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Basic Sciences. Statistics --- Geology --- Kriging. --- Applied Statistics. --- Statistical methods.

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Dear Colleagues, The composition, structure and function of forest ecosystems are the key features characterizing their ecological properties, and can thus be crucially shaped and changed by various biotic and abiotic factors on multiple spatial scales. The magnitude and extent of these changes in recent decades calls for enhanced mitigation and adaption measures. Remote sensing data and methods are the main complementary sources of up-to-date synoptic and objective information of forest ecology. Due to the inherent 3D nature of forest ecosystems, the analysis of 3D sources of remote sensing data is considered to be most appropriate for recreating the forest’s compositional, structural and functional dynamics. In this Special Issue of Forests, we published a set of state-of-the-art scientific works including experimental studies, methodological developments and model validations, all dealing with the general topic of 3D remote sensing-assisted applications in forest ecology. We showed applications in forest ecology from a broad collection of method and sensor combinations, including fusion schemes. All in all, the studies and their focuses are as broad as a forest’s ecology or the field of remote sensing and, thus, reflect the very diverse usages and directions toward which future research and practice will be directed.

normalized difference vegetation index (NDVI) --- SRTMGL1 --- SPOT-6 --- urban ecology --- terrestrial laser scanner --- Lantana camara --- terrestrial laser scanning --- harvester --- product recovery --- imputation --- optimization --- multi-spectral --- function --- ZiYuan-3 stereo images --- spatial noise --- 3D remote sensing --- tree measurement --- diameter at breast height (DBH) --- DSM --- metabolic scale theory --- municipal forestry --- digital photogrammetry --- Norway spruce --- missing observations --- interrater agreement --- measurement error --- stump height --- Fractional cover analysis --- google earth engine --- high-voltage power transmission lines --- habitat fragmentation --- codispersion coefficient --- forest fire --- tree height --- nu SVR --- RapidEye --- uneven-aged mountainous --- random Hough transform --- kriging --- street trees --- ground validation --- Google Street View --- laser --- species identification --- composition --- maximum forest heights --- mountainous areas --- landscape fragmentation --- Landsat 8 --- forest canopy height --- allometric scaling and resource limitation model --- urban forestry --- point cloud --- GSV --- stump diameter --- structure --- 3D --- codispersion map --- forest ecology --- polarimetery --- crowdsourced data

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The Special Issue Modeling and Simulation in Engineering, belonging to the section Engineering Mathematics of the Journal Mathematics, publishes original research papers dealing with advanced simulation and modeling techniques. The present book, “Modeling and Simulation in Engineering I, 2022”, contains 14 papers accepted after peer review by recognized specialists in the field. The papers address different topics occurring in engineering, such as ferrofluid transport in magnetic fields, non-fractal signal analysis, fractional derivatives, applications of swarm algorithms and evolutionary algorithms (genetic algorithms), inverse methods for inverse problems, numerical analysis of heat and mass transfer, numerical solutions for fractional differential equations, Kriging modelling, theory of the modelling methodology, and artificial neural networks for fault diagnosis in electric circuits. It is hoped that the papers selected for this issue will attract a significant audience in the scientific community and will further stimulate research involving modelling and simulation in mathematical physics and in engineering.

Research & information: general --- Mathematics & science --- category theory --- mathematical modelling --- abstraction --- formal approaches --- functors --- surrogate model --- Kriging --- high-dimensional problems --- principal component dimension reduction --- trochoidal milling --- variable feed --- spiral groove --- CAM --- Levy walks --- anomalous diffusion --- fractional material derivative --- combustion process --- local estimate --- Monte Carlo method --- modeling --- analog circuits --- fault diagnosis --- neural networks --- carbon nanotubes --- heat transfer --- nanofluid --- rotating --- stretching/shrinking --- adjoint --- gradient-descent --- junctions --- transport equation --- unsteady flow --- rotation --- hybrid nanofluid --- stretching sheet --- radiation --- inverse modeling --- calcium leaching --- grout curtain --- hydraulic conductivity --- optimization --- fuzzy model --- response surface methodology --- diesel engine performance --- biodiesel --- anomalous diffusion equation --- continuous time random walk --- roughness scaling extraction --- fractal dimension --- accelerated algorithm --- Weierstrass–Mandelbrot function --- milling vibration signal --- spot volatility --- change of frequency --- roughness of volatility --- hurst exponent --- Chinese A-share market --- ferrofluidslip effect --- Stefan blowing --- thermodiffusion --- n/a --- Weierstrass-Mandelbrot function

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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.

Research & information: general --- Geography --- geographic information system (GIS) --- pocket beaches --- coastal management --- Interreg --- climate change --- remote sensing --- drone --- Sicily --- Malta --- Gozo --- Comino --- systematic literature review --- anomaly intrusion detection --- deep learning --- IoT --- resource constraint --- IDS --- evapotranspiration --- penman-monteith equation --- artificial neural network --- canopy conductance --- Ziz basin --- water quality --- satellite image analysis --- modeling approach --- nitrate --- dissolved oxygen --- chlorophyll a --- time series analysis --- environmental monitoring --- water extraction --- modified normalized difference water index (MNDWI) --- machine learning algorithm --- hyperspectral --- proximal sensing --- panicle initiation --- normalized difference vegetation index (NDVI) --- green ring --- internode-elongation --- Sentinel 1 and 2 --- Copernicus Sentinels --- crop classification --- food security --- agricultural monitoring --- data analysis --- SAR --- random forest --- 3D bale wrapping method --- equal bale dimensions --- mathematical model --- minimal film consumption --- optimal bale dimensions --- round bales --- Sentinel-2 --- SVM --- RF --- Boufakrane River watershed --- irrigation requirements --- water resources --- sustainable land use --- agriculture --- invasive plants --- precision agriculture --- rice farming --- site-specific weed management --- nitrogen prediction --- 1D convolution neural networks --- cucumber --- crop yield improvement --- mango leaf --- CCA --- vein pattern --- leaf disease --- cubic SVM --- chlorophyll-a concentration --- transfer learning --- overfitting --- data augmentation --- guava disease --- plant disease detection --- crops diseases --- entropy --- features fusion --- machine learning --- object-based classification --- density estimation --- histogram --- land use --- crop fields --- soil tillage --- data fusion --- multispectral --- sensor --- probe --- temperature profile --- forest roads --- simulation --- autonomous robots --- smart agriculture --- environmental protection --- photogrammetry --- path planning --- internet of things --- modeling --- convolutional neural networks --- machine vision --- computer vision --- modular robot --- selective spraying --- vision-based crop and weed detection --- Faster R-CNN --- YOLOv5 --- band selection --- CNN --- NDVI --- hyperspectral imaging --- crops --- urban flood --- Sentinel-1a --- Synthetic Aperture Radar (SAR) --- 3D Convolutional Neural Network --- multi-temporal data --- land use classification --- GIS --- Coatzacoalcos --- algorithms --- clustering --- pest control --- site-specific --- virtual pests --- rice plant --- weed --- hyperspectral imagery --- sustainable agriculture --- green technologies --- Internet of Things --- natural resources --- sustainable environment --- IoT ecosystem --- hyperspectral remoting sensing --- crop mapping --- image classification --- deep transfer learning --- hyperparameter optimization --- metaheuristic --- soil attribute --- ordinary Kriging --- rational sampling numbers --- spatial heterogeneity --- sampling --- soil pH --- spatial variation --- ordinary kriging --- Land Use/Land Cover --- LISS-III --- Landsat --- Vision Transformer --- Bidirectional long-short term memory --- Google Earth Engine --- Explainable Artificial Intelligence

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Precipitation is a well-recognized pillar in global water and energy balances. An accurate and timely understanding of its characteristics at the global, regional, and local scales is indispensable for a clearer understanding of the mechanisms underlying the Earth’s atmosphere–ocean complex system. Precipitation is one of the elements that is documented to be greatly affected by climate change. In its various forms, precipitation comprises a primary source of freshwater, which is vital for the sustainability of almost all human activities. Its socio-economic significance is fundamental in managing this natural resource effectively, in applications ranging from irrigation to industrial and household usage. Remote sensing of precipitation is pursued through a broad spectrum of continuously enriched and upgraded instrumentation, embracing sensors which can be ground-based (e.g., weather radars), satellite-borne (e.g., passive or active space-borne sensors), underwater (e.g., hydrophones), aerial, or ship-borne.

satellite radiance --- WRF-Hydro --- meteorological radar --- QPE --- microstructure of rain --- TMPA --- evaluation --- precipitation --- volume matching --- CFSR --- GMI --- terminal velocity --- TRMM-TMPA --- surface rain intensity --- retrieval algorithm --- rain gauges --- tropical cyclone --- CMORPH --- T-Matrix --- Global Precipitation Measurement (GPM) --- statistical evaluation --- vertical air velocity --- heavy rainfall prediction --- GPM IMERG v5 --- Tianshan Mountains --- Red River Basin --- precipitation retrieval --- satellite precipitation --- PERSIANN-CCS --- validation network --- PEMW --- satellite rainfall estimate --- high latitude --- Cyprus --- GPM --- wet deposition --- CloudSat --- thundercloud --- GPS --- satellite remote sensing --- assessment --- numerical weather prediction --- mineral dust --- complex terrain --- mesoscale precipitation patterns --- GNSS meteorology --- lumped models --- satellites --- Southern China --- error analysis --- topography --- cloud scavenging --- radar reflectivity–rain rate relationship --- CHAOS --- RADOLAN --- hydrometeor classification --- TRMM --- thunderstorm --- CHIRPS --- satellite precipitation retrieval --- GPM/IMERG --- GSMaP --- bias correction --- Precise Point Positioning --- Mainland China --- supercooled droplets detection --- SEID --- Saharan dust transportation --- Huaihe River basin --- GPM Microwave Imager --- satellite --- TMPA 3B42RT --- forecast model --- quality indexes --- SEVIRI --- radiometer --- triple collocation --- satellite precipitation product --- Mandra --- synoptic weather types --- drop size distribution (DSD) --- Amazon Basin --- weather radar --- X-band radar --- downscaling --- precipitation rate --- neural networks --- rain rate --- CMIP --- GPM-era IMERG --- GR models --- weather --- typhoon --- satellite rainfall retrievals --- TRMM 3B42 v7 --- validation --- low-cost receivers --- rainfall retrieval techniques --- snowfall detection --- GPM satellite --- Zenith Tropospheric Delay --- 3B42 --- hurricane Harvey --- PERSIANN_CDR --- TRMM 3B42 V7 --- snow water path retrieval --- DPR --- satellite precipitation adjustment --- Peninsular Spain --- RMAPS --- daily rainfall estimations --- streamflow simulation --- regional climate models --- Red–Thai Binh River Basin --- Ensemble Precipitation (EP) algorithm --- cloud radar --- disdrometer --- TRMM-era TMPA --- hydrometeorology --- MSG --- radar data assimilation --- dust washout process --- runoff simulations --- geostationary microwave sensors --- radar --- topographical and seasonal evaluation --- goGPS --- XPOL radar --- TMPA 3B42V7 --- telemetric rain gauge --- harmonie model --- tropical storm rainfall --- linear-scaling approach --- Milešovka observatory --- precipitable water vapor --- heavy precipitation --- hydrological simulation --- reflectivity --- Ka-band --- Tibetan Plateau --- satellite rainfall estimates --- regional rainfall regimes --- Lai Nullah --- microwave scattering --- remote sensing --- pre-processing --- rainfall rate --- MSWEP --- climatology --- VIC model --- CMORPH_CRT --- IMERG --- single frequency GNSS --- PERSIANN --- flood-inducing storm --- climate models --- Pakistan --- precipitating hydrometeor --- data assimilation --- rainfall --- kriging with external drift --- dual-polarization --- quantitative precipitation estimates --- flash flood --- Satellite Precipitation Estimates --- gridded radar precipitation --- regional rainfall sub-regimes --- polar systems