Remote Sensing of Environment

Remote Sensing of Environment
Title	Remote Sensing of Environment
Discipline	Earth science; NASA; European Space Agency; United States Geological Survey
Abbreviation	RSE
Publisher	Elsevier
Country	Netherlands
Frequency	Semimonthly
History	Established 1969
Impact	High

Remote Sensing of Environment Remote Sensing of Environment is a multidisciplinary field linking observational Landsat missions, Sentinel satellites, and airborne platforms to analyses used by UNEP, WMO, FAO, NASA, and ESA. Research connects legacy datasets from NOAA and USGS with modern missions such as Terra, Aqua, Envisat, IKONOS, WorldView-3, and MODIS, informing policy at institutions like IPCC and CBD. The discipline draws on methods developed at centers including Jet Propulsion Laboratory, Goddard Space Flight Center, EUMETSAT, and universities such as Stanford University, Massachusetts Institute of Technology, University of Cambridge, and University of California, Berkeley.

Overview and Scope

Remote sensing integrates observations from Landsat 8, Sentinel-2, Copernicus Programme, SPOT, RADARSAT, and TerraSAR-X to monitor phenomena studied by IUCN, World Bank, UNFCCC, and CITES. Applications intersect with projects at NOAA, US Forest Service, NCEI, and research programs such as Global Forest Watch, GEO, and Global Land Cover Facility. The scope covers land surface, cryosphere, ocean color, and atmospheric composition, informing assessments by IPCC, GBIF, IMO, and disaster responses coordinated by UNDRR.

Principles and Techniques

Fundamental principles derive from radiometry and spectroscopy pioneered alongside instruments on NOAA-20, Aqua, and Terra, with algorithms influenced by work at Jet Propulsion Laboratory, GSFC, and ESTEC. Techniques include optical multispectral analysis used in Landsat research, thermal infrared approaches developed for ASTER, microwave and SAR methods from RADARSAT and Sentinel-1, and LiDAR profiling advanced by ICESat and GEDI. Key scientific contributions trace to researchers affiliated with Columbia University, University of Oxford, Peking University, ETH Zurich, and institutes like CSIRO and CONAE. Methodological frameworks align with standards from ISO, CEOS, and best practices promoted by GEO.

Sensors and Platforms

Sensors span passive imagers on Landsat 9, Sentinel-2, and MODIS to active systems on Sentinel-1, RADARSAT-2, TerraSAR-X, and airborne LiDAR operated by USGS, NOAA, British Antarctic Survey, and Scripps Institution of Oceanography. Platforms include low Earth orbit constellations like Planet Labs and Spire Global, geostationary assets such as GOES-R series, and high-altitude UAVs used by research teams at University of Oxford and Massachusetts Institute of Technology. The ecosystem also involves commercial players such as Maxar Technologies, Airbus Defence and Space, BlackSky Global, and governmental programs like ISRO, CNSA, and JAXA.

Data Processing and Analysis

Processing workflows leverage software and infrastructures developed by Google Earth Engine, ESA Climate Office, USGS EarthExplorer, NASA Earthdata, and research groups at Carnegie Mellon University, University of Texas at Austin, University of Washington, and University of California, Los Angeles. Analytical methods include machine learning models inspired by work at Google Research, DeepMind, Microsoft Research, and universities like Stanford University and Massachusetts Institute of Technology. Time series and change detection approaches reference datasets from Landsat, Sentinel, MODIS, VIIRS, and assimilation frameworks used by ECMWF and NCEP. Open data initiatives from USGS, ESA, NASA, and Copernicus Programme enable reproducible pipelines used in collaborations with WMO, UNEP, and World Resources Institute.

Applications and Case Studies

Applications include land cover mapping for Amazon rainforest conservation coordinated with WWF and Conservation International, agricultural monitoring for FAO and USAID programs, wildfire mapping informing Cal Fire and California Department of Forestry and Fire Protection, ice-sheet studies supporting British Antarctic Survey and NSIDC, and coastal change analyses relevant to IMO and UNESCO. Urban expansion studies engage municipal programs in New York City, Shanghai, London, Mumbai, and São Paulo and connect to smart-city initiatives by World Bank and European Investment Bank. Public health applications link to WHO and epidemiological studies at CDC.

Limitations, Challenges, and Ethics

Challenges include data gaps highlighted during missions like Envisat failures, radiometric calibration issues experienced with Landsat 7 scan-line corrector anomalies, and legal frameworks governed by institutions such as ITU and national agencies like FAA and EASA. Ethical considerations involve data privacy debates exemplified by cases in San Francisco, regulatory scrutiny similar to discussions around Google Street View, and equity issues raised by collaborations with Indigenous and Tribal Peoples and organizations like UN Permanent Forum on Indigenous Issues. Technical limitations intersect with policy arenas including UNFCCC reporting, capacity building by UNDP, and funding priorities set by NSF and multinational development banks.

Category:Remote sensing