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Remote Sensing
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Advances of Remote Sensing in Mapping Arid/Semi-arid Environment
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Advances of Remote Sensing in Mapping Arid/Semi-arid Environment

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Geology, Geomorphology and Hydrology".

Deadline for manuscript submissions: closed (30 November 2021) | Viewed by 4174

Special Issue Editor

Prof. Dr. Farouk El-Baz

E-Mail Website
Guest Editor
Boston University, Center for Remote Sensing, Boston, MA 02215, USA
Interests: remote sensing in archaeology; application of space-borne data to ground-water exploration; use of space photography to study arid lands and define changes to their environments as well as their geological features.

Special Issue Information

Dear Colleagues,

Arid and semi-arid lands cover over 30 percent of the surfaces of the Earth. Yet, we know little about their response to environmental changes. Natural as well as human-made changes to arid lands cause lasting as well as mitigatable effects. However, we must be able to recognize the extent, nature, causes and effects of those changes. That information is required for us to live with them or modify their effects. Thus, we must be armed with information on the nature of affected surface features to be able to ascertain the nature of changes and their potential mitigation.

Advances in remote sensing technologies during the last few decades allow us to collect basic information. Upon completion of the Apollo program of lunar investigation, attention was directed toward studying the Earth from space. Thus, digital images, in increasingly complex and varied methodologies, began to accumulate. Data variety, quality, and quantity represented a steadfast interest in studying the Earth from space. In particular, this increased the significance of arid land study from space because of the paucity of cloud cover.

Thus, remote sensing satellites offer the scientific community a vast store of data of arid lands in various parts of the electro-magnetic spectrum. It is a treasure trove of information, particularly as some of arid lands are covered by sand deposits that are penetrated by radar waves from Earth orbit. All such data provide a treasure trove of information related to the origin and nature of, as well as the environmental changes to, arid lands.

Thus, this volume is dedicated to scientific reports on Advances of Remote Sensing in Mapping Arid/Semi-Arid Environment.

Prof. Dr. Farouk El-Baz
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

  • multispectral images
  • imaging radar
  • change detection
  • environmental change
  • drylands
  • image classification
  • digital enhancement

Published Papers (1 paper)

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Research

28 pages, 11413 KiB  
Article
An Assessment of the Hydrological Trends Using Synergistic Approaches of Remote Sensing and Model Evaluations over Global Arid and Semi-Arid Regions
by Wenzhao Li, Hesham El-Askary, Rejoice Thomas, Surya Prakash Tiwari, Karuppasamy P. Manikandan, Thomas Piechota and Daniele Struppa
Remote Sens. 2020, 12(23), 3973; https://doi.org/10.3390/rs12233973 - 4 Dec 2020
Cited by 12 | Viewed by 3552
Abstract
Drylands cover about 40% of the world’s land area and support two billion people, most of them living in developing countries that are at risk due to land degradation. Over the last few decades, there has been warming, with an escalation of drought [...] Read more.
Drylands cover about 40% of the world’s land area and support two billion people, most of them living in developing countries that are at risk due to land degradation. Over the last few decades, there has been warming, with an escalation of drought and rapid population growth. This will further intensify the risk of desertification, which will seriously affect the local ecological environment, food security and people’s lives. The goal of this research is to analyze the hydrological and land cover characteristics and variability over global arid and semi-arid regions over the last decade (2010–2019) using an integrative approach of remotely sensed and physical process-based numerical modeling (e.g., Global Land Data Assimilation System (GLDAS) and Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS) models) data. Interaction between hydrological and ecological indicators including precipitation, evapotranspiration, surface soil moisture and vegetation indices are presented in the global four types of arid and semi-arid areas. The trends followed by precipitation, evapotranspiration and surface soil moisture over the decade are also mapped using harmonic analysis. This study also shows that some hotspots in these global drylands, which exhibit different processes of land cover change, demonstrate strong coherency with noted groundwater variations. Various types of statistical measures are computed using the satellite and model derived values over global arid and semi-arid regions. Comparisons between satellite- (NASA-USDA Surface Soil Moisture and MODIS Evapotranspiration data) and model (FLDAS and GLDAS)-derived values over arid regions (BSh, BSk, BWh and BWk) have shown the over and underestimation with low accuracy. Moreover, general consistency is apparent in most of the regions between GLDAS and FLDAS model, while a strong discrepancy is also observed in some regions, especially appearing in the Nile Basin downstream hyper-arid region. Data-driven modelling approaches are thus used to enhance the models’ performance in this region, which shows improved results in multiple statistical measures ((RMSE), bias (ψ), the mean absolute percentage difference (|ψ|)) and the linear regression coefficients (i.e., slope, intercept, and coefficient of determination (R2)). Full article
(This article belongs to the Special Issue Advances of Remote Sensing in Mapping Arid/Semi-arid Environment)
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