Sustainable Agriculture and Advances of Remote Sensing (Volume 1)

• Autore: Paraforos Dimitrios
• Pubblicazione: MDPI - Multidisciplinary Digital Publishing Institute, 2022
• Descrizione fisica: 1 online resource (324 p.)
• Soggetto topico: Geography; Research & information: general
• Soggetto non controllato: 1D convolution neural networks; 3D bale wrapping method; 3D Convolutional Neural Network; agricultural monitoring; agriculture; algorithms; anomaly intrusion detection; artificial neural network; autonomous robots; band selection; Bidirectional long-short term memory; Boufakrane River watershed; canopy conductance; CCA; chlorophyll a; chlorophyll-a concentration; climate change; clustering; CNN; coastal management; Coatzacoalcos; Comino; computer vision; convolutional neural networks; Copernicus Sentinels; crop classification; crop fields; crop mapping; crop yield improvement; crops; crops diseases; cubic SVM; cucumber; data analysis; data augmentation; data fusion; deep learning; deep transfer learning; density estimation; dissolved oxygen; drone; entropy; environmental monitoring; environmental protection; equal bale dimensions; evapotranspiration; Explainable Artificial Intelligence; Faster R-CNN; features fusion; food security; forest roads; geographic information system (GIS); GIS; Google Earth Engine; Gozo; green ring; green technologies; guava disease; histogram; hyperparameter optimization; hyperspectral; hyperspectral imagery; hyperspectral imaging; hyperspectral remoting sensing; IDS; image classification; internet of things; Internet of Things; internode-elongation; Interreg; invasive plants; IoT; IoT ecosystem; irrigation requirements; land use; land use classification; Land Use/Land Cover; Landsat; leaf disease; LISS-III; machine learning; machine learning algorithm; machine vision; Malta; mango leaf; mathematical model; metaheuristic; minimal film consumption; modeling; modeling approach; modified normalized difference water index (MNDWI); modular robot; multi-temporal data; multispectral; natural resources; NDVI; nitrate; nitrogen prediction; normalized difference vegetation index (NDVI); object-based classification; optimal bale dimensions; ordinary kriging; ordinary Kriging; overfitting; panicle initiation; path planning; penman-monteith equation; pest control; photogrammetry; plant disease detection; pocket beaches; precision agriculture; probe; proximal sensing; random forest; rational sampling numbers; remote sensing; resource constraint; RF; rice farming; rice plant; round bales; sampling; SAR; satellite image analysis; selective spraying; sensor; Sentinel 1 and 2; Sentinel-1a; Sentinel-2; Sicily; simulation; site-specific; site-specific weed management; smart agriculture; soil attribute; soil pH; soil tillage; spatial heterogeneity; spatial variation; sustainable agriculture; sustainable environment; sustainable land use; SVM; Synthetic Aperture Radar (SAR); systematic literature review; temperature profile; time series analysis; transfer learning; urban flood; vein pattern; virtual pests; Vision Transformer; vision-based crop and weed detection; water extraction; water quality; water resources; weed; YOLOv5; Ziz basin
• Persona (resp. second.): MuzirafutiAnselme; RandazzoGiovanni; LanzaStefania; ParaforosDimitrios
• Sommario/riassunto: 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 publishing the results, among others.
• Altri titoli varianti: Sustainable Agriculture and Advances of Remote Sensing
• Titolo autorizzato: Sustainable Agriculture and Advances of Remote Sensing (Volume 1)
• ISBN: 3-0365-5338-X
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910619464703321
• Lo trovi qui: Univ. Federico II