Abstract
The development of several time series analysis programs using satellite images has provided many applications based on resources from geostatistics field. Currently, the use of statistical tests applied to vegetation indexes has enabled the analysis of different natural phenomena, such as drought events in watershed areas. The objective of this article is to provide a comparative analysis between NDVI and EVI vegetation index data made available by MOD13Q1 project of MODIS sensor for drought mapping using vegetation condition index (VCI) in the Serra Azul stream sub-basin, MG. The methodology adopted the Cox-Stuart statistical test for seasonality analysis and Pearson's linear correlation to verify the influence of different indexes on delimitation of drought in a watershed. The results indicated the NDVI vegetation index as more efficient than EVI in spatial characterization of studied watershed region, mainly in identification of seasonality. The VCI proved to be highly feasible for monitoring drought in study period between 2013 and 2018, allowing the effective delimitation of drought conditions in the Serra Azul stream sub-basin. In addition, the effectiveness of MODIS sensor data in characterizing drought events that affected the study area was proven.
Highlights
The development of several Earth observation programs has provided, through spectral analyzes of the environment, increasingly adequate responses to different natural variations and anthropogenic actions that occur on planets surface
The objective of this article is to provide a comparative analysis between normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) vegetation index data made available by MOD13Q1 project of MODIS sensor for drought mapping using vegetation condition index (VCI) in the Serra Azul stream sub-basin, MG
The drought variation was identified through data from the MOD13Q1 product, the methodology used was divided into five analyzes, namely: selection of the study area, of the vegetation condition index and correlation obtaining data from the MODIS sensor, analysis of the results generated with meteorological of the vegetation indexes time series, calculation data (Figure 1)
Summary
The development of several Earth observation programs has provided, through spectral analyzes of the environment, increasingly adequate responses to different natural variations and anthropogenic actions that occur on planets surface. Remote sensing data applications can be performed from the perspective of earth's surface analysis, through variables that are used directly in drought monitoring such as vegetation indexes (DECHANT; MORADKHANI, 2014, 2015). Vegetation indexes are mathematical formulations that use remote sensing spectral data to estimate the behavior of vegetation cover in a region. These formulations allow to analyze the vegetation activity as well as foliage variation in terms of seasonality (BONIFACIO; DUGDALE; MILFORD, 1993; FORMAGGIO, SANCHES, 2017)
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