Dominant woody plant species recognition with a hierarchical model based on multimodal geospatial data for subtropical forests

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.

Development of mobile GIS system for forest resources second-class inventory

A special mobile GIS（Geographic Information System） system used for forest resources second-class inventory was developed on the basis of traditional forest resources inventory,remote sensing,GPS（Globe Positioning System） and embedded technology.Portable instrument,embedded development and the integration technology of RS（Remote Sensing）,GIS and GPS are all used in this special mobile GIS system.Further,the system composition,key techniques,and current situation of the practical application in China were analyzed in the study.The results are important for applying modern high-tech for the planning and design of digital forest resources to improve the precision and efficiency of inventory and reduce the labor cost and financial investment.

Dynamics of forest biomass carbon stocks from 1949 to 2008 in Henan Province,east-central China

We estimated forest biomass carbon storage and carbon density from 1949 to 2008 based on nine consecutive forest inventories in Henan Province,China.According to the definitions of the forest inventory,Henan forests were categorized into five groups: forest stands,economic forests,bamboo forests,open forests,and shrub forests.We estimated biomass carbon in forest stands for each inventory period by using the continuous biomass expansion factor method.We used the mean biomass density method to estimate carbon stocks in economic,bamboo,open and shrub forests.Over the 60-year period,total forest vegetation carbon storage increased from34.6 Tg(1 Tg = 1×10;g) in 1949 to 80.4 Tg in 2008,a net vegetation carbon increase of 45.8 Tg.By stand type,increases were 39.8 Tg in forest stands,5.5 Tg in economic forests,0.6 Tg in bamboo forests,and-0.1 Tg in open forests combine shrub forests.Carbon storageincreased at an average annual rate of 0.8 Tg carbon over the study period.Carbon was mainly stored in young and middle-aged forests,which together accounted for 70–88%of the total forest carbon storage in different inventory periods.Broad-leaved forest was the main contributor to forest carbon sequestration.From 1998 to 2008,during implementation of national afforestation and reforestation programs,the carbon storage of planted forest increased sharply from 3.9 to 37.9 Tg.Our results show that with the growth of young planted forest,Henan Province forests realized large gains in carbon sequestration over a 60-year period that was characterized in part by a nation-wide tree planting program.

The Research of Carbon Emission and Carbon Sequestration Potential of Forest Vegetation in China

The study of China s carbon emissions and carbon sequestration potential is of great practical significance to the formulation of carbon neutrality strategies and methods of China.Carbon emission is an inevitable outcome of the initial stage of economic development,especially the right of developing countries existence and development.The carbon emission of China has been maintained at a low level for a long time and reached the top of the world in 2005.However,per capita carbon emission was still only 46.28%of the United States in 2016.China s total CO_(2) emissions are expected to reach 17-19 Gt/a by 2030.To achieve the goal of carbon neutrality in 2060,the main problems are the low technical capacity of emission reduction and the unreasonable structure of energy consumption.Therefore,replacing coal with gas is one of the most effective ways of emission reduction.By 2060,the carbon sequestration capacity of forest vegetation will reach or exceed 759.14 Mt/a and the CO_(2) sequestration capacity will reach 2783.5 Mt/a.According to that,China s carbon intensity must reduce by 95.39%on the basis of the carbon intensity in 2017,reaching 640 t/100 million yuan.The carbon sequestration capacity of terrestrial vegetation(forest,grassland)will reach or exceed 1380.3 Mt/a and the CO_(2) sequestration capacity will reach 5069.3 Mt/a.According to that,China s carbon intensity must reduce by 91.07%on the basis of the carbon intensity in 2017,reach 1152 t C per 100 million yuan.