Founded in Lund, Sweden, in 2016, VULTUS is a venture-funded private enterprise with the mission of eliminating waste in farming through the use of remote sensing. VULTUS has substantial experience working in the area of land and crop monitoring for field management purposes. The company utilizes satellite constellations developed by the space agencies ESA and NASA and has developed its proprietary processing pipeline (also known as remote sensing pipeline) to provide globally available measurements of nitrogen uptake, vegetation health and moisture levels. Its primary commercial service is delivered through a software application that is leveraged by numerous farming platforms in Europe and Asia. Currently, its products have an outreach to 9 million hectares, providing support to thousands of farmers in improving their management efficiencies. Through this work, VULTUS has developed a deep understanding in the use of remote sensing for farming purposes, including its limitations and many strengths. Its core competencies involve programming, remote sensing and precision agriculture practices.

Main Role in WATERAGRI

Capitalising upon its internal competencies within remote sensing, geographic information system (GIS) and data compatibility, VULTUS will be responsible for most of the remote sensing development and integration, primarily in WP2. The outputs from the VULTUS remote sensing pipeline will provide easy-to-interpret outputs of crop-specific agronomic states, complementing the information given by the water and nutrient balance models in WP 3 and WP7. Furthermore, VULTUS will aid in the dissemination and exploitation of the WATERAGRI findings with existing sales channels and venture capital financing.

Vultus AB – Consortium partner

Key persons

Qiang Wang, PhD (male) holds a PhD in geoscience & remote sensing from the University of Twente (Netherlands). He has 10 years of professional experience in remote sensing in optical and radar fields. He has been involved in international projects such as The Netherlands Organization for Scientific Research as well as the Natural Science Foundation of China (NSFC). He has 10 publications including an article published in Remote Sensing of Environment. His field of interests include remote sensing for agriculture and hydrology as well as image analysis by machine learning techniques.

Varunika Jain, PhD (female) holds a PhD in Science with specialisation in Geomatics from Faculty of Science, Nirma University (India). She has 10 years of rich experience in research and operational projects in the field of microwave and optical remote sensing, field survey and open source platform with publications in national and international journals. She was a part of flagship project FASAL under the Ministry of Agriculture, India. She has coordinated the national level team for paddy acreage estimation using Synthetic Aperture Radar data and ancillary data under FASAL project. Her research interests are aligned to understanding the interactions of Electro-magnetic Radiation with vegetation (both agricultural crops and forests) especially under the microwave region of spectrum and contribution towards climate change studies.

Yuwei Zhao, MSc (male) holds an MSc in Embedded and Intelligent Systems from Halmstad University (Sweden). He has 6 years of professional experience in System Analysis, System Architecture, Data Modeling and Design Patterns. His expertise is also in Machine Learning Algorithms and Data Mining techniques. He worked in the QlikTech R&D department and was responsible for data modeling relevant to pattern recognition, behavioral analysis, time series analysis, predictive modeling, visualization and more. He spear-headed development of the Amazon Web Services (AWS) serverless architecture for our Alfa version Application Programing Interface (API) . Meanwhile, he is responsible for the development of the algorithms for remote sensing data processing and analysis. Moreover, he is also responsible for implementing machine learning algorithms and signal processing for several GIS missions.