A5004459526- Soil Geostatistics and Mapping
- Geochemistry and Geologic Mapping
- Soil erosion and sediment transport
- Soil Carbon and Nitrogen Dynamics
- Geophysical and Geoelectrical Methods
- Remote Sensing in Agriculture
- Soil and Land Suitability Analysis
- Soil and Unsaturated Flow
- Soil Management and Crop Yield
- Hydrology and Watershed Management Studies
- Conservation, Biodiversity, and Resource Management
- Image Processing and 3D Reconstruction
- Remote Sensing and LiDAR Applications
- Mineral Processing and Grinding
- Geography and Environmental Studies
- Landslides and related hazards
- Coastal wetland ecosystem dynamics
- Cassava research and cyanide
- Remote-Sensing Image Classification
- Geochemistry and Elemental Analysis
- Land Use and Ecosystem Services
- Radioactivity and Radon Measurements
- Geology and Paleoclimatology Research
- Geomagnetism and Paleomagnetism Studies
- Soil Moisture and Remote Sensing
Universidade de São Paulo
2019-2024
Forest Science and Research Institute
2021-2022
Abstract The Earth’s surface dynamics provide essential information for guiding environmental and agricultural policies. Uncovered unprotected surfaces experience several undesirable effects, which can affect soil ecosystem functions. We developed a technique to identify global bare areas their based on multitemporal remote sensing images aid the spatiotemporal evaluation of anthropic natural phenomena. its changes were recognized by Landsat image processing over time range 30 years using...
Terrain analysis is an important tool for modeling environmental systems. Aiming to use the cloud-based computing capabilities of Google Earth Engine (GEE), we customized algorithm calculating terrain attributes, such as slope, aspect, and curvatures, different resolution geographical extents. The calculation method based on geometry elevation values estimated within a 3 × spheroidal window, it does not rely projected data. Thus, partial derivatives are calculated considering great circle...
Evaluation of spatial variability and mapping soil properties is critical for sustainable agricultural production in arid lands. The main objectives the present study were to spatialize organic carbon (SOC), particle size distribution(clay, sand, silt contents), calcium carbonate equivalent (CCE) by integrating multisource environmental covariates, including digital elevation model (DEM) remote sensing data machine learning (Cubist, Cu random forest, RF) an region Iran. Additionally,...
Although many Soil Spectral Libraries (SSLs) have been created globally, these libraries still not operationalized for end-users. To address this limitation, study an online Brazilian Service (BraSpecS). The system was based on the Library (BSSL) with samples collected in Visible–Near–Short-wave infrared (vis–NIR–SWIR) and Mid-infrared (MIR) ranges. interactive platform allows users to find spectra, act as custodians of data, estimate several soil properties classification. tested by 500 65...
Abstract. Geophysical sensors combined with machine learning algorithms were used to understand the pedosphere system and landscape processes model soil attributes. In this research, we parent material, terrain attributes, data from geophysical in different combinations test compare novel We also analyzed importance of pedoenvironmental variables predictive models. For that, collected physicochemical (gamma-ray emission uranium, thorium, potassium; magnetic susceptibility apparent electric...
The pressure for food production has expanded agriculture frontiers worldwide, posing a threat to water resources. For instance, placing crop systems over hydromorphic soils (HS), have direct impact on groundwater and influence the recharge of riverine ecosystems. Environmental regulations improved past decades, but it is difficult detect protect these soils. To overcome this issue, we applied temporal remote sensing strategy generate synthetic soil image (SYSI) associated with random forest...
Soil classification is important to organize the knowledge of soil characteristics. Spectroscopy has increased in last years as a technique for descriptive and quantitative evaluation soils. Thus, our objective was assess qualitative methods on classification, based model profiles. Soils different environments Roraima state, Brazil, were evaluated represented by 16 profiles, providing 109 samples, which analyzed particle size distribution, chemical attributes spectral measurement....
Soil apparent electrical conductivity (ECa) is related to various soil attributes and processes. This research aimed understand the relationship between ECa paedogenesis, lithology attributes. The study area located in São Paulo State, Brazil. samples were collected for physical-chemical analysis from 79 locations (0–20 cm layer). A geophysical field-portable equipment (Geonics EM38-MK2 meter) was used measure ECa. For that, four toposequences selected on landscape. Sixteen profiles...
Abstract. Geophysical sensors combined with machine learning algorithms have been used to understand the pedosphere system, landscape processes and model soil attributes. In this research, we parent material, terrain attributes data from geophysical in different combinations, test compare novel Also, analyzed importance of pedoenvironmental variables predictive models. For that, collected physico-chemical (gamma-ray emission uranium, thorium potassium, magnetic susceptibility apparent...
This study analyzed the role of soil health (SH) and ecosystem services (ESs) in global mangrove research articles from 1958 to 2024. The SH approach is vital for evaluating mangroves’ ability provide ES. However, most studies made no reference these topics, an important gap that must be addressed. We performed a systematic literature review Scopus database using following prompts: Level 1: “mangrove*” “soil” or “sediment”; 2: “soil health” quality”; 3: quality” “ecosystem service*”...