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Remote Sensing Applications-Society and Environment

Remote Sensing Applications-Society and Environment
简称:REMOTE SENS APPL
ISSN:2352-9385
EISSN:2352-9385
研究方向:Multiple-
自引率:6.70%
五年影响因子:4.9
JCI期刊引文指标 :0.83
h-index:暂无h-index数据
Gold OA文章占比:24.04%

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Remote Sensing Applications-Society and Environment英文简介

Remote Sensing of Environment (RSE) serves the Earth observation community with the publication of results on the theory, science, applications, and technology of studies contributing to advance the science of remote sensing. Thoroughly interdisciplinary, RSE publishes on terrestrial, oceanic and atmospheric sensing. The emphasis of the journal is on biophysical and quantitative approaches to remote sensing at local to global scales and covers a wide range of applications and techniques:

Applications
? Land cover mapping, vegetation species identification and mapping

? Land surface energy and water balance

? Disturbance (fire, insect, harvest)

? Agriculture (crop mapping, yield prediction, phenology, soil properties, management practices)

? Forest and rangeland productivity and inventories

? Ecological applications & Ecosystem services (wetland, biodiversity, habitat, animal population, etc.)

? Urban applications (mapping, energy consumption, population, etc.)

? Terrestrial ecosystem productivity and carbon cycles

? Soil properties (moisture, organic matter, texture, structure, etc.)

? Geological Applications (minerals, landslide, subsidence, geomorphology, earth quake, etc.)

? Hydrology and water resources

? Inland and coastal waters

? Oceanography and marine science

? Cryosphere, mapping and modelling

? Atmospheric science and meteorology

? Snow, ice and glaciers


Techniques & Methods
? Feature extraction from RS images: segmentation and classification, surface structural, biochemical or physiological traits estimation from RS data

? Radiative transfer modelling

? Machine and deep learning for RS data analysis

? RS Data assimilation

? Satellite time series analysis & change detection

? Satellite data fusion (spectral, spatial and temporal)

? Satellite sensor systems characterization including radiometric and geometric calibration

? New remote sensing missions and systems

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自引率趋势图


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