Vegetation anomalies associated with the ENSO phenomenon in the Cauca river valley, Colombia
The main factors affecting the production and yield of sugarcane are variety, agronomic management, soil type and climate, of which the first three there is some control, while the climate is one factor of which you cannot have any control, therefore, it should be monitored. Colombia, being located...
Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
Universitat Politécnica de Valencia
2017-12-01
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Series: | Revista de Teledetección |
Subjects: | |
Online Access: | https://polipapers.upv.es/index.php/raet/article/view/7715 |
Summary: | The main factors affecting the production and yield of sugarcane are variety, agronomic management, soil type and climate, of which the first three there is some control, while the climate is one factor of which you cannot have any control, therefore, it should be monitored. Colombia, being located in the equatorial pacific, is affected by two atmospheric oceanic phenomena known as “El Niño” and “La Niña”, which make up the climatic phenomenon of ENSO (El Niño-Southern Oscillation) and affect the quantity and the number of days with rainfall and influences the production of sugarcane. The objective of this work is to identify spatially and temporally the zones with greater and lower impact of the ENSO phenomenon in the cultivation of sugarcane in Colombia through the use of the Standard Vegetation Index (SVI) and the Rainfall Anomally Index (RAI) using EVI/MODIS images and precipitation data from meteorological stations on a quarterly basis for the period 2000-2015. A similar trend was found between both indices in the “El Niño” and “Neutral” seasons, while in the “La Niña” season the RAI tended to rise while the SVI decreased when the RAI was very high, this tendency being much more marked in areas with floods caused by the overflow of the main rivers. In addition, a comparison was made between the SVI index and a productivity anomaly index (IAP), finding a direct correlation between both (R2 = 0.4, p<0.001). This work showed that through the use of vegetation indexes, a temporal analysis of the impact of climate on an agricultural crop can be carried out, especially with ENSO conditions. |
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ISSN: | 1133-0953 1988-8740 |