本文選題：洪澇過程 + 時序遙感影像　； 參考：《長江流域資源與環(huán)境》2017年11期

【摘要】：洪澇災(zāi)情的準(zhǔn)確測度需要同時兼顧淹沒區(qū)的面積大小和淹水時長信息。利用淹沒區(qū)內(nèi)由水和作物等多種地物所組成的"復(fù)合水體"不同于水體的波譜時間變化特性,將不同洪災(zāi)時期的水體指數(shù)和植被指數(shù)進(jìn)行信息復(fù)合,以有效凸顯水體和洪澇淹沒區(qū)之間的影像差異,據(jù)此進(jìn)行了災(zāi)初期、峰期和中后期等3個時次受淹范圍的有效識別。在此基礎(chǔ)上,根據(jù)洪澇災(zāi)情隨著淹沒時長而加重以及災(zāi)區(qū)內(nèi)淹水時長非均勻分布的特性,建立基于淹沒時長的受淹面積不等權(quán)參與的洪災(zāi)擴(kuò)展動態(tài)度指數(shù)(Variation Index of Flood,VIF)和區(qū)域災(zāi)情比較指數(shù)(Comparison Index of Flood Disaster,CIFD)兩種模型,并將模型應(yīng)用于鄱陽湖區(qū)2016年夏季農(nóng)業(yè)洪澇災(zāi)害的時空變化遙感監(jiān)測。結(jié)果顯示,應(yīng)用上述兩種模型不僅可以準(zhǔn)確獲取鄱陽湖區(qū)本次農(nóng)業(yè)洪澇災(zāi)情的演變趨勢,而且能夠方便地對比分析區(qū)域內(nèi)不同地方的受災(zāi)程度。鄱陽湖區(qū)在2016年6月23日~7月25日期間的洪澇災(zāi)情具有由弱增強(qiáng)再趨弱的特征,其VIF指數(shù)由初始階段(6月23日~7月9日)的3.75降至后續(xù)階段(7月9日~7月23日)的1.29;鄱陽縣是研究區(qū)內(nèi)受災(zāi)最嚴(yán)重的區(qū)域,其CIFD指數(shù)值居于研究區(qū)內(nèi)各受災(zāi)縣市之首,該縣受災(zāi)總面積以及多次被淹的災(zāi)區(qū)面積均高于其他縣市。
[Abstract]:The accurate measurement of flood and waterlogging disaster needs to take into account the area size and flooding time information. In this paper, the information of water body index and vegetation index in different flood period is combined by using the time variation characteristics of wave spectrum of "composite water", which is composed of water, crops and other ground objects in the inundated area, which is different from the water body. In order to effectively highlight the image difference between the water body and the flooded area, the range of flooding in the early, the peak and the middle and late stages of the disaster was effectively identified. On this basis, according to the characteristics of the flood and waterlogging disaster situation aggravated with the flooding time and the non-uniform distribution of the flooding duration in the disaster area, In this paper, two kinds of models of flood expansion dynamic index (Index of flooding VIFs) and comparison Index of Flood disaster (CIFD) based on inundation duration of inundated area with unequal weight participation are established, and two kinds of models are established, which are: (1) flood expansion dynamic index (Index) and (2) regional disaster comparison index (comparison Index of Flood disaster). The model is applied to the remote sensing monitoring of agricultural flood and waterlogging disasters in the Poyang Lake region in 2016. The results show that the above two models can not only accurately obtain the evolution trend of agricultural flood and waterlogging in Poyang Lake region, but also can easily compare and analyze the disaster degree of different places in the Poyang Lake region. The flood and waterlogging in Poyang Lake region from June 23 to July 25, 2016 has the characteristics of weak enhancement and then weakening. The VIF index decreased from 3.75 in the initial stage (June 23 to July 9) to 1.29 in the subsequent stage (from July 9 to July 23). Poyang County is the most affected area in the study area, and its CIFD index is the highest in all counties and cities in the study area. The total area affected by the county and repeatedly flooded disaster area are higher than other counties and cities.
【作者單位】： 湖北大學(xué)資源環(huán)境學(xué)院;農(nóng)業(yè)部遙感應(yīng)用中心武漢分中心;
【基金】：國家自然科學(xué)基金項目(41371344,40601003) 農(nóng)業(yè)部—農(nóng)業(yè)農(nóng)村資源監(jiān)測統(tǒng)計項目(06162130111242026) 安徽省智慧城市與地理國情監(jiān)測重點實驗室開放基金(2016-K-02Z)~~
【分類號】：S422;TP79

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