黑河流域中游农作物遥感估产技术方法研究

发布时间：2018-04-22 20:23

本文选题：黑河流域 + 净初级生产力　；参考：《西南交通大学》2017年硕士论文

【摘要】：黑河流域是我国第二大内陆河,也是我国重要的商品粮生产基地。中游地区的气候、水利条件适合农作物生长,流域内主要种植玉米、小麦等多种商品粮作物。了解主要农作物的产量及其分布对于国家相关部门制定农业和经济等相关战略计划具有一定的意义。利用遥感技术进行估产的方法较多,其中CASA模型结合了生态学原理和遥感技术,相对于其它模型,它拥有输入参数少、机理性较强、估算结果比较准确等优点。选择CASA模型对黑河流域中游地区的产量进行估算,由于研究区的气候干旱少雨,灌溉是农作物最主要的水源,在以往的研究中没有考虑灌溉因素对估算结果的影响,本文将在这方面进行改进,基于CASA模型,以ENVI、ArcMap等软件为平台,以MODIS遥感数据、气象数据等为输入数据,首先估算了黑河流域中游地区的NPP,验证该模型在研究区内的适应性,然后进行了农作物产量估算。主要研究内容和结论如下:1分析了黑河流域中游地区遥感估产技术研究进展,基于改进的CASA模型对黑河流域中游地区主要农作物,包括玉米、小麦、油菜籽和大麦进行了估产,结果表明流域内的作物产量分布呈现"西北低东南高"的现象。2对CASA模型的输入数据的处理方法进行研究。采用薄盘光滑样条插值法对气温、降雨数进行插值。使用ArcMap的太阳辐射计算工具计算太阳辐射。3为清晰直观表达估产结果,利用遥感数字地图制图技术,进行了专题要素表示方法、色彩等的选择设计,制作了 2007、2012和2014年的4种主要农作物的产量分布图。4为获得灌溉因子,对黑河流域中游地区的灌溉量进行了估算,并将灌溉因子用于对CASA模型的改进。将估算NPP与其它研究成果进行对比,证明了本研究的估算结果在一定的合理区间,然后与MOD17-NPP数据进行了相关性分析。研究表明,加入灌溉因子后的模型模拟效果更好,估算的结果精度更高。5为分析产量积累过程与作物NDVI之间的关系,本文基于CASA模型估算出每种农作物的月产量,并将月产量与月NDVI进行比较。结果表明,农作物的月产量与NDVI线性关系明显,进而表明NDVI与作物单产具有显著的线性关系。
[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.
【学位授予单位】：西南交通大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：S127

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