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Poortinga, A., Bastiaanssen, W., Simons, G., Saah, D., Senay, G., Fenn, M., Bean, B., & Kadyszewski, J. (2017). A Self-Calibrating Runoff and Streamflow Remote Sensing Model for Ungauged Basins Using Open-Access Earth Observation Data. Remote Sensing, 9, 86.
https://doi.org/10.3390/rs9010086

has been cited by the following article:

• TITLE: Spatio-Temporal Determination of Irrigated Paddy Rice Pixels Using Evapotranspiration and Vegetation Indices: A Case Study for Ca River Basin in Vietnam

  AUTHORS: Chung N. Luong, Lan T. Ha, Thanh C. Pham, Hung X. Dinh, Thanh T. Hoang, Hoan N. Nguyen, Tuan V. Nguyen, Phung X. Nguyen

  KEYWORDS: Remote Sensing, Drought Management, Irrigated Paddy

  JOURNAL NAME: Journal of Geoscience and Environment Protection, Vol.8 No.12, December 16, 2020

  ABSTRACT: Improving irrigation monitoring and efficiency is a current priority of the Government of Vietnam, focusing primarily on the agricultural sector which consumes most of the available surface and groundwater. This paper presents how remote sensing can be used in an integrated manner to achieve better understanding of key eco-hydrological processes including precipitation, evapotran-spiration, irrigation and crop growth. The results indicated that Normalized Difference Vegetation Index derived from Moderate Resolution Imaging Spectroradiometer (MODIS) can be applied to determine irrigated pixels on a spatial and temporal basis. The validation using measured water level showed a Pearson correlation of 0.7 proving the high accuracy of this method. The inclusion of these technologies is deemed necessary to improve water resources monitoring and management and hence, ensure long-term drought resilience and water and food security. Ca River Basin in the central Vietnam was selected as a case study to test this approach.