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Table of Content

    28 February 2022, Volume 0 Issue 1
    Table of Contents
    Contents and cover
    2022, 0(1):  0-0. 
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    Integrated Management and Administration
    Analysis on Policy Evolution andIndustry Development of Forestry Biomass Energy in China
    ZHAO Chengle, MENG Gui, WU Shuirong, ZHANG Chao, LIU Yefei
    2022, 0(1):  1-7.  doi:10.13466/j.cnki.lyzygl.2022.01.001
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    The development and utilization of forestry biomass energy has become one of the important measures to optimize China's energy structure and cope with global climate change.Based on the comprehensive summary of the development status of China's forestry biomass energy industry,this paper systematically reviewed the evolution and characteristics of China's forestry biomass energy policies. For example,the development of China's forestry biomass energy industry has always adhered to the basic principles of "not competing with grain for land,not competing with people for grain",and timely adjusted the policy objectives according to the needs of different stages of national development.In view of the current problems in the process of developing the forestry biomass energy,such as lack of pertinence in the related laws and regulations,high threshold of obtaining demonstration funds from governments and single channel of product market financing,this paper put forward the policy recommendations including improvement of forestry biomass energy related laws and regulations,promoting insurance policy and enhancing the financial support to the forestry biomass energy industry.

    Scientific Research
    Autocorrelation Analysis of Quantitative Index of Stand Spatial Structure Based on Moran's I
    QING Dongsheng, PENG Jinxiang, LI Jianjun, DENG Qiaoling, LIU Shuai
    2022, 0(1):  8-17.  doi:10.13466/j.cnki.lyzygl.2022.01.002
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    In order to study the autocorrelation of spatial structure indexes between object trees and adjacent trees in stand spatial unit,the spatial logical relationship between object trees and adjacent trees was analyzed.Twenty five 20m×20m sample plots were set up in Daweishan Nature Reserve,Wuyunjie Nature Reserve and Lutou Forest Farm,the forest spatial unit based on Voronoi diagram was constructed,the adjacent trees of each object forest were determined,and the mixing degree,open ratio,DBH size ratio and competition index were selected as the quantitative indexes of forest spatial structure,and the values of each index were calculated. Finally,combined with the basic principle of global Moran's I index,the autocorrelation analysis scheme of stand spatial structure unit index was constructed to analyze the stand in the study sample plot.The results showed that the stand in the study area was a medium mixed forest,and the trees in this area were in a medium crowded state. There were great differences in DBH distribution between the object trees in the study area and the adjacent trees in its spatial unit,and the competition between trees was relatively obvious.From the perspective of spatial relationship,the mixing degree and open ratio of trees in the study area were positively correlated with their adjacent trees in space,and logically showed aggregation;The DBH size ratio and competition index of trees were negatively correlated with their adjacent trees in space,which was logically discrete. In addition,the spatial relationship between the trees in the survey area and their adjacent trees was mainly competition. The mixing degree and competition index of the trees in the stand may be the main spatial indicators leading to the heterogeneity between them and the surrounding adjacent trees.

    Development of Carbon Growth Models and Analysis of Carbon Sequestration Capacity for Larch Forest Stands in the Northeast of China
    ZENG Weisheng
    2022, 0(1):  18-23.  doi:10.13466/j.cnki.lyzygl.2022.01.003
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    On the background of implementing the strategy of carbon peak and carbon neutralization,the carbon sequestration capacity of forest ecosystem has become the focus of attention. Based on the carbon storage data of 1 091 sample plots from the 9th national forest inventory in three provinces of northeast China,the carbon growth models of both natural and planted larch forest stands were developed,the impacts of topographic and soil factors to model parameters were analyzed,and the differences of carbon sequestration capacity between natural and planted larch forest stands were compared. The results showed that 1) the annual carbon growth (AG) of planted larch forest stands reached to the highest 2.70 t/hm2 at 12 years old,and the mean carbon growth (MG) reached to the highest 1.85 t/hm2 at 20 years old;while the AG of natural stands reached to the highest 0.94 t/hm2 at 18 years old,and the MG reached to the highest 0.78 t/hm2 at 32 years old;2) when forest stand age was 30,the mean carbon storage per hectare of planted larch forest stands was up to 49.36t/hm2,which was 111%higher than 23.37t/hm2 of natural stands;and when forest stand age was 50,that of planted stands was up to 55.47t/hm2,which was 53%higher than 36.30t/hm2 of natural stands;3)the developed carbon growth models for both natural and planted larch forest stands reflected objectively the overall average growth process of carbon storage in three northeast provinces,of which mean prediction errors were about 5%,total relative errors were nearly to zero for modeling and less than 2% for cross-validation;4) the impacts of topographic and soil factors to the growth of planted larch forest stands were not significant,only slope position had significant impact to the growth of natural stands;the carbon sequestration capacity of planted larch forest stands was obviously higher than the natural stands.

    Analyze of Spectral Characterization and Physiological Parameters in Populus Euphratica Leaves under Different Groundwater Burial Depths
    ZHANG Dongdong, WEN Yunmeng, WANG Jiaqiang, LI Fuqing, CAI Haihui, LIU Weiyang
    2022, 0(1):  24-34.  doi:10.13466/j.cnki.lyzygl.2022.01.004
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    The study was conducted in the field in the Tarim River basin,with a typical desert riparian forest plant,Populus euphratica as the study object and set five different groundwater depth gradients (0~2 m,2~4 m,4~6 m,6~8 m and 8~10 m). Physiological indicators (MDA,PAL,leaf water content,chlorophyll) and leaf reflectance spectra were analyzed by measuring Populus euphratica under different groundwater burial depth gradients. The results showed that the changes of leaf water content and MDA content tended to decrease at first and increase afterwards with increasing depth of groundwater burial,while the changes of chlorophyll density and PAL activity tended to increase at first and decrease afterwards. Both MDA content and PAL activity magnitude were more sensitive to changes in groundwater burial depth,while the possible salt stress at low burial depths had a greater effect on plants than drought stress,and had a greater effect on chlorophyll density and MDA content at burial depths of 0~2 m. However,the differences in leaf water content at the five burial depths were small. In the 350~900nm band,poplar had the characteristics of "one peak and two valleys". In the "blue valley",the order of poplar reflectance at different burial depths was: 4~6m>0~2m>6~8m>8~10m>2~4m. At the "Green Peak",the order of poplar reflectance at different depths was: 4~6m>6~8m>0~2m>8~10m>2~4m,which was consistent with the difference at the "Red Valley". By correlation analysis of physiological indexes and spectra,the original spectra and leaf water content all reached a highly significant negative correlation after the wavelength of 429 nm,and reached the maximum value of negative correlation at the wavelength of 645 nm (r of -0.60530),with a small overall change. However,the correlation coefficient between the chlorophyll density and the spectrum had a maximum at 710nm on the red side (r of -0.63655). The "trilateral" parameters of the poplar spectra varied greatly at different depths of burial,and the water content of the leaves reached a highly significant level with the red valley amplitude,with the strongest correlation (r of -0.577).The variation characteristics of these indicators and spectral curves are intended to provide some basis for the research and identification of drought resistance of Populus euphratica,and the construction of ecological environment and vegetation restoration in arid areas.

    Prediction of Potential Distribution and Climate Change of Rare Species Cephalotaxus oliveri
    LIU Zengli, HU Lile
    2022, 0(1):  35-42.  doi:10.13466/j.cnki.lyzygl.2022.01.005
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    Cephalotaxus oliveri is an II-class national protection of wild plant and a tertiary relic species in China. Understanding its distribution range and its response to climatic factors is helpful to protect the species under climate change. In this study,geographical distribution records from literature and specimen was used to analyze the potential geographical distribution of C.oliveri in China through MaxEnt model. Moreover,based on CMIP6 date from Digital Terrain of China,C. oliveri potential distribution under four climate change scenarios in the following 80 yearswas predicted. The results showed that:1) precipitation in the driest month,slope and annual precipitation were the main climatic factors affecting the distribution of C.oliveri. 2)Under the current climate conditions,highly suitable habitat for C. oliveri accounted for 1.7% of the area of China,mainly concentrated in the southwest edge of the Sichuan Basin,Wuling Mountains - Shennongjia,Xuefeng Mountain,Nanling,Luoxiao Mountain,Dabie Mountain,mountains in Southern Anhui - Tianmu Mountain,Wuyi Mountain - mountains in Southern Zhejiang,Daiyun Mountain and Central Mountains in Taiwan. However,under current climatic conditions,the southwest population (located in Yunnan Province) was not in the range of highly suitable habitat,which may be related to the relatively few definite distribution points and microhabitat effects in the local.3)Overall,the response of C.oliveri distribution to future climate (warm and humid) would be insensitive. Under the four scenarios of climate change,the model predicted that the spatial distribution of highly suitable habitat of the species would not change significantly. The area of low,medium,highly suitable habitat and all degree of suitable habitat would generally increase. The most highly suitable habitat of the species would slightly change under future climate except the SSP245 scenario,which would decrease continually.

    Study on the Characteristics and Relationship of Soil Moisture and Litter Fall of Three Vegetation Types in Ai-lao Mountain
    ZHU Xiuwen, GUO Zihao, YANG Shuangna, GONG Hede
    2022, 0(1):  43-51.  doi:10.13466/j.cnki.lyzygl.2022.01.006
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    In the Ai-lao Mountain Nature Reserve,Pu'er City,Yunnan Province,this research selected three vegetation types as the objects,including mid-montane moist evergreen broad-leaved forest,mountain top mossy coppiceforest and secondary forest of Populus Yunnanensis,and measured 10-50cm,70cm,90cm,110cm,130cm and 150cm soil moisture content by TDR time domain reflectometer,collected the dry weight of litter (leaf,branch,flower and fruit,bark,moss lichen and other litter) to analyze soil moisture and litter features of different vegetation types and the relationship between them. The results showed that: 1) The soil moisture,as a whole,was represented by the middle-mountain moist evergreen broad-leaved forest>secondary forest of Populus Yunnanensis>mountain top mossy coppice forest. 2) Litter of 3 vegetation types,except for the dry weight of branches and bark,all had significant differences (P<0.05),and the composition of litter was similar,mainly composed of branches and leaves. 3) In the mid-mountain moist evergreen broad-leaved forest,the soil water content only had a very significant positive correlation with the dry leaf weight (P<0.01);in the mountain top mossy coppice,the soil water content only had the negative correlation with the dry weight of moss lichen,and was positively correlated with other indicators;the soil water content in the secondary forest of Populus yunnanensis was negatively correlated with the dry weight of leaf and moss lichen,and positively correlated with the other indicators. RDA analysis results of moss lichen,leaf dry weight and other litter dry weights had greater influence on the soil moisture content of the three vegetation than the dry weight of flowers,fruits,bark and dead branches;in soil moisture content of mid-montane humid evergreen broad-leaved forest,the fitting effect with the total amount of litter was better than that of the other two,which was y=78.601x+35.374.The cultivation of evergreen broad-leaved forest is conducive to the conservation of soil water resources in the mountains.

    Study on Spatial Distribution of Land Desertification Sensitivity in Naiman Banner
    ZHAO Kai, YUE Yongjie, HE Rong, WANG Yaqian, WU Yunzhula
    2022, 0(1):  52-60.  doi:10.13466/j.cnki.lyzygl.2022.01.007
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    Taking Naiman Banner as the research object,this paper selected five factors as evaluation indexes: dryness index,windy sand days,soil silt content,vegetation coverage and slope. The study area was divided into five grades: extremely sensitive,highly sensitive,moderately sensitive,slightly sensitive and insensitive. The spatial distribution and influencing factors of land desertification sensitivity were studied and analyzed. The results showed that: 1) on the whole,in 2020,Naiman Banner had the largest land area with mild desertification sensitivity,accounting for 29.7% of the total area;Followed by high sensitive land,accounting for 22.9%;Moderately sensitive land,accounting for 22.2%;Insensitive grade,accounting for 15.2%;The land area of extremely sensitive grade accounted for the lowest,which was 10.0%. The land desertification sensitivity of Naiman Banner decreased from north to south in space. 2) In terms of natural conditions,the main reason for the spatial difference of desertification sensitivity was vegetation coverage,followed by windy sand days,dryness index,soil silt content and slope. 3) From the perspective of land use,human activities also had a certain impact on land desertification. The sensitivity of land desertification was positively correlated with the area of cultivated land and sandy land,and negatively correlated with the area of forest land.

    Influence of Land Use on Landscape Pattern Evolution of Rocky Desertification in Karst Areas of Yunnan,China
    TIAN Xiangyun, ZHANG Chao, CHEN Qi, SHI Xiaorong, WANG Yan
    2022, 0(1):  61-69.  doi:10.13466/j.cnki.lyzygl.2022.01.008
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    In order to explore the land use types and the temporal and spatial characteristics and evolution laws of rocky desertification grades in karst areas of Yunnan Province,the effects of different land use types on rocky desertification grades were analyzed. The data of land use type was obtained based on GlobeLand30,and the data of rocky desertification grade was obtained by using ENVI to classify the decision tree of Landsat image. The spatial analysis of land use type and rocky desertification landscape pattern were carried out by ArcGIS and Fragstats. The results in the karst area of Yunnan from 2000 to 2020 showed that: 1) The main types of land use were cultivated land,woodland and grassland,and the area of cultivated land and construction land was increased year by year. 2)The area of non-rocky desertification increased year by year,the area of severe rocky desertification decreased year by year,the overall grade of rocky desertification tended to improve,and the area of high-grade rocky desertification patch decreased,namely the dominance decreased. 3) Rocky desertification mainly occured in woodland and shrubbery,the area of rocky desertification in cultivated land showed an increasing trend,and the area of rocky desertification in woodland and grassland showed a decreasing trend except for the grade of extremely severe rocky desertification. 4) The PAFRAC of land use type and rocky desertification landscape pattern decreased by 0.0007 and 0.0022 respectively,while COHESION,AI,DIVISION,SHDI and SHEI showed negative correlation. The complexity of rocky desertification landscape type decreased with the change of land use landscape type,and the situation of rocky desertification improved continuously. This study was helpful to evaluate the effectiveness of rocky desertification control and provided a scientific basis for ecological restoration and rocky desertification control in the future.

    Changes in Woodland Cover and its Altitude Gradient Analysis in Fujian Province
    ZUO Xueman, YAN Guodong, CHEN Jin, WU Zhilong, HU Xisheng
    2022, 0(1):  70-77.  doi:10.13466/j.cnki.lyzygl.2022.01.009
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    Taking Fujian Province as the research area,using the remote sensing data of land use with spatial resolution of 30m × 30m provided by the Resource and Environmental Science and Data Center in 2000,2010 and 2020,the temporal and spatial variation laws of forest land cover in Fujian Province were analyzed. And the effect of different altitude gradients on forest cover changes was studied with DEM data.The results showed that: 1) The total forest area of the study area in 2000,2010,and 2020 was 76,279.98km 2,75,807.97km2,and 75,595.75km2,respectively;the total forest area was decreasing;2) From 2000 to 2020,the center of gravity of forest land did not shift greatly;the distribution range of forest land showed a trend of expansion as a whole;in terms of spatial changes,whether it was 2000-2010 or 2010-2020,the stable area had certain advantages,with the area of about 1,200,000km2;from 2000 to 2010,the forest land loss area was 1134.78km2,and the forest land acquisition area was 662.78km2;from 2010 to 2020,the forest land loss area was 316.50km2,and the forest land acquisition area was 102.61km2;3) From 2000 to 2010,Forest land wasmainly converted with construction land and grassland,and 648.56 km2 of woodland was converted to construction land,and 577.51 km2 of woodland was convertedfrom grassland;from 2010 to 2020,forest land was mainly converted to construction land,and 240.47 km2 of woodland was transferred to construction land;4) At altitudes <500m,both the loss and gain of forest land reached the maximum;with the increase of altitude,the loss/gain area of forest land gradually decreased,and when the altitude >2000m,the loss and gain of forest land hardly occured.

    Analysis on Spatiotemporal Pattern of China's Timber Market
    LI Linbei, LI Jianquan, GUO Huimin
    2022, 0(1):  78-85.  doi:10.13466/j.cnki.lyzygl.2022.01.010
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    In order to study the spatiotemporal pattern and dynamic changes of China's timber market,based on the production data of China's provincial commercial timber from 1997 to 2020,this paper applied the concentration ratio,space Gini coefficient,gravity model,Global Moran's I and local Getis-Ord Gi,combined with ArcGIS and GeoDa analysis software to conduct the research. The results showed that from 1997 to 2020,the concentration ratio of China's timber market increased from 43.62% to 64.10%,and the spatial Gini coefficient increased from 0.044 to 0.129,indicating that the degree of spatial imbalance has increased;The distribution center of gravity has shifted from Shandong Province to Jiangsu,Henan,Hubei and Hunan Provinces;There was a significant spatial autocorrelation between provincial timber markets,with the global Moran's index decreasing from 0.36 in 1997 to 0.22 in 2020;The hot spots changed from Heilongjiang and Jilin Provinces to Yunnan,Guangdong,Guangxi,Hunan and Guizhou Provinces. So the regional distribution difference of China's timber market expanded and the degree of concentration increased;The center of gravity and hot spots of spatial distribution migrated from northeast to southwest;The distribution of China's timber market showed a positive spatial correlation,and the agglomeration area tended to be stable.

    Environmental Risk Assessment of Tourism Carbon Emission in Jiangsu Province Based on Forest Carbon Sink Threshold
    TU Wei, LIU Qinpu
    2022, 0(1):  86-94.  doi:10.13466/j.cnki.lyzygl.2022.01.011
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    Based on forest carbon sink,the environmental safety threshold model of tourism carbon emission was constructed to evaluate the environmental risk of tourism carbon emission. The results showed that :1) in the past 15 years,the tourism carbon emission in Jiangsu Province presented an overall growth state,which was characterized by four stages of smooth growth-steady growth-rapid growth-substantial growth. The tourism carbon emission increased from 13.633 million tons to 129.365 million tons,a total increase of 8.49 times. The differences of tourism carbon emission among 13 cities in the province gradually narrowed. Nanjing,Suzhou and Wuxi maintained high carbon emission,while Suqian,Yancheng and Huai 'an saw rapid growth in tourism carbon emission intensity.2) The environmental safety threshold of tourism carbon emission in Jiangsu Province varied from 1.579 million tons to 11.460 million tons in the past 15 years. The environmental safety threshold based on forest carbon sink kept improving,with an average value of 0.659 million tons. The environmental safety threshold of tourism carbon emission in municipality level varied from 1.605 million tons to 11.833 million tons. Suzhou,Nanjing and Wuxi had the highest environmental safety threshold,while Suqian had the lowest. 3) In the past 15 years,the environmental risk of tourism carbon emission in Jiangsu Province has entered the extremely serious risk state,experiencing a trend of decline,wandering,accelerating rise,steady and continuous rise,presenting a "spoon" type. The difference of environmental risk among 13 cities in Jiangsu Province continued to narrow,and the number of environmental risk areas increased from 3 to 10. The evolution and current situation of environmental risk of tourism carbon emission in Jiangsu Province is worrying.

    Research on the Impact of Pocket Parks on Urban Thermal Environment from the Perspective of Heat Island Effect
    ZHUO Zhixiong, WU Tianjie, HONG Changxing, HUANG Qitang
    2022, 0(1):  95-105.  doi:10.13466/j.cnki.lyzygl.2022.01.012
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    This article took Fuzhou City,the head of the latest four "furnace cities" as the research site. From the perspective of thermal environment,it took pocket parks as the research object,analyzed the relationship between pocket parks and the urban thermal environment through thermal environment measurement data,and discussed the relationship between the landscape characteristics of pocket parks and urban design indicators and urban thermal environment so as to provide suggestions for the construction and optimization of future pocket parks. The results showed that: 1) Pocket parks were cooler than surrounding city streets during the day and night,and can improve the urban thermal environment on a micro-scale. 2) Green coverage,area,shape index of pocket parks and thermal environment were negatively correlated,when the perimeter of the park was less than 300m,the relationship with the average temperature was positive,when the pocket park was greater than 300m,the relationship with the temperature was negative. 3) The building density had a significant positive relationship with the air temperature of the pocket park. At night,the display was relatively weak,the plot ratio had a parabolic relationship with the temperature,and the plot ratio exceeded a certain value (1.25) to reduce the ambient temperature. 4) The green coverage rate and shape index of the pocket park had a certain impact on the cooling degree of the surrounding environment. The greater the coverage,the more complex the shape index and the greater the temperature drops.

    Technical Application
    Classification of Vertical Forest Structure of Overstory in Subtropical Forests Using Airborne Lidar Data
    ZHOU Xiangbei, LI Chungan, YU Zhu, CHEN Zhongchao, SU Kai
    2022, 0(1):  106-113.  doi:10.13466/j.cnki.lyzygl.2022.01.013
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    The vertical structure classification of forest plays an important role in ecology and forestry. A vertical canopy profile (pseudo-wave) was obtained by fitting the frequency distribution of height and coverage of discrete laser point cloud in Guangxi by using the tenth order polynomial method,which reflected the vertical distribution of canopy material. Canopy structure parameters such as effective peak,stand surface height,sub-storey height,and crown ratio were extracted by pseudo-wave and classification rules were established to divide the vertical structure of stands into six types.Confusion matrix was used to evaluate the classification accuracy,and an area of 1369km2 was selected for mapping to test the generalization of classification rules. The results showed that: 1) In the classification results of 1 147 sample plots,the overall classification accuracy was 93.9%,and the Kappa coefficient was 0.913;2) The error rates of single-peak,double-peak and triple-peak were 6.2%,7.4% and 9.1% respectively,while the error rates of Chinese fir forest,pine forest,eucalyptus forest and broadleaved forest were 9%,6.4%,2.4% and 6.9%,respectively,indicating that the more complex the vertical structure of the stand,the lower the accuracy of classification;3) The accuracy of each forest layer was higher than 96%,the omission errors were less than 4%,and the commission errors were less than 10%,indicating that each forest layer can be accurately detected;4) The coverage of classification rules in mapping areas reached 99.8%. In this study,vertical forest classification method with high accuracy,good generalization and rich spatial information is suitable for overstory vertical structure classification mapping of large regional subtropical forest.

    A Method to Validate Airborne LIDAR CHM Producton Individual Tree Level
    FU Anmin, GAO Xianlian, WU Fayun, GAO Jinping
    2022, 0(1):  114-123.  doi:10.13466/j.cnki.lyzygl.2022.01.014
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    The accuracy and precision of Airborne LIDAR canopy height model (CHM) product was accessedon in dividual tree level,using forest ground measurements with high-precision position. The analysis procedures were based on dominant trees sampling by spatial analysis tool,iterative elimination of outliers,correlation analysis,and rules for error grading statistics.The method was applied in Northeast Tiger and Leopard National Park. The CHM product was collected by LIDAR RIEGL-VQ-1560i with 10 pulse/m2. The results showed that: 1) CHM and "real" height had a significant linear correlation,R2=0.97;CHM products were slightly lower than the "real" height,about 0.7m;Roughly,there was an uncertainty of ±2m(2σ) for each tree;2) For each tree species (group),all CHMs were slightly lower than the "real" height too,ranging from 0.3m to 1.3m;Roughly,There was an uncertainty of ±1.4 ~±2.4m(2σ) for different species;Significantly,the CHM height of the larch was about 1.3m lower than the "real" value;3) the result of error grading statistics showed proportion of CHM with 0~ ±1m error was 57.6%; proportion of CHM with 0~±2m error was 79.4%;proportion of CHM with more than +2m error was 18.6%; proportion of CHM with less than -2m error was 2.0 %. It indicated that about 1/5 of the products had lower CHM values,which needed to be further explored. The results showed that the method could effectively identify the quality problems of CHM products,and provide a guarantee for the quality control of airborne LIDAR forest survey projects under complex operating conditions in large-scale and mountainous forest areas.

    Single Tree Recognition Algorithm Based on Multi-Layer K-means in Forest Point Cloud
    GU Zhixin, PEI Fangrui
    2022, 0(1):  124-131.  doi:10.13466/j.cnki.lyzygl.2022.01.015
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    When the K-means algorithm is used for single tree recognition for the forest point cloud data collected by the current Lidar (Light Detection And Ranging,LIDAR),the algorithm has a long convergence time and is prone to clustering for forest scenes with high density of trees. An improved multi-layer K-means single tree recognition algorithm was proposed.Taking the point cloud data of the Larix olgensis plantation in Mengjiagang Forest Farm in Jiamusi City,Heilongjiang Province as the experimental object,the RANSAC algorithm and radius outlier denoising algorithm were used to remove ground points and non-trunk and non-ground points in the data.Finally,the single tree recognition was carried out through the multi-layer K-means algorithm.The results showed that the improved multi-layer K-means algorithm had a single tree recognition accuracy rate of 91.01% and the false calculation amount of the trees was 0.Compared with the traditional K-means algorithm,the convergence time of the algorithm was shortened by 48.13%.It can be concluded that the multi-layer K-means algorithm is more efficient,and single tree identification in complex and dense forest plots has better results.The cost of surveying forest structure is reduced,which is of great significance to the calculation of forest structure parameters,the protection of forest resources and the overall planning.

    Single Tree Parameters Extraction of Broad-Leaved Forest Based on UAV Tilting Photography
    CHEN Zhoujuan, CHENG Guang, BU Yuankun, HUANG Wei, CHEN Jiahui, LI Weizhong
    2022, 0(1):  132-141.  doi:10.13466/j.cnki.lyzygl.2022.01.016
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    Extracting single tree parameters based on UAV tilting photography data is a hot topic in forestry research. Taking ginkgo(Ginkgo biloba L.) broad-leaved forest as the research object,based on UAV tilting photography data,this paper used the local maximum based algorithm to identify the single tree vertex and extract the single tree height under three detection windows(3m×3m、5m×5m、7m×7m),and the accuracies of recognition and extraction were verified respectively. Then,this paper applied the seed region growth algorithm and marker-controlled watershed algorithm for tree canopy extraction,and the extraction accuracies of two algorithms were compared. The results showed that: 1) Under the three single tree detection windows,the F scores of ginkgo tree vertex recognition were 0.87,0.88 and 0.83 respectively. The 5×5m window had the best recognition effect,and in its tree height prediction fitting equation,R2 reached 0.99 and RMSE was 1.91m;2) When the relative error threshold of predicted canopy was 30%,the accuracies of seed region growth algorithm and marker-controlled watershed algorithm in extracting crown area were 73.14% and 63.43% respectively. In establishing the linear regression relationship between predicted and measured canopy,the R 2 of the two algorithms were 0.98 and 0.97,and the RMSE were 1.79m 2 and 2.44m2 respectively. In general,the single tree canopy segmentation accuracy of seed region growth algorithm was higher than that of marker-controlled watershed algorithm. This study points out that the UAV tilting photography technology is feasible in the automatic and accurate single tree identification and segmentation of ginkgo broad-leaved forest,thus it has great application potential in forestry investigation.

    Research on Deep Learning Classification of Forest Types Based on Multi-temporal GF-1 Images
    YANG Dan, LI Chonggui, ZHANG Jiazheng
    2022, 0(1):  142-149.  doi:10.13466/j.cnki.lyzygl.2022.01.017
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    In order to explore the effect of deep learning method on forest vegetation classification based on multi-temporal GF-1 images. This paper took Mengjiagang Forest Farm in Heilongjiang Province as the research area,took multi-temporal GF-1 images and Digital Elevation Model (DEM) as data sources,and constructed a multi-feature data set by extracting spectral features,vegetation index,texture features and topographic features,and combined with VSURF algorithm for feature optimization. At the same time,the optimized U-Net,SegNet,and DeepLab V3+models were used to classify the forest stand types,and compared with the maximum likelihood method and random forest method. The results showed as follows: 1) The classification accuracy of multi-temporal images was significantly better than that of single-temporal images; 2)Based on VSURF algorithm,16 feature variables were selected from the 97 features constructed,in which NDVI,RVI,mean,homogeneity,contrast,correlation and DEM features were retained because of their high contribution,and the other variables were eliminated,so as to avoid the "dimension disaster" to a certain extent and improve the efficiency of the model;3) Among the three depth learning methods,U-Net model had the highest classification accuracy,with an overall accuracy of 87.18%,kappa coefficient was 0.710,DeepLab V3+model followed,and SegNet model had the lowest accuracy. Constructing the optimal feature combination based on multi-temporal GF-1 images,combined with deep learning methods,has certain reference value for the classification of forest stand types.

    Research Briefing
    Effects of Flight Height and Canopy Density on Canopy Extraction of Metasequoia glyptostroboides
    ZHOU Chenqin, YU Yongjun, FANG Luming, LIU Yuzhen, HU Jianjin
    2022, 0(1):  150-156.  doi:10.13466/j.cnki.lyzygl.2022.01.018
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    Tree crown is an important index for tree species identification,estimation of tree DBH and forest volume,and monitoring tree growth. UAV remote sensing has the advantages of low cost and high precision,which is very suitable for obtaining high-resolution images. This paper took Metasequoia glyptostroboides forest in Qingshan Lake scenic spot,Lin'an District,Hangzhou as the research object,used UAV to obtain remote sensing images with different flight heights and different canopy density as the data source,and extracted the average crown width based on object-oriented method. Taking the average crown width measured on the ground as a reference,under the condition of relatively low canopy density,when the flight altitude were 65m,70m and 75m,the crown extraction accuracy were 95.39%,94.80% and 94.29% respectively. Under the condition of relatively high canopy density,the extraction accuracy of crown width were 89.10%,88.10% and 88.03% respectively. The results showed that within the research range,with the increase of UAV height,the accuracy of crown width extraction gradually decreased,and it was also applicable in two different canopy closures,which was more than 88% in two models. This method is efficient and reliable,and has important practical significance in forest resources investigation.

    Spatial Distribution of Ancient Trees and Effects of Land Use Change in Yubei District,Chongqing
    YANG Qiong, LIN Zhiyuan, DING Pengfei, LIU Gangming, WANG Haiyang
    2022, 0(1):  157-165.  doi:10.13466/j.cnki.lyzygl.2022.01.019
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    The purpose of this study was to explore the species composition,individual number,source,age structure and distribution of ancient trees in Yubei District of Chongqing,and the impact of land use type change on ancient trees,so as to highlight the value of ancient trees in inheriting history and culture,improve urban environment and protect regional biodiversity. Based on the existing data of ancient trees,this study conducted a field survey of ancient trees in Yubei District from March to June in 2021,and supplemented some data. Excel,ArcGIS,Spss Statistics 25 and other software were used to analyze the grade,family,species composition and growth of ancient trees in Yubei District. The spatial distribution characteristics were summarized,and the land use types were divided in Yubei District. The change of land use types was studied,and the influence of land use type change on ancient trees was revealed. The results showed that the rapid urbanization made the ancient trees face the problems of habitat deterioration and narrow growth and development space,and most of the preserved ancient trees in the highly urbanized area were the trees with strong adaptability. On this basis,the targeted conservation strategies of ancient trees were put forward.

    Hydrological Effects of Litter Layer in Four Typical Shrubs in Guangxi Zhuang Autonomous Region
    DAI Fenglin, CHEN Fangqing, LV Kun, LIU Yangyun
    2022, 0(1):  166-173.  doi:10.13466/j.cnki.lyzygl.2022.01.020
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    Litter layer in shrub communities plays an important role in soil and water conservation.In order to explore the differences in hydrological effects of different shrubs,litters were sampled from community under storey of four typical shrubs distributed in Guangxi Zhuang Autonomous Region in cluding Alchornea trewioides,Vitex negundo,Maesa japonica and Bauhinia purpurea communities. The water and soil conservation effect of the litter layer and its mechanism were revealed by measuring parameters such as litter volume,water holding rate and water in terception volume.The total litter accumulation ranged from 3.80 t/hm 2 to 4.84 t/hm2 in the four shrubs.The largest accumulation appeared in the A.trewioides community. There were significant differences among the four shrubs in the natural moisture content and the maximum water holding rate of the litter layer,which of B. purpurea community were significantly higher than the other three shrubs. The total effective in terception of litter in the four shrubs ranged from 5.3 t/hm 2 to 7.28 t/hm2.The order of the total effective interception of each community type was as follows:A. trewioides>V.negundo>B. purpurea> M.japonica. The total effective interception of the A. trewioides community was 11.15%,35.06% and 36.84% higher than that of V. negundo,B. purpurea and M. japonica community,respectively.The litter layer of A. trewioides and B. purpurea community had better hydrological effects in the four typical shrubs.

    Status Analysis and Restoration Suggestions of Degraded Forest in Three-North Engineering Area of Inner Mongolia
    DUAN He, ZHANG Jianbo, ZHANG Zhongwang
    2022, 0(1):  174-179.  doi:10.13466/j.cnki.lyzygl.2022.01.021
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    In order to accurately grasp the distribution of degraded forest land in the Three-North Shelterbelt Project area of Inner Mongolia,promote the construction of the Three-North Shelterbelt Project,and continuously improve the quality of forest resources and the ecological environment in the Three-North Shelterbelt Project area of Inner Mongolia,Forestry and Grassland Bureau of Inner Mongolia Autonomous Region organized the survey of degraded forest land in the Three-North Shelterbelt Project area in 2021. The results showed that the area of degraded forest in the Three-North Project area was 3019432.30 hectares,of which 16.86% and 83.14% were degraded forest and degraded shrub land. The main reasons for forest degradation were physiology,site,disaster and human activities. The area of forest degradation caused by physiology and disaster accounted for 45.81% and 38.13% respectively. Mildly degraded,moderately degraded,and severely degraded areas accounted for 0.88%,64.86% and34.26 %,respectively. The degraded forests were mainly distributed in the western part of Inner Mongolia,and further measures such as renewal,restoration,tending,enclosure and habitat restoration should be taken to restore the degraded forests so as to maintain the achievements of regional ecological construction.