Please wait a minute...
img

官方微信

遥感技术与应用  2022, Vol. 37 Issue (1): 94-107    DOI: 10.11873/j.issn.1004-0323.2022.1.0094
青促会十周年专栏     
黑河流域湿地、农田、草地生态系统碳通量变化特征及驱动因子分析
白雪洁1,2(),王旭峰1(),柳晓惠3,周旭强4
1.中国科学院西北生态环境资源研究院,甘肃省遥感重点实验室,甘肃 兰州 730000
2.中国科学院大学,北京 100049
3.会宁县农业农村局,甘肃 会宁 730799
4.西北师范大学,甘肃 兰州 730070
Dynamics and Driving Factors of Carbon Fluxes in Wetland, Cropland and Grassland Ecosystems in Heihe River Basin
Xuejie Bai1,2(),Xufeng Wang1(),Xiaohui Liu3,Xuqiang Zhou4
1.Northwest Institute of Eco-Environment and Resources,Chinese Academy of Sciences,Key Laboratory of Remote Sensing of Gansu Province,Heihe Remote Sensing Experimental Research Station,Lanzhou 730000,China
2.University of Chinese Academy of Sciences,Beijing 100049,China
3.Huining Prefectural Bureau of Agriculture and Rural Affairs,Huining 730799,China
4.Northwest Normal University,Lanzhou 730070,China
 全文: PDF(8080 KB)   HTML
摘要:

为了认识黑河流域湿地、农田、草地生态系统不同时间尺度的碳通量特征及与环境因子的关系,并为干旱区生态系统碳源/汇效应评估提供理论依据。采用涡度相关技术对黑河流域湿地、农田、草地生态系统进行长达7 a的碳通量、气象因子观测,分析了净生态系统生产力(NEP)、生态系统呼吸(Reco)、总初级生产力(GPP)在日际、季节、年际3种尺度的动态变化机制,并比较了碳通量与植被指数NDVI、EVI的季节变化异同。经分析发现:①黑河流域湿地与草地、农田生态系统均在日尺度上呈现明显的单峰“倒U”分布,草地于12:00到达峰值,湿地与农田于13:00到达峰值,峰值碳通量农田>湿地>草地;②季节尺度上,湿地与农田、草地生态系统碳通量以及NDVI、EVI均呈单峰“倒U”分布,6~9月生长季为明显碳吸收,7月份到达全年峰值,碳吸收峰值为农田>湿地>草地,NDVI、EVI峰值则为阿柔站>湿地站>大满站>大沙龙站。③年固碳能力为农田(648.90 gC/m2/a)>湿地(627.51 gC/m2/a)>草地(228.15 gC/m2/a、307.89 gC/m2/a)。④与环境因子做相关分析发现,日时间尺度上,湿地生态系统的NEP、Reco、GPP与潜热、气温、饱和水汽压差、辐射显著相关(p<0.05),农田与草地生态系统NEP、Reco、GPP受潜热、气温、土壤温度的影响较大;在季节尺度上,站点碳通量与各环境因子的相关性较高。但在年际尺度上,NEP、GPP、Reco与环境因素的相关性普遍较低,且无明显规律,其中阿柔站(草地)、大满站(农田)碳通量主要受到气温、2 cm土壤湿度、潜热以及降水的影响较大,大沙龙站(草地)则主要受到气温控制,湿地站(湿地)则与潜热相关性最强;另外阿柔站与湿地站碳通量与植被指数NDVI、EVI均呈现年际上的显著相关。本研究能为西北地区生态系统的碳收支、调控因子分析提供理论支撑。

关键词: 涡度相关法碳通量净生态系统生产力生态呼吸总初级生产力植被指数    
Abstract:

The Heihe River Basin is the second largest inland river basin in China. The Heihe River basin has been studied as a representative basin in arid area. In order to explore the characteristics of carbon fluxes of wetland, cropland and grassland ecosystems in Heihe River Basin, the Net Ecosystem Productivity (NEP), Ecosystem Respiration (Reco), Gross Primary Productivity (GPP) and meteorological factors were observed and analyzed. To further understand the carbon source/sink effect and its climate regulation mechanism, in this study, the correlation between carbon fluxes (NEP, GPP and Reco) and driving factors were calculated at different time scales. The result indicated that: (1) The temporal variation of NEP in wetland, grassland and cropland ecosystems in the Heihe River Basin was a single peak "inverted U" on daily scale, and the carbon fluxes of grassland reached the peak at 12:00 am, the carbon fluxes of wetland and cropland reached the peak at 13:00 pm; (2) On seasonal scale, the temporal variation of carbon fluxes of wetland, cropland and grassland ecosystems showed patterns of single peaks. During the growing season which from June to September, carbon absorption reached peak in July and the peak value of carbon absorption was farmland>wetland>grassland. (3) The average annual NEP for Shidi site (reed), Daman site (cropland), Arou site (grassland) and Dashalong site (grassland) are 627.51 gC/m2/a, 648.90 gC/m2/a, 228.15 gC/m2/a and 307.89 gC/m2/a, respectively. (4) The results showed that NEP, Reco and GPP of wetland ecosystem were significantly correlated with LE, Tair, VPD and Rg, NEP, Reco and GPP of cropland and grassland ecosystem were greatly affected by LE, Tair and Tsoil. However, there was no significant correlation between NEP, GPP, Reco and environmental factors on annual scale. The annual carbon fluxes of Arou (grassland) and Daman (cropland) were positive correlated with Tair and Ms(R>0.4), and negative correlated with LE and Rain (R<-0.4) annual carbon fluxes of Dashalong (grassland) was negative correlated with Tair, the annual carbon fluxes of Shidi (reed) was mainly negative controlled by LE. In addition, the inter-annual carbon fluxes variation at Arou and Shidi were significantly correlated with NDVI and EVI(0.6

Key words: Eddy covariance    Carbon Fluxes    Net Ecosystem Production    Ecosystem respiration    GPP    NDVI    EVI
收稿日期: 2020-12-04 出版日期: 2022-04-08
ZTFLH:  TP79  
基金资助: 国家自然科学基金项目(41771466);科技部重点研发计划(2017YFA0604801)
通讯作者: 王旭峰     E-mail: baixj@lzb.ac.cn;wangxufeng@lzb.ac.cn
作者简介: 白雪洁(1995-),女,山西运城人,硕士研究生,主要从事碳通量研究。E?mail: baixj@lzb.ac.cn
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章  
白雪洁
王旭峰
柳晓惠
周旭强

引用本文:

白雪洁,王旭峰,柳晓惠,周旭强. 黑河流域湿地、农田、草地生态系统碳通量变化特征及驱动因子分析[J]. 遥感技术与应用, 2022, 37(1): 94-107.

Xuejie Bai,Xufeng Wang,Xiaohui Liu,Xuqiang Zhou. Dynamics and Driving Factors of Carbon Fluxes in Wetland, Cropland and Grassland Ecosystems in Heihe River Basin. Remote Sensing Technology and Application, 2022, 37(1): 94-107.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2022.1.0094        http://www.rsta.ac.cn/CN/Y2022/V37/I1/94

图1  黑河流域站点分布图
站点下垫面位置LAT/°LON/°

ELEV

/m

MAT

/℃

MAP

/mm

LE

/Wm-2

Rg

/Wm-2

Tsoil

/℃

RH

/%

VPD

/hPa

大沙龙站沼泽化高寒草甸上游98.940 6°E38.839 9°N373 9-3.89360.4850.40210.020.0756.822.44
阿柔站高寒草甸上游100.464 3°E38.047 3°N303 3-0.12357.5752.68189.584.2659.593.37
大满站玉米中游100.372 23°E38.855 51°N155 66.47126.5267.64177.178.9457.916.56
湿地站芦苇中游100.446 4°E38.975 1°N146 09.677.91109.21188.508.2144.989.11
表1  站点情况及环境因子
站点

架高

/m

超声风速仪开路CO2/H2O分析仪

间距

/cm

阿柔超级站3.5CSAT3Li7500A15
大沙龙站4.5CSAT3Li7500RS15
大满超级站4.5CSAT3Li7500A17
湿地站5.2GillLi7500A25
表2  站点架高、超声风速仪与CO2/H2O分析仪
图2  各站点NEP、Reco和GPP日变化特征
图3  2013~2019年各站点NEP、Reco和GPP的季节变化
图4  2013~2019年各站点NDVI和EVI的季节变化
图5  2013~2019年各站点NEP、Reco and GPP的年际变化(umol/m2/a)与年际变化率(%)
图6  2013~2019年各站点环境因子的年际变化
图7  各站点与环境因子、植被指数在日、季节尺度上的Person相关性(P <0.05)
图8  各站点NEP、Reco、GPP与环境因子、植被指数之间的年际Person相关(斜纹:P >= 0.05;纯色:P < 0.05)
1 Tarin T, Nolan R H, Eamus D . et al. Carbon and water fluxes in two adjacent Australian semi-arid ecosystems[J].Agricultural and Forest Meteorology,2020,281. DOI.org/10.1016/j.agrformet.2019.107853.
2 Li Guodong, Zhang Junhua, Chen Cong,et al.Research progress on carbon storage and flux in different terrestrial ecosystem in China under global[J]. Ecology and Environment Sciences,2013,22(5): 873-878.
2 李国栋,张俊华,陈聪,等.气候变化背景下中国陆地生态系统碳储量及碳通量研究进展[J].生态环境学报,2013,22(5): 873-878.
3 Ahlstrom A, Raupach M R, Schurgers G, et al. The dominant role of semi-arid ecosystems in the trend and variability of the land CO2 sink[J].Science,2015,348(6237): 895-899.
4 Wang Fuqiang, Liu Yangli, Yang Huan,et al. Carbon Flux characteristics and influencing factors of riverside wetland ecosystem in Cold Region[J]. International Journal Hydroelectric Energy,2018,36(10): 68-71.
4 王富强,刘扬李,杨欢,等.寒区滨河湿地生态系统碳通量特征及影响因素[J].水电能源科学,2018,36(10): 68-71.
5 Jiang Guoqing, Wang Yujie, Sun Rui,et al. Dynamics of CO2 flux and analysis of light use efficiency over a wetland in Zhangye,China[J]. Arid Land Geography,2016,39(4): 809-816.
5 蒋国庆,王玉洁,孙睿,等.张掖湿地CO2通量变化特征及光能利用率分析[J].干旱区地理,2016,39(4): 809-816.
6 Aslan-Sungur G, Lee X H, Evrendilek F, et al. Large interannual variability in net ecosystem carbon dioxide exchange of a disturbed temperate peatland[J].Science of the Total Environment,2016,554: 192-202.
7 Dise N B. Peatland Response to Global Change[J].Science,2009,326(5954): 810-811.
8 Wang H, Li X, Xiao J, et al. Carbon fluxes across alpine, oasis, and desert ecosystems in northwestern China: The importance of water availability[J].Science of the Total Environment,2019,697. DOI.org/10.1016/j.scitotenv.2019. 33978
9 Chen Zhi, Yu Guirui, Zhu Xianjin, et al. Spatial pattern and regional characteristics of terrestrial ecosystem carbon fluxes in the northern hemisphere[J]. Quaternary Sciences,2014,34(4):710-722.
9 陈智,于贵瑞,朱先进,等.北半球陆地生态系统碳交换通量的空间格局及其区域特征[J].第四纪研究,2014,34(4):710-722.
10 Tian Rongcai, Wen Shuangya, Yang Huibing, et al. Research Progress on Carbon Flux in Agro-ecosystem Based on Eddy Covariance System[J]. Acta Laser Biology Sinica,2019,28(5):415-420.
10 田容才,文双雅,阳会兵.基于涡度相关法的农田生态系统碳通量研究进展[J].激光生物学报,2019,28(5): 415-420.
11 Lin Tongbao, Wang Zhiqiang, Song Xuelei,et al.CO2 flux and impact factors in winter wheat field ecosystem[J]. Chinese Journal of Eco-Agriculture,2008,16(6):1458-1463.
11 林同保,王志强,宋雪雷,等.冬小麦农田二氧化碳通量及其影响因素分析[J].中国生态农业学报,2008,16(6):1458-1463.
12 Gao Yun, Guo Weihua. Main controlling factors of carbon flux of typical economic crops in arid area of northwest China[J]. Rural Economy and Science-Technology,2017,28(22): 34-35.
12 高云,郭维华.西北旱区典型经济作物碳通量主控因子研究[J].农村经济与科技,2017,28(22): 34-35.
13 Tong Xiaojuan, Li Jun, Liu Du, et al. Characteristics and controlling factors of photosynthesis in a maize ecosystem on the North China Plain[J].Acta Ecologica Sinica,2011,31(17): 4889-4899.
13 同小娟,李俊,刘渡.华北平原玉米田生态系统光合作用特征及影响因素[J].生态学报,2011,31(17): 4889-4899.
14 Gou Qianqian, Qu Jianjun, Han Zhiwen, et al. Contrastive analysis of microclimate and CO2 flux in different season in Xihu desert wetland of extreme arid region[J]. Arid Land Geography,2014,37(6): 1119-1127.
14 缑倩倩,屈建军,韩致文.极端干旱区荒漠-湿地生态系统小气候特征与碳通量变化季节对比[J].干旱区地理,2014,37(6): 1119-1127.
15 Li Yü, Kang Xiaoming, Hao Yanbin, et al. Carbon,water and heat fluxes of a reed(Phragmites australis) wetland in the Yellow River Delta,China[J]. Acta Ecologica Sinica,2014,34(15): 4400-4411.李玉,康晓明,郝彦宾,等.黄河三角洲芦苇湿地生态系统碳、水热通量特征[J].生态学报,2014 34(15): 4400-4411.
16 Li Jinqun, Ge Jiwen, Peng Fengjiao, et al. Studies on Carbon-water Flux and Water Use Efficiency in Dajiuhu Peat Wetland Ecosystem[J]. Safety and Environmental Engineering,2019,26(1):14-25.
16 李金群,葛继稳,彭凤姣,等.大九湖泥炭湿地生态系统碳水通量及水分利用效率研究[J].安全与环境工程,2019,26(1): 14-25.
17 Wang Lili, Yang Tao, Gao Chen, et al. Diurnal Variation of Net Ecosystem CO2 Exchange of Nanji Wetland Ecosystem in Poyang Lake[J]. Journal of Ecology and Rural Environment,2017,33(11): 1007-1012.
17 王莉莉,杨涛,高晨,等.鄱阳湖南矶湿地净生态系统CO2交换量的日变化特征[J].生态与农村环境学报,2017,33(11): 1007-1012.
18 Han G X, Yang L Q, Yu J B, et al. Environmental Controls on Net Ecosystem CO2 Exchange over a Reed (Phragmites australis) Wetland in the Yellow River Delta, China[J].Estuaries and Coasts,2013,36(2):401-413.
19 An Xiang, Chen Yunming, Tang Yakun, et al. Factors Affecting the Spatial Variation of Carbon Use Efficiency and Carbon Fluxes in East Asian Forest and Grassland[J]. Research of Soil and Water Conservation,2017,24(5):79-87,92.
19 安相,陈云明,唐亚坤.东亚森林、草地碳利用效率及碳通量空间变化的影响因素分析[J].水土保持研究,2017,24(5):79-87,92.
20 Chen Yinping, Niu Yayi, Li Wei, et al. Characteristics of Carbon Flux in Sandy Grassland Ecosystem under Natural Restoration in Horqin Sandy Land[J]. Plateau Meteorology,2019,38(3): 650-659.
20 陈银萍,牛亚毅,李伟,等.科尔沁沙地自然恢复沙质草地生态系统碳通量特征[J].高原气象,2019,38(3): 650-659.
21 Wang Haibo, Ma Mingguo, Wang Xunfeng, et al. Carbon flux variation characteristics and its influencing factors in an alpine meadow ecosystem on eastern Qinghai-Tibetan plateau[J]. Journal of Arid Land Resources and Environment,2014,28(6):50-56.
21 王海波,马明国,王旭峰,等.青藏高原东缘高寒草甸生态系统碳通量变化特征及其影响因素[J].干旱区资源与环境,2014,28(6):50-56.
22 Zhang Fawei, Li Yingnian, Cao Guangmin, et al. CO2 fluxes and their driving factors over alpine meadow grassland ecosystems in the northern shore of Qinghai Lake, China[J]. Chinese Journal of Plant Ecology, 2012,36(3):187-198.
22 张法伟,李英年,曹广民,等.青海湖北岸高寒草甸草原生态系统CO2通量特征及其驱动因子[J].植物生态学报,2012,36(3): 187-198.
23 Wang Xiang, Zheng Wei, Zhu Yaqiong, et al. Effects of plowing and sowing on carbon and Water Fluxes in mountain meadow in Zhaosu Basin[J]. Chinese Journal of Grassland,2017,39(2): 1-10.
23 王祥,郑伟,朱亚琼,等.人工草地建植对昭苏盆地山地草甸碳水通量特征的影响[J].中国草地学报,2017,39(2): 1-10.
24 Yue Guangyang, Zhao Lin, Zhao Yonghua, et al. Research advances of Grassland Ecosystem CO2 Flux on Qinghai-Tibetan Plateau[J]. Journal of Glaciology and Geocryology,2010,32(1): 166-174.
24 岳广阳,赵林,赵拥华,等.青藏高原草地生态系统碳通量研究进展[J].冰川冻土,2010,32(1):166-174.
25 Chen Shiping, You Cuihai, Hu Zhongmin, et al. Eddy covariance technique and its applications in flux observations of terrestrial ecosystems[J]. Chinese Journal of Plant Ecology, 2020,44(4): 291-304.
25 陈世苹,游翠海,胡中民,等.涡度相关技术及其在陆地生态系统通量研究中的应用[J].植物生态学报,2020,44(4): 291-304.
26 Shen Yan, Liu Yunfen, Wang Yan, et al. Advances in applying the Eddy-Covariance technique to calculate Heat, Moisture and CO2 Flux[J]. Journal of Nanjing Institute of Meteorology,2005,28(4):559-566.
26 沈艳,刘允芬,王堰.应用涡动相关法计算水热、CO2通量的国内外进展概况[J].南京气象学院学报,2005,28(4):559-566.
27 Shi Guifen, He Weiguang. Application of Eddy covariance technology in Flux research of farmland ecosystem[J]. Modern Agricultural Science And Technology,2019(6):141-143.
27 史桂芬,贺伟光.涡度相关技术在农田生态系统通量研究中的应用[J].现代农业科技,2019(6):141-143.
28 Liu S, Li X, Xu Z, et al. The Heihe integrated observatory network: A basin‐scale land surface processes observatory in China[J].Vadose Zone Journal,2018,17(1):1-21.
29 Xu Ziwei, Liu Shaomin, Che Tao, et al. Operation and maintenance and data quality control of the Heihe integrated observatory network[J]. Resources Science,2020,42(10):1975-1986.
29 徐自为,刘绍民,车涛,等.黑河流域地表过程综合观测网的运行、维护与数据质量控制[J].资源科学,2020,42(10):1975-1986.
30 Lasslop G, Reichstein M, Papale D, et al. Separation of net ecosystem exchange into assimilation and respiration using a light response curve approach: critical issues and global evaluation[J].Global Change Biology,2010,16(1):187-208.
31 Lovett G, Cole J, Pace M. Is net ecosystem production equal to ecosystem carbon accumulation?[J].Ecosystems,2006,9(1):152-155.
32 Tao Zhen, Shen Chengde, Gao Quangzhou, et al. Soil Organic Carbon Storage and Vertical Distribution of Alpine Meadow on the Tibetan Platea[J].Acta Geographica Sinica,2006,61(7):720-728.
32 陶贞,沈承德,高全洲,等.高寒草甸土壤有机碳储量及其垂直分布特征[J]. 地理学报,2006,61(7):720-728.
33 Biederman J A, Scott R L, Bell T W, et al. CO2 exchange and evapotranspiration across dryland ecosystems of southwestern North America[J].Global Change Biology,2017,23(10): 4204-4221.
34 Jia X, Zha T S, Gong J N, et al. Carbon and water exchange over a temperate semi-arid shrubland during three years of contrasting precipitation and soil moisture patterns[J].Agricultural and Forest Meteorology,2016,228: 120-129.
35 Domingo F, Serrano-Ortiz P, Were A, et al. Carbon and water exchange in semiarid ecosystems in SE Spain[J].Journal of Arid Environments,2011,75(12): 1271-1281.
36 Serrano-Ortiz P, Domingo F, Cazorla A,et al.Interannual CO2 exchange of a sparse Mediterranean shrubland on a carbonace-ous substrate[J]. Journal of Geophysical Research-Biogeosciences,2009,114:G04015. DOI.org/10.1029/2009JG000983.
37 Wu Fangtao, Cao Shengkui, Cao Guangchao, et al. Variation of CO2 Flux of alpine wetland ecosystem of kobresia tibetica wet meadow in Lake Qinghai[J].Journal of Ecology and Rural Environment, 2018,34(2): 124-131.
37 吴方涛,曹生奎,曹广超,等.青海湖高寒藏嵩草湿草甸湿地生态系统CO2通量变化特征[J].生态与农村环境学报,2018,34(2):124-131.
38 Cao S K, Cao G C, Chen K L,et al. Characteristics of CO2, water vapor, and energy exchanges at a headwater wetland ecosystem of the Qinghai Lake[J].Canadian Journal of Soil Science,2019,99(3): 227-243.
39 Chen Xiaoping. Variations and influence mechanism of Carbon and Water Flux in Horqin Dune and meadow wetland landscape[D]. Hohhot:Inner Mongolia Agricultural University,2018.
39 陈小平. 科尔沁沙丘—草甸湿地水热碳通量变化及响应机制研究[D].呼和浩特:内蒙古农业大学,2018.
40 Chen Z, Yu G R, Ge J P,et al. Roles of Climate, Vegetation and soil in regulating the spatial variations in ecosystem Carbon dioxide fluxes in the Northern Hemisphere[J].Plos One,2015,10(4):e0125265. DOI:10.1371/journal.pone.0125265 .
doi: 10.1371/journal.pone.0125265
41 Baldocchi D H, Chu H M, Reichstein M. Inter-annual variability of net and gross ecosystem carbon fluxes: a review[J]. Agricultural and Forest Meteorology,2018,249:520-533.
[1] 郭擎,朱丽娅,李安,顾铃燕. 基于NDVI变化检测的滑坡遥感精细识别[J]. 遥感技术与应用, 2022, 37(1): 17-23.
[2] 李淑贞,徐大伟,范凯凯,陈金强,佟旭泽,辛晓平,王旭. 基于无人机与卫星遥感的草原地上生物量反演研究[J]. 遥感技术与应用, 2022, 37(1): 272-278.
[3] 马锦典,江洪. SEVI指数消除4种十米级空间分辨率卫星影像地形阴影影响的效果评价[J]. 遥感技术与应用, 2021, 36(5): 1100-1110.
[4] 吴川虎,陶于祥,罗小波. 基于Google Earth Engine的重庆市植被指数长时间序列S-G滤波方法的改进与实现[J]. 遥感技术与应用, 2021, 36(5): 1189-1198.
[5] 罗玲,毛德华,张柏,王宗明,杨桄. 芦苇湿地植被NPP估算方法探索与应用[J]. 遥感技术与应用, 2021, 36(4): 742-750.
[6] 朱曼,张立福,王楠,林昱坤,张琳姗,王飒,刘华亮. 基于Sentinel-2的UNVI植被指数及性能对比研究[J]. 遥感技术与应用, 2021, 36(4): 936-947.
[7] 屈炀,袁占良,赵文智,陈学泓,陈家阁. 基于多时序特征和卷积神经网络的农作物分类[J]. 遥感技术与应用, 2021, 36(2): 304-313.
[8] 帅艳民,杨健,吴昊,邵聪颖,徐辛超,刘明岳,刘涛,梁继. 基于无人机观测的水稻冠层样方多角度反射特点分析[J]. 遥感技术与应用, 2021, 36(2): 342-352.
[9] 刘莹,朱秀芳,徐昆,陈令仪,郭锐. 干旱对灌溉和雨养农田生态系统生产力的影响对比分析[J]. 遥感技术与应用, 2021, 36(2): 381-390.
[10] 孙奇,关琳琳,焦全军,刘新杰,戴华阳. 基于植被指数融合的冬小麦生物量反演研究[J]. 遥感技术与应用, 2021, 36(2): 391-399.
[11] 杨昊翔,张丽,闫敏,林光辉. 基于高时空分辨率融合影像的红树林总初级生产力遥感估算[J]. 遥感技术与应用, 2021, 36(2): 453-462.
[12] 侯吉宇,周艳莲,刘洋. 不同叶面积指数遥感数据模拟中国总初级生产力的时空差异[J]. 遥感技术与应用, 2020, 35(5): 1015-1027.
[13] 王雅楠,韦瑾,汤旭光,韩旭军,马明国. 应用叶绿素荧光估算植被总初级生产力研究进展[J]. 遥感技术与应用, 2020, 35(5): 975-989.
[14] 唐希颖,崔耀平,李楠,付一鸣,刘小燕,闰亚迪. 2000~2015年北京市土地利用强度及其辐射反馈评估[J]. 遥感技术与应用, 2020, 35(3): 587-595.
[15] 王红岩,汪晓帆,高亮,李强子,赵龙才,杜鑫,张源. 基于季相变化特征的撂荒地遥感提取方法研究[J]. 遥感技术与应用, 2020, 35(3): 596-605.