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Elsevier

Journals in Environmental monitoring and analysis

This collection emphasizes techniques and technologies for detecting, measuring, and analyzing environmental parameters. Supporting scientists, engineers, and regulators, it features advanced sensors, data analysis methods, and case studies. These resources enable effective environmental surveillance, pollution management, and policy implementation for a sustainable future.

  • Remote Sensing of Environment

    • ISSN: 0034-4257
    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:Applicati... cover mapping, vegetation species identification and mappingLand surface energy and water balanceDisturbance (fire, insect, harvest)Agriculture (crop mapping, yield prediction, phenology, soil properties, management practices)Forest and rangeland productivity and inventoriesEcologica... applications & Ecosystem services (wetland, biodiversity, habitat, animal population, etc.)Urban applications (mapping, energy consumption, population, etc.)Terrestrial ecosystem productivity and carbon cyclesSoil properties (moisture, organic matter, texture, structure, etc.)Geological Applications (minerals, landslide, subsidence, geomorphology, earth quake, etc.)Hydrology and water resourcesInland and coastal watersOceanography and marine scienceCryosphere, mapping and modellingAtmospheric science and meteorologySnow, ice and glaciersTechniques & MethodsFeature extraction from RS images: segmentation and classification, surface structural, biochemical or physiological traits estimation from RS dataRadiative transfer modellingMachine and deep learning for RS data analysisRS Data assimilationSatellit... time series analysis & change detectionSatellite data fusion (spectral, spatial and temporal)Satellite sensor systems characterization including radiometric and geometric calibrationNew remote sensing missions and systemsThe journal Remote Sensing of Environment invites proposals for Special Issues. For more details on the SI proposal process and how to submit a SI, please refer to the relevant section - Journal Specific Information - of the Guide for Authors.
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  • Spatial Statistics

    • ISSN: 2211-6753
    Spatial Statistics publishes articles on the theory and application of spatial and spatio-temporal statistics. It favours manuscripts that present theory generated by new applications, or in which new theory is applied to an important practical case. A purely theoretical study will only rarely be accepted. Pure case studies and algorithms without methodological development are not acceptable for publication.Spatial Statistics concerns the quantitative analysis of spatial and spatio-temporal data, including their statistical dependencies, heterogeneity, accuracy and uncertainties. Methodology for spatial statistics is typically found in probability theory, stochastic modelling and mathematical statistics as well as in information and computer science. Spatial statistics is used in mapping, assessing spatial data quality, sampling design optimisation, modelling of spatial structures, and drawing of valid inference and causality from a limited set of spatio-temporal data. Application fields include:• The physical domains, e.g. environment, climate, agriculture, ecology, geosciences oceanography and remote sensing. • The social/economic domains, e.g. epidemiology, population characteristics, and disease mapping.Spatial Statistics encourages the submission of short communications and case studies in spatial statistics (i.e. manuscripts up to 3000 words presenting novel spatial statistical applications).Spatia... Statistics aims to publish reproducible science. Authors are encouraged to submit and publish data, procedures, models and methods that support your research publication. It provides facilities to interlink those with your published articles.Spatial Statistics has an open attitude towards the latest developments in data science, deep learning and geoAI, as long as a substantial statistical component is present.
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  • Computers, Environment and Urban Systems

    • ISSN: 0198-9715
    Computers, Environment and Urban Systems is an interdisciplinary journal publishing cutting-edge and innovative computer-based research on urban systems, systems of cities, and built and natural environments , that privileges the geospatial perspective. The journal provides a stimulating presentation of perspectives, research developments, overviews of important new technologies and uses of major computational, information-based, and visualization innovations. Applied and theoretical contributions demonstrate the scope of computer-based analysis fostering a better understanding of urban systems, the synergistic relationships between built and natural environments, their spatial scope and their dynamics.Application areas include infrastructure and facilities management, physical planning and urban design, land use and transportation, business and service planning, coupled human and natural systems, urban planning, socio-economic development, emergency response and hazards, and land and resource management. Examples of methodological approaches include decision support systems, geocomputation, spatial statistical analysis, complex systems and artificial intelligence, visual analytics and geovisualization, ubiquitous computing, and space-time simulation.Contribut... emphasizing the development and enhancement of computer-based technologies for the analysis and modeling, policy formulation, planning, and management of environmental and urban systems that enhance sustainable futures are especially sought. The journal also encourages research on the modalities through which information and other computer-based technologies mold environmental and urban systems.Audience: Urban and regional planners and policy analysts, environmental planners, economic geographers, geospatial information scientists and technologists, regional scientists and policy makers, architectural designers.
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