Vegetation indices associated with coffee agroforestry systems in western Honduras
DOI:
https://doi.org/10.15517/s34jkr60Keywords:
agroforestry, Sentinel-2, remote sensing, geographic information systemsAbstract
Introduction. Coffee is the most important tree crop in the world. In Honduras, this crop represents 5% of the country's total income. Objective. Calculate vegetation indices (VI) and the level of association with different land uses and cover in western Honduras. Materials and methods. For the IV´s, Sentinel 2A-2B images from the Copernicus program were used. The VI´s used were Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI), Normalized Difference Moisture Index (NDMI), and Moisture Stress Index (MSI). The land uses taken as reference were Broadleaf Forest (B-L), Coniferous Forest (B-C), Mixed Forest (B-M), Coffee plantations (SAF-C), and Pastures and Crops (P-C). Results. Land uses classified as B-M (75%) and B-L (63%) have the highest percentages of pixels in the highest NDVI categories, while P-C (13%) has the lowest. For SAVI, SAF-C (94%) and B-C (91%) achieved the highest percentages of pixels in the highest categories, while P-C (75%) had the lowest. For the NDMI index, the highest weighted values of humidity were found in B-M (48%) and B-L (41%) and the lowest was for P-C (1.78%). For MSI, the highest weighted values are B-M with 36% and the lowest value is B-L with 1.62%. Conclusions. The analysis shows a significant association between the IV levels used and land uses (X2 = 369.4; p-value = 0,0001). B-L and B-M are the two land uses that have the greatest similarity and that reflect the highest levels of IV. SAF-C had its greatest association with B-C and the land uses that presented the lowest levels of association were P-C and SAF-C.
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