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Arnaldoa

Print version ISSN 1815-8242On-line version ISSN 2413-3299

Abstract

FLORES, Nathalie; CASTRO, Irene  and  APONTE, Héctor. Evaluation of the vegetation units in Los Pantanos De Villa (Lima, Peru) using geographical information systems and teledetection. Arnaldoa [online]. 2020, vol.27, n.1, pp.303-321. ISSN 1815-8242.  http://dx.doi.org/10.22497/arnaldoa.271.27119.

Coastal wetlands of Peru are important because of the multiple services they provide to surrounding towns. To protect these ecosystems, it is important to monitor their areas and the changes that occurred in them. Los Pantanos de Villa is a Ramsar wetland in the city of Lima, and, like many coastal wetlands in the region, has undergone multiple natural and anthropogenic changes. In this work, high and medium resolution satellite images were used (such as WorldView 3 images dated May 2018 and CBERS2, 2B and 4 from 2004, 2008 and 2018) with the objective of defining, identifying and characterizing vegetation units and the analysis of changes in vegetation cover in the area using the NDVI (Normalized Difference Vegetation Index). The methodology included obtaining and acquiring satellite images, basic and thematic cartographic information. These were sometimes a geometric correction, reality techniques and algorithms of classification and obtaining of the NDVI; all this using the ARGIS software and making multiple field outputs. As a result, 8 vegetation units were identified that correspond to the gramadal, totoral, intervened area-bodies of water, juncal, short-cut, aquatic, carrizal, and salicornial. The result obtained from the NDVI analysis indicates that the area without vegetation went from occupying 1.96 ha in 2004 to occupying 38.75ha in 2018; the mixed vegetation class went from 100.24 ha in 2004 to 148,344 ha in 2018; Dense vegetation class went from 130,146 ha to 40,285 ha in 2018. The increase in the area without vegetation is a sign of how the change in land use, due to different human activities, can affect a coastal wetland.

Keywords : GIS; land use; NDVI; Ramsar; wetland.

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