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Special Issue "Remote Sensing of Arid/Semiarid Lands II"

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

Deadline for manuscript submissions: 31 October 2023 | Viewed by 2773

Special Issue Editors

1. Department of Remote Sensing, University of Würzburg, Würzburg, Germany
2. Department of Photogrammetry and Remote Sensing, Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, Tehran, Iran
Interests: ecosystem monitoring; vegetation health; time series remote sensing; LiDAR
Special Issues, Collections and Topics in MDPI journals
Department of Environmental Engineering, University of Patras, G. Seferi 2, GR-30100 Agrinio, Greece
Interests: geoinformatics on wildland fires; natural disasters and landscape ecology; applied multivariate methods, geostatistics and point pattern analysis with special emphasis on spatio-temporal analysis of wildland fire ignition points; positional uncertainty and data modeling
Special Issues, Collections and Topics in MDPI journals
Department of Forestry, Lorestan University, P.O. Box, Khorramabad 68151-44316, Iran
Interests: vegetation mapping using satellite imagery; monitoring semi-arid woody vegetation; forest change modelling; estimating the attributes of trees using 3D data

Special Issue Information

Dear Colleagues,

This is the 2nd volume of the Special Issue “Remote Sensing of Arid/Semiarid Lands”, it was a great success.

Recent publication trends reveal the continuous progress in the application of remote sensing and Earth observation approaches for semi-arid vegetation monitoring. Many previous surveys were conducted based on the fundamental assumption that drought and other extreme climate events affect the ecological environment for vegetation in semi-arid zones, yet with a response lag of vegetation to drought that differs from ecosystem to ecosystem. Phenomena like changing patterns in soil use, natural disasters, climatic change and wildfires alter the spatial dynamics of arid and semi-arid vegetation.

Amongst the remote sensing methods and despite their inherent intuition, vegetation index-based approaches are still advantageous given their simple calculation and intuitive interpretability. In particular, permanent sample plots established within semi-arid regions could offer excellent locations for long-term and mostly remote-sensing-based spectral trajectory analysis of

Vegetation. Furthermore, approaches based on vegetation phenology could also provide invaluable insights for the trajectory analysis of semi-arid vegetation, which have so far been largely understudied, and remote-sensing-assisted phenological investigations seem to be lacking for semi-arid regions.

In addition, spatiotemporal image-fusion approaches have experienced rapid progress for various remote-sensing applications in recent decades as a constantly growing field of

research, which calls for their augmented applications across arid and semi-arid vegetation zones. Finally, approaches based on new technologies like UAVs, terrestrial and mobile laser scanners (for small-scale quantification and monitoring) as well as large-scale applications via new satellite data series (in active and passive domains) are required to be calibrated for arid and semi-arid vegetation, in particular across remote and mountainous areas.

In this Special Issue, we aim to cover those and other relevant topics and sub-topics by welcoming reviews, case studies and communications from all over the world. In particular, we welcome submissions with the following thematic emphases:

  • Remote sensing applications for soil erosion monitoring across arid and semi-arid areas;
  • Applications for spatial extrapolations and upscaling from plant to plant groups and landscapes;
  • Approaches for pest, disease and decline monitoring across arid and semi-arid natural vegetation;
  • Applications based on terrestrial platforms (TLS, iPhone, GeoSLAM etc.) for small-scale vegetation monitoring across arid and semi-arid regions;
  • Applications for estimating growing stock, woody biomass and bioenergy across arid and semi-arid trees;
  • Species distribution mapping and monitoring;
  • Approaches to overcome challenges faced when processing remote sensing data sources like soil background reflectance, atmospheric effects, shadows and grouped tree crowns in coppice structures;
  • Spatial and temporal forests change modelling across arid and semi-arid areas;
  • Defining and modelling ecosystem services of arid and semi-arid woodlands;
  • Assessing the impact of climate change on arid and semi-arid vegetation.

Dr. Hooman Latifi
Dr. Nikos Koutsias
Dr. Hamed Naghavi
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at 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 2500 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.


  • arid woody vegetation
  • semi-arid woody vegetation
  • remote sensing
  • UAV photogrammetry
  • coppice structure
  • burned area mapping
  • tree detection and delineation
  • spatial ecology

Published Papers (1 paper)

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Vegetation Growth Response and Trends after Water Deficit Exposure in the Loess Plateau, China
Remote Sens. 2023, 15(10), 2593; - 16 May 2023
Viewed by 2352
Understanding the impact of water availability on vegetation growth in the context of climate change is crucial for assessing the resilience of vegetation to environmental shifts. In this study, the relationship between vegetation growth and water availability was studied using a variety of [...] Read more.
Understanding the impact of water availability on vegetation growth in the context of climate change is crucial for assessing the resilience of vegetation to environmental shifts. In this study, the relationship between vegetation growth and water availability was studied using a variety of indicators. The Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), and Solar-Induced Chlorophyll Fluorescence (SIF) were utilized as vegetation growth indicators, while the standardized precipitation evapotranspiration index (SPEI) and soil moisture indicators served as water use indices. To investigate the vegetation response to water deficit in the Loess Plateau during the growing season from 2000 to 2020, Spearman’s rank correlation coefficients were calculated using a 5-year sliding window approach. The spatial and temporal heterogeneity of vegetation response to water deficit during the growing seasons were also explored. The results showed that: (1) with the improvement of moisture conditions, vegetation growth recovered significantly, and there was no expansion trend for vegetation water deficit. (2) The most sensitive timescale of vegetation to water deficit was 6–8 months; the response degree and sensitivity of vegetation to water surplus and deficit were the highest from June to August; and broadleaved forest was the vegetation type most sensitive to water deficit in the early growing season, while grass was the vegetation type most sensitive to water deficit during the mid and late growing seasons. (3) Soil moisture emerged as the dominant factor influencing vegetation growth in the Loess Plateau, followed by precipitation, albeit to a lesser extent. These findings contribute to understanding the mechanism and characteristics of the response of vegetation to climate fluctuations induced by global climate change. Full article
(This article belongs to the Special Issue Remote Sensing of Arid/Semiarid Lands II)
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