Sustainable Agriculture and Advances of Remote Sensing (Volume 2)

Agriculture, as the main source of alimentation and the most important economic activity globally, is being affected by the impacts of climate change. To maintain and increase our global food system production, to reduce biodiversity loss and preserve our natural ecosystem, new practices and technol...

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Bibliographic Details
Format: eBook
Language:English
Published: MDPI - Multidisciplinary Digital Publishing Institute 2022
Subjects:
CCA
CNN
GIS
IDS
IoT
RF
SAR
SVM
Online Access:Open Access: DOAB: description of the publication
Open Access: DOAB, download the publication
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720 1 |a Lanza, Stefania  |4 edt 
720 1 |a Lanza, Stefania  |4 oth 
720 1 |a Muzirafuti, Anselme  |4 edt 
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245 0 0 |a Sustainable Agriculture and Advances of Remote Sensing (Volume 2) 
260 |b MDPI - Multidisciplinary Digital Publishing Institute  |c 2022 
300 |a 1 online resource (322 p.) 
336 |a text  |b txt  |2 rdacontent 
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520 |a Agriculture, as the main source of alimentation and the most important economic activity globally, is being affected by the impacts of climate change. To maintain and increase our global food system production, to reduce biodiversity loss and preserve our natural ecosystem, new practices and technologies are required. This book focuses on the latest advances in remote sensing technology and agricultural engineering leading to the sustainable agriculture practices. Earth observation data, in situ and proxy-remote sensing data are the main source of information for monitoring and analyzing agriculture activities. Particular attention is given to earth observation satellites and the Internet of Things for data collection, to multispectral and hyperspectral data analysis using machine learning and deep learning, to WebGIS and the Internet of Things for sharing and publication of the results, among others. 
540 |a Creative Commons  |f https://creativecommons.org/licenses/by/4.0/  |2 cc  |u https://creativecommons.org/licenses/by/4.0/ 
546 |a English 
650 7 |a Geography  |2 bicssc 
650 7 |a Research & information: general  |2 bicssc 
653 |a 1D convolution neural networks 
653 |a 3D bale wrapping method 
653 |a 3D Convolutional Neural Network 
653 |a agricultural monitoring 
653 |a agriculture 
653 |a algorithms 
653 |a anomaly intrusion detection 
653 |a artificial neural network 
653 |a autonomous robots 
653 |a band selection 
653 |a Bidirectional long-short term memory 
653 |a Boufakrane River watershed 
653 |a canopy conductance 
653 |a CCA 
653 |a chlorophyll a 
653 |a chlorophyll-a concentration 
653 |a climate change 
653 |a clustering 
653 |a CNN 
653 |a coastal management 
653 |a Coatzacoalcos 
653 |a Comino 
653 |a computer vision 
653 |a convolutional neural networks 
653 |a Copernicus Sentinels 
653 |a crop classification 
653 |a crop fields 
653 |a crop mapping 
653 |a crop yield improvement 
653 |a crops 
653 |a crops diseases 
653 |a cubic SVM 
653 |a cucumber 
653 |a data analysis 
653 |a data augmentation 
653 |a data fusion 
653 |a deep learning 
653 |a deep transfer learning 
653 |a density estimation 
653 |a dissolved oxygen 
653 |a drone 
653 |a entropy 
653 |a environmental monitoring 
653 |a environmental protection 
653 |a equal bale dimensions 
653 |a evapotranspiration 
653 |a Explainable Artificial Intelligence 
653 |a Faster R-CNN 
653 |a features fusion 
653 |a food security 
653 |a forest roads 
653 |a geographic information system (GIS) 
653 |a GIS 
653 |a Google Earth Engine 
653 |a Gozo 
653 |a green ring 
653 |a green technologies 
653 |a guava disease 
653 |a histogram 
653 |a hyperparameter optimization 
653 |a hyperspectral 
653 |a hyperspectral imagery 
653 |a hyperspectral imaging 
653 |a hyperspectral remoting sensing 
653 |a IDS 
653 |a image classification 
653 |a internet of things 
653 |a Internet of Things 
653 |a internode-elongation 
653 |a Interreg 
653 |a invasive plants 
653 |a IoT 
653 |a IoT ecosystem 
653 |a irrigation requirements 
653 |a land use 
653 |a land use classification 
653 |a Land Use/Land Cover 
653 |a Landsat 
653 |a leaf disease 
653 |a LISS-III 
653 |a machine learning 
653 |a machine learning algorithm 
653 |a machine vision 
653 |a Malta 
653 |a mango leaf 
653 |a mathematical model 
653 |a metaheuristic 
653 |a minimal film consumption 
653 |a modeling 
653 |a modeling approach 
653 |a modified normalized difference water index (MNDWI) 
653 |a modular robot 
653 |a multi-temporal data 
653 |a multispectral 
653 |a natural resources 
653 |a NDVI 
653 |a nitrate 
653 |a nitrogen prediction 
653 |a normalized difference vegetation index (NDVI) 
653 |a object-based classification 
653 |a optimal bale dimensions 
653 |a ordinary kriging 
653 |a ordinary Kriging 
653 |a overfitting 
653 |a panicle initiation 
653 |a path planning 
653 |a penman-monteith equation 
653 |a pest control 
653 |a photogrammetry 
653 |a plant disease detection 
653 |a pocket beaches 
653 |a precision agriculture 
653 |a probe 
653 |a proximal sensing 
653 |a random forest 
653 |a rational sampling numbers 
653 |a remote sensing 
653 |a resource constraint 
653 |a RF 
653 |a rice farming 
653 |a rice plant 
653 |a round bales 
653 |a sampling 
653 |a SAR 
653 |a satellite image analysis 
653 |a selective spraying 
653 |a sensor 
653 |a Sentinel 1 and 2 
653 |a Sentinel-1a 
653 |a Sentinel-2 
653 |a Sicily 
653 |a simulation 
653 |a site-specific 
653 |a site-specific weed management 
653 |a smart agriculture 
653 |a soil attribute 
653 |a soil pH 
653 |a soil tillage 
653 |a spatial heterogeneity 
653 |a spatial variation 
653 |a sustainable agriculture 
653 |a sustainable environment 
653 |a sustainable land use 
653 |a SVM 
653 |a Synthetic Aperture Radar (SAR) 
653 |a systematic literature review 
653 |a temperature profile 
653 |a time series analysis 
653 |a transfer learning 
653 |a urban flood 
653 |a vein pattern 
653 |a virtual pests 
653 |a Vision Transformer 
653 |a vision-based crop and weed detection 
653 |a water extraction 
653 |a water quality 
653 |a water resources 
653 |a weed 
653 |a YOLOv5 
653 |a Ziz basin 
793 0 |a DOAB Library. 
856 4 0 |u https://directory.doabooks.org/handle/20.500.12854/93234  |7 0  |z Open Access: DOAB: description of the publication 
856 4 0 |u https://mdpi.com/books/pdfview/book/6132  |7 0  |z Open Access: DOAB, download the publication