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008			211011s2022 si | s |||| 0|eng d
020			_a9789811658471
024	7		_a10.1007/978-981-16-5847-1 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aS494.5.D3 _b2022 EB
245	0	0	_aData Science in Agriculture and Natural Resource Management _cedited by G. P. Obi Reddy, Mehul S. Raval, J. Adinarayana, Sanjay Chaudhary
250			_a1st edition 2022
264		1	_aSingapore _bSpringer International Publishing _c2022
300			_a1 recurso en línea (XVIII, 316 páginas) _b106 ilustraciones, 93 ilustraciones a color
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aStudies in Big Data _x2197-6511 _v96
505	0		_aData 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			_aThis 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.
988			_aSpringer_Robotics_2022
650		7	_9665994 _aAgricultura _xProceso de datos
776	0	8	_iPrinted edition: _z9789811658464
776	0	8	_iPrinted edition: _z9789811658488
776	0	8	_iPrinted edition: _z9789811658495
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-16-5847-1 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b03/2023 _dz _eu _zSI