Time Series MODIS and in Situ Data Analysis for Mongolia Drought

Drought is a period of abnormally dry weather with a serious shortage of water supply. Drought indices can be an advantageous indicator to assess drought for taking further response actions. However, drought indices based on ground meteorological measurements could not completely reveal the land use...

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Main Authors: Munkhzul Dorjsuren, Yuei-An Liou, Chi-Han Cheng
Format: Article
Language:English
Published: MDPI AG 2016-06-01
Series:Remote Sensing
Subjects:
PET
Online Access:http://www.mdpi.com/2072-4292/8/6/509
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spelling doaj-1f411790d28d4d70aa85bc83414da7742020-11-24T20:53:55ZengMDPI AGRemote Sensing2072-42922016-06-018650910.3390/rs8060509rs8060509Time Series MODIS and in Situ Data Analysis for Mongolia DroughtMunkhzul Dorjsuren0Yuei-An Liou1Chi-Han Cheng2Graduate Institute of Space Science, National Central University, Jhongli District, Taoyuan City 320, TaiwanGraduate Institute of Space Science, National Central University, Jhongli District, Taoyuan City 320, TaiwanTaiwan Group on Earth Observation, Zhubei City 30274, Hsinchu County, TaiwanDrought is a period of abnormally dry weather with a serious shortage of water supply. Drought indices can be an advantageous indicator to assess drought for taking further response actions. However, drought indices based on ground meteorological measurements could not completely reveal the land use effects over a regional scale. On the other hand, the satellite-derived products provide consistent, spatial and temporal comparisons of global signatures for the regional-scale drought events. This research is to investigate the drought signatures over Mongolia by using satellite remote sensing imagery. The evapotranspiration (ET), potential evapotranspiration (PET) and two-band Enhanced Vegetation Index (EVI2) were extracted from MODIS data. Based on the standardized ratio of ET to PET (ET/PET) and EVI2, the Modified Drought Severity Index (MDSI) anomaly during the growing season from May–August for the years 2000–2013 was acquired. Fourteen-year summer monthly data for air temperature, precipitation and soil moisture content of in situ measurements from sixteen meteorological stations for four various land use areas were analyzed. We also calculated the percentage deviation of climatological variables at the sixteen stations to compare to the MDSI anomaly. Both comparisons of satellite-derived and observed anomalies and variations were analyzed by using the existing common statistical methods. The results demonstrated that the air temperature anomaly (T anomaly) and the precipitation anomaly (P anomaly) were negatively (correlation coefficient r = −0.66) and positively (r = 0.81) correlated with the MDSI anomaly, respectively. The MDSI anomaly distributions revealed that the wettest area occupied 57% of the study area in 2003, while the driest (drought) area occurred over 54% of the total area in 2007. The results also showed very similar variations between the MDSI and T anomalies. The highest (wettest) MDSI anomaly indicated the lowest T anomaly, such as in the year 2003, while the lowest (driest) MDSI anomaly had the highest T anomaly in 2007. By comparing the MDSI anomaly and soil moisture content at a 10-cm depth during the study period, it is found that their correlation coefficient is 0.74.http://www.mdpi.com/2072-4292/8/6/509MODISevapotranspiration (ET)PETtwo-band Enhanced Vegetation Index (EVI2)MDSI anomalyMongolia
collection DOAJ
language English
format Article
sources DOAJ
author Munkhzul Dorjsuren
Yuei-An Liou
Chi-Han Cheng
spellingShingle Munkhzul Dorjsuren
Yuei-An Liou
Chi-Han Cheng
Time Series MODIS and in Situ Data Analysis for Mongolia Drought
Remote Sensing
MODIS
evapotranspiration (ET)
PET
two-band Enhanced Vegetation Index (EVI2)
MDSI anomaly
Mongolia
author_facet Munkhzul Dorjsuren
Yuei-An Liou
Chi-Han Cheng
author_sort Munkhzul Dorjsuren
title Time Series MODIS and in Situ Data Analysis for Mongolia Drought
title_short Time Series MODIS and in Situ Data Analysis for Mongolia Drought
title_full Time Series MODIS and in Situ Data Analysis for Mongolia Drought
title_fullStr Time Series MODIS and in Situ Data Analysis for Mongolia Drought
title_full_unstemmed Time Series MODIS and in Situ Data Analysis for Mongolia Drought
title_sort time series modis and in situ data analysis for mongolia drought
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2016-06-01
description Drought is a period of abnormally dry weather with a serious shortage of water supply. Drought indices can be an advantageous indicator to assess drought for taking further response actions. However, drought indices based on ground meteorological measurements could not completely reveal the land use effects over a regional scale. On the other hand, the satellite-derived products provide consistent, spatial and temporal comparisons of global signatures for the regional-scale drought events. This research is to investigate the drought signatures over Mongolia by using satellite remote sensing imagery. The evapotranspiration (ET), potential evapotranspiration (PET) and two-band Enhanced Vegetation Index (EVI2) were extracted from MODIS data. Based on the standardized ratio of ET to PET (ET/PET) and EVI2, the Modified Drought Severity Index (MDSI) anomaly during the growing season from May–August for the years 2000–2013 was acquired. Fourteen-year summer monthly data for air temperature, precipitation and soil moisture content of in situ measurements from sixteen meteorological stations for four various land use areas were analyzed. We also calculated the percentage deviation of climatological variables at the sixteen stations to compare to the MDSI anomaly. Both comparisons of satellite-derived and observed anomalies and variations were analyzed by using the existing common statistical methods. The results demonstrated that the air temperature anomaly (T anomaly) and the precipitation anomaly (P anomaly) were negatively (correlation coefficient r = −0.66) and positively (r = 0.81) correlated with the MDSI anomaly, respectively. The MDSI anomaly distributions revealed that the wettest area occupied 57% of the study area in 2003, while the driest (drought) area occurred over 54% of the total area in 2007. The results also showed very similar variations between the MDSI and T anomalies. The highest (wettest) MDSI anomaly indicated the lowest T anomaly, such as in the year 2003, while the lowest (driest) MDSI anomaly had the highest T anomaly in 2007. By comparing the MDSI anomaly and soil moisture content at a 10-cm depth during the study period, it is found that their correlation coefficient is 0.74.
topic MODIS
evapotranspiration (ET)
PET
two-band Enhanced Vegetation Index (EVI2)
MDSI anomaly
Mongolia
url http://www.mdpi.com/2072-4292/8/6/509
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AT yueianliou timeseriesmodisandinsitudataanalysisformongoliadrought
AT chihancheng timeseriesmodisandinsitudataanalysisformongoliadrought
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