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Zhanmang Liao

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Journal article
Published: 28 September 2015 in Remote Sensing
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Existing drought indices have been widely used to monitor meteorological drought and agricultural drought; however, few of them are focus on drought monitoring for grassland regions. This study presented a new drought index, the Grassland Drought Index (GDI), for monitoring drought conditions in global grassland regions. These regions are vital for the environment and human society but susceptible to drought. The GDI was constructed based on three measures of water content: precipitation, soil moisture (SM), and canopy water content (CWC). The precipitation information was extracted from the available precipitation datasets, and SM was estimated by downscaling exiting soil moisture data to a 1 km resolution, and CWC was retrieved based on the PROSAIL (PROSPECT + SAIL) model. Each variable was scaled from 0 to 1 for each pixel based on absolute minimum and maximum values over time, and these scaled variables were combined with the selected weights to construct the GDI. According to validation at the regional scale, the GDI was correlated with the Standardized Precipitation Index (SPI) to some extent, and captured most of the drought area identified by the United States Drought Monitor (USDM) maps. In addition, the global GDI product at a 1 km spatial resolution substantially agreed with the global Standardized Precipitation Evapotranspiration Index (SPEI) product throughout the period 2005–2010, and it provided detailed and accurate information about the location and the duration of drought based on the evaluation using the known drought events.

ACS Style

Binbin He; Zhanmang Liao; Xingwen Quan; Xing Li; Junjie Hu. A Global Grassland Drought Index (GDI) Product: Algorithm and Validation. Remote Sensing 2015, 7, 12704 -12736.

AMA Style

Binbin He, Zhanmang Liao, Xingwen Quan, Xing Li, Junjie Hu. A Global Grassland Drought Index (GDI) Product: Algorithm and Validation. Remote Sensing. 2015; 7 (10):12704-12736.

Chicago/Turabian Style

Binbin He; Zhanmang Liao; Xingwen Quan; Xing Li; Junjie Hu. 2015. "A Global Grassland Drought Index (GDI) Product: Algorithm and Validation." Remote Sensing 7, no. 10: 12704-12736.

Journal article
Published: 24 August 2015 in Remote Sensing
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In this study, the Standardized Precipitation Evaporation Index (SPEI) was applied to characterize the drought conditions in Southwest China from 1982–2012. The SPEI was calculated by precipitation and temperature data for various accumulation periods. Based on the SPEI, the multi-scale patterns, the trend, and the spatio-temporal extent of drought were evaluated, respectively. The results explicitly showed a drying trend of Southwest China. The mean SPEI values at five time scales all decreased significantly. Some moderate and severe droughts were captured after 2005 and the droughts were even getting aggravated. By examining the spatio-temporal extent, the aggravating condition of drought was further revealed. To investigate the performance of SPEI, correlation analysis was conducted between SPEI and two remotely sensed drought indices: Soil Moisture Condition Index (SMCI) and Vegetation Condition Index (VCI). The comparison was also conducted with the Standardized Precipitation Index (SPI). The results showed that for both SMCI and VCI, the SPI and SPEI had approximate correlations with them. The SPEI could better monitor the soil moisture than the SPI in months with significant increase of temperature. The correlations between the VCI and SPI/SPEI were lower; nevertheless, the SPEI was slightly superior to the SPI.

ACS Style

Xing Li; Binbin He; Xingwen Quan; Zhanmang Liao; Xiaojing Bai. Use of the Standardized Precipitation Evapotranspiration Index (SPEI) to Characterize the Drying Trend in Southwest China from 1982–2012. Remote Sensing 2015, 7, 10917 -10937.

AMA Style

Xing Li, Binbin He, Xingwen Quan, Zhanmang Liao, Xiaojing Bai. Use of the Standardized Precipitation Evapotranspiration Index (SPEI) to Characterize the Drying Trend in Southwest China from 1982–2012. Remote Sensing. 2015; 7 (8):10917-10937.

Chicago/Turabian Style

Xing Li; Binbin He; Xingwen Quan; Zhanmang Liao; Xiaojing Bai. 2015. "Use of the Standardized Precipitation Evapotranspiration Index (SPEI) to Characterize the Drying Trend in Southwest China from 1982–2012." Remote Sensing 7, no. 8: 10917-10937.