Data Science in Agriculture and Natural Resource Management

Data Science: Principles and Concepts in Data Analysis and Modelling.- Data Science: Tools, Techniques and Potential Applications in Earth Observation Studies.- Data Science in Agriculture and Natural Resource Management: An Overview.- Applications of Reinforcement Learning and Recurrent Neural Network Based Deep Learning Frameworks in Agriculture.- Precision Farming Using Emerging Technologies.- An Architecture for Quality Centric Crop Production.- Integrating UAV and Field Sensor Data for Better Decision Making in Broadacre Cropping Systems.- Object Based Crop Classification for Precision Farming.- Disruptive Innovations in Precision Agriculture - Towards BD Analytics for Better GeoFarmatics.- A Paradigm-shift in Global Cropland Maps and Products for Food and Water Security in the Twenty-first Century: Petabyte Scale Satellite Big-data Analytics, Machine Learning, and Cloud Computing.- Big Data Analytics for Climate Resilient Supply Chains: Opportunities and Way Forward.- Mapping Croplands Using Machine Learning Algorithms and Spectral Matching Techniques.- Applications of Computer Vision in Precision Agriculture.- Innovative Geoportal Platforms for Sustainable Management of Natural Resources.