利用哨兵2号卫星数据NDVI时间序列监测作物物候

M. Boori, K. Choudhary, R. Paringer, A. Sharma, A. Kupriyanov, S. Corgne
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引用次数: 10

摘要

作物物候监测对粮食安全、农业可持续发展和提高生产力具有重要的产量估算和田间管理意义。了解气候和当地因素对作物生长的影响也很重要。全球可用卫星(如Sentinel-2)的空间和时间分辨率不断提高,为通过植被指数时间序列系统监测作物提供了独特的机会。为了探讨Sentinel-2在作物物候监测中的适用性,我们分析了俄罗斯萨马拉机场地区农田2018年的归一化差异植被指数(NDVI)时间序列。该研究为作物物候监测和精准管理提供了有价值的支持。利用NDVI检测作物分蘖、拔节和成熟期,可为作物建模、推广灌溉、施肥管理、收获确定等提供支持,最终提高粮食安全。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Monitoring Crop Phenology Using NDVI Time Series from Sentinel 2 Satellite Data
Monitoring crop phenology is a great importance to yield estimation and agriculture field management for food security, sustainable development of agriculture and to improve productivity. It's also important to understand how climate and local factors are effect on crop growth. The increasing spatial and temporal resolution of globally available satellites such as Sentinel-2 gives a unique opportunity to monitor crops systematically by vegetation index time-series. To explore the applicability of Sentinel-2 for crop phenology monitoring, we analyzed the Normalized Differential Vegetation Index (NDVI) time series with crop calendar for the year 2018 from crop fields in Samara airport area, Russia. This work has great potential to provide valuable support for monitoring crop phenology and providing precise management strategy. The dates of active tillering, jointing and maturity detected from NDVI could be useful in supporting crop modeling, extension irrigation, fertilization management, harvest determination and in last enhance food security.
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