Your search found 3 records
1 Hao, W.; Jianhua, W.; Dong, J. 2003. Modern information technology based directional retrieval of annual precipitation of the Yellow River basin. In Yellow River Conservancy Commission. Proceedings, 1st International Yellow River Forum on River Basin Management – Volume III. Zhengzhou, China: The Yellow River Conservancy Publishing House. pp.286-291.
River basins ; Precipitation ; Remote sensing / China / Yellow River Basin
(Location: IWMI-HQ Call no: 333.91 G592 YEL Record No: H034689)

2 Hao, W.; Mei, X.; Cai, Xueliang; Du, J.; Liu, Q. 2011. Crop planting extraction based on multi-temporal remote sensing data in Northeast China. In Chinese. Transactions of the Chinese Society of Agricultural Engineering, 27(1):201-207. [doi: https://doi.org/ 10.3969/j.issn.1002-6819.2011.01.033]
Crop yield ; Water productivity ; Remote sensing ; Time series analysis / China / Northeast China
(Location: IWMI HQ Call no: e-copy only Record No: H043831)
https://vlibrary.iwmi.org/pdf/H043831.pdf
(1.88 MB)
Crop area and its spatial distribution are generally considered to be essential data inputs for crop yield estimation, assessment of water productivity and adjustment of cropping structure to support science and policy applications focused on understanding the role and response of the agricultural sector to environmental change issues. The objective of this research was to evaluate the applicability of time-series MODIS 250m normalized difference vegetation index (NDVI) data for large-area crop mapping over Northeast China. Spatial pattern of crop planting was obtained based on 16-day time-series MODIS 250m NDVI data from 2007 to 2008, Landsat enhanced thematic mapper plus (ETM+) images, and ground truth data using Optimal Iteration Unsupervised Classification, spectral matching technique (SMT) and Google Earth. Sub-pixel area fraction estimate was applied to estimate cropland area, rice area, spring maize area and soybean area. We found that the position precision was 85.7%, their correlation coefficient compared with statistic was 0.916, 0.685, 0.746 and 0.681 respectively, and that there was significant difference between these groups by using paired samples test. Results indicated that the method can accurately reflect various crop distributions in Northeast China and be applied for large-area crops classification and crop planting extraction.

3 Liu, Q.; Yan, C.; Yang, J.; Mei, X.; Hao, W.; Ju, H. 2015. Impacts of climate change on crop water requirements in Huang-Huai-Hai Plain, China. In Hoanh, Chu Thai; Johnston, Robyn; Smakhtin, Vladimir. Climate change and agricultural water management in developing countries. Wallingford, UK: CABI. pp.48-62. (CABI Climate Change Series 8)
Climate change ; Water requirements ; Weather ; Meteorological stations ; Crop production ; Evapotranspiration ; Winter wheat ; Precipitation ; Solar radiation ; Wind speed ; Relative humidity ; Temperature / China / Huang-Huai-Hai Plain
(Location: IWMI HQ Call no: IWMI Record No: H047371)
http://www.iwmi.cgiar.org/Publications/CABI_Publications/climate-change-series/chapter-4.pdf
(740 KB)

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