京津冀地区冬小麦面积估算和旱情遥感监测研究

发布时间：2018-06-24 10:24

本文选题：冬小麦 + 混合像元分解　；参考：《北京林业大学》2015年硕士论文

【摘要】：农情信息是农业生产和农业抗旱减灾管理的依据,遥感技术的引入,使农情监测更具有实时性、全面性和可靠性,为了探讨遥感技术在作物信息和农业旱情监测中的适用性及其优势,本文以京津冀地区冬小麦为研究对象,采用MODIS数据、气象数据和冬小麦生长发育指标,利用传统分类法和混合像元分解法,提取并估算研究区冬小麦种植面积,利用植被指数和陆地表面温度构建干旱指数,分别从全生育期尺度和多年时间尺度对研究区冬小麦的旱情进行监测,得到如下结论：(1)利用MODIS数据进行大范围农作物面积监测是可行的。确定了冬小麦面积提取的最佳时相组合,即头年10月出苗期、11月分蘖期和次年5-6月抽穗期-收获期,提取的2012年冬小麦种植面积结果与实际种植分布趋势基本一致,与实际数据和高分辨率TM影像、Google earth影像的精度检验结果均达到82%以上,符合精度要求,表明该方法在农作物面积估测中具有较强的应用价值；(2)分别提取了2002年和2012年京津冀冬小麦种植面积,结果表明近10年京津冀地区冬小麦种植总面积有所减少,减少约0.7%,各个地市面积变化程度不同。冬小麦麦田分布总体呈现逐步集中化趋势,虽然部分地区麦田减少,但大部分地区,特别是中南部地区的冬小麦呈现大面积连片播种；(3)利用植被指数和地表温度构建NDVI-Ts二维特征空间,提取干边和湿边,计算TVDI干旱指数。选取2012年4月22日的TVDI与实测土壤相对湿度进行相关性分析,二者呈负相关关系；利用全生育期监测结果与同期降水量数据对比分析,TVDI可以在长时间序列中很好的监测旱情变化,以上结果表明TVDI指数可以用于评价研究区干旱情况。从10月上旬(播种期)到4月上旬(拔节期)京津冀地区旱情持续严重,干旱缺水面积达到60%以上,从4月上旬(拔节期)到6月上旬(收获期),旱情有所缓解,土壤墒情逐步好转。京津冀地区的旱情总体呈现出由北向南逐渐加剧的趋势；(4)由调整后的干旱定级标准获取了冬小麦旱情等级分布图,从分蘖到越冬期,冬小麦种植区域几乎全部呈现缺水干旱状态。进入拔节期后,麦田旱情由北向南减轻,全区缺水干旱面积有所降低。从抽穗到乳熟期,冬小麦大部分地块TVDI等级为正常和湿润,而干旱地块面积极少,旱情明显好转；(5)冬小麦生育期降水量和需水量吻合度较差,特别在抽穗期以后,二者的差距明显增大,缺水严重。由TVDI干旱指数分析发现,近10年冬小麦抽穗期内,其主产区土壤墒情达到适宜或湿润,明显优于周边非冬小麦区,一定程度上反映当地在该生育期内重点加强了农业灌溉管理。从2009年以后,麦田旱情较前几年严重。从空间分布来看,西部太行山山前平原冬麦区的土墒持续明显好于东部河北低平原冬麦区,存在麦田灌溉不足、灌溉不均衡的现象。由TVDI和冬小麦亩产量相关性分析发现,二者存在较显著的负相关关系,表明基于TVDI的旱情监测,也可以反映冬小麦产量在时间和空间上的分布,为及时有效地预测区域内冬小麦产量状况提供依据,同时,也为冬小麦遥感估产提供了一种新的思路。
[Abstract]:Agricultural information is the basis of agricultural production and agricultural drought relief and disaster reduction management. The introduction of remote sensing technology makes the monitoring of agricultural situation more real-time, comprehensive and reliable. In order to discuss the applicability and advantages of remote sensing technology in crop information and agricultural drought monitoring, this paper takes winter wheat in Beijing Tianjin Hebei region as the research object and uses MODIS data. Meteorological data and winter wheat growth and development indexes were used to extract and estimate the planting area of Winter Wheat in the study area by using traditional classification method and mixed pixel decomposition method. The drought index was constructed by using vegetation index and land surface temperature. The drought conditions of the winter wheat in the study area were monitored from the whole growth period scale and the year time scale respectively. (1) it is feasible to use MODIS data to monitor the area of crop area in large range. The best time phase combination of winter wheat area extraction is determined, that is, the emergence period of October, the tillering period in November and the heading period of the next year 5-6 months, and the results of the winter wheat planting area in 2012 are basically the same as the actual planting distribution trend. And high resolution TM images, the accuracy test results of Google earth images are above 82%, which conforms to the precision requirements. It shows that the method has a strong application value in crop area estimation. (2) the planting area of Winter Wheat in Beijing, Tianjin and Hebei was extracted in 2002 and 2012 respectively. The results showed the total area of winter wheat planting in Beijing, Tianjin and Hebei region for nearly 10 years. The distribution of wheat field in winter wheat showed a gradual centralization trend, although the wheat field in some areas decreased, but the winter wheat in most areas, especially in the central and southern regions, showed a large area of continuous sowing, and (3) the NDVI-Ts two-dimensional feature space was constructed with the vegetation index and the surface temperature of NDVI-Ts. In the meantime, the dry edge and wet edge were extracted and the TVDI drought index was calculated. The correlation analysis between the April 22, 2012 TVDI and the measured soil relative humidity was selected, and the two were negatively correlated. Using the monitoring results of the whole growth period and the precipitation data of the same period, the TVDI could monitor the drought changes well in the long sequence, and the above results showed that T The VDI index can be used to evaluate the drought in the study area. From the early October (sowing period) to the first ten days of April (jointing period), the drought situation in Beijing, Tianjin and Hebei region continued to be serious, and the dry water shortage area reached over 60%. From the early April (jointing period) to the first ten days of June (harvest period), the drought situation was relieved and the soil moisture was gradually improved. The drought situation in Beijing Tianjin Hebei region showed a general appearance. The trend from north to South gradually intensified; (4) the drought level distribution map of winter wheat was obtained from the adjusted drought grading standard. From tillering to overwintering period, almost all winter wheat planting areas showed water shortage and drought condition. After the jointing period, the drought of wheat fields decreased from north to south, and the area of water shortage and drought in the whole region decreased. From heading to milk ripening. During the period, the TVDI grade of most of winter wheat was normal and humid, and the area of dry land was very few, and the drought situation was obviously better. (5) the rainfall and water demand in winter wheat were in poor anastomosis, especially after the heading stage, the gap between the two was obviously increased and the water shortage was serious. It was found by the analysis of the drought index of the winter wheat in the last 10 years of the winter wheat during the heading period. The soil moisture in the production area is suitable or moist, which is obviously superior to the surrounding non winter wheat areas. To a certain extent, the agricultural irrigation management has been strengthened in this period. Since 2009, the drought situation in the wheat field is more serious than that in the previous years. From the spatial distribution, the soil moisture in the winter wheat area in the western Taihang Mountain is better than that in the eastern Hebei. In the low plain winter wheat area, there was a lack of irrigation and uneven irrigation in the wheat field. The correlation analysis of the yield of TVDI and winter wheat showed that there was a significant negative correlation between the two people. It showed that the drought monitoring based on TVDI could also reflect the distribution of winter wheat yield in time and space, and to predict winter wheat production in the region and effectively. It also provides a new idea for remote sensing yield estimation of winter wheat.
【学位授予单位】：北京林业大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：S512.11;S423;S127

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