University of Twente Student Theses


Within-Season Crop Type Mapping Based On The Time Series Of Sentinel-1, Sentinel-2, Weather, And Historical Cropland Data

Henriette, Ishimwe (2023) Within-Season Crop Type Mapping Based On The Time Series Of Sentinel-1, Sentinel-2, Weather, And Historical Cropland Data.

[img] PDF
Abstract:This study addresses the challenges of crop classification in remote sensing due to limited ground truth labels by utilizing historical ground information. By incorporating data from previous seasons or years, classification accuracy can be enhanced, reducing the need for costly ground truth data collection and enabling early and in-season mapping. The research focuses on within-season crop type mapping in the Flevoland province, Netherlands, using Sentinel-1 and Sentinel-2 data, historical cropland data, and weather information. The study aims to understand the impact of weather conditions, satellite sensor characteristics, and temporal shifts on crop dynamics and phenological metrics when training the model with historical cropland data. Analysis of phenological metrics from both Sentinel-1 (C-band Synthetic Aperture Radar) and Sentinel-2 (multispectral optical) data shows distinct patterns for different crop types. Sentinel-1 excels in detecting early vegetation growth due to its all-weather capability, while Sentinel-2 is hindered by cloud cover during cloudy periods. Weather parameters, such as temperature and precipitation, significantly influence inter-annual variations in phenology. Thermal time is introduced to align crop dynamics across different years, enhancing within-season crop type mapping accuracy, with June identified as the optimal temporal window. The study emphasizes the importance of combining optical and SAR data for comprehensive vegetation analysis. Crop rotation practices impact growth patterns and classification accuracy. This research has implications for agriculture stakeholders, enabling timely crop monitoring, contributing to food security, and promoting sustainable agricultural practices. Further research in this area promises to advance agricultural monitoring and management.
Item Type:Essay (Master)
Faculty:ITC: Faculty of Geo-information Science and Earth Observation
Subject:48 agricultural science
Programme:Geoinformation Science and Earth Observation MSc (75014)
Link to this item:
Export this item as:BibTeX
HTML Citation
Reference Manager


Repository Staff Only: item control page