Suchergebnisse

This 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.

This study investigated the influence of land use on water quality parameters in the subtropical basin of Jundiaí-Mirim river. Water samples were collected to measure nutrients concentration and direct measurements by multiparameter probe were performed, as well as landscape analysis, using satellite images and visits in the sampling sites, besides analysis of population density data. Data were standardized and the correlation between the variables was measured using Spearman approach. Land use in the surrounding area of the sampling points had strong and significant correlations (p < 0.05) with some of the water quality parameters evaluated. These correlations had different causes, explained by the land use in a 50 m radius, or 500 m radius, or even beyond these environments studied. Landscape analysis has proved to be an important tool for understanding the interaction between water quality and land use.