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Data science in agriculture and natural resource management

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Data science in agriculture and natural resource managementedited by G. P. Obi Reddy ... [et al.].
其他作者:	Reddy, G. P. Obi.
出版者:	Singapore :Springer Singapore :2022.
面頁冊數:	xviii, 316 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	AgricultureData processing.
電子資源:	https://doi.org/10.1007/978-981-16-5847-1
ISBN:	9789811658471$q(electronic bk.)

Data science in agriculture and natural resource management
Data science in agriculture and natural resource management[electronic resource] /edited by G. P. Obi Reddy ... [et al.]. - Singapore :Springer Singapore :2022. - xviii, 316 p. :ill., digital ;24 cm. - Studies in big data,v. 962197-6511 ;. - Studies in big data ;v.1..

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.

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 experts sharing their experiences very lucidly through case studies, suitable illustrations and tables. The contents have been designed to fulfil the needs of geospatial, data science, agricultural, natural resources and environmental sciences of traditional universities, agricultural universities, technological universities, research institutes and academic colleges worldwide. It will help the planners, policymakers and extension scientists in planning and sustainable management of agriculture and natural resources. The authors believe that with its uniqueness the book is one of the important efforts in the contemporary cyber-physical systems.

ISBN: 9789811658471$q(electronic bk.)

Standard No.: 10.1007/978-981-16-5847-1doiSubjects--Topical Terms:

376865
Agriculture
--Data processing.

LC Class. No.: S494.5.D3 / D37 2022

Dewey Class. No.: 630.2085

Data science in agriculture and natural resource management
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505 0 $a 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.
520 $a 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 experts sharing their experiences very lucidly through case studies, suitable illustrations and tables. The contents have been designed to fulfil the needs of geospatial, data science, agricultural, natural resources and environmental sciences of traditional universities, agricultural universities, technological universities, research institutes and academic colleges worldwide. It will help the planners, policymakers and extension scientists in planning and sustainable management of agriculture and natural resources. The authors believe that with its uniqueness the book is one of the important efforts in the contemporary cyber-physical systems.
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