Remote Sensing in Applications of Geoinformation

Edited by
January 2022
174 pages
  • ISBN978-3-0365-2325-5 (Hardback)
  • ISBN978-3-0365-2326-2 (PDF)

This book is a reprint of the Special Issue Remote Sensing in Applications of Geoinformation that was published in

Environmental & Earth Sciences

Remote sensing, especially from satellites, is a source of invaluable data which can be used to generate synoptic information for virtually all parts of the Earth, including the atmosphere, land, and ocean. In the last few decades, such data have evolved as a basis for accurate information about the Earth, leading to a wealth of geoscientific analysis focusing on diverse applications. Geoinformation systems based on remote sensing are increasingly becoming an integral part of the current information and communication society. The integration of remote sensing and geoinformation essentially involves combining data provided from both, in a consistent and sensible manner. This process has been accelerated by technologically advanced tools and methods for remote sensing data access and integration, paving the way for scientific advances in a broadening range of remote sensing exploitations in applications of geoinformation.

This volume hosts original research focusing on the exploitation of remote sensing in applications of geoinformation. The emphasis is on a wide range of applications, such as the mapping of soil nutrients, detection of plastic litter in oceans, urban microclimate, seafloor morphology, urban forest ecosystems, real estate appraisal, inundation mapping, and solar potential analysis.

  • Hardback
© 2022 by the authors; CC BY-NC-ND license
inundation mapping; flood mapping; automatic thresholding; Sentinel-2; wetlands; marshland; Camargue; Doñana; 3D modelling; LiDAR; CityGML; solar potential; general valuation; Cyprus; artificial intelligence; mass appraisals; real estate; algorithms; mathematical models; AVM; CAMA; urban forest; landscape metrics; LiDAR; aerial images; street view images; semantic segmentation; convolutional neural network (CNN); spatial clustering; Eastern Mediterranean Sea; multiple filtering; skeletonization; structural interpretation; air temperature; surface temperature; LiDAR; multiple linear regression; Landsat 8; urban heat island; Sentinel-2; satellite images; plastic litter; spectral indices; spectroscopy; remote sensing; UAVs; soil nutrients; field spectroscopy; Landsat (OLI); partial least-squares and regression; Wadi El-Garawla; n/a