本文選題：黑河流域 + 凈初級生產(chǎn)力�。� 參考：《西南交通大學(xué)》2017年碩士論文

【摘要】：黑河流域是我國第二大內(nèi)陸河,也是我國重要的商品糧生產(chǎn)基地。中游地區(qū)的氣候、水利條件適合農(nóng)作物生長,流域內(nèi)主要種植玉米、小麥等多種商品糧作物。了解主要農(nóng)作物的產(chǎn)量及其分布對于國家相關(guān)部門制定農(nóng)業(yè)和經(jīng)濟等相關(guān)戰(zhàn)略計劃具有一定的意義。利用遙感技術(shù)進(jìn)行估產(chǎn)的方法較多,其中CASA模型結(jié)合了生態(tài)學(xué)原理和遙感技術(shù),相對于其它模型,它擁有輸入?yún)?shù)少、機理性較強、估算結(jié)果比較準(zhǔn)確等優(yōu)點。選擇CASA模型對黑河流域中游地區(qū)的產(chǎn)量進(jìn)行估算,由于研究區(qū)的氣候干旱少雨,灌溉是農(nóng)作物最主要的水源,在以往的研究中沒有考慮灌溉因素對估算結(jié)果的影響,本文將在這方面進(jìn)行改進(jìn),基于CASA模型,以ENVI、ArcMap等軟件為平臺,以MODIS遙感數(shù)據(jù)、氣象數(shù)據(jù)等為輸入數(shù)據(jù),首先估算了黑河流域中游地區(qū)的NPP,驗證該模型在研究區(qū)內(nèi)的適應(yīng)性,然后進(jìn)行了農(nóng)作物產(chǎn)量估算。主要研究內(nèi)容和結(jié)論如下:1分析了黑河流域中游地區(qū)遙感估產(chǎn)技術(shù)研究進(jìn)展,基于改進(jìn)的CASA模型對黑河流域中游地區(qū)主要農(nóng)作物,包括玉米、小麥、油菜籽和大麥進(jìn)行了估產(chǎn),結(jié)果表明流域內(nèi)的作物產(chǎn)量分布呈現(xiàn)"西北低東南高"的現(xiàn)象。2對CASA模型的輸入數(shù)據(jù)的處理方法進(jìn)行研究。采用薄盤光滑樣條插值法對氣溫、降雨數(shù)進(jìn)行插值。使用ArcMap的太陽輻射計算工具計算太陽輻射。3為清晰直觀表達(dá)估產(chǎn)結(jié)果,利用遙感數(shù)字地圖制圖技術(shù),進(jìn)行了專題要素表示方法、色彩等的選擇設(shè)計,制作了 2007、2012和2014年的4種主要農(nóng)作物的產(chǎn)量分布圖。4為獲得灌溉因子,對黑河流域中游地區(qū)的灌溉量進(jìn)行了估算,并將灌溉因子用于對CASA模型的改進(jìn)。將估算NPP與其它研究成果進(jìn)行對比,證明了本研究的估算結(jié)果在一定的合理區(qū)間,然后與MOD17-NPP數(shù)據(jù)進(jìn)行了相關(guān)性分析。研究表明,加入灌溉因子后的模型模擬效果更好,估算的結(jié)果精度更高。5為分析產(chǎn)量積累過程與作物NDVI之間的關(guān)系,本文基于CASA模型估算出每種農(nóng)作物的月產(chǎn)量,并將月產(chǎn)量與月NDVI進(jìn)行比較。結(jié)果表明,農(nóng)作物的月產(chǎn)量與NDVI線性關(guān)系明顯,進(jìn)而表明NDVI與作物單產(chǎn)具有顯著的線性關(guān)系。
[Abstract]:The Heihe River Basin is the second largest inland river in China and an important commodity grain production base in China. In the middle reaches, the climate and water conservancy conditions are suitable for crop growth. Corn, wheat and other commercial grain crops are mainly planted in the watershed. Understanding the yield and distribution of major crops is of great significance for the relevant departments of the country to formulate strategic plans for agriculture and economy. There are many methods to estimate yield by remote sensing technology. CASA model combines ecological principle and remote sensing technology. Compared with other models, it has the advantages of less input parameters, stronger mechanism, and more accurate estimation results. The CASA model was selected to estimate the yield in the middle reaches of Heihe River Basin. Irrigation is the most important water source for crops because of the drought and rainfall in the study area, and the influence of irrigation factors on the estimation results has not been taken into account in previous studies. In this paper, based on the CASA model, the CASA model is used as the platform, the remote sensing data and meteorological data of MODIS are used as input data, and the adaptability of the model in the middle reaches of Heihe River Basin is verified. Then the crop yield was estimated. The main research contents and conclusions are as follows: 1. Based on the improved CASA model, the yield estimation of main crops, including corn, wheat, rapeseed and barley, in the middle reaches of Heihe River Basin is analyzed. The results showed that the distribution of crop yield in the watershed presented the phenomenon of "low and southeast high in the northwest". 2. The method of processing the input data of CASA model was studied. The thin disk smooth spline interpolation method is used to interpolate the temperature and rainfall. The solar radiation calculation tool of ArcMap is used to calculate solar radiation to express the estimation result clearly and intuitively. By using the technology of remote sensing digital map mapping, the selection and design of thematic elements and colors are carried out. The yield distribution of four main crops in 2007 / 12 and 2014 was used as the irrigation factor to estimate the irrigation amount in the middle reaches of Heihe River Basin, and the irrigation factor was used to improve the CASA model. By comparing the estimated NPP with other research results, it is proved that the estimated results of this study are in a reasonable range, and then the correlation analysis is carried out with the MOD17-NPP data. The results show that the model with irrigation factor has better simulation effect and the precision of estimation is higher. 5. 5 is to analyze the relationship between yield accumulation process and crop NDVI. Based on CASA model, the monthly yield of each crop is estimated in this paper. The monthly yield was compared with the monthly NDVI. The results showed that the linear relationship between monthly crop yield and NDVI was obvious, and the linear relationship between NDVI and crop yield was significant.
【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：S127

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