本文選題：低溫冷害 + 區(qū)域產(chǎn)量監(jiān)測(cè)��； 參考：《江蘇農(nóng)業(yè)科學(xué)》2017年16期

【摘要】：水稻結(jié)實(shí)率是水稻產(chǎn)量構(gòu)成因素中的重要組成,其受氣象環(huán)境影響較大,因此,建立水稻結(jié)實(shí)率估算模型對(duì)區(qū)域水稻產(chǎn)量監(jiān)測(cè)具有重要作用。在2012、2013年水稻光譜觀測(cè)試驗(yàn)的基礎(chǔ)上,以遙感影像為數(shù)據(jù)源,提出了能夠在水稻抽穗至成熟階段反映低溫冷害影響的遙感指數(shù)(cold vegetation index,CVI),并分析了CVI值與水稻產(chǎn)量要素、溫度因子的關(guān)系。在此基礎(chǔ)上,以抽穗至成熟階段的CVI和平均氣溫為自變量,采用線性回歸方法,構(gòu)建水稻結(jié)實(shí)率估算模型。為驗(yàn)證該模型,選擇蘇皖2省一季稻為研究對(duì)象,并以MOD09A1產(chǎn)品為遙感數(shù)據(jù)源,對(duì)水稻結(jié)實(shí)率估算模型進(jìn)行了點(diǎn)和面上的模擬和評(píng)價(jià)。結(jié)果顯示,抽穗開花至成熟階段CVI和在此期間的溫度條件與水稻結(jié)實(shí)率存在顯著的相關(guān)關(guān)系,是影響結(jié)實(shí)率的2個(gè)重要因素。站點(diǎn)估算的結(jié)實(shí)率相對(duì)誤差小于11%,平均相對(duì)誤差為4%,估算值空間分布與觀測(cè)值基本一致,表明該模型的模擬結(jié)果能夠較好地反映水稻結(jié)實(shí)率的空間分布情況和不同氣候年景下結(jié)實(shí)率的變化。綜上所述,提出的CVI和建立的結(jié)實(shí)率估算模型適用于區(qū)域水稻低溫冷害監(jiān)測(cè)和災(zāi)損評(píng)估。
[Abstract]:Rice seed setting rate is an important component of rice yield components, which is greatly affected by meteorological environment. Therefore, the establishment of rice seed setting rate estimation model plays an important role in regional rice yield monitoring. On the basis of rice spectral observation experiment in 2012 and 2013, a new remote sensing index cold vegetation index CVII was proposed based on remote sensing images to reflect the effects of low temperature chilling injury from heading to mature stage of rice, and the CVI value and rice yield factors were analyzed. The relationship between temperature factors. On the basis of this, using CVI and mean temperature from heading to maturity as independent variables, a linear regression model was established to estimate the seed setting rate of rice (Oryza sativa L.). In order to verify the model, the model of rice seed setting rate in Jiangsu and Anhui provinces was simulated and evaluated with MOD09A1 as remote sensing data source. The results showed that there was a significant correlation between CVI from heading flowering to maturation stage and the temperature conditions during this period, which were two important factors affecting the seed setting rate of rice (Oryza sativa L.). The relative error of the seed setting rate estimated by the station is less than 11 and the average relative error is 4. The spatial distribution of the estimated value is basically consistent with the observed value. The results show that the simulation results of this model can reflect the spatial distribution of rice seed setting rate and the variation of seed setting rate under different climatic conditions. In conclusion, the proposed CVI and the established seed setting rate estimation model are suitable for regional rice chilling damage monitoring and damage assessment.
【作者單位】： 南京信息工程大學(xué)氣象災(zāi)害預(yù)報(bào)預(yù)警與評(píng)估協(xié)同創(chuàng)新中心/江蘇省農(nóng)業(yè)氣象重點(diǎn)實(shí)驗(yàn)室;中國人民解放軍94592部隊(duì)氣象臺(tái);
【基金】：國家科技支撐計(jì)劃(編號(hào):2011BAD32B01) 國家公益性行業(yè)(氣象)科研專項(xiàng)(編號(hào):GYHY201306036;GYHY201306035;GYHY201506055) 江蘇高校優(yōu)勢(shì)學(xué)科建設(shè)工程
【分類號(hào)】：S127;S511

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本文編號(hào)：2014196