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Vegetation supply water index based on MODIS data Analysis of the in Yunnan in spring of 2012

机译:基于云南2012年云南MODIS数据分析的植被供应水指数

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Today, drought has become a world problem, which is affecting agriculture more and more seriously. China is a large agricultural country, so drought is nor ignored for China. Drought hazards in agriculture growing, so timely and accurate monitoring of the development of drought is necessary to reduce the harm of drought. Over the years, many scholars established a variety of drought monitoring models, aiming at better monitoring of drought. Southwest China has been the drought-prone areas and Yunnan Province is the most serious area. [Method]: In this paper, in February 2012-May period of remote sensing data obtained with moderate-resolution imaging spectrometer (MODIS) conducts dynamic monitoring of drought in Yunnan. Normalized Difference Vegetation Index (NDVI) is calculated with the first bang and the second bang of MODIS data and Negative NDVI values that are representative of the water and snow should be removed. By split window algorithm method, land surface temperature (LST) in Yunnan is retrieved with 31-band and 32-band of MODIS data, but some places in where there is much cloud are removed. Then the Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) calculated Vegetation Supply Water Index (VSWI) that dynamically monitors the drought in Yunnan. this model's results are validated based on 10 cm-shallow soil moisture data measured by the meteorological stations at the 0.05 confidence level and passed the correlation test which indicates that the results calculated by the model is sensitive to changes in drought. In the soil moisture data, some data collection sites have been irrigated, so these data should be removed. So this drought index can be used to monitor drought developments and we can get real-time, accurate drought. These monitoring results as a basis, We can make timely and correct drought policy to reduce losses caused by the drought; [Conclusions] :from spring drought monitoring results can be seen that Northwest- Yunnan has been in a semi- arid and arid state. In February and May, it is more serious drought, drought affecting a wide range. There are two reasons about development of drought: First, the terrain reasons, northwest, eastern and Central Yunnan are the highland area, low rainfall, dry climate, so the severe drought in these areas; Second, the climatic reason, the spring belongs to the dry season, Rainfall is relatively small and its distribution is not balance. Relative to previous years, three months and it rarely rains in March and May, so it is severe drought. In recent years, natural hazards occur frequently on the world in witch drought is most. Drought is characterized by a wide spread range, long duration and great harm. China is a large agricultural country so it be harmed when drought occurred witch hinders the development of society. So it is necessity of Real-time, dynamic and accurate monitoring of drought. Only in this way, can we minimize the damage.
机译:今天,干旱已成为一个世界问题,这会越来越认真地影响农业。中国是一个大型农业国家,所以干旱也不忽视中国。农业生长的干旱危害,所以及时准确地监测干旱的发展,是减少干旱的危害。多年来,许多学者建立了各种各样的干旱监测模型,旨在更好地监测干旱。西南中国一直是干旱普遍的地区,云南省是最严重的地区。 [方法]:本文在2012年2月 - 5月,用中等分辨率成像光谱仪(MODIS)获得的遥感数据的延长感测数据进行动态监测云南干旱。归一化差异植被指数(NDVI)由第一爆发计算,第二个爆炸的MODIS数据和负面的NDVI值,应该被移除。通过拆分窗口算法方法,用31波段和32波段检索云南的陆表面温度(LST),但删除了很多云的地方的一些位置。然后是归一化差异植被指数(NDVI)和陆表面温度(LST)计算的植被供应水指数(VSWI),动态监测云南干旱。该模型的结果是基于由0.05置信水平的气象站测量的10厘米浅的土壤水分数据验证,并通过了相关试验,表明模型计算的结果对干旱的变化敏感。在土壤湿度数据中,已经灌溉了一些数据收集网站,因此应删除这些数据。因此,这种干旱指数可用于监测干旱的发展,我们可以获得实时,准确的干旱。这些监测结果作为基础,我们可以及时纠正干旱政策,以减少干旱造成的损失; [结论]:从春季干旱监测结果可以看出,西北云南一直处于半干旱和干旱状态。 2月和5月,它是更严重的干旱,干旱影响广泛。有关干旱的发展有两个原因:第一,地形原因,西北,东部和中部云南都是高地地区,降雨量低,气候干燥,所以这些地区的严重干旱;二,气候原因,春天属于旱季,降雨相对较小,其分布不平衡。相对于前几年,三个月,3月份很少下雨,可能是严重的干旱。近年来,在巫婆干旱的世界中经常出现自然危害。干旱的特点是广泛的扩展范围,持续时间长,危害很大。中国是一个大型农业国家,所以当干旱发生时受到伤害,巫婆阻碍了社会的发展。因此,需要实时,动态和准确监测干旱的必要性。只有这样,我们只能最大限度地减少损坏。

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