate impacts on forest ecosystems.展开更多
Brandt et al.reported the results of their analysis from high-resolution satellite images,covering more than 1.3 million square kilometers of the Western Sahara and Sahel in West Africa.They mapped the locations and s...Brandt et al.reported the results of their analysis from high-resolution satellite images,covering more than 1.3 million square kilometers of the Western Sahara and Sahel in West Africa.They mapped the locations and sizes of approximately 1.8 billion trees.Prior to this,scientists had never made such a detailed map of trees in such a large area.Commercial satellites have begun to collect data and can detect small ground objects that are 1 square meter or less in size.Therefore,the field of terrestrial remote sensing may have a significant advance from mainly a comprehensive landscape-scale measurement to mapping the position and canopy size of each tree at a regional or even global scale.This progress will revolutionize how we think,monitor,simulate,and manage the global terrestrial ecosystem.展开更多
基金supported by the National Technology Extension Fund of Forestry,Forest Vegetation Carbon Storage Monitoring Technology Based on Watershed Algorithm ([2019]06)Fundamental Research Funds for the Central Universities (No.PTYX202107).
文摘Since the launch of the Google Earth Engine(GEE)cloud platform in 2010,it has been widely used,leading to a wealth of valuable information.However,the potential of GEE for forest resource management has not been fully exploited.To extract dominant woody plant species,GEE combined Sen-tinel-1(S1)and Sentinel-2(S2)data with the addition of the National Forest Resources Inventory(NFRI)and topographic data,resulting in a 10 m resolution multimodal geospatial dataset for subtropical forests in southeast China.Spectral and texture features,red-edge bands,and vegetation indices of S1 and S2 data were computed.A hierarchical model obtained information on forest distribution and area and the dominant woody plant species.The results suggest that combining data sources from the S1 winter and S2 yearly ranges enhances accuracy in forest distribution and area extraction compared to using either data source independently.Similarly,for dominant woody species recognition,using S1 winter and S2 data across all four seasons was accurate.Including terrain factors and removing spatial correlation from NFRI sample points further improved the recognition accuracy.The optimal forest extraction achieved an overall accuracy(OA)of 97.4%and a maplevel image classification efficacy(MICE)of 96.7%.OA and MICE were 83.6%and 80.7%for dominant species extraction,respectively.The high accuracy and efficacy values indicate that the hierarchical recognition model based on multimodal remote sensing data performed extremely well for extracting information about dominant woody plant species.Visualizing the results using the GEE application allows for an intuitive display of forest and species distribution,offering significant convenience for forest resource monitoring.
基金supported by the National Natural Science Foundation of China(No.31870620)the National Technology Extension Fund of Forestry([2019]06)the Fundamental Research Funds for the Central Universities(No.PTYX202107)。
文摘The physiological characteristics of trees change with age,suggesting that growth-related climate signals vary over time.This study aimed to clarify the impacts of different diameter classes on the chronological characteristics of Pinus massoniana Lamb.and its response to climatic factors.Chronologies of P inus massoniana were established in small diameter(14.1 cm),middle diameter(27.3 cm),and large diameter(34.6 cm)trees according to dendrochronology.The results show that:(1)radial growth of different diameter classes had varied characteristics and climate sensitivities;(2)radial growth of small diameter trees was affected by climatic factors of the previous and the current year,while large diameter trees were mainly affected by climatic factors of the current year;and(3)precipitation and temperature were key factors that restricted the radial growth of small and large diameter trees,respectively.
基金National Nature Science Foundation of China(No.32371871)。
文摘Warm-wet climatic conditions are widely regarded as conducive to remarkable tree growth,alleviating climatic pressures.However,the notable decline in tree growth observed in the southern edge of boreal forests has heightened concerns over the spatial-temporal dynamics of forest decline.Currently,attaining a comprehensive grasp of the underlying patterns and their propelling factors remains a formidable challenge.We collected tree ring samples from a network of 50 sites across the Greater Xing'an Mountains.These samples were subsequently grouped into two distinct clusters,designated as Groups A and B.The percentage change of growth(GC,%)and the proportion of declining sites were utilized to assess forest decline.The decline in tree growth within Larix gmelinii forests exhibits significant regional variation,accompanied by temporal fluctuations even within a given region.Group A exhibited a pronounced increase in frequency(59.26%)of occurrences and encountered more severe declines(21.65%)in tree growth subsequent to the 1990s,contrasting sharply with Group B,which observed lower frequencies(20.00%)and relatively less severe declines(21.02%)prior to the 1980s.The primary impetus underlying the opposite radial growth increments observed in Larix gmelinii trees from the interplay between their differential response to temperatures and wetter climatic conditions,which is significantly influenced by varying stand densities.In cold-dry conditions,low-density forests may experience soil water freezing,exacerbating drought conditions and thereby inhibiting tree growth,in Group B.Trees growth in high-density stands is restrained by warm-wet conditions,in Group A.These results provide new insights into the variability at the southern edge of the boreal forest biome with different responses to density and climate.
基金supported by the project of the National Technology Extension Fund of Forestry,‘Forest Vegetation Carbon Storage Monitoring Technology Based on Watershed Algorithm’([2019]06)the National Natural Science Foundation of China,‘Study on Crown Models for Larix olgensis Based on Tree Growth’(31870620).
文摘Quantifying forest stand parameters is crucial in forestry research and environmental monitoring because it provides important factors for analyzing forest structure and comprehending forest resources.And the estimation of crown density and volume has always been a prominent topic in forestry remote sensing.Based on GF-2 remote sensing data,sample plot survey data and forest resource survey data,this study used the Chinese fir(Cunninghamia lanceolata(Lamb.)Hook.)and Pinus massoniana Lamb.as research objects to tackle the key challenges in the use of remote sensing technology.The Boruta feature selection technique,together with multiple stepwise and Cubist regression models,was used to estimate crown density and volume in portions of the research area’s stands,introducing novel technological methods for estimating stand parameters.The results show that:(i)the Boruta algorithm is effective at selecting the feature set with the strongest correlation with the dependent variable,which solves the problem of data and the loss of original feature data after dimensionality reduction;(ii)using the Cubist method to build the model yields better results than using multiple stepwise regression.The Cubist regression model’s coefficient of determination(R^(2))is all more than 0.67 in the Chinese fir plots and 0.63 in the P.massoniana plots.As a result,combining the two methods can increase the estimation accuracy of stand parameters,providing a theoretical foundation and technical support for future studies.
基金grants from the National Natural Science Foundation of China(No.31870620)the Fundamental Research Funds for the Central Universities(No.PTYX202107)the National Technology Extension Fund of Forestry([2019]06)。
文摘Digital aerial photograph(DAP)data is processed based on Structure from Motion(Sf M)algorithm and regional net adjustment method to generate digital surface discrete point clouds similar to Light Detection and Ranging(LiDAR)and digital orthophoto mosaic(DOM)similar to optical remote sensing image.In this study,we obtained highresolution images of mature forests of Chinese fir by unmanned aerial vehicle(UAV)flying through crossroute flight,and then reconstructed the threedimensional point clouds in the UAV aerial area by SfM technique.The point cloud segmentation(PCS)algorithm was used for the individual tree segmentation,and the F-score of the three sample plots were 0.91,0.94,and 0.94,respectively.Individual tree biomass modeling was conducted using 155 mature Chinese fir forests which were correctly segmented.The relative root mean squared error(rRMSE)values of random forest(RF),bagged tree(BT)and support vector regression(SVR)were 34.48%,35.74%and 40.93%,respectively.Our study demonstrated that DAP point clouds had great potential to extract forest vertical parameters and could be applied successfully in individual tree segmentation and individual tree biomass modeling.
基金supported by Anhui Province Universities Outstanding Talented Person Support Project(No.gxyq2022097)Major Project of Natural Science Research of Anhui Provincial Department of Education(No.2022AH040150,No.KJ2021ZD0130,No.KJ2021ZD0131)+5 种基金Key Project of Natural Science Research of Anhui Provincial Department of Education(Grant No.KJ2020A0721)The guiding plan project of Chuzhou science and Technology Bureau(No.2021ZD008)“113”Industry Innovation Team of Chuzhou city in Anhui provincethe Project of Natural Science Research of An-hui Provincial Department of Education(No.2022AH030112,No.2022AH040156)the Academic Foundation for Top Talents in Disciplines of Anhui Universities(No.gxbj ZD2022069)the Innovation Program for Returned Overseas Chinese Scholars of Anhui Province(No.2021LCX014)。
文摘A peak is an important topographic feature crucial in quantitative geomorphic feature analysis,digital geomorphological mapping,and other fields.Most peak extraction methods are based on the maximum elevation in a local area but ignore the morphological characteristics of the peak area.This paper proposes three indices based on the morphological characteristics of peaks and their spatial relationship with ridge lines:convexity mean index(CM-index),convexity standard deviation(CSD-index),and convexity imbalance index(CIBindex).We develop computation methods to extract peaks from digital elevation model(DEM).Subsequently,the initial peaks extracted by neighborhood statistics are classified using the proposed indices.The method is evaluated in the Qinghai Tibet Plateau and the Loess Plateau in China.An ASTER Global DEM(ASTGTM2 DEM)with a grid size of 30 m is chosen to assess the suitability of the proposed mountain peak extraction and classification method in different geomorphic regions.DEM data with grid sizes of 30 m and 5 m are used for the Loess Plateau.The mountain peak extraction and classification results obtained from the different resolution DEM are compared.The experimental results show that:(1)The CM-index and the CSDindex accurately reflect the concave or convex morphology of the surface and can be used as supplements to existing surface morphological indices.(2)The three indices can identify pseudo mountain peaks and classify the remaining peaks into single ridge peak(SR-Peak)and multiple ridge intersection peak(MRI-Peak).The visual inspection results show that the classification accuracy in the different study areas exceeds 75%.(3)The number of peaks is significantly higher for the 5 m DEM than for the 30 m DEM because more peaks can be detected at a finer resolution.
基金supported by the National Natural Science Foundation of China(Grant No.31870620)the Fundamental Research Funds for the Central Universities(Grant No.PTYX202107).
文摘Background:The relationship between climate and radial growth of trees exhibits spatial variation due to environ-mental changes.Therefore,elucidation of how the growth–climate responses of trees vary in space is essential for understanding forest growth dynamics to facilitate scientific management with the ongoing global climate warming.To explore the altitudinal and slope variations of these interactions,tree-ring width chronologies of Larix olgensis A.Henry were analyzed in the southern Lesser Khingan Mountains,Northeast China.Results:The radial growth of L.olgensis exhibited significant 5-to 10-year periodic changes at three altitudes and two slopes,and the frequency change occurred mainly during the early growth stage and after 2000.The radial growth of L.olgensis was significantly negatively correlated with September precipitation only at low altitudes,but also with the mean temperature in July–August and the mean maximum temperature in June–August at high altitudes.The radial growth of L.olgensis at low and middle altitudes as well as on the sunny slope led to a higher demand for moisture,while temperature was the key limiting factor at high altitudes and on the shady slope.Conclusions:The climate–radial growth relationship of L.olgensis exhibits altitudinal and slope variability.This study quantitatively describes the spatially varying growth–climate responses of L.olgensis in the southern Lesser Khingan Mountains,which provides basic data for the management of L.olgensis forests and the prediction of future climate impacts on forest ecosystems.
文摘Brandt et al.reported the results of their analysis from high-resolution satellite images,covering more than 1.3 million square kilometers of the Western Sahara and Sahel in West Africa.They mapped the locations and sizes of approximately 1.8 billion trees.Prior to this,scientists had never made such a detailed map of trees in such a large area.Commercial satellites have begun to collect data and can detect small ground objects that are 1 square meter or less in size.Therefore,the field of terrestrial remote sensing may have a significant advance from mainly a comprehensive landscape-scale measurement to mapping the position and canopy size of each tree at a regional or even global scale.This progress will revolutionize how we think,monitor,simulate,and manage the global terrestrial ecosystem.
