Assessment of the Water Area in the Lowland Region of the Mekong River Using MODIS EVI Time Series

被引:0
|
作者
Chien Pham Van [1 ]
Giang Nguyen-Van [1 ]
机构
[1] Thuyloi Univ, 175 Tay Son, Hanoi, Vietnam
关键词
MODIS images; Mekong River; EVI; DELTA;
D O I
10.1007/978-3-030-38364-0_18
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents an application of reconstructing Moderate-Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) time series to extract the water area in the lowland region of the Mekong River. Firstly, MODIS13A1 EVI time series with land surface reflectance 16day and 500 m spatial resolution is collected from 2000 to 2017, resulting total of 411 images. Then, these images are used for reconstructing EVI time-series by using the Whittaker smoother method on the Google Earth Engine. Next, the water area in each image is computed based on the smooth EVI value. The results showed that the extracting water areas in year 2000 was in line with the observed water elevation at Tan Chau station (for the Mekong Delta) and at Phnom Penh station (for the Cambodian region). The correlation coefficient between the extracting water area and water elevation equals to 0.885 for the Mekong Delta while its value is 0.924 for the Cambodian region. The extracting water area from MODIS13A1 EVI for the lowland region of the Mekong River can be used for assessment of inundated area resulting from different flow conditions as well as for studying inundation processes in the lowland region of the Mekong River when using hydrodynamic models.
引用
收藏
页码:197 / 207
页数:11
相关论文
共 50 条
  • [1] Winter wheat planting area extraction based on MODIS EVI image time series
    Zhang X.
    Shuai T.
    Yang H.
    Huang C.
    Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 2010, 26 (SUPPL. 1): : 220 - 224
  • [2] Mapping Crop Cycles in China Using MODIS-EVI Time Series
    Li, Le
    Friedl, Mark A.
    Xin, Qinchuan
    Gray, Josh
    Pan, Yaozhong
    Frolking, Steve
    REMOTE SENSING, 2014, 6 (03) : 2473 - 2493
  • [3] Monitoring Forest Growth Disturbance Using Time Series MODIS EVI Data
    Liu Lijuan
    Pang Yong
    Zhang Xiaoyang
    Svein Solberg
    Fan Wenyi
    Li Zengyuan
    Li Mingze
    Chinese Forestry Science and Technology, 2012, 11 (03) : 62 - 62
  • [4] Forecasting time series water levels on Mekong river using machine learning models
    Thanh-Tung Nguyen
    Quynh Nguyen Huu
    Li, Mark Junjie
    2015 SEVENTH INTERNATIONAL CONFERENCE ON KNOWLEDGE AND SYSTEMS ENGINEERING (KSE), 2015, : 292 - 297
  • [5] Extraction of Rice Planting Area Based on MODIS-EVI Time Series and Phenological Characteristics
    Tian M.
    Shan J.
    Lu B.
    Huang X.
    Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery, 2022, 53 (08): : 196 - 202
  • [6] Reconstruction of time series MODIS EVI data using de-noising algorithms
    Priyadarshi, Niraj
    Chowdary, V. M.
    Srivastava, Y. K.
    Das, Iswar Chandra
    Jha, Chandra Shekhar
    GEOCARTO INTERNATIONAL, 2018, 33 (10) : 1095 - 1113
  • [7] Preliminary study on cropping pattern mapping using MODIS EVI image time series
    Zhang, Xia
    Jiao, Quanjun
    Zhang, Bing
    Chen, Zhengchao
    Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 2008, 24 (05): : 161 - 165
  • [8] Winter wheat area estimation from MODIS-EVI time series data using the Crop Proportion Phenology Index
    Pan, Yaozhong
    Li, Le
    Zhang, Jinshui
    Liang, Shunlin
    Zhu, Xiufang
    Sulla-Menashe, Damien
    REMOTE SENSING OF ENVIRONMENT, 2012, 119 : 232 - 242
  • [9] Land cover classification of the North China Plain using MODIS_EVI time series
    Zhang Xia
    Sun Rui
    Zhang Bing
    Tong Qingxi
    ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2008, 63 (04) : 476 - 484
  • [10] Wavelet approach applied to EVI/MODIS time series and meteorological data
    Moreira, Andreise
    Fontana, Denise Cybis
    Kuplich, Tatiana Mora
    ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2019, 147 : 335 - 344