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Monitoring Vegetation Response Based on Remote Sensing and Climate Data...
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Monitoring Vegetation Response Based on Remote Sensing and Climate Data (Second Edition)

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Agriculture and Vegetation".

Deadline for manuscript submissions: 15 September 2024 | Viewed by 698

Special Issue Editors

Dr. Rui Yao

E-Mail Website
Guest Editor
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
Interests: urban heat island; urbanization; vegetation; climate change; land surface phenology
Special Issues, Collections and Topics in MDPI journals
Dr. Mario Cunha

E-Mail Website
Guest Editor
1. Sciences Faculty, Porto University (FCUP) Rua do Campo Alegre, s.n. 4169-007 Porto, Portugal
2. Researcher at Institute for Systems and Computer Engineering, Technology (INESC TEC) Portugal, R. Dr. Roberto Frias, Porto, Portugal
Interests: remote sensing; crop modelling; climate change; precision agriculture; orchards/vineyards monitoring
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Vegetation plays a key role in the system of the earth and has a significant impact on carbon, water and energy cycles. Changes in vegetation can indirectly reflect changes in the environmental quality, and indicate climate and environmental evolutions. The accurate assessment of vegetation change (including vegetation cover, greeness, phenology and productivity, etc.) and its response to climate change and human activity is crucial to the realization of environmental protection and sustainable development. 

This Special Issue (Volume II) aims to enhance our understanding of vegetation change and its response to climate change and human activity, which is an important aspect of remote sensing with regard to vegetation. We invite authors to contribute to this Special Issue to improve and consolidate our current knowledge in this field. Manuscripts related to theories, methods and applications are welcome.

Submissions may include, but are not limited to:

  • Vegetation cover change;
  • Vegetation phenology change;
  • Vegetation productivity change;
  • Crop yield change;
  • Response of vegetation to climate and human activity;
  • Effect of vegetation on environment.

Dr. Rui Yao
Dr. Mario Cunha
Guest Editors

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

  • vegetation cover
  • vegetation phenology
  • vegetation productivity
  • crop yield
  • NDVI/EVI/LAI
  • climate change
  • human activity detection/monitoring

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Published Papers (1 paper)

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Research

17 pages, 5541 KiB  
Article
Spatial Scale Effect on Fractional Vegetation Coverage Changes and Driving Factors in the Henan Section of the Yellow River Basin
by Rongxi Wang, Hongtao Wang, Cheng Wang, Jingjing Duan and Shuting Zhang
Remote Sens. 2024, 16(14), 2575; https://doi.org/10.3390/rs16142575 - 13 Jul 2024
Viewed by 465
Abstract
Vegetation plays a crucial role in terrestrial ecosystems, and the FVC (Fractional Vegetation Coverage) is a key indicator reflecting the growth status of vegetation. The accurate quantification of FVC dynamics and underlying driving factors has become a hot topic. However, the scale effect [...] Read more.
Vegetation plays a crucial role in terrestrial ecosystems, and the FVC (Fractional Vegetation Coverage) is a key indicator reflecting the growth status of vegetation. The accurate quantification of FVC dynamics and underlying driving factors has become a hot topic. However, the scale effect on FVC changes and driving factors has received less attention in previous studies. In this study, the changes and driving factors of FVC at multiple scales were analyzed to reveal the spatial and temporal change in vegetation in the Henan section of the Yellow River basin. Firstly, based on the pixel dichotomy model, the FVC at different times and spatial scales was calculated using Landsat-8 data. Then, the characteristics of spatial and temporal FVC changes were analyzed using simple linear regression and CV (Coefficient of Variation). Finally, a GD (Geographic Detector) was used to quantitatively analyze the driving factors of FVC at different scales. The results of this study revealed that (1) FVC showed an upward trend at all spatial scales, increasing by an average of 0.55% yr−1 from 2014 to 2022. The areas with an increasing trend in FVC were 10.83% more than those with a decreasing trend. (2) As the spatial scale decreased, the explanatory power of the topography factors (aspect, elevation, and slope) for changes in FVC was gradually strengthened, while the explanatory power of climate factors (evapotranspiration, temperature, and rainfall) and anthropogenic activities (night light) for changes in FVC decreased. (3) The q value of evapotranspiration was always the highest across different scales, peaking notably at a spatial scale of 1000 m (q = 0.48). Full article
(This article belongs to the Special Issue Monitoring Vegetation Response Based on Remote Sensing and Climate Data (Second Edition))
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