Volume XLII-3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 137-141, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-137-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 137-141, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-137-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  30 Apr 2018

30 Apr 2018

SPATIO-TEMPORAL VARIATIONS OF SOIL WATER USE IN THE GROWING SEASON IN NORTHEAST CHINA USING MODIS DATA

s. Chang, F. Huang, B. Li, H. Qi, and H. Zhai s. Chang et al.
  • School of Geographical Sciences, Northeast Normal University, Renmin Street, Changchun, China

Keywords: Soil Water Use, Gross Primary Productivity, Visible and Shortwave Infrared Drought Index (VSDI), MODIS, Spatio-temporal Pattern, Growing Season, Northeast China

Abstract. Water use efficiency is known as an important indicator of carbon and water cycle and reflects the transformation capacity of vegetation water and nutrients into biomass. In this study, we presented a new indicator of water use efficiency, soil water use level (SWUL), derived from satellite remote sensing based gross primary production and the Visible and Shortwave Infrared Drought Index (VSDI). SWUL based on MODIS data was calculated for the growing season of 2014 in Northeast China, and the spatial pattern and the variation trend were analyzed. Results showed that the highest SWUL was observed in forestland with the value of 36.65. In cropland and grassland, the average SWUL were 26.18 and 29.29, respectively. SWUL showed an increased trend in the first half period of the growing season and peaked around the 200th day. After the 220th day, SWUL presented a decreasing trend. Compared to the soil water use efficiency (SWUE), SWUL might depict the water use status at finer spatial resolution. The new indicator SWUL can help promote understanding the water use efficiency for regions of higher spatial heterogeneity.