| In recent years, the frequent occurrence of drought has plagued the sustainable development of human society, especially on agriculture. Therefore, the research of an objective, dynamic, real-time drought monitoring method is quite necessary. The spatiotemporal evolution characteristics of drought and development trend research about the new method will have importantly practical significance for the implementation of drought monitoring, crop layout and disaster prevention and mitigation. This paper did quantitative analysis for the drought monitoring study of Jilin province,based on meteorological(build SPI) and remote sensing(inversion TVDI) data respectively. In order to achieve the drought conditions of Jilin, I selected approximately 63 years(1951-2013) of monthly precipitation observations of Jilin province, analyzed the precipitation characteristics and trends about ground meteorological stations changes, and built five different time scales of SPIs. In nearly15 years of using 2000-2014 May to October monthly NDVI and LST data inversion TVDI to monitor drought space TVDI of monthly changes in Jilin Province. Specifically, the paper utilized May to October monthly NDVI and LST data from 2000 to 2014 to get inversion TVDI, monitoring the drought space changes of Jilin over month. Based on the reconstruction of the 1 km resolution Jilin 2000-2014 monthly from May to October of TVDI drought spatial information datasets, via a variety of spatial data timing analysis methods, the paper researched the characteristics of spatiotemporal evolution of the drought and temporal trends in Jilin Province. This paper has made the following results and conclusions:(1) By analyzing the annual precipitation, mean cumulative anomaly change,precipitation five-year moving average and linear change in trend graphs derived from data set 1951-2013 precipitation(22 meteorological stations of Jilin), the characteristics and trends by annual precipitation over the 60 years are acquired. The results show that the rainfall in Jilin Province is unevenly distributed by time and space, the overall performance indicates a decreasing trend from southeast to northwest, The precipitation mainly concentrated from May to October, and the relative concentration of precipitation decreases from west to east. Nearly 60 years of precipitation appear a greater volatility and fluctuating decline; The cumulative anomaly curve shows precipitation has obvious stage characteristics in Jilin Province.(2) Monthly precipitation is used to calculate one month, three months, six months, nine months, 12 months, a total of five different time scales of SPI for analysis of the drought situation in Jilin Province. The analysis results show that different time scales of SPIs presentdifferent sensitivity to precipitation. With time scales increasing, SPI randomness is weakening and persistence is enhancing. While the time scale is increasing, there exists a phenomenon of drought beginning and ending time of the corresponding delay, which also reflects the cumulative impact of pre-precipitation changes. The multi-time scale of SPIs’ visible changes illustrate the following findings: SPI1 better reveal the precipitation changes due to frequent droughts and replacement; SPI3.SPI6 is more sensitive on identification of drought occurrence and duration; The time scales for the long term as SPI12 play an significant identify role on the duration of drought impact.(3) Based on the LST-NDVI feature space, I use standardized NDVI and LST remote sensing images from 2000 to 2014 and IDL programming language under ENVI environment to run output LST-NDVI scatter plot. Finally I can obtain the corresponding maximum and the minimum surface temperature NDVI, which can determine the dry and wet edge parameters, and it is used to calculate TVDI of the research area as each month. By analyzing the spatial variation of monthly TVDI Jilin, The results showed that occurring and developing processes and spatial distribution of drought event from May to October in 2009 and 2010 was monitored and it is consistent with actual situation.(4)The validation results show that TVDI and SPI are highly reliable, Correlation analysis indicate that in addition to August 2009, all other months correlation coefficient have passed P <0.05 significance test, and there are 8 through 12 periods P <0.01 significance test from May to October in 2009 and 2010. Besides, the correlation between TVDI and short term scale SPI is more significant, indicating TVDI is a near-real-time drought monitoring method, which can better reveal frequent droughts and floods due to changes in precipitation change, and identify the occurrence and duration of drought-sensitive, and is suitable for monitoring a the relative degree of drought years, a period of particular regions.(5) In order to study the feature about the spatial variation of drought in Jilin, the paper did the following procedures.. Firstly,drought monitoring capabilities of Jilin TVDI drought spatial information datasets from May to October 2000-2014 time series of monthly information was validated, the results showed that TVDI can better monitor the relative degree of drought in a particular year at the regional level a period, but due to TDVI only present the relative value which about drought conditions of the same image, the time series information on drought monitoring capabilities are limited, namely TVDI have no comparability on time. In this paper, in the same period of 2000-2014 Remote Sensing fit multiple sets feature space to fit the wet side of the argument TVDI, and the use of improved methods TVDI reconstructed 2000-2014 Jilin Province from May to October in the monthly drought TVDI spatial information datasets. Corresponding sites each month with different time scales TVDI SPI correlation through the P <0.01 bilateral significance test, ie improved drought monitoring results TVDI inversion method is comparable in time, use it to JilinDrought temporal evolution of research information.(6) The spatial and temporal changes of drought in from May to October in 2000 to 2014 Jilin province were studied using TVDI and a variety of spatiotemporal timing analysis methods. The results showed that the frequency of droughts in the spatial distribution are quite different, the overall decrease was from northwest to southeast, droughts occurred in September of the most widely used high-frequency region, followed by the May, June, and finally July, August, October. Standard deviation descending followed October, September,July, May, June, August. Where a higher degree of dispersion in October, drought vary widely with the annual fluctuation; The lower the degree of dispersion of August, drought annual fluctuation is small, low frequency changes in drought events that occurred many years without drought or prone to years of continuous drought. The linear trends and rank correlation analysis of TVDI and times show that negative correlation dominates in the recent15 years in October, drought has an descending trend over years, and drought of other months is exacerbating over time; According to the results of F test and T test, September is the most significant, and August is the least significant; Significance test results in areas of low linear trend have uncertainty in the statistical characteristics, which is mainly due to the reason that the length of the time series of this study is only 15 years, while Some pixel inversion TVDI may have short term volatility changes, resulting in a bad linear regression fit significance. |
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