remotesensing-logo

Journal Browser

Journal Browser

Remote Sensing for Monitoring Natural Hazards and Impact of Climate Change

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".

Deadline for manuscript submissions: closed (31 August 2020) | Viewed by 4735

Special Issue Editor


E-Mail Website
Guest Editor
NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
Interests: climate change; interannual-variability; natural hazards, aerosols; black carbon; remote sensing; land-atmosphere interaction

Special Issue Information

Dear Colleagues,

We are glad to announce a special issue of Remote Sensing, focussing on “Monitoring Natural Hazards and Impact of Climate Change”. This is a highly relevant topic for the current time when we are seeing an ever-increasing number of different natural hazards, threatening human life and property. According to an estimate by NOAA (https://www.ncdc.noaa.gov/billions/) of all billion-dollar disasters affecting the US since 1980, almost 50% of the total loss and 52% of total events, has been incurred in the last decade alone. Globally, the numbers are even more staggering, with one study (Leaning and Guha-Sapir, The New England Journal of Medicine) estimating that the number of natural disasters between 2000 to 2009 was three times more compared to that between 1980 to 1989, 80% of which was caused by climate-related events. 

It is becoming increasingly clear that climate change has a large role to play in this. Increased greenhouse gas emissions and rising temperatures have multiple ramifications in terms of increased drought events and more severe storms and cyclones. Human-induced pollutants such as black carbon, aerosols, etc can drastically alter the global radiation balance resulting in changing monsoon cycles and increased risk of cataclysmic flood events. The consequences are many and perilous. Hence, there is a need to document recent advances made in better monitoring of different natural hazards and demonstrate the clear impact of climate change. We hope to get your support in compiling this special issue and making a key contribution in this regard. 

Dr. Sudipta Sarkar
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • natural hazards
  • climate change
  • interannual-variability
  • monitoring
  • anthropogenic impact
  • long-term trends

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

22 pages, 10690 KiB  
Article
Trends in Long-Term Drought Changes in the Mekong River Delta of Vietnam
by Vu Hien Phan, Vi Tung Dinh and Zhongbo Su
Remote Sens. 2020, 12(18), 2974; https://doi.org/10.3390/rs12182974 - 12 Sep 2020
Cited by 15 | Viewed by 4427
Abstract
In recent years, short droughts in the dry season have occurred more frequently and caused serious damages to agriculture and human living in the Mekong River Delta of Vietnam (MRD). The paper attempts to quantify the trends of drought changes in the dry [...] Read more.
In recent years, short droughts in the dry season have occurred more frequently and caused serious damages to agriculture and human living in the Mekong River Delta of Vietnam (MRD). The paper attempts to quantify the trends of drought changes in the dry seasons from 2001 to 2015 in the region, using daily MODIS MOD09GQ and MOD11A1 data products. Here, we exploit the Temperature Vegetation Dryness Index (TVDI) to assess levels of droughts. For each image-acquisition time, the TVDI image is computed, based on the Normalized Difference Vegetation Index (NDVI), derived from red and near infrared reflectance data, and the Land Surface Temperature (LST), derived from thermal infrared data. Subsequently, a spatiotemporal pattern of drought changes is estimated, based on mean TVDI values of the dry seasons during the observed period, by a linear regression. As a result, the state of drought in the dry seasons in the MRD has mostly been at light and moderate levels, occupying approximately 62% and 34% of the total area. Several sub-areas in the center have an increased trend of drought change, occupying approximately 12.5% of the total area, because impervious surface areas increase, e.g., the obvious land use change, from forest land and land for cultivation for perennial trees being strongly converted to built-up land for residence and public transportation. Meanwhile, several sub-areas in the coastal regions have a negative trend of drought change because water and absorbent surface areas increase, e.g., most of land for cultivation for perennial trees has been converted to aquaculture land. These cases usually occur in and surrounding forest and wet land, also occupying approximately 12.5% of the total area. Full article
Show Figures

Graphical abstract

Back to TopTop