主要农作物归一化差异植被指数与气象因素之间的联系

Agrology Pub Date : 2024-07-09 DOI:10.32819/202406
P. Lykhovyd, R. Vozhehova, L. Hranovska, I. Bidnyna
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摘要

归一化差异植被指数(NDVI)常用于监测气象事件。本研究的目的是确定乌克兰草原区主要农作物(即冬小麦、冬油菜、谷物玉米、大豆和向日葵)的空间归一化植被指数与气温和降水量之间的关系。研究范围包括八个地区的耕地:克里米亚、赫尔松、米科廖夫、敖德萨、扎波罗热、第聂伯罗彼得罗夫斯克、基洛沃格勒和哈尔科夫。产量数据来自乌克兰国家统计局的官方机构。月气温和降雨量气象数据取自地区水文气象中心。NDVI 值取自 GIMMS 全球农业监测系统,该系统提供分辨率为 250 米的地形 MODIS NDVI 8 天平滑时间序列。研究对象为 2021-2022 年的冬油菜和向日葵;2017 年和 2020 年的谷物玉米;2022 年的冬小麦;以及 2017 年的大豆。我们发现,所研究作物的月 NDVI 值与降雨量之间几乎没有相关性或相关性较弱。气温的相关性较强,向日葵、大豆和冬小麦的相关系数最大,分别为 0.76、0.72 和 -0.72。根据气温建立的线性回归模型可以很好地预测上述作物的归一化差异植被指数,相对误差在 10%-20%之间。向日葵归一化差异植被指数模型的总体拟合度和准确度最高。只有冬季作物与气温呈负相关,这表明这些作物的栽培品种不耐热。
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The link between the normalized difference vegetation index in major crops and meteorological factors
Normalized difference vegetation index (NDVI) is frequently used in monitoring of meteorological events. The goal of this study was to establish the relationship between the spatial NDVI with air temperature and precipitation amounts in major crops cultivated in the steppe zone of Ukraine, namely, winter wheat, winter rapeseed, grain corn, soybeans, and sunflower. The study included the croplands of eight regions: the Crimea, Kherson, Mykolaiv, Odesa, Zaporizhzhia, Dnipropetrovsk, Kirovohrad, and Kharkiv. The yield data were retrieved from the official bodies of the State Statistical Service of Ukraine. The meteorological data on monthly air temperature and rainfall were retrieved from regional hydrometeorological centers. The NDVI values were retrieved from the GIMMS Global Agricultural Monitoring System, which provides Terrain MODIS NDVI 8-Day smoothed time series with 250 m resolution. The study was performed for the 2021-2022 for winter rapeseed and sunflower; 2017 and 2020 for grain corn; 2022 for winter wheat; and 2017 for soybeans. We found almost no or weak correlation between monthly NDVI values of the studied crops and rainfall amounts. A stronger correlation was found for air temperature, with the greatest values of the correlation coefficient of 0.76, 0.72, –0.72 for sunflower, soybeans, and winter wheat, respectively. The linear regression models, developed to predict NDVI based on the air temperature for the mentioned crops, provided good prediction accuracy with the relative error within 10–20%. The best overall fit and accuracy was produced by the model of sunflower’s NDVI. Only winter crops were observed to have a negative correlation with air temperature, suggesting that the cultivated varieties of these crops are heat-intolerant.
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