【摘要】：綠色植物對紅光波段具有很強的吸收性,對近紅外波段具有很強的反射性,這兩種波段進行歸一化差值運算可以得到歸一化植被指數(shù)(NDVI),歸一化植被指數(shù)對植物的生長狀況及生理活性變化的反映具有很強的敏感性,利用NDVI監(jiān)測冬小麥生長狀況以及農(nóng)田墑情,指導(dǎo)農(nóng)業(yè)生產(chǎn),對現(xiàn)代化冬小麥田間管理技術(shù)的發(fā)展具有重大的意義。本次研究于西北農(nóng)林科技大學(xué)旱區(qū)農(nóng)業(yè)節(jié)水重點實驗室灌溉站內(nèi)進行了大田冬小麥實驗,實驗灌水量60 L/m2(W1)、50 L/m2(W2)和30 L/m2(W3),0 L/m2(W4)共4個水平。分別在越冬期,拔節(jié)期,灌漿期進行一次灌溉。采用播種量控制密度,高密度(D1)播種量150kg//hm2,低密度播種量(D2)75kg/hm2。在冬小麥越冬期、拔節(jié)期、灌漿期、成熟期分別采集NDVI,田間氣象數(shù)據(jù),土壤水分數(shù)據(jù)。分析冬小麥NDVI日變化規(guī)律及其與氣象因素及土壤水分的相關(guān)關(guān)系,并利用多元回歸及逐步回歸兩種方法建立模型,為冬小麥的大田信息監(jiān)測提供理論和技術(shù)支持。本論文分別分析了冬小麥NDVI日變化規(guī)律、NDVI與氣象因素相關(guān)關(guān)系,以及NDVI與土壤水分的相關(guān)關(guān)系,并得出以下結(jié)論。(1)研究分析了不同生育期內(nèi)冬小麥的NDVI日變化規(guī)律。得出NDVI與單日內(nèi)時間序列呈現(xiàn)較好的二次拋物線性的相關(guān)關(guān)系,在冬小麥越冬期,NDVI擬合結(jié)果的決定系數(shù)為0.9、0.934,拔節(jié)期的決定系數(shù)為0.954、0.887,灌漿期決定系數(shù)都為0.829。但在冬小麥越冬期的NDVI總體變化幅度不大;灌漿期NDVI波動較大,是由于這一生育期內(nèi),天氣變化異常,導(dǎo)致冬小麥NDVI波動較大。經(jīng)實測數(shù)據(jù)驗證得出,模型精度較好。針對冬小麥不同生育期NDVI與時間序列的二次拋物線反演模型,可為冬小麥NDVI快速獲取技術(shù)提供理論支持。(2)研究分析了不同生育期內(nèi)NDVI與氣象因素相關(guān)性。得出冬小麥越冬期NDVI與氣溫以及相對濕度的相關(guān)性最高,拔節(jié)期NDVI與氣溫及地溫的相關(guān)性最高,灌漿期地溫、相對濕度與冬小麥NDVI相關(guān)性最好。對于地溫,氣溫,相對濕度這些氣象因素,冬小麥NDVI與之都存在一定的相關(guān)性,不同的氣象因素與冬小麥不同生育NDVI間相關(guān)性存在一定差異。相關(guān)模型可以修正冬小麥在異常天氣狀況條件下的NDVI。(3)研究分析了對不同生育期冬小麥NDVI與土壤水分相關(guān)關(guān)系,并且分別采用多元回歸法及逐步回歸法進行模擬。結(jié)果表明,不同生育期冬小麥NDVI與不同深度的土壤水分通過差值處理后存在一定的相關(guān)關(guān)系,在越冬期,NDVI差值與20cm及60cm深度土層的土壤含水量差值相關(guān)性較好。在拔節(jié)期NDVI差值與表層10cm處以及40cm深度土壤水分差值相關(guān)性較好。在灌漿期NDVI與土壤水分的相關(guān)性與拔節(jié)期較為相似,同樣也是10cm深度以及60cm深度的土壤含水量差值與NDVI差值相關(guān)性較好。三個不同生育期冬小麥都表現(xiàn)出表層10cm處以及60cm深度下的土壤水分差值與NDVI差值有較好的相關(guān)性。可見NDVI只適用于反演這兩種深度下的土壤含水量。有關(guān)結(jié)論為NDVI反演冬小麥土壤水分提供參考。
[Abstract]:Green plants have strong absorption to red light band and strong reflectivity to near infrared band. Normalized vegetation index (NDVI) can be obtained by normalized difference calculation between the two bands. Normalized vegetation index has strong sensitivity to plant growth status and physiological activity changes. NDVI is used to monitor winter small. It is of great significance for the development of modern winter wheat field management technology to guide the agricultural production by the growth of wheat and the soil moisture in the field. 4) A total of 4 levels were conducted at overwintering stage, jointing stage and filling stage. The density was controlled by seeding rate, the density (D1) was 150 kg / / hm2, and the low density (D2) was 75 kg / hm2. NDVI, field meteorological data and soil moisture data were collected at overwintering stage, jointing stage, filling stage and maturity stage of winter wheat. The relationship between NDVI and meteorological factors and soil moisture was studied. The models were established by multiple regression and stepwise regression to provide theoretical and technical support for field information monitoring of winter wheat. The results are as follows. (1) The daily variation of NDVI of Winter Wheat in different growth stages is studied and analyzed. The results show that NDVI has a good quadratic parabolic linear correlation with the time series in one day. In winter wheat, the determination coefficient of NDVI fitting results is 0.9, 0.934, the determination coefficient of jointing stage is 0.954, 0.887, and the filling stage is decided. The definite coefficients are all 0.829. But the NDVI of Winter Wheat in overwintering period has little change, and the NDVI of grain filling period fluctuates greatly, which is due to the abnormal weather changes during this growing period, resulting in the great fluctuation of NDVI of winter wheat. The model can provide theoretical support for rapid NDVI acquisition of winter wheat. (2) The correlation between NDVI and meteorological factors in different growth stages was studied and analyzed. The correlation between NDVI and ground temperature, air temperature and relative humidity is the best. There is a certain correlation between NDVI and these meteorological factors, and there is a certain difference between different meteorological factors and different growth and development of winter wheat. The results showed that there was a certain correlation between NDVI and soil moisture in different growth stages and different depths. In overwintering stage, the difference of NDVI and soil moisture in depth of 20 cm and 60 cm was different. The correlation between NDVI and soil moisture at 10 cm and 40 cm depth at jointing stage was better than that at jointing stage. The correlation between NDVI and soil moisture at filling stage was similar to that at jointing stage. The results showed that there was a good correlation between NDVI and soil moisture difference at the depth of 60 cm and 10 cm. NDVI was only suitable for inversion of soil moisture at these two depths.
【學(xué)位授予單位】：西北農(nóng)林科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：S512.11;S152.7

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