Data Science in Agriculture and Natural Resource Management /
This book aims to address emerging challenges in the field of agriculture and natural resource management using the principles and applications of data science (DS). The book is organized in three sections, and it has fourteen chapters dealing with specialized areas. The chapters are written by expe...
| Corporate Author: | |
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| Other Authors: | , , , |
| Format: | eBook |
| Language: | English |
| Published: |
Singapore :
Springer Singapore : Imprint: Springer,
2022.
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| Edition: | 1st ed. 2022. |
| Series: | Studies in Big Data,
96 |
| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
Table of Contents:
- 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.