Method for evaluating plant cover and quantification using pixel to pixel correlation indices

dc.contributorUniversidade Estadual Paulista (UNESP)
dc.date.accessioned2022-04-29T08:28:04Z
dc.date.accessioned2022-12-20T02:42:01Z
dc.date.available2022-04-29T08:28:04Z
dc.date.available2022-12-20T02:42:01Z
dc.date.created2022-04-29T08:28:04Z
dc.date.issued2018-07-01
dc.identifierJournal of Urban and Environmental Engineering, v. 12, n. 2, p. 245-256, 2018.
dc.identifier1982-3932
dc.identifierhttp://hdl.handle.net/11449/228687
dc.identifier10.4090/juee.2018.v12n2.245256
dc.identifier2-s2.0-85066758028
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/5408822
dc.description.abstractThis study brings results on Normalized Difference Vegetation Index (NDVI), the Adjusted Vegetation Index of Soil (SAVI) and the Index of Water by Normalized Difference (NDWI) through a method that uses correlation matrices built on a pixel to pixel combination for spatial and temporal analysis of plant cover. The study was developed by using Landsat 8 images from January and August, 2015. Image processing was performed with ArcGis and Matlab building correlation matrices to evaluate variations of each index in Brazilian vegetation. Results showed decreasing values of the three indices from wet to dry period. Climatic conditions influenced on the vigor and moisture content of vegetation. The pixel to pixel correlation method is appropriated to study vegetation changes and quantify increase, decrease or maintenance of vegetation.
dc.languageeng
dc.relationJournal of Urban and Environmental Engineering
dc.sourceScopus
dc.subjectCorrelation matrixes
dc.subjectPixels
dc.subjectPlant cover
dc.subjectRemote sensing
dc.subjectVegetation index
dc.titleMethod for evaluating plant cover and quantification using pixel to pixel correlation indices
dc.typeArtículos de revistas


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