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Hydrological processes in forested watersheds are influenced by environmental, physiological, and biometric factors such as precipitation, radiation, temperature, species type, leaf area, and extent and structure of forest ecosystems. Over the past two centuries, forest coverage and forest structures have been impacted globally by anthropogenic activities, for example, forest harvesting, and conversion of forested landscapes for plantations and urbanization. In addition, since the industrial revolution, climate change has resulted in profound impacts on forest ecosystems due to higher carbon dioxide (CO2) concentration or CO2 fertilization, warmer temperatures, changes in frequency and intensity of extreme weather events and natural disturbances. As a result, hydrological processes in forested watersheds have been altered by these natural and anthropogenic factors and these changes are expected to accelerate due to future changing climatic conditions.

East Asia --- climate variability --- metals --- woody litter --- extreme weather events --- frequency analysis --- relative contribution --- streamflow variability --- probability distribution --- trace metal --- climate change --- annual streamflow --- hydroclimatology --- forest disturbances --- river discharge --- climate warming --- Weihe River --- non-woody litter --- riparian forest --- low flow --- Central Asia --- canopy filtering --- flood --- SWAT --- Chu River --- annual water yield --- forest hydrology --- throughfall --- flow regimes --- Schrenk spruce (Picea schrenkiana Fisch. et Mey.) --- tree rings --- forest floor --- reforestation --- land-use change --- low flows --- watershed management --- high flow --- forest disturbance --- subalpine forest --- gap-edge canopy --- human activities --- boreal forest --- Tianshan Mountains --- closed canopy --- groundwater level --- fruit tree planting --- hydrological model --- high flows --- cumulative effects --- reconstruction --- headwater stream --- partial least squares (PLS) regression --- streamflow

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The topics of the book cover forest parameter estimation, methods to assess land cover and change, forest disturbances and degradation, and forest soil drought estimations. Airborne laser scanner data, aerial images, as well as data from passive and active sensors of different spatial, spectral and temporal resolutions have been utilized. Parametric and non-parametric methods including machine and deep learning methods have been employed. Uncertainty estimation is a key topic in each study. In total, 15 articles are included, of which one is a review article dealing with methods employed in remote sensing aided greenhouse gas inventories, and one is the Editorial summary presenting a short review of each article.

forest structure change --- EBLUP --- small area estimation --- multitemporal LiDAR and stand-level estimates --- forest cover --- Sentinel-1 --- Sentinel-2 --- data fusion --- machine-learning --- Germany --- South Africa --- temperate forest --- savanna --- classification --- Sentinel 2 --- land use land cover --- improved k-NN --- logistic regression --- random forest --- support vector machine --- statistical estimator --- IPCC good practice guidelines --- activity data --- emissions factor --- removals factor --- Picea crassifolia Kom --- compatible equation --- nonlinear seemingly unrelated regression --- error-in-variable modeling --- leave-one-out cross-validation --- digital surface model --- digital terrain model --- canopy height model --- constrained neighbor interpolation --- ordinary neighbor interpolation --- point cloud density --- stereo imagery --- remotely sensed LAI --- field measured LAI --- validation --- magnitude --- uncertainty --- temporal dynamics --- state space models --- forest disturbance mapping --- near real-time monitoring --- CUSUM --- NRT monitoring --- deforestation --- degradation --- tropical forest --- tropical peat --- forest type --- deep learning --- FCN8s --- CRFasRNN --- GF2 --- dual-FCN8s --- random forests --- error propagation --- bootstrapping --- Landsat --- LiDAR --- La Rioja --- forest area change --- data assessment --- uncertainty evaluation --- inconsistency --- forest monitoring --- drought --- time series satellite data --- Bowen ratio --- carbon flux --- boreal forest --- windstorm damage --- synthetic aperture radar --- C-band --- genetic algorithm --- multinomial logistic regression --- n/a

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Forest tree improvement has mainly been implemented to enhance the productivity of artificial forests. However, given the drastically changing global environment, improvement of various traits related to environmental adaptability is more essential than ever. This book focuses on genetic information, including trait heritability and the physiological mechanisms thereof, which facilitate tree improvement. Nineteen papers are included, reporting genetic approaches to improving various species, including conifers, broad-leaf trees, and bamboo. All of the papers in this book provide cutting-edge genetic information on tree genetics and suggest research directions for future tree improvement.

early selection --- stomatal characteristics --- water stress --- water relations --- specific leaf area --- Eucalyptus clones --- LTR-retrotransposon --- Ty3-gypsy --- Ty1-copia --- IRAP --- molecular markers --- bamboo --- Phyllostachys --- genetic diversity --- populations structure --- AMOVA --- central-marginal hypothesis --- cline --- Pinaceae --- trailing edge population --- Sakhalin fir --- sub-boreal forest --- gibberellin --- male strobilus induction --- transcriptome --- conifer --- Cryptomeria japonica --- linkage map --- male sterility --- marker-assisted selection --- C. fortunei --- differentially expressed genes --- phenylpropanoid metabolism --- candidate genes --- Camellia oleifera --- leaf senescence --- transcriptome analysis --- senescence-associated genes --- physiological characterization --- cpDNA --- next generation sequencing --- northern limit --- nucleotide diversity --- phylogeny --- In/Del --- SNP --- SSR --- Chinese fir --- heartwood --- secondary metabolites --- widely targeted metabolomics --- flavonoids --- amplicon sequencing --- AmpliSeq --- genomic selection --- Japanese cedar (Cryptomeria japonica) --- multiplexed SNP genotyping --- spatial autocorrelation error --- pine wood disease --- resistance to pine wood nematode --- inoculation test --- multisite --- cumulative temperature --- Pinus thunbergii --- Thujopsis dolabrata --- EST-SSR markers --- varieties --- population structure --- pine wilt disease --- Bursaphelenchus xylophilus --- genotype by environment interaction --- Japanese black pine --- variance component --- local adaptation --- silviculture --- seed zone --- tree improvement program --- breeding --- genotype × environment interaction --- mast seeding --- seed production --- thinning --- forest tree breeding --- high-throughput phenotyping --- epigenetics --- genotyping --- genomic prediction models --- quantitative trait locus --- breeding cycle --- Cryptomeria japonica var. sinensis --- demographic history --- RAD-seq --- ancient tree --- conservation --- infrared thermography --- chlorophyll fluorescence --- cumulative drought stress --- genetic conservation --- genetic management --- pine wood nematode --- pine wood nematode-Pinus thunbergii resistant trees --- n/a

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Quantitative land remote sensing has recently advanced dramatically, particularly in China. It has been largely driven by vast governmental investment, the availability of a huge amount of Chinese satellite data, geospatial information requirements for addressing pressing environmental issues and other societal benefits. Many individuals have also fostered and made great contributions to its development, and Prof. Xiaowen Li was one of these leading figures. This book is published in memory of Prof. Li. The papers collected in this book cover topics from surface reflectance simulation, inversion algorithm and estimation of variables, to applications in optical, thermal, Lidar and microwave remote sensing. The wide range of variables include directional reflectance, chlorophyll fluorescence, aerosol optical depth, incident solar radiation, albedo, surface temperature, upward longwave radiation, leaf area index, fractional vegetation cover, forest biomass, precipitation, evapotranspiration, freeze/thaw snow cover, vegetation productivity, phenology and biodiversity indicators. They clearly reflect the current level of research in this area. This book constitutes an excellent reference suitable for upper-level undergraduate students, graduate students and professionals in remote sensing.

gross primary production (GPP) --- interference filter --- Visible Infrared Imaging Radiometer Suite (VIIRS) --- cost-efficient --- precipitation --- topographic effects --- land surface temperature --- Land surface emissivity --- scale effects --- spatial-temporal variations --- statistics methods --- inter-annual variation --- spatial representativeness --- FY-3C/MERSI --- sunphotometer --- PROSPECT --- passive microwave --- flux measurements --- urban scale --- vegetation dust-retention --- multiple ecological factors --- leaf age --- standard error of the mean --- LUT method --- spectra --- SURFRAD --- Land surface temperature --- aboveground biomass --- uncertainty --- land surface variables --- copper --- Northeast China --- forest disturbance --- end of growing season (EOS) --- random forest model --- probability density function --- downward shortwave radiation --- machine learning --- MODIS products --- composite slope --- daily average value --- canopy reflectance --- spatiotemporal representative --- light use efficiency --- hybrid method --- disturbance index --- quantitative remote sensing inversion --- SCOPE --- GPP --- South China’s --- anisotropic reflectance --- vertical structure --- snow cover --- land cover change --- start of growing season (SOS) --- MS–PT algorithm --- aerosol --- pixel unmixing --- HiWATER --- algorithmic assessment --- surface radiation budget --- latitudinal pattern --- ICESat GLAS --- vegetation phenology --- SIF --- metric comparison --- Antarctica --- spatial heterogeneity --- comprehensive field experiment --- reflectance model --- sinusoidal method --- NDVI --- BRDF --- cloud fraction --- NPP --- VPM --- China --- dense forest --- vegetation remote sensing --- Cunninghamia --- high resolution --- geometric-optical model --- phenology --- LiDAR --- ZY-3 MUX --- point cloud --- multi-scale validation --- Fraunhofer Line Discrimination (FLD) --- rice --- fractional vegetation cover (FVC) --- interpolation --- high-resolution freeze/thaw --- drought --- Synthetic Aperture Radar (SAR) --- controlling factors --- sampling design --- downscaling --- n/a --- Chinese fir --- MRT-based model --- RADARSAT-2 --- northern China --- leaf area density --- potential evapotranspiration --- black-sky albedo (BSA) --- decision tree --- CMA --- fluorescence quantum efficiency in dark-adapted conditions (FQE) --- surface solar irradiance --- validation --- geographical detector model --- vertical vegetation stratification --- spatiotemporal distribution and variation --- gap fraction --- phenological parameters --- spatio-temporal --- albedometer --- variability --- GLASS --- gross primary productivity (GPP) --- EVI2 --- machine learning algorithms --- latent heat --- GLASS LAI time series --- boreal forest --- leaf --- maize --- heterogeneity --- temperature profiles --- crop-growing regions --- satellite observations --- rugged terrain --- species richness --- voxel --- LAI --- TMI data --- GF-1 WFV --- spectral --- HJ-1 CCD --- leaf area index --- evapotranspiration --- land-surface temperature products (LSTs) --- SPI --- AVHRR --- Tibetan Plateau --- snow-free albedo --- PROSPECT-5B+SAILH (PROSAIL) model --- MCD43A3 C6 --- 3D reconstruction --- photoelectric detector --- multi-data set --- BEPS --- aerosol retrieval --- plant functional type --- multisource data fusion --- remote sensing --- leaf spectral properties --- solo slope --- land surface albedo --- longwave upwelling radiation (LWUP) --- terrestrial LiDAR --- AMSR2 --- geometric optical radiative transfer (GORT) model --- MuSyQ-GPP algorithm --- tree canopy --- FY-3C/MWRI --- meteorological factors --- solar-induced chlorophyll fluorescence --- metric integration --- observations --- polar orbiting satellite --- arid/semiarid --- homogeneous and pure pixel filter --- thermal radiation directionality --- biodiversity --- gradient boosting regression tree --- forest canopy height --- Landsat --- subpixel information --- MODIS --- humidity profiles --- NIR --- geostationary satellite --- South China's --- MS-PT algorithm