A5073057500- Remote Sensing in Agriculture
- Remote Sensing and LiDAR Applications
- Land Use and Ecosystem Services
- Geochemistry and Geologic Mapping
- Soil Geostatistics and Mapping
- Forest ecology and management
- Remote-Sensing Image Classification
- Spectroscopy and Chemometric Analyses
- Remote Sensing and Land Use
- Conservation, Biodiversity, and Resource Management
- Urban Heat Island Mitigation
- Species Distribution and Climate Change
- Advanced Image Fusion Techniques
- Leaf Properties and Growth Measurement
- Geography and Environmental Studies
- Environmental and biological studies
- Water Quality and Pollution Assessment
- Soil Management and Crop Yield
- Plant Water Relations and Carbon Dynamics
- Bamboo properties and applications
- Soil erosion and sediment transport
- Fire effects on ecosystems
- Synthetic Aperture Radar (SAR) Applications and Techniques
- Soil and Land Suitability Analysis
- Water Quality Monitoring and Analysis
National Institute for Space Research
2015-2024
Our limited understanding of the climate controls on tropical forest seasonality is one biggest sources uncertainty in modeling change impacts terrestrial ecosystems. Combining leaf production, litterfall and observations from satellite ground data Amazon forest, we show that seasonal variation production largely triggered by signals, specifically, insolation increase (70.4% total area) precipitation (29.6%). Increase drives growth absence water limitation. For these non-water-limited...
Several methods have been proposed to delineate management zones in agricultural fields, which can guide interventions of the farmers increase crop yield. In this study, we propose a new approach using remote sensing data at three farm sites located southern Brazil. The is based on hypothesis that measured aboveground biomass (AGB) cover crops correlated with cash-crop yield and be estimated from surface reflectance and/or vegetation indices (VIs). Therefore, used seven different statistical...
We report large-scale estimates of Amazonian gap dynamics using a novel approach with large datasets airborne light detection and ranging (lidar), including five multi-temporal 610 single-date lidar datasets. Specifically, we (1) compared the fixed height relative methods for delineation established relationship between static dynamic gaps (newly created gaps); (2) explored potential environmental/climate drivers explaining occurrence generalized linear models; (3) cross-related our findings...
Tropical rainforests from the Brazilian Amazon are frequently degraded by logging, fire, edge effects and minor unpaved roads. However, mapping extent of degradation remains challenging because lack frequent high-spatial resolution satellite observations, occlusion understory disturbances, quick recovery leafy vegetation, limitations conventional reflectance-based remote sensing techniques. Here, we introduce a new approach to map forest caused road construction based on deep learning (DL),...
Tropical forests and savannas are responsible for the largest proportion of global Gross Primary Productivity (GPP), a major component carbon cycle. However, there still deficiencies in spatial temporal information tropical photosynthesis its relations with environmental controls. The MOD17 product, based on Light Use Efficiency (LUE) concept, has been updated to provide GPP estimates around globe. In this research, collections 5.0, 5.5 6.0 their sources uncertainties were assessed by using...
Abstract. Bamboo-dominated forests comprise 1 % of the world's and 3 Amazon forests. The Guadua spp. bamboos that dominate southwest are semelparous; thus flowering fruiting occur once in a lifetime before death. These events massive spatially organized patches every 28 years produce huge quantities necromass. bamboo–fire hypothesis argues increased dry fuel after die-off enhances fire probability, creating opportunities favor bamboo growth. In this study, our aim is to map bamboo-dominated...
The relations between reflectance and soil constituents of groups, stratified according to the organic matter (OM) content, were quantitatively analysed in 400-2500 nm spectral region. In order demonstrate OM influence, a group samples was submitted removal this constituent by H2O2. Despite relatively poor correlations obtained with reflectance, seems be main component responsible for lowering 550-700 range. presence more than 1.7 per cent effaces iron features induces reduction greater 40...
We used RapidEye and Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra data to study terrain illumination effects on 3 vegetation indices (VIs) 11 phenological metrics over seasonal deciduous forests in southern Brazil. applied TIMESAT for the analysis of Enhanced Vegetation Index (EVI) Normalized Difference (NDVI) derived from MOD13Q1 product calculate metrics. related VIs with cosine incidence angle i (Cos i) inspected percentage changes before after topographic C-correction. The...
Soil salinization due to irrigation affects agricultural productivity in the semi-arid region of Brazil. In this study, performance four computational models estimate electrical conductivity (EC) (soil salinization) was evaluated using laboratory reflectance spectroscopy. To investigate influence bandwidth and band positioning on EC estimates, we simulated spectral resolution two hyperspectral sensors (airborne ProSpecTIR-VS orbital Hyperspectral Infrared Imager (HyspIRI)) three...
Abstract Soils from central Brazil have been intensively used over the last decades because of rapid conversion savannas ( Cerrado ) into corn/soybean fields. The objective this work is to study modifications in physical properties soils Rio Verde watershed, as a function land use time for agriculture, determined classification Landsat satellite images between 1980 and 2010. Soil samples were collected at surface (0–20 cm) subsurface (20–40 horizons different classes (<10, 10–20, 20–30,...