Latin American GRSS and ISPRS Remote Sensing Conference
10 - 13 November 2025 • Iguazu Falls, Brazil
Conference Agenda
Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
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Daily Overview | |
| Location: Florestan Fernandes III |
| 10:30am - 12:30pm |
OP03: Production-Economy: Agriculture Location: Florestan Fernandes III Chair: Marcelo Scavuzzo Discriminative Spectral Regions for Detecting Huanglongbing in Citrus Plants through Statistical Analysis 10:50am - 11:10am Estimation of grassland nitrogen content using UAV ultra-wide RGB images 11:10am - 11:30am Analysis of spectral responses in soybean crops with different levels of phytonematode infestation at different phenological stages using MSI/Sentinel-2 sensor imagery 11:30am - 11:50am Potential of SAR-derived features for detecting structural variations in coffee plots 11:50am - 12:10pm Evaluating pollinator diversity in the Brazilian Atlantic Forest biome using geospatial and Machine Learning Tools 12:10pm - 12:30pm Convolutional Neural Network (CNN) Architecture for Detecting Fusarium wilt in Banana Crops Using UAV-Based Multispectral Imaging |
| 2:00pm - 3:40pm |
OP06: Environment-Ecology: Water & Hydrology Location: Florestan Fernandes III Chair: Marcos Benedito Schimalski Integration of satellite and field data for the detection of a harmful algal bloom in a reservoir 2:20pm - 2:40pm Deep learning reveals spatial patterns in water contamination over Ciénaga de la Virgen using Sentinel-2 imagery. 2:40pm - 3:00pm MAPAQUALI – Modular system for continuous monitoring of water quality by remote sensing 3:00pm - 3:20pm Turbidity estimation in Paraná River middle basin using remote sensing techniques 3:20pm - 3:40pm Multi and hyperspectral characterization of a RAMSAR water body based on an optical water type approach 3:40pm - 4:00pm A Novel Model for Cyanobacterial Chlorophyll-a Estimation: Fusing Satellite Remote Sensing and In Situ Data |

