A5070677264- Remote Sensing in Agriculture
- Crop Yield and Soil Fertility
- Soybean genetics and cultivation
- Geography and Environmental Studies
- Soil and Land Suitability Analysis
- Leaf Properties and Growth Measurement
- Rural Development and Agriculture
- Agricultural and Food Sciences
- Land Use and Ecosystem Services
- Bioenergy crop production and management
- Energy, Environment, Agriculture Analysis
- Water Quality Monitoring Technologies
- Environmental and biological studies
- Soil erosion and sediment transport
- Advanced Computational Techniques and Applications
- Water Systems and Optimization
- Geotechnical and Geomechanical Engineering
- Logistics and Infrastructure Analysis
- Forest ecology and management
- Science and Education Research
- Smart Agriculture and AI
- Soil Management and Crop Yield
- Wheat and Barley Genetics and Pathology
- Spectroscopy and Chemometric Analyses
- Environmental Sustainability and Education
Universidade Estadual do Oeste do Paraná
2016-2024
Universidade Estadual do Paraná
2017-2022
Objective: To estimate the Permanent Preservation Areas (PPAs) necessary to comply with Forest Code, according Law No. 12,727 of October 17, 2012. Theoretical Framework: Review water resource and native vegetation conservation policies, emphasizing integration geospatial data for environmental compliance sustainability. Method: Delimitation watersheds was adopted using QGIS, utilizing ALOS radar images analysis through MSI Sentinel-2 on Google Earth Engine platform. The procedures included...
Accurate and timely regional estimates of agricultural production are key for decision makers. This study aims to understand how different machine learning techniques impact soybean yield estimation in extracting maximum information from remotely sensed MODIS enhanced vegetation index (EVI) that is constrained by phenology. Specifically, a methodology developed incorporating phenological aligned with EVI acquisition each pixel selecting the most significant predictors out 36 using feature...
Brazilian farming influences directly the worldwide economy. Thus, fast and reliable information on areas sown with main crops is essential for planning logistics public or private commodity market policies. Recent practices have embraced remote sensing to provide dynamics. Medium-to-low resolution free orbital images, such as those from Landsat 8 Sentinel 2, been used crop mapping; however, satellite image processing requires high computing power, especially when monitoring vast areas....
The strategic logistics of agricultural production and storage aggregates information related to storage. In this sense, time, location, distance from producer consumer markets are considered, emphasizing the importance grain logistics. Natural Neighbor multiquadric equation spatial interpolation methods used predict these variables value at non-sampled locations, for asymmetric categorical data, respectively. This study investigated prediction (tons) (soybean, first crop corn, second-crop...
RESUMO O Estado do Paraná caracteriza-se por uma grande variabilidade de épocas semeadura (DS) e, consequentemente, pelo desenvolvimento máximo vegetativo (DMDV), colheita (DC) e ciclo (CI) para a cultura da soja. objetivo deste trabalho foi estimar essas datas o período primavera-verão ano-safra 2011/2012, meio séries temporais imagens Índice Vegetação Realçado (do inglês Enhanced Vegetation Index - EVI) sensor Modis (Moderate Resolution Imaging Spectroradiometer). Gerou-se um perfil...
Knowledge of the agricultural calendar crops is essential to better estimate and forecast cultivation large-scale crops. The aim this study was sowing date (SD), maximum vegetative development (DMVD), harvest (HD) soybean corn in state Paraná, Brazil. Dates from 120 farms Enhanced Vegetation Index (EVI) Moderate Resolution Imaging Spectroradiometer (MODIS) 2011 2014 were used into a seasonal trend analysis obtain patterns. results indicate that majority sown during October DMVD occurs...
Due to the difficulty in discriminating soybean and corn mappings obtained by time series of satellite images, this study aimed apply data mining techniques separate corn. Pure pixels selection from Landsat-8 were extracted used build a standard spectro-temporal EVI profile for both crops. These profiles with Timesat software and, further incorporated Weka software. Five out eleven variables each crop found through decision tree, technique. five sufficient achieve separation crops an...
The knowledge of Sowing Dates (SD), Maximum Vegetative Development (MVDD), and Harvest (HD) crops is important for estimating forecasting large-scale productivity. Prior information on harvest date also useful in optimizing grain reception logistics improving business decision-making agro-industrial companies. This study aimed to develop a method predict the HD soybeans from MVDD, which was obtained crop maps state Paraná between 2011/2012 2013/2014 years. TIMESAT software used perform...
O estado do Parana ocupa uma posicao importante no cenario nacional na producao de soja, sendo responsavel por mais 18% da brasileira, produzindo que o quarto maior produtor mundial, a China. Para monitorar agricola, informacao area e fundamental neste processo. Diversas tecnicas metodos podem ser empregados, incluindo algoritmos Aprendizado Maquina ( Machine Learning) . Logo, este trabalho tem como objetivo comparar quatro aprendizado maquina para mapear soja partir imagens sensor Landsat-8...
The objective of this study was to evaluate the correlations between vegetation indices (VI), obtained by RGB camera on flights Remotely piloted aircraft System (RPA), with yield maps agricultural crops. Monitoring carried out during 4 harvest seasons: soybean 2018/19, maize (2019), 2019/20 and wheat (2020), in two areas a rural property located Toledo, Paraná. During harvests, periodic were performed using DJI-branded RPA Phantom 3 Advanced. For generation orthomosaic, Agisoft PhotoScan...
Abstract Information related to the climate, sowing time, harvest, and crop development is essential for defining appropriate strategies agricultural activities, which helps both producers responsible bodies. Paraná, second largest soybean producer in Brazil, has high climatic variability, greatly influences planting, harvesting, productivity periods. Therefore, objective of this study was regionalize state considering decennial metrics associated with climate variables enhanced vegetation...
Proximal sensors have been used to characterize the crop biophysical properties by reflectance values and/or using Vegetation Indices (IV). Our goal with this work is compare NDVI (Normalized Difference Index) spectra-temporal profiles obtained active (GreenSeeker 505 Handheld) and passive (FieldSpec4 model Standard-Res) proximal monitor soybeans beans. It was monitored agricultural fields Nidera 5909RG variety beans Imperador variety, located in municipality of Cascavel, Parana state,...
This study had two objectives - firstly, to analyze the total static and dynamic capacity of agricultural storage in Paraná State, Brazil secondly, verify if followed growth grain production. The was performed by mesoregion for 2013/2014 2014/2015 crop years. methodology used descriptive from an database Secretariat Agriculture Supply (SEAB), National Register System Storage Units (SICARM), interviews were also made with agroindustrial cooperatives official agencies. It identified that State...
Climate change can affect the development of soybean cultivation, impacting your productivity. Thus, agrometeorological information is essential in order to improve productivity strategies. The objective paper was analyze influence and occurrence seasonality following variables on productivity: mean air temperature [TMean] (ºC), accumulated rainfall value [Rain] (mm), global solar radiation [Sr] (MJ m-2 day-1), potential evapotranspiration [ETp] ten-day variations maximum vegetative date...