Application of Remote Sensing and GIS in Droughts and Floods Assessment and Monitoring

Edited by
April 2023
128 pages
  • ISBN978-3-0365-7146-1 (Hardback)
  • ISBN978-3-0365-7147-8 (PDF)

This book is a reprint of the Special Issue Application of Remote Sensing and GIS in Droughts and Floods Assessment and Monitoring that was published in

Biology & Life Sciences
Chemistry & Materials Science
Environmental & Earth Sciences
Public Health & Healthcare

This Special Issue collates seven papers regarding the assessment or monitoring of hydrological disasters such as droughts and flood using remote sensing and geography information system (GIS) techniques.. The new published research focused on evaluations and models of various hydrological hazards such as droughts and floods. Furthermore, we include two original scientific articles addressing the subject of water quality. This Special Issue received investigations based on different techniques such as remote sensing, GIS, machine learning and monitoring. All papers present findings characterized as unconventional, provocative, innovative and methodologically new. Scientific findings presented in this Special Issue highlight how a combination of various modern analysis techniques (e.g., remote sensing, GIS) can improve our understanding of complex hydrological hazards such as droughts and floods. We hope that the research contained within this Special Issue is useful to the scientific community, policymakers and stakeholders at large in the field of hydrological hazards.

  • Hardback
© 2022 by the authors; CC BY-NC-ND license
GRACE; drought; mainland China; extreme climate; climatic conditions; urban floods; rainfall movement direction (RMD); rainfall intensity (RI); peak runoff; Linear Directional Mean (LDM); Shenzhen; flood forecasting; error correction; residual property; ridge coefficient criterion; rainstorm mode; high dimension; dimension reduction; cluster; surface water; monitoring history; change trends in surface water quality; water quality protection; “Thirteenth Five-Year Plan” period; water environment quality; Heilongjiang Province; correlation analysis; surface water; manifold learning; machine learning; spatial–temporal distribution of rainstorms; feature extraction; Beijing; Shenzhen; n/a