Dynamic monitoring of drought based on Temperature Vegetation Dryness Index in Guangdong Province

doi:10.11686/cyxb20140212

Abstract

Abstract: Guangdong Province has been suffering from seasonal drought and the dynamic monitoring of drought by remote sensing data could be an important tool. The EVI-T_S space was constructed by Moderate Resolution Imaging Spectro radiometer (MODIS) data, the dry and wet edges were extracted with a linear fitting method and then the Temperature Vegetation Dryness Index (TVDI) was calculated for Guangdong Province in 2011 and the Temporal-spatial distribution of drought was analyzed. 1) With an increase of the Enhanced Vegetation Index (EVI), the maximum land surface temperature decreased and the difference value between the maximum and minimum land surface temperature also decreased. The maximum and minimum land surface temperature both had an approximately linear relation to the EVI. The seasonal variation of EVI-T_S space was obvious. When the temperature decreased, the EVI-T_S space shrank and with a change of temperature, the intercept of the dry and wet edges changed correspondingly, i.e. the intercept was smaller in winter and bigger in summer. 2) Winter drought was very serious, while spring and autumn drought were also serious to some degree in Guangdong Province in 2011. The drought in winter and spring had similar distribution areas, and the grade weakened gradually from south to north. The drought in coastal areas was more serious than in inland areas. The geographical distribution of autumn drought approximately increased from south to north, which was the opposite to winter and spring droughts. According to the weather data in Guangdong Province, the results of the drought monitoring by remote sensing were in conformity with reality. 3) There was a significant negative correlation between TVDI and soil moisture and the results showed that the soil moisture can be successfully reflected by the TVDI data. The TVDI was negatively correlated with precipitation, temperature and mean relative humidity. TVDI had a high correlation coefficient with precipitation. TVDI was sensitive to precipitation on the station scale, which is a similar trend to the change of TVDI and precipitation in the time series. Continuous precipitation for a certain time was followed by a decline in the TVDI which indicated slight drought only and vice versa.

CLC Number:

WANG Ying, WANG Jing-song, YAO Yu-bi, ZHAO Fu-nian. Dynamic monitoring of drought based on Temperature Vegetation Dryness Index in Guangdong Province[J]. Acta Prataculturae Sinica, 2014, 23(2): 98-107.

References

[1] 李华朋, 张树清, 高自强, 等. MODIS植被指数监测农业干旱的适宜性评价[J]. 光谱学与光谱分析, 2013, 33(3): 756-761.
[2] 亚行技援中国干旱管理战略研究课题组. 中国干旱灾害风险管理战略研究[M]. 北京: 中国水利水电出版社, 2011: 1-2.
[3] 高懋芳, 张虹鸥, 秦晓敏, 等. 广东省农业旱灾遥感监测[J]. 国土资源遥感, 2008, (3): 94-99.
[4] 王静爱, 孙恒, 徐伟, 等. 近50年中国旱灾的时空变化[J]. 自然灾害学报, 2002, 11(2): 1-6.
[5] 李慧, 王鹏新. 基于Terra-MODIS和NOAA-AVHRR数据的条件植被温度指数干旱监测及其对比分析[J]. 干旱区资源与环境, 2013, 27(3): 61-66.
[6] 花立民. 玛曲草原植被NDVI与气候和载畜量变化的关系分析[J]. 草业学报, 2012, 21(4): 224-235.
[7] 周伟, 王倩, 章超越, 等. 黑河上游草地NDVI时空变化规律及其对气候因子的响应分析[J]. 草业学报, 2013, 22(1): 138-147.
[8] 王浩, 李文龙, 杜国祯, 等. 基于3S技术的甘南草地覆盖度动态变化研究[J]. 草业学报, 2012, 21(3): 26-37.
[9] Sandholt I, Rasmussen K, Andersen J. A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status[J]. Remote Sensing of Environment, 2002, 79(2): 213-224.
[10] 冯蜀青, 殷青军, 肖建设, 等. 基于温度植被旱情指数的青海高寒区干旱遥感动态监测研究[J]. 干旱地区农业研究, 2006, 24(5): 141-145.
[11] Patel N R, Anapashsha R, Kumar S, et al. Assessing potential of MODIS derived temperature/vegetation condition index (TVDI) to infer soil moisture status[J]. International Journal of Remote Sensing, 2009, 30(1): 23-39.
[12] 齐述华, 王长耀, 牛铮. 利用温度植被旱情指数 (TVDI) 进行全国旱情监测研究[J]. 遥感学报, 2003, 7(5): 420-427.
[13] Gao Z, Gao W, Chang N B. Integrating temperature vegetation dryness index (TVDI) and regional water stress index (RWSI) for drought assessment with the aid of LANDSAT TM/ETM+ images[J]. International Journal of Applied Earth Observation and Geoinformation, 2011, 13(3): 495-503.
[14] 吴孟泉, 崔伟宏, 李景刚. 温度植被干旱指数 (TVDI) 在复杂山区干旱监测的应用研究[J]. 干旱区地理, 2007, 30(1): 30-35.
[15] 赵莉荣, 武伟, 刘洪斌, 等. 基于温度植被干旱指数法的农业干旱研究[J]. 西南师范大学学报(自然科学版), 2009, 34(2): 80-84.
[16] Wan Z, Wang P, Li X. Using MODIS land surface temperature and normalized difference vegetation index products for monitoring drought in the southern Great Plains[J]. USA, International Journal of Remote Sensing, 2004, 25(1): 61-72.
[17] 王正兴, 刘闯, Huete A. 植被指数研究进展:从AVHRR-NDVI到MODIS-EVI[J]. 生态学报, 2003, 23(5): 979-987.
[18] 王正兴, 刘闯, 陈文波, 等. MODIS增强型植被指数EVI与NDVI初步比较[J]. 武汉大学学报(信息科学版), 2006, 31(5): 407-410.
[19] Wan Z. MODIS land surface temperature products users’ guide[Z]. Institute for Computational Earth System Science, University of California, Santa Barbara, CA. http://www. icess. ucsb. edu/modis/LstUsrGuide/usrguide. html, 2006.
[20] Huete A R. A soil adjusted vegetation index (SAVI)[J]. Remote Sensing of Environment, 1988, (25): 295-309.
[21] 李文梅, 覃志豪, 李文娟, 等. MODIS NDVI与MODIS EVI的比较分析[J]. 遥感信息, 2010, 6: 73-78.
[22] 李云鹏, 司瑶冰, 刘朋涛, 等. 基于空间信息的内蒙古农业干旱监测研究[J]. 干旱区资源与环境, 2011, 25(11): 125-131.
[23] 于敏, 程明虎. 基于NDVI-T_S特征空间的黑龙江省干旱监测[J]. 应用气象学报, 2010, 21(2): 221-228.
[24] Carlson T N, Gillies R R, Perry E M. A method to make use of thermal infrared temperature and NDVI measurements to infer surface soil water content and fractional vegetation cover[J]. Remote Sensing Reviews, 1994, 9(1-2): 45-59.
[25] Price J C. Using spatial context in satellite data to infer regional scale evapotranspiration[J]. Geoscience and Remote Sensing, IEEE Transactionson, 1990, 28(5): 940-948.
[26] Moran M S, Clarke T R, Inoue Y, et al. Estimating crop water deficit using the relation between surface-air temperature and spectral vegetation index[J]. Remote Sensing of Environment, 1994, 49(3): 246-263.
[27] 叶琦, 赵萍, 孙静. 基于MODIS/NDVI与EVI的皖江流域植被覆盖比较分析[J]. 长江流域资源与环境, 2012, 21(3): 361-368.
[28] Hope A S, Petzold D E, Goward S N, et al. Simulating canopy reflectance and thermal infrared emissions for estimating evapotranspiration[J]. Water Resources Bulletin, 1987, 22(6): 1011-1019.
[29] Nemani R R, Running S W. Estimation of regional surface resistance to evapotranspiration from NDVI and thermal-IR AVHRR data[J]. Journal of Applied Meteorology, 1989, 28(4): 276-284.
[30] Carlson T. An overview of the “triangle method” for estimating surface evapotranspiration and soil moisture from satellite imagery[J]. Sensors, 2007, 7(8): 1612-1629.