Deep Learning Application for Image Detection with Aerial and Satellite Imagery for the Department of Agriculture, Environment and Rural Affairs of United Kingdom
Tuesday, May 12, 2020
The use of satellite imagery becomes more popular and important in analysis for various fields of the economy and business especially in agriculture. This talk will present intelligent system that automates process of counting grazing cattle and sheep for the Department of Agriculture, Environment and Rural Affairs (DAERA) of the United Kingdom. DAERA’s data of animal locations and movements are currently based on herd keepers’ addresses, complemented by on-site surveys. In order to reduce the need for physical inspections and manual livestock counting to validate subsidy claims and improve the assessment and management of disease outbreaks, enabling authorities to target their actions we’ve proposed solution based on aerial/satellite imagery and Convolutional Neural Networks. This talk will highlight orthophotomap and satellite imagery data preparation process, geospatial data processing, object detection and semantic segmentation modelling for counting cattle and sheep.