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Estimating and mapping forest biomass in northeast China using joint forest resources inventory and remote sensing data

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Journal of forestry Research 2018年第3期29卷 789-803页

作者： Xinchuang Wang Shidong Wang Limin Dai Henan Polytechnic University Jiaozuo 454000People’s Republic of China State Key Laboratory of forest and Soil Ecology Institute of Applied EcologyChinese Academy of SciencesShenyang 110164People’s Republic of China

Being able to accurately estimate and map forest biomass at large scales is important for a better understanding of the terrestrial carbon cycle and for improving the effectiveness of forest management. In this study, forest plot sample data, forest resources inventory(FRI) data, and SPOT Vegetation(SPOT-VGT) normalized difference vegetation index(NDVI) data were used to estimate total forest biomass and spatial distribution of forest biomass in northeast China(with 1 km resolution). Total forest biomass at both county and provincial scales was estimated using FRI data of 11 different forest types obtained by sampling 1156 forest plots, and newly-created volume to biomass conversion models. The biomass density at the county scale and SPOT-VGT NDVI data were used to estimate the spatial distribution of forest biomass. The results suggest that the total forest biomass was 2.4 Pg(1 Pg = 10g), with an average of 77.2 Mg ha, during the study period. forests having greater biomass density were located in the middle mountain ranges in the study area. Human activities affected forest biomass at different elevations, slopes and aspects. The results suggest that the volume to biomass conversion models that could be developed using more plot samples and more detailed forest type classifications would be better suited for the study area and would provide more accurate biomass estimates. Use of both FRI and remote sensing data allowed the down-scaling of regional forest biomass statistics to forest cover pixels to produce a relatively fineresolution biomass map.

关键词： forest biomass Biomass density Spatial distribution Human disturbance remote sensing

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Integrating remote sensing and 3-PG model to simulate the biomass and carbon stock of Larix olgensis plantation

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forest Ecosystems 2024年第4期11卷 543-555页

作者： Yu Bai Yong Pang Dan Kong Key Laboratory of National forestry and Grassland Administration on forestry remote sensing and Information System Institute of Forest Resource Information

Accurate estimations of biomass and its temporal dynamics are crucial for monitoring the carbon cycle in forest ecosystems and assessing forest carbon sequestration *** studies have shown that integrating process-based models(PBMs)with remote sensing data can enhance simulations from stand to regional scales,significantly improving the ability to simulate forest growth and carbon stock ***,the utilization of PBMs for large-scale simulation of larch carbon storage distribution is still *** this study,we applied the parameterized 3-PG(Physiological Principles Predicting Growth)model across the Mengjiagang forest Farm(MFF)to make broad-scale predictions of the biomass and carbon stocks of Larix olgensis *** model was used to simulate average diameter at breast height(DBH)and total biomass,which were later validated with a wide range of observation data including sample plot data,forest management inventory data,and airborne laser scanning *** results showed that the 3-PG model had relatively high accuracy for predicting both DBH and total biomass at stand and regional scale,with determination coefficients ranging from 0.78 to *** on the estimation of total biomass,we successfully produced a carbon stock map of the Larix olgensis plantation in MFF with a spatial resolution of 20 m,which helps with relevant management *** findings indicate that the integration of 3-PG model and remote sensing data can well predict the biomass and carbon stock at regional and even larger *** addition,this integration facilitates the evaluation of forest carbon sequestration capacity and the development of forest management plans.

关键词： 3-PG model Larch Biomass Carbon stock ALS

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Toward Establishing a Low-cost UAV Coordinated Carbon Observation Network(LUCCN):First Integrated Campaign in China

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Advances in Atmospheric Sciences 2024年第1期41卷 1-7页

作者： Dongxu YANG Tonghui ZHAO Lu YAO Dong GUO Meng FAN Xiaoyu REN Mingge LI Kai WU Jing WANG Zhaonan CAI Sisi WANG Jiaxu GUO Liangfu CHEN Yi LIU Carbon Neutrality Research Center(CNRC) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Key Laboratory of Middle Atmospheric Physics and Global Environment Observation(LAGEO) Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China State Key Laboratory of remote sensing Science Aerospace Information Research InstituteChinese Academy of SciencesBeijing 100101China National remote sensing Center of China Beijing 100036China The Administrative Center for China’s Agenda 21 Beijing 100862China

In this study,we introduce our newly developed measurement-fed-perception self-adaption Low-cost UAV Coordinated Carbon Observation Network(LUCCN)*** LUCCN primarily consists of two categories of instruments,including ground-based and UAV-based in-situ *** use the GMP343,a low-cost non-dispersive infrared sensor,in both ground-based and UAV-based *** first integrated measurement campaign took place in Shenzhen,China,4 May *** the campaign,we found that LUCCN’s UAV component presented significant data-collecting advantages over its ground-based counterpart owing to the relatively high altitudes of the point emission sources,which was especially obvious at a gas power plant in *** emission flux was calculated by a crosssectional flux(CSF)method,the results of which differed from the Open-Data inventory for Anthropogenic Carbon dioxide(ODIAC).The CSF result was slightly larger than others because of the low sampling rate of the whole emission cross *** LUCCN system will be applied in future carbon monitoring campaigns to increase the spatiotemporal coverage of carbon emission information,especially in scenarios involving the detection of smaller-scale,rapidly varying sources and sinks.

关键词： CO_(2) measurement networks power station carbon emission cross-sectional flux method

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Accuracy of tree mapping based on hand-held laser scanning comparing leaf-on and leaf-off conditions in mixed forests

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Journal of forestry Research 2024年第5期35卷 14-25页

作者： Frederico Tupinambá-Simões Adrián Pascual Juan Guerra-Hernández Cristóbal Ordóñez Tiago de Conto Felipe Bravo iuFOR Sustainable Forest Management Research InstituteUniversity of Valladolid&INIAValladolidSpain Department of Geographical Sciences University of MarylandCollege ParkMD 20742USA forest Research Centre School of AgricultureUniversity of LisbonTapada da Ajuda1349‑017 LisbonPortugal

The use of mobile laser scanning to survey forest ecosystems is a promising,scalable technology to describe forest 3D structures at high *** confirm the con-sistency in the retrieval of forest structural parameters using hand-held laser scanning(HLS),before operationalizing the method,confirming the data is *** analyzed the per-formance of tree-level mapping based on HLS under differ-ent phenology conditions on a mixed forest in western Spain comprising Pinus pinaster and two deciduous species,Alnus glutinosa and Quercus *** area was surveyed twice during the growing season(July 2022)and once in the deciduous season(February 2022)using several scan-ning *** reference data(418 trees,15 snags)was used to calibrate the HLS data and to assess the influence of phenology when converting 3D data into tree-level attrib-utes(DBH,height and volume).The HLS-based workflow was robust at isolating tree positions and recognizing stems despite changes in ***-six percent of all pairs matched below 65 *** DBH,phenology barely altered *** observed a strong agreement when comparing HLS-based tree height *** values exceeded 2 m when comparing height measurements,confirming height data should be carefully used as reference in remote sensing-based inventories,especially for deciduous *** volume was more precise for pines(r=0.95,and rela-tive RMSE=21.3–23.8%)compared to deciduous species(r=0.91–0.96,and relative RMSE=27.3–30.5%).HLS data and the forest structural complexity tool performed remark-ably,especially in tree positioning considering mixed forests and mixed phenology conditions.

关键词： Precision forestry forest monitoring Mobile laser scanning forest inventory

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Flood susceptibility mapping using a novel integration of multi-temporal sentinel-1 data and eXtreme deep learning model

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Geoscience Frontiers 2024年第3期15卷 67-84页

作者： Rami Al-Ruzouq Abdallah Shanableh Ratiranjan Jena Mohammed Barakat A.Gibril Nezar Atalla Hammouri Fouad Lamghari GIS&remote sensing Center Research Institute of Sciences and EngineeringUniversity of SharjahSharjah 27272United Arab Emirates Civil and Environmental Engineering Department University of SharjahSharjah 27272United Arab Emirates Department of Earth and Environmental Sciences Prince El-Hassan bin Talal Faculty for Natural Resources&EnvironmentThe Hashemite UniversityZarqaJordan Fujairah Research Centre Fujairah CityAl Hilal TowerAl Hilal CityFujairahUnited Arab Emirates

Flash floods(FFs)are amongst the most devastating hazards in arid regions in response to climate change and can cause the loss of agricultural land,human lives and *** of the major challenges is the high-intensity rainfall events affecting low-lying areas that are vulnerable to *** works in this field have been conducted using ensemble machine learning models and geohydrological ***,the current advancement of eXtreme deep learning,which is named eXtreme deep factorisation machine(xDeepFM),for FF susceptibility mapping(FSM)is lacking in the *** current study introduces a new model and employs a previously unapplied approach to enhance FSM for capturing the severity of *** proposed approach has three main objectives:(i)During-and after-flood effects are assessed through flood detection techniques using Sentinel-1 data.(ii)Flood inventory is updated using remote sensing-based *** derived flood effects are implemented in the next step.(iii)An FSM map is generated using an xDeepFM ***,this study aims to apply xDeepFM to estimate susceptible areas using 13 factors in the emirates of Fujairah,*** performance metrics show a recall of 0.9488),an F1-score of 0.9107),precision of(0.8756)and an overall accuracy of 90.41%.The accuracy of the applied xDeepFM model is compared with that of traditional machine learning models,specifically the deep neural network(78%),support vector machine(85.4%)and random forest(88.75%).Random forest achieves high accuracy,which is due to its strong performance that depends on factors contribution,dataset size and quality,and available computational ***,the xDeepFM model works efficiently for complicated prediction problems having high non-collinearity and huge *** obtained map denotes that the narrow basins,lowland coastal areas and riverbank areas up to 5 km(Fujairah)are highly prone to FF,whilst the alluvial plains in Al Dhaid and hilly regio

关键词： Flood susceptibility mapping eXtreme Deep Factorisation Machine Sentinel-1 remote sensing

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Quantification of CO_(2) Emissions from Three Power Plants in China Using OCO-3 Satellite Measurements

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Advances in Atmospheric Sciences 2024年第11期41卷 2276-2288页

作者： Yang YANG Minqiang ZHOU Wei WANG Zijun NING Feng ZHANG Pucai WANG College of Data Science Jiaxing UniversityJiaxing 314000China LAGEO Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China CNRC Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Key Laboratory of Atmospheric Environment and Extreme Meteorology Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Shanghai Ecological Forecasting and remote sensing Center Shanghai 200030China Department of Atmospheric and Oceanic Sciences/Institute of Atmospheric Sciences Fudan UniversityShanghai 200082China

Coal-fired power plants are a major carbon source in China. In order to assess the evaluation of China's carbon reduction progress with the promise made on the Paris Agreement, it is crucial to monitor the carbon flux intensity from coal-fired power plants. Previous studies have calculated CO_(2) emissions from point sources based on Orbiting Carbon Observatory-2 and-3(OCO-2 and OCO-3) satellite measurements, but the factors affecting CO_(2) flux estimations are uncertain. In this study, we employ a Gaussian Plume Model to estimate CO_(2) emissions from three power plants in China based on OCO-3 XCO_(2) measurements. Moreover, flux uncertainties resulting from wind information, background values,satellite CO_(2) measurements, and atmospheric stability are discussed. This study highlights the CO_(2) flux uncertainty derived from the satellite measurements. Finally, satellite-based CO_(2) emission estimates are compared to bottom-up *** satellite-based CO_(2) emission estimates at the Tuoketuo and Nongliushi power plants are ~30 and ~10 kt d^(-1) smaller than the Open-Data inventory for Anthropogenic Carbon dioxide(ODIAC) respectively, but ~10 kt d^(-1) larger than the ODIAC at Baotou.

关键词： OCO-3 power plant CO_(2)emission Gaussian Plume Model

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Changes in culm surface temperature with maturity of the bamboo species Guadua angustifolia

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Journal of forestry Research 2016年第2期27卷 419-425页

作者： Nils Nolke Juan Carlos Camargo Garcia Christoph Klein Andrea Polle Chair of forest inventory and remote sensing Universitat GottingenBusgenweg 537077 GottingenGermany Faculty of Environmental Sciences Technological Universityof PereiraLa JulitaPereiraColombia Department of forest Botany and Tree Physiology Universiat GottingenBiJsgenweg 237077 GottingenGermany

We used thermal images of bamboo culms of Guadua angustifolia Kunth to analyze the relationship between culm surface temperature and maturity, driven by the hypothesis that young culms may exhibit lower surface temperatures than old ones. The culm surface temperature shows small but constant differences between three age classes of 1, 2, and 3 years. Our findings indicate that surface temperature may be applied as an additional indi- cator to support the determination of maturity of guadua culms besides the visual assessment of the culms.

关键词： Bamboo culms Thermal images Bamboowood quality

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

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Journal of forestry Research 2024年第3期35卷 111-130页

作者： Xin Chen Yujun Sun State forestry&Grassland Administration Key Laboratory of forest Resources&Environmental Management Beijing Forestry UniversityBeijing 100083People's Republic of China

Since the launch of the Google Earth Engine(GEE)cloud platform in 2010,it has been widely used,leading to a wealth of valuable ***,the potential of GEE for forest resource management has not been fully *** 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 *** 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 *** 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 ***,for dominant woody species recognition,using S1 winter and S2 data across all four seasons was *** terrain factors and removing spatial correlation from NFRI sample points further improved the recognition *** 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,*** 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 *** the results using the GEE application allows for an intuitive display of forest and species distribution,offering significant convenience for forest resource monitoring.

关键词： Google Earth Engine Sentinel forest resource inventory data Dominant woody plant species Subtropics Model performance

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Mapping forest age using National forest inventory,airborne laser scanning,and Sentinel-2 data

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forest Ecosystems 2020年第4期7卷 793-806页

作者： Johannes Schumacher Marius Hauglin Rasmus Astrup Johannes Breidenbach National forest inventory Norwegian Institute of Bioeconomy ResearchÅsNorway

Background:The age of forest stands is critical information for forest management and conservation,for example for growth modelling,timing of management activities and harvesting,or decisions about protection ***,area-wide information about forest stand age often does not *** this study,we developed regression models for large-scale area-wide prediction of age in Norwegian *** model development we used more than 4800 plots of the Norwegian National forest inventory(NFI)distributed over Norway between latitudes 58°and 65°N in an 18.2 Mha study *** variables were based on airborne laser scanning(ALS),Sentinel-2,and existing public map *** performed model validation on an independent data set consisting of 63 spruce stands with known ***:The best modelling strategy was to fit independent linear regression models to each observed site index(SI)level and using a SI prediction map in the application of the *** most important predictor variable was an upper percentile of the ALS heights,and root mean squared errors(RMSEs)ranged between 3 and 31 years(6%to 26%)for SI-specific models,and 21 years(25%)on *** deviance(MD)ranged between^(−1) and 3 *** models improved with increasing SI and the RMSEs were largest for low SI stands older than 100 *** a mapped SI,which is required for practical applications,RMSE and MD on plot level ranged from 19 to 56 years(29%to 53%),and 5 to 37 years(5%to 31%),*** the validation stands,the RMSE and MD were 12(22%)and 2 years(3%),***:Tree height estimated from airborne laser scanning and predicted site index were the most important variables in the models describing ***,we obtained good results,especially for stands with high *** models could be considered for practical applications,although we see considerable potential for improvements if better SI maps were available.

关键词： forest age Lidar Optical satellite images remote sensing forest inventory

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A century of National forest inventory in Norway–informing past,present,and future decisions

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forest Ecosystems 2020年第4期7卷 602-620页

作者： Johannes Breidenbach Aksel Granhus Gro Hylen Rune Eriksen Rasmus Astrup National forest inventory Norwegian Institute of Bioeconomy ResearchÅsNorway

Past:In the early twentieth century,forestry was one of the most important sectors in Norway and an agitateddiscussion about the perceived decline of forest resources due to over-exploitation was *** base thediscussion on facts,the young state of Norway established Landsskogtakseringen–the world’s first National forestinventory(NFI).Field work started in 1919 and was carried out by *** were recorded on 10m wide stripswith 1–5 km *** quality and land cover categories were recorded along each *** for the firstcounty were published in 1920,and by 1930 most forests below the coniferous tree line were *** 2ndto 5th inventories followed in the years 1937–*** of 1954,temporary sample plot clusters on a 3 km×3 kmgrid were used as sampling ***:The current NFI grid was implemented in the 6th NFI from 1986 to 1993,when permanent plots ona 3 km×3 km grid were established below the coniferous tree *** of the 7th inventory in 1994,the NFIis continuous,and 1/5 of the plots are measured *** trees with a diameter≥5 cm are recorded oncircular,250 m2 *** NFI grid was expanded in 2005 to cover alpine regions with 3 km×9 km and 9km×9 km *** 2012,the NFI grid within forest reserves was doubled along the cardinal *** temporary plots are used periodically to facilitate county-level *** of today,more than 120variables are recorded in the NFI including bilberry cover,drainage status,deadwood,and forest *** are monitored and trees outside forests are ***:Considerable research efforts towards the integration of remote sensing technologies enable thepublication of the Norwegian forest Resource Map since 2015,which is also used for small area estimation atthe municipality *** the analysis side,capacity and software for long term growth and yield prognosisare being ***,we foresee the inclusion of further variables for monitoring ec

关键词： forest forest annually

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