Spatiotemporal Variability of Gross Primary Productivity in Türkiye: A Multi-Source and Multi-Method Assessment

被引:0
|
作者
Basakin, Eyyup Ensar [1 ,2 ]
Stoy, Paul C. [2 ]
Demirel, Mehmet Cuneyd [1 ]
Pham, Quoc Bao [3 ]
机构
[1] Istanbul Tech Univ, Civil Engn Dept, Hydraul Div, TR-34469 Istanbul, Turkiye
[2] Univ Wisconsin Madison, Dept Biol Syst Engn, Madison, WI 53706 USA
[3] Univ Silesia Katowice, Inst Earth Sci, Fac Nat Sci, Bedzinska St 60, PL-41200 Sosnowiec, Poland
关键词
remote sensing; gross primary productivity; innovative trend analysis; empirical mode decomposition; carbon cycle; Modified Mann-Kendall; EMPIRICAL MODE DECOMPOSITION; NET PRIMARY PRODUCTIVITY; CARBON-DIOXIDE; CLIMATE-CHANGE; WINTER-WHEAT; ECOSYSTEM; TURKEY; VEGETATION; FLUXES; GPP;
D O I
10.3390/rs16111994
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
We investigated the spatiotemporal variability of remotely sensed gross primary productivity (GPP) over T & uuml;rkiye based on MODIS, TL-LUE, GOSIF, MuSyQ, and PMLV2 GPP products. The differences in various GPP products were assessed using Kruskal-Wallis and Mann-Whitney U methods, and long-term trends were analyzed using Modified Mann-Kendall (MMK), innovative trend analysis (ITA), and empirical mode decomposition (EMD). Our results show that at least one GPP product significantly differs from the others over the seven geographic regions of T & uuml;rkiye (chi(2) values of 50.8, 21.9, 76.9, 42.6, 149, 34.5, and 168; p < 0.05), and trend analyses reveal a significant increase in GPP from all satellite-based products over the latter half of the study period. Throughout the year, the average number of months in which each dataset showed significant increases across all study regions are 6.7, 8.1, 5.9, 9.6, and 8.7 for MODIS, TL-LUE, GOSIF, MuSyQ, and PMLV2, respectively. The ITA and EMD methods provided additional insight into the MMK test in both visualizing and detecting trends due to their graphical techniques. Overall, the GPP products investigated here suggest 'greening' for T & uuml;rkiye, consistent with the findings from global studies, but the use of different statistical approaches and satellite-based GPP estimates creates different interpretations of how these trends have emerged. Ground stations, such as eddy covariance towers, can help further improve our understanding of the carbon cycle across the diverse ecosystem of T & uuml;rkiye.
引用
收藏
页数:30
相关论文
共 50 条
  • [1] Uncertainties of gross primary productivity of Chinese grasslands based on multi-source estimation
    He, Panxing
    Ma, Xiaoliang
    Han, Zhiming
    Meng, Xiaoyu
    Sun, Zongjiu
    FRONTIERS IN ENVIRONMENTAL SCIENCE, 2022, 10
  • [2] Improving global gross primary productivity estimation by fusing multi-source data products
    Zhang, Yahai
    Ye, Aizhong
    HELIYON, 2022, 8 (03)
  • [3] Response of ecosystem gross primary productivity to drought in northern China based on multi-source remote sensing data
    Zhang, Ting
    Zhou, Junzhi
    Yu, Ping
    Li, Jianzhu
    Kang, Yanfu
    Zhang, Bo
    JOURNAL OF HYDROLOGY, 2023, 616
  • [4] Multi-Source Remote Sensing Based Modeling of Vegetation Productivity in the Boreal: Issues & Opportunities
    Melser, Ramon
    Coops, Nicholas C.
    Wulder, Michael A.
    Derksen, Chris
    CANADIAN JOURNAL OF REMOTE SENSING, 2023, 49 (01)
  • [5] Multi-source data-driven estimation of urban net primary productivity: A case study of Wuhan
    Chen, Jinlong
    Shao, Zhenfeng
    Huang, Xiao
    Hu, Bin
    INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2024, 127
  • [6] Assessment of Grassland Degradation on the Tibetan Plateau Based on Multi-Source Data
    Wang, Shanshan
    Jia, Lizhi
    Cai, Liping
    Wang, Yijia
    Zhan, Tianyu
    Huang, Anqi
    Fan, Donglin
    REMOTE SENSING, 2022, 14 (23)
  • [7] Spatiotemporal variations and driving forces of regional-scale NPP based on a multi-method integration: a case study in the Beibu Gulf Economic Zone
    Zhou, Lv
    Dong, Qiulin
    Pan, YuanJin
    Yang, Fei
    He, MeiLin
    Huang, Xiang
    Xu, Jiao
    ECOLOGICAL INDICATORS, 2025, 174
  • [8] Building Contour Optimization Method for Multi-Source Data
    Hu Xiang
    Wu Jianhua
    Wei Ning
    Tu Haowen
    ACTA OPTICA SINICA, 2023, 43 (12)
  • [9] Estimating Vegetation Primary Production in the Heihe River Basin of China with Multi-Source and Multi-Scale Data
    Cui, Tianxiang
    Wang, Yujie
    Sun, Rui
    Qiao, Chen
    Fan, Wenjie
    Jiang, Guoqing
    Hao, Lvyuan
    Zhang, Lei
    PLOS ONE, 2016, 11 (04):
  • [10] Evaluation of Spatiotemporal Changes in Cropland Quantity and Quality with Multi-Source Remote Sensing
    Liu, Han
    Wang, Yu
    Sang, Lingling
    Zhao, Caisheng
    Hu, Tengyun
    Liu, Hongtao
    Zhang, Zheng
    Wang, Shuyu
    Miao, Shuangxi
    Ju, Zhengshan
    LAND, 2023, 12 (09)