Title
Vegetation cover estimation from high-resolution satellite images based on chromatic characteristics and image processing
Date Issued
16 November 2020
Access level
metadata only access
Resource Type
conference paper
Author(s)
Huillcen Baca H.A.
Ponce Atencio Y.
Tadeo F.T.
Publisher(s)
IEEE Computer Society
Abstract
The change in ecosystems and the loss of biodiversity are global problems, one of the ecosystems with the most signifi-cant degradation is the high areas of the Andes, composed mostly of natural pastures. In the Andahuaylas province, Apurimac region, Peru, there is a high-impact Andean area for the collection of water for human consumption and irrigation; this area is called the Chumbao River Micro-basin the problem is that this area is presenting essential changes in its surface, corresponding to natural pastures, especially of the species fescue (festuca dolycophylla) and paco (aciachne pulvinata) these changes do not have any estimates or studies that allow adequate decision-making in the adoption of preventive and corrective measures for the conservation of ecology, the environment, and water collection.Under this approach, this work proposes a method of estimating vegetation cover for those species, through the chromatic characteristics of each species, using high-resolution satellite images, extracted from the PERUSAT-1 satellite the method consists of dividing the global satellite image into small images, converting them into the HSV color system (Hue, Saturation, and Value). Evaluating the range of chromatic characteristics of each species and performing range segmentation, subsequently fine-Tuning the segmentation with morphological deformations and calculate the final area.The results obtained an accuracy of 91.56%, taking as a reference the result of the estimation of traditional vegetation cover; this result was tested in an area of 3824.45 m2 with the presence of both species therefore, our proposal is a reliable method for calculating vegetation cover and can be used for large surface areas, saving human and financial resources and with almost instantaneous results, compared to the traditional way.
Volume
2020-November
Language
Spanish
OCDE Knowledge area
Ecología
Ingeniería de sistemas y comunicaciones
Subjects
Scopus EID
2-s2.0-85098670890
Source
Proceedings - International Conference of the Chilean Computer Science Society, SCCC
Resource of which it is part
Proceedings - International Conference of the Chilean Computer Science Society, SCCC
ISSN of the container
15224902
ISBN of the container
978-172818328-2
Conference
39th International Conference of the Chilean Computer Science Society, SCCC 2020
Sources of information:
Directorio de Producción Científica
Scopus