A5064716153- Remote Sensing in Agriculture
- Land Use and Ecosystem Services
- Remote Sensing and Land Use
- Remote Sensing and LiDAR Applications
- Smart Agriculture and AI
- Soil Geostatistics and Mapping
- Climate change impacts on agriculture
- Soil and Land Suitability Analysis
- Sustainable Agricultural Systems Analysis
- Rangeland Management and Livestock Ecology
- Agroforestry and silvopastoral systems
- Soil Carbon and Nitrogen Dynamics
- Leaf Properties and Growth Measurement
- Soil erosion and sediment transport
- Agriculture Sustainability and Environmental Impact
- Agriculture and Rural Development Research
- Plant Water Relations and Carbon Dynamics
- Remote-Sensing Image Classification
- Soybean genetics and cultivation
- Horticultural and Viticultural Research
- Biofuel production and bioconversion
- Bioenergy crop production and management
- Spectroscopy and Chemometric Analyses
- Effects of Environmental Stressors on Livestock
- Plant Ecology and Soil Science
Universidade Estadual de Campinas (UNICAMP)
2016-2025
Fast and accurate quantification of the available pasture biomass is essential to support grazing management decisions in intensively managed fields. The increasing temporal spatial resolutions offered by new generation orbital platforms, such as Planet CubeSat satellites, have improved capability monitoring using remotely sensed data. Here, we assessed feasibility spectral textural information derived from PlanetScope imagery for estimating aboveground (AGB) canopy height (CH) fields...
Abstract Grasslands are the largest contributor of nitrous oxide (N 2 O) emissions in agriculture sector due to livestock excreta and nitrogen fertilizers applied soil. Nitrification inhibitors (NIs) added N input have reduced O emissions, but can show a range efficiencies depending on climate, soil, management conditions. A meta-analysis study was conducted investigate factors that influence efficiency NIs fertilizer reducing focused grazing systems. Data from peer-reviewed studies...
Timely and efficient land-cover mapping is of high interest, especially in agricultural landscapes. Classification based on satellite images over the season, while important for cropland monitoring, remains challenging subtropical areas due to diversity management systems seasonal cloud cover variations. This work presents supervised object-based classifications year at 2-month time-steps a heterogeneous region 12,000 km2 Sao Paulo Brazil. Different methods remote-sensing datasets were...
Integrated crop–livestock systems (ICLS) are among the main viable strategies for sustainable agricultural production. Mapping these is crucial monitoring land use changes in Brazil, playing a significant role promoting Due to highly dynamic nature of ICLS management, mapping them challenging task. The objective this research was develop method using deep learning algorithms applied on Satellite Image Time Series (SITS) data cubes, which consist Sentinel-2 (S2) and PlanetScope (PS) satellite...
Pasture land occupies extensive areas and is increasingly of interest for sustainable intensification, use diversification, greenhouse gas emission mitigation, bioenergy expansion. Accurate maps pasture other managed covers are needed monitoring, intercomparison, assessing potential uses, planning. Yet, can be generated from different types classification datasets – i.e. as a or cover type well sources. In this study our aim was to assess compare definitions pasture, examine variability in...
Process-based models (PBM) are important tools for understanding the benefits of Integrated Crop-Livestock Systems (ICLS), such as increasing land productivity and improving environmental conditions. PBM can provide insights into contribution agricultural production to climate change help identify potential greenhouse gas (GHG) mitigation carbon sequestration options. Rehabilitation degraded lands is a key strategy achieving food security goals reduce need new land. This study focused on...
Abstract To meet rising demands for agricultural products, existing lands must either produce more or expand in area. Yield gaps (YGs)—the difference between current and potential yield of systems—indicate the ability to increase output while holding land area constant. Here, we assess YGs global grazed‐only permanent pasture using a climate binning approach. We create snapshot circa 2000 empirical yields meat milk production from cattle, sheep, goats by sorting pastures into bins defined...
Regenerative agricultural practices are a suitable path to feed the global population. Integrated Crop–livestock systems (ICLSs) key approaches once area provides animal and crop production resources. In Brazil, expectation is increase of ICLS fields by 5 million hectares in next five years. However, few methods have been tested regarding spatial temporal scales map monitor fields, none these use SAR data. Therefore, this work, we explored potential three machine deep learning algorithms...
Abstract Despite the recent discoveries of considerable fossil fuel reserves, Brazil is one only great economic and industrial powers with very high amounts renewable energy in its electricity matrix. Approximately 79.3% electric supply comes from resources, which hydroelectric power represents 70.6%. The two primary concerns regarding hydroelectricity are damage caused to environment by construction dams uncertainty cases long drought seasons. This article presents an analysis on...
Vegetation indices are widely used to monitor crop development and generally as input data in models forecast yield. The first step of this study consisted using monthly Maximum Value Composites create correlation maps Enhanced Index (EVI) from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor mounted on Terra satellite historical yield during the soybean cycle Paraná State, Brazil, 2000/2001 2010/2011. We compared ability forecasting based specific masks. ran a preliminary...
Crop identification is an important task in the process of yield estimation; however, sometimes it can be difficult when using images medium to low spatial resolution due mixing heterogeneous areas within pixel. Therefore, selecting pixels that best represent area/crop could alternative input data estimate models. The objective this study was select soya bean based on temporal stability technique and test ability these predict yield. conducted at county level Paraná state, Brazil, during 11...
The recent advances in unmanned aerial vehicle (UAV)-based remote sensing systems have broadened the applications for agriculture. Despite great possibilities of using UAVs to monitor agricultural fields, specific problems related missing parts UAV orthomosaics due drone flight restrictions are common monitoring, especially large areas. In this study, we propose a methodological framework impute PlanetScope (PS) and Sentinel-2 (S2) data random forest (RF) algorithm an integrated...
Abstract. Land use and land cover (LULC) classification has long been an essential topic in Earth Observation research plays a key role the sustainable development of agriculture. This study evaluated accuracy LULC based on initial clustering step heterogeneous agricultural landscape using PlanetScope imagery while checking for variability among their Normalized Difference Vegetation Index (NDVI) temporal signatures. We adopt object-based image analysis to generate image-objects then extract...
MODIS time series carries valuable long-term data essential to support several studies such as biogeochemical modelling. However, there is a lack of validation applying at fine-scale monitor pasture management practices. In this study, we assessed the potential sensor in monitoring four intensively managed mixed-pastures fields located São Paulo State, Brazil. The spectral response was compared with Sentinel-2, and ability two sensors predicting aboveground biomass (AGB) canopy height (CH)...