Acta Geobalcanica (Jun 2020)
MONITORING THE CROPS PHENOLOGY USING TIME SERIES SENTINEL 2 IMAGES
Abstract
It is important to know the beginning and the end of the growing season at the plot level, in order to understand the dynamics of crops and agricultural systems, but also to know the phenological values related to the crop calendar. Detailed data of seasonal vegetation changes can be obtained using the time series of Sentinel 2 images, by recognizing the spectral signal that cultures have in all phenological stages. In recent decades, studying the phenology of vegetation has become increasingly. The influence of climate change on the evolution of vegetation can be quantified by a series of biological indicators, highlighting the impact of changing phenological dynamics on ecosystem functions and functionality. By studying the phenology of the terrestrial surface in accordance with the crop calendar using time series of vegetation indices obtained from Sentinel 2 images, a new way of monitoring the vegetation response to climate change has been developed. The study area is located in Iasi county, between 47 ° 18′01 ″ N and 27 ° 05′54 ″E, maize, wheat and soybeans being the most important crops grown in the region. The analyses were carried out in a cropland area located in NE of Romania characterized by continental climate (hot dry summers and cool winter). Soils are mainly chernozem (48.62%), followed by alluviosols (6.78%) and anthrosols (2.43%). The aim of this study was to understand the phenological stages of the crops and to monitor the crops taking into account the time-series images and vegetation indices. In order to achieve this, based on the specifics of the agricultural land use, the updated crop calendar highlighted the phenological stages of crops, being selected from fifteen Sentinel 2 only nine (2018-2019) satellite images to monitoring multiannual vegetation changes. Vegetation indices included in the analysis were: Normalized Differentiation Vegetation Index (NDVI), Enhanced Vegetation Index (EVI2) and Adjusted Soil Vegetation Index (SAVI). For the development of efficient agricultural management policies that facilitate the implementation of sustainable systems, it is necessary an efficient mapping of agricultural lands.
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