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Spatial-temporal evolution of vegetation evapotranspiration in Hebei Province, China
WANG Qian-feng, TANG Jia, ZENG Jing-yu, QU Yan-ping, ZHANG Qing, SHUI Wei, WANG Wu-lin, YI Lin, LENG Song
2018, 17 (09): 2107-2117.   DOI: 10.1016/S2095-3119(17)61900-2
Abstract422)      PDF in ScienceDirect      
Evapotranspiration (ET) is the sum of soil or water body evaporation and plant transpiration from the earth surface and ocean to the atmosphere, and thus plays a significant role in regulating carbon and water resource cycles.  The time-series data set from the remote sensing MOIDS product (MOD16) was used to study the spatial-temporal evolution of vegetation evapotranspiration in salinized areas during 2000–2014 by analyzing the variability, spatial patterns and Mann-Kendall (MK) nonparametric trends for the time series.  The results indicate that inter-annual and intra-annual variations of ET across various vegetated areas show seasonal changes, with the abnormal months identified.  The cultivated land displays a greater degree of spatial heterogeneity and the spatial pattern of ET in the area covered by broadleaved deciduous forests corresponds to a higher ET rate and increased water consumption.  A widespread decline of ET is observed only in cultivated areas.  However, agricultural cultivation doesn’t worsen water shortage and soil salinization problems in the region, and water shortage problems are worsening for other vegetated areas.  This research provides a basis of reference for the reasonable allocation of water resources and restructuring of vegetation patterns in salinized areas.
 
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Spatial Exploration of Multiple Cropping Efficiency in China Based on Time Series Remote Sensing Data and Econometric Model
ZUO Li-jun, WANG Xiao, LIU Fang , YI Ling
2013, 12 (5): 903-913.   DOI: 10.1016/S2095-3119(13)60308-1
Abstract1445)      PDF in ScienceDirect      
This study explored spatial explicit multiple cropping efficiency (MCE) of China in 2005 by coupling time series remote sensing data with an econometric model - stochastic frontier analysis (SFA). We firstly extracted multiple cropping index (MCI) on the basis of the close relationship between crop phenologies and moderate-resolution imaging spectroradiometer (MODIS) enhanced vegetation index (EVI) value. Then, SFA model was employed to calculate MCE, by considering several indicators of meteorological conditions as inputs of multiple cropping systems and the extracted MCI was the output. The result showed that 46% of the cultivated land in China in 2005 was multiple cropped, including 39% doublecropped land and 7% triple-cropped land. Most of the multiple cropped land was distributed in the south of Great Wall. The total efficiency of multiple cropping in China was 87.61% in 2005. Southwestern China, Ganxin Region, the middle and lower reaches of Yangtze River and Huanghuaihai Plain were the four agricultural zones with the largest rooms for increasing MCI and improving MCE. Fragmental terrain, soil salinization, deficiency of water resources, and loss of labor force were the obstacles for MCE promotion in different zones. The method proposed in this paper is theoretically reliable for MCE extraction, whereas further studies are need to be done to investigate the most proper indicators of meteorological conditions as the inputs of multiple cropping systems.
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