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Applicability Of Drought Monitoring Based On Vegetation Index And Land Surface Temperature In Winter-wheat-growing Area In Hebei Province

Posted on:2012-02-24Degree:MasterType:Thesis
Country:ChinaCandidate:P ChenFull Text:PDF
GTID:2120330335977701Subject:Atmospheric physics and atmospheric environment
Abstract/Summary:PDF Full Text Request
With the significant warming of global climate, the frequency and intensity of drought in china continuously strengthened. It seriously threaten the agricultural production, and has great influence on development of soeiety and economy. So, it is of great significance to master the regulation of time and space variety of drought. This paper presented a case study for the winter wheat growing areas in the plain of south-central Hebei Province, where a severe drought happened in the spring of 2007. From the perspective of points and region, VTCI, VSWI and the meteorological station data were selected to analyse the development trend of spring drought, using the MODIS NDVI and LST products. A comparative analysis of TVDI and VSWI was carried out to evaluate the adaptability of drought monitoring models. Taking into account the connection between meteorological drought and agricultural drought, based on the standardised precipitation index(SPI), this thesis further verified the application value of VTCI in drought monitoring in the studied area. It would provide technique support for the agricultural drought monitoring and warning in north china. The main conclusions of this paper were as follows:(1) By analyzing the relativity of VTCI/VSWI and relative humidity of soil at different depths, the results showed in order of 20cm>10cm>50cm. It means that the remote sensing monitoring based on NDVI and LST have good response on changes in surface soil water; when the correlation of the two index with soil relative humidity were contrasted, we can see that the VTCI had better correlation with soil relative humidity than VSWI. The above results indicated that the VTCI is more applicable in the study area.(2) From the drought distribution based on the two remote-sensing monitoring index, we can see that the results from VSWI index showed continuing severe drought and over moisture, however, the drought distribution based on VTCI index indicated that the drought becomes visible in March,22,2007, following development for more than a month, the drought become worst, then a large-scale precipitation process effectively weakenned the drought in late May. In the view of dynamic state of drought, VTCI can reflect the emergence, development and remission of drought with much more truth and certainty.(3) Because of the problem in the monitoring results of VSWI, this thesis select some stations with different vegetation cover conditions to analyze the reasons. The result indicated that the sites with bad vegetation cover often have continuous drought, and the continuous wet areas often have sites with good vegetation cover. In contrast, the monitoring result created by VTCI is more reasonable, and its time trend is more consistent with surface soil water. Therefore, this thesis summarize that VSWI is lack of adaptability to complicated underlaying surface, but VTCI is good to overcome this shortcomings. So, VTCI is more suitable for the complex surface conditions in central and southern plains of Hebei Province.(4) Meteorological drought is the direct source of agricultural drought, there is intimate connection between them. After making a calculated standardised precipitation index(SPI) in different time period and further comparative analysis with VTCI, it is found that the drought based on the VTCI changed more consistently with time variations of SPI-1 (current precipitation) than that of SPI-2(accumulation precipitation of current and preliminary phase). It indicated that VTCI is more sensitive to current precipitation. However there is small differences between the drought grades obtained from the two methods, usually, the drought degree based on SPI is lower than that from VTCI.
Keywords/Search Tags:Winter Wheat, Drought, Remote Sensing Monitoring, Vegetation Index, Land Surface Temperature
PDF Full Text Request
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