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Re-estimating the changes and ranges of forest biomass carbon in China during the past 40 years

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Forest Ecosystems 2019年第4期6卷 396-413页

作者： Xiaolu Zhou Xiangdong Lei Caixia Liu Huabing Huang Carl Zhou Changhui Peng Research center for ecological Forecasting and Global Change Northwest A&F UniversityYangling 712100China ecological Modeling and Carbon Science Department of Biology ScienceUniversity of Quebec at MontrealMontrealQC H3C 3P8Canada Institute of Forest Resource Information Techniques Chinese Academy of ForestryBeijing 100091China State Key Laboratory of remote sensing Science Institute of Remote Sensing and Digital EarthChinese Academy of SciencesBeijing 100101China Faculty of Health Sciences University of OttawaOttawaON K1N 6N5Canada.

Background: In recent decades the future of global forests has been a matter of increasing concern, particularly in relation to the threat of forest ecosystem responses under potential climate change. To the future predictions of these responses, the current forest biomass carbon storage(FCS) should first be clarified as much as possible,especially at national scales. However, few studies have introduced how to verify an FCS estimate by delimiting the reasonable ranges. This paper addresses an estimation of national FCS and its verification using two-step process to narrow the uncertainty. Our study focuses on a methodology for reducing the uncertainty resulted by converting from growing stock volume to above-and below-ground biomass(AB biomass), so as to eliminate the significant bias in national scale ***: We recommend splitting the estimation into two parts, one part for stem and the other part for AB biomass to preclude possible significant bias. Our method estimates the stem biomass from volume and wood density(WD), and converts the AB biomass from stem biomass by using allometric ***: Based on the presented two-step process, the estimation of China’s FCS is performed as an example to explicate how to infer the ranges of national FCS. The experimental results demonstrate a national FCS estimation within the reasonable ranges(relative errors: + 4.46% and-4.44%), e.g., 5.6–6.1 PgC for China’s forest ecosystem at the beginning of the 2010 s. These ranges are less than 0.52 PgC for confirming each FCS estimate of different periods during the last 40 years. In addition, our results suggest the upper-limits by specifying a highly impractical value of WD(0.7 t·m-3) on the national scale. As a control reference, this value decides what estimate is impossible to achieve for the FCS ***: Presented methodological analysis highlights the possibility to determine a range that the true value could be located in. The two-ste

关键词： Allometric equation Forest carbon Stem-biomass proportion Volume-derived method Wood density

SPATIO-TEMPORAL CHARACTERISTICS OF NO2 IN PRD URBAN GROUP AND THE ANTHROPOGENIC INFLUENCES ANALYSIS BASED ON OMI remote sensing DATA

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Journal of Tropical meteorology 2016年第4期22卷 568-577页

作者：刘显通郑腾飞万齐林谭浩波邓雪娇李菲邓涛 Guangzhou Institute of Tropical and Marine meteorology/Guangdong Provincial Key Laboratory of Regional Numerical Weather Prediction CMA ecological Meteorological center of Guangdong Province

Spatio-temporal distribution characteristics and variation trends of tropospheric NO_2 in Pearl River Delta(PRD) urban group and its adjacent areas were analyze from 2005 to 2013 based on remote sensing data from ozone monitoring instrument(OMI) satellite, and further explored the impact of human activities on NO_2. Compared with the ground observation data, the OMI NO_2 remote sensing data displayed high reliability. Due to active industrial production, high car ownership, great energy and power consumption, the average tropospheric NO_2concentration(7.4×1015molec/cm2) of PRD region is about 3 times of the adjacent areas. At the same time, the regional high pollution NO_2 in PRD region as a whole, the urban group effect is remarkable. Sinusoidal model can well fit the periodic variation of the NO_2 in PRD and adjacent areas. NO_2 concentration was highest in winter while lowest in summer. The concentration of NO_2 in PRD region is decreasing in recent 9 years, which has a significantly negative correlation with the second industry output and car ownership. This suggests that the nitrogen oxide emissions governance in PRD region had achieved initial results. The concentration of NO_2 increased significantly in the eastern and northern Guangdong Province, there are good positive correlations with the second industrial outputs and car ownerships, it is thus clear that industrial emissions and automobile exhausts are important sources of NO_2 in these regions. The concentration of NO_2 in western Guangdong area is stable.

关键词： Pearl River Delta urban group NO2 spatial and temporal distribution anthropogenic influences

A Deep Learning Application for Building Damage Assessment Using Ultra-High-Resolution remote sensing Imagery in Turkey Earthquake

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International Journal of Disaster Risk Science 2023年第6期14卷 947-962页

作者： Haobin Xia Jianjun Wu Jiaqi Yao Hong Zhu Adu Gong Jianhua Yang Liuru Hu Fan Mo Academy of ecological Civilization Development for JingJin-Ji Tianjin Normal UniversityTianjin 300387China Faculty of Geographical Science Beijing Normal UniversityBeijing 100875China College of Ecology and Environment Institute of Disaster PreventionLangfang 065201China Dpto.de Ingeniería Civil Escuela Politécnica Superior de AlicanteUniversidad de AlicanteE-03080 AlicanteSpain Land satellite remote sensing Application center Ministry of Natural ResourcesBeijing 100048China

Rapid building damage assessment following an earthquake is important for humanitarian relief and disaster emergency *** February 2023,two magnitude-7.8 earthquakes struck Turkey in quick succession,impacting over 30 major cities across nearly 300 km.A quick and comprehensive understanding of the distribution of building damage is essential for e fficiently deploying rescue forces during critical rescue *** article presents the training of a two-stage convolutional neural network called BDANet that integrated image features captured before and after the disaster to evaluate the extent of building damage in *** on high-resolution remote sensing data from WorldView2,BDANet used predisaster imagery to extract building outlines;the image features before and after the disaster were then combined to conduct building damage *** optimized these results to improve the accuracy of building edges and analyzed the damage to each building,and used population distribution information to estimate the population count and urgency of rescue at different disaster *** results indicate that the building area in the Islahiye region was 156.92 ha,with an affected area of 26.60 *** damaged buildings accounted for 15.67%of the total building area in the affected *** population distribution data indicated approximately 253,297,and 1,246 people in the collapsed,severely damaged,and lightly damaged areas,*** verification showed that the BDANet model exhibited good performance in handling high-resolution images and can be used to directly assess building damage and provide rapid information for rescue operations in future disasters using model weights.

关键词： BDANet Building damage assessment Deep learning Disaster assessment Emergency rescue Ultra-high-resolution remote sensing

Spatial prediction and analysis of Himalayan marmot plague natural epidemic foci in China based on HJ-1 satellite data

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Science China Earth Sciences 2010年第S1期53卷 8-15页

作者： GAO MengXu1,4,LI XiaoWen1,2,CAO ChunXiang1,ZHANG Hao1,LI Qun3,ZHOU Hang3 HE QiSheng1,4,XU Min1,4,ZHAO Jian1,4,ZHENG Sheng1,4 & CHEN Wei1,4 1State Key Laboratory of remote sensing Science,Jointly Sponsored by the Institute of remote sensing Applications of Chinese Academy of Sciences and Beijing Normal University,Beijing 100101,China 2School of Geography,Beijing Normal University,Beijing 100875,China 3Office for Disease Control and Emergency Response,Chinese center for Disease Control and Prevention,Beijing 102206,China 4Graduate University of Chinese Academy of Sciences,Beijing 100049,China State Key Laboratory of remote sensing Science Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University Beijing China Graduate University of Chinese Academy of Sciences Beijing China School of Geography Beijing Normal University Beijing China Office for Disease Control and Emergency Response Chinese Center for Disease Control and Prevention Beijing China

Plague,caused by the gram-negative bacterium Yersinia pestis,is a serious and rapidly progressing illness in humans that can be fatal if not treated *** Qinghai-Tibet Plateau is the largest area of natural Himalayan marmot(Marmota himalayana) plague foci in China and covers more than 630000 *** County in Gansu Province is a part of this natural focus of plague and was chosen as a study *** study used an ecological niche modeling(ENM) approach to predict the potential distribution of the Himalayan *** and Disaster Monitor satellite(HJ-1) data was used to investigate environment factors that affect plague host animal *** animal point data from active surveillance was combined with environmental variables from the HJ-1 satellite and other databases,and the models of the potential distribution of Himalayan marmot were produced with the Genetic Algorithm for Rule-Set Production(GARP).The probability of marmot presence was divided into 0-5%,5%-20%,20%-40%,40%-80%,and 80%-100% *** with 80%-100% probability exhibited the greatest potential for the presence of Himalayan *** to the predicted potential distribution of Himalayan marmot in the study area,active surveillance of plague hosts and plague control and prevention could be more efficient.

关键词： Himalayan marmot plague spatial prediction GARP HJ-1 satellite

Forecast Error and Predictability for the Warm-sector and the Frontal Rainstorm in South China

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Journal of Tropical meteorology 2023年第1期29卷 128-141页

作者：孙璐王秋萍陈思远高彦青张旭鹏时洋马旭林 Meteorological Institute of Shaanxi Province Xi'an 710016 China Key Laboratory of Eco-Environment and meteorology for the Qinling Mountains and Loess Plateau Shaanxi Meteorological BureauXi'an 710014 China Nanjing University of Information Science and Technology Nanjing 210044 China Qingdao Air Traffic Management Station of CAAC QingdaoShandong 266108 China Shanghai ecological Forecasting and remote sensing center Shanghai 200030 China China Institute for Radiation Protection Taiyuan 030006 China Guangdong Meteorological Observatory Guangzhou 510640 China

In south China, warm-sector rainstorms are significantly different from the traditional frontal rainstorms due to complex mechanism, which brings great challenges to their forecast. In this study, based on ensemble forecasting, the high-resolution mesoscale numerical forecast model WRF was used to investigate the effect of initial errors on a warmsector rainstorm and a frontal rainstorm under the same circulation in south China, respectively. We analyzed the sensitivity of forecast errors to the initial errors and their evolution characteristics for the warm-sector and the frontal rainstorm. Additionally, the difference of the predictability was compared via adjusting the initial values of the GOOD member and the BAD member. Compared with the frontal rainstorm, the warm-sector rainstorm was more sensitive to initial error, which increased faster in the warm-sector. Furthermore, the magnitude of error in the warm-sector rainstorm was obviously larger than that of the frontal rainstorm, while the spatial scale of the error was smaller. Similarly, both types of the rainstorm were limited by practical predictability and inherent predictability, while the nonlinear increase characteristics occurred to be more distinct in the warm-sector rainstorm, resulting in the lower inherent *** comparison between the warm-sector rainstorm and the frontal rainstorm revealed that the forecast field was closer to the real situation derived from more accurate initial errors, but only the increase rate in the frontal rainstorm was restrained evidently.

关键词： warm-sector rainstorm frontal rainstorm error evolution predictability

A COMPARISON OF THE RETRIEVAL OF ATMOSPHERIC TEMPERATURE PROFILES USING OBSERVATIONS OF THE 60 GHZ AND 118.75 GHZ ABSORPTION LINES

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Journal of Tropical meteorology 2018年第2期24卷 151-162页

作者： HE Qiu-rui WANG Zhen-zhan HE Jie-ying ZHANG Lan-jie Key Laboratory of Microwave remote sensing National Space Science Center Chinese Academy of SciencesBeijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China

The Microwave Temperature Sounder-Ⅱ(MWTS-Ⅱ) and Microwave Humidity and Temperature Sounder(MWHTS) onboard the Fengyun-3 C(FY-3 C) satellite can be used to detect atmospheric temperature profiles. The MWTS-II has 13 temperature sounding channels around the 60 GHz oxygen absorption band and the MWHTS has 8 temperature sounding channels around the 118.75 GHz oxygen absorption line. The data quality of the observed brightness temperatures can be evaluated using atmospheric temperature retrievals from the MWTS-Ⅱ and MWHTS observations. Here, the bias characteristics and corrections of the observed brightness temperatures are described. The information contents of observations are calculated, and the retrieved atmospheric temperature profiles are compared using a neural network(NN) retrieval algorithm and a one-dimensional variational inversion(1 D-var) retrieval algorithm. The retrieval results from the NN algorithm show that the accuracy of the MWTS-Ⅱ retrieval is higher than that of the MWHTS retrieval, which is consistent with the results of the radiometric information analysis. The retrieval results from the 1 D-var algorithm show that the accuracy of MWTS-Ⅱ retrieval is similar to that of the MWHTS retrieval at the levels from 850-1,000 h Pa, is lower than that of the MWHTS retrieval at the levels from 650-850 h Pa and 125-300 h Pa, and is higher than that of MWHTS at the other levels. A comparison of the retrieved atmospheric temperature using these satellite observations provides a reference value for assessing the accuracy of atmospheric temperature detection at the 60 GHz oxygen band and 118.75 GHz oxygen line. In addition, based on the comparison of the retrieval results, an optimized combination method is proposed using a branch and bound algorithm for the NN retrieval algorithm, which combines the observations from both the MWTS-Ⅱand MWHTS instruments to retrieve the atmospheric temperature profiles. The results show that the optimal combination can further i

关键词： Fengyun-3C satellite Microwave Temperature Sounder-II microwave humidity and temperature sounder one-dimensional variational retrieval algorithm neural networks retrieval algorithm

Review and Development on the Studies of Chinese Meteorological satellite and satellite meteorology

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Acta meteorologica Sinica 2006年第3期20卷 259-274页

作者：方宗义许健民赵凤生 National satellite Meteorological center

Meteorological satellite and satellite meteorology are the fastest developing new branches in the atmospheric sciences. Today the meteorological satellite has become a key element in the global atmospheric sounding system while the satellite meteorology is covering the main components of earth＇s system science. This article describes the major achievements that China has made in these fields in the past 30 years. The following contents are involved：（1） History and present status of China＇s meteorological satellites. It covers the development, launch, operation, technical parameters of China＇s polar and geostationary meteorological satellites. （2） Major achievements on remote sensing principle and method. It describes the retrieval of atmospheric temperature and humidity profiles, cloud character retrieval, aerosol character retrieval, precipitation retrieval as well as meteorological satellite data application. weather analysis and forecast, numerical change. Besides, the new results on data the generation of cloud wind. （3） Achievement on the studies of This part covers the applications of meteorological satellite data to forecast, climate monitoring, and prediction of short-term climate assimilation, climate monitoring, and forecast are also included.

关键词： meteorological satellite satellite meteorology satellite data application retrieval method

ecological Assessment of Oxygen Balance:A Case Study of China’s Natural Oxygen Bars

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Journal of Meteorological Research 2023年第3期37卷 404-416页

作者： Hao GAO Xiuzhen HAN Xiurong WANG Yu FU Chen MIAO Key Laboratory of Radiometric Calibration and Validation for Environmental satellites National Satellite Meteorological Centre(National Centre for Space Weather)/CMA Innovation Centre for Fengyun Meteorological Satellites(FYSIC)China Meteorological Administration(CMA)Beijing 100081 Public Meteorological Service Centre China Meteorological AdministrationBeijing 100081 Carbon Neutrality Research center Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029 National remote sensing center of China Beijing 100036

ecological assessment plays a vital role in sustainable development of the environment,and thus exploration of specific and integrated ecological assessment methods has become a critical *** this study,based on the concept of oxygen balance and by accommodating both natural factors and socioeconomic elements,we establish an oxygen(O_(2))balance index(OBI),i.e.,the ratio of the O_(2)production from the ecosystem to the O_(2)consumption by human behavior,based on the net primary productivity(NPP),fuel consumption,gross domestic production(GDP),population data,and so *** results show that the spatial distributions of OBI in China are intimately correlated to the regional vegetation and socioeconomic *** estimated OBI values are then validated by statistical data from 27 counties in China,and it is found that the OBI reflects the ecological environment status ***,the average OBI values derived from 190 natural oxygen bars in China reveal extreme imbalance between O_(2)production and consumption in highly developed regions,especially in the cities,in contrast to good O_(2)balance in areas with high-quality ecological status and less *** findings from this study have quantitatively captured the regional ecological quality,providing guidance for sustainable natural and socioeconomic developments in local areas of China.

关键词： oxygen balance index(OBI) ecological environment remote sensing China’s natural oxygen bars meteorological satellites

Marine aquaculture mapping using GF-1 WFV satellite images and full resolution cascade convolutional neural network

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International Journal of Digital Earth 2022年第1期15卷 2047-2060页

作者： Yongyong Fu Shucheng You Shujuan Zhang Kun Cao Jianhua Zhang Ping Wang Xu Bi Feng Gao Fangzhou Li College of Resources and Environment Shanxi University of Finance and EconomicsTaiyuanPeople’s Republic of China Land satellite remote sensing Application center BeijingPeople’s Republic of China Agricultural Ecology and Resource Protection Shandong Agricultural Ecology and Resource Protection StationJinanPeople’s Republic of China center of Resource and Ecology Environment Research Chinese Academy of Fishery SciencesBeijingPeople’s Republic of China College of Environmental and Resource Sciences Zhejiang UniversityHangzhouPeople’s Republic of China Zhejiang ecological Civilization Academy AnjiPeople’s Republic of China Development Research center for Surveying and Mapping Ministry of Natural ResourcesBeijingPeople’s Republic of China

Growing demand for seafood and reduced fishery harvests have raised intensive farming of marine aquaculture in coastal regions,which may cause severe coastal water problems without adequate environmental *** mapping of mariculture areas is essential for the protection of coastal ***,due to the limited spatial coverage and complex structures,it is still challenging for traditional methods to accurately extract mariculture areas from medium spatial resolution(MSR)*** solve this problem,we propose to use the full resolution cascade convolutional neural network(FRCNet),which maintains effective features over the whole training process,to identify mariculture areas from MSR ***,the FRCNet uses a sequential full resolution neural network as the first-level subnetwork,and gradually aggregates higher-level subnetworks in a cascade ***,we perform a repeated fusion strategy so that features can receive information from different subnetworks simultaneously,leading to rich and representative *** a result,FRCNet can effectively recognize different kinds of mariculture areas from MSR *** show that FRCNet obtained better performance than other classical and recently proposed *** developed methods can provide valuable datasets for large-scale and intelligent modeling of the marine aquaculture management and coastal zone planning.

关键词： Mariculture areas GaoFen-1 wide-field-of-view images fully convolutional neural networks deep learning