Geotechnology Applied to Analysis of Vegetation Dynamics and Occurrence of Forest Fires on Indigenous Lands in Cerrado-Amazonia Ecotone

Abstract

The Cerrado-Amazonia Ecotone is one of the largest ecosystems in Brazil and is internationally considered a biodiversity hotspot. The occurrence of fires is common in these areas, directly affecting biomass losses and the reduction of vegetative vigor of forest typologies. Information obtained through remote sensing and geoprocessing can assist in the evaluation of vegetation behavior and its relation to the occurrence of forest fires. In this context, the objective of the present study was to analyze temporal vegetation dynamics, as well as their relationship with rainfall and fire occurrence on Indigenous lands, located in the Cerrado-Amazonia Ecotone of Mato Grosso state, Brazil. Normalized Difference Vegetation Index (NDVI) images of the MOD13Q1 MODIS product and burnt area of the MCD45A1 MODIS product, and rainfall images from the Tropical Rainfall Measuring Mission (TRMM) sensor were used. The period analyzed was from 2007 to 2016. After pre-processing the NDVI, TRMM and burnt area images, correlation analyses were performed between the rainfall, vegetation index and burnt area images, considering different lags (−3 to 3), to obtain the best response time for the variables. The analyses of inter-annual vegetation index trends were carried out following Mann–Kendall monotonic trend and seasonal trend analysis methodologies. Significant correlations were observed between NDVI and rainfall (R = 0.84), in grass regions and between NDVI and burnt area (R = −0.74). The Mann–Kendall monotonic trend indicates vegetation index stability with positive variations in grass regions. The analysis of seasonal trends identified different vegetation responses, with this biome presenting a diverse phytophysiognomy and seasonal vegetation with different phases for amplitudes. This variation is evidenced by the various phytophysiognomies and their responses in relation to biomass gains and losses. The correlation and regression of the NDVI and rainfall in the vegetation type of grass areas show that the burnt area tends to increase with the reduction of NDVI. Finally, no defined pattern of vegetation cycles or phases was observed in terms of seasonality and the proposed methodology can be adapted to other world biomes.

Evaluation of the Ability of SLSTR (Sentinel-3B) and MODIS (Terra) Images to Detect Burned Areas Using Spatial-Temporal Attributes and SVM Classification

“…These twin satellites provide images with a GSD of 500 m/pixel and a range of 1420 km in visible (VIS), infrared (IR), and thermal (TIR) wavelengths, with a temporal resolution of 1 day at the equator, giving high potential for rapid detection and tracking of forest fires, as well as for the systematic monitoring of the recovery process of burned areas [11,15,16]. MODIS is widely used in the Cerrado for mapping burned areas [17], active fire detection [18], forest fire product quality [19,20] and carbon fluxes [21], spectral indices, and time series analysis [22][23][24]. Despite recent research on the use of the SLSTR in the context of forest fires, it has not yet been used exclusively in the Cerrado biome; on the other hand, it has been successfully applied in some countries in the southern hemisphere [11,25].…”

Modeling and Mapping of Forest Fire Occurrence in the Lower Silesian Voivodeship of Poland Based on Machine Learning Methods

“…Similar variables describing fuel conditions, such as rainfall, temperature, wind speed, and relative humidity, have been used in other studies [10][11][12]. Vegetation indices have been widely used to predict fire risk [13][14][15][16][17] in forest fire occurrence modeling due to the strong influence of human activities on fire ignition [18][19][20][21]. Terrain-related factors, such as slope, elevation, and aspect, are usually derived from a digital elevation model (DEM).…”