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Remote Sensing
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Remote Sensing Application in the Carbon Flux Modelling
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Remote Sensing Application in the Carbon Flux Modelling

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing and Geo-Spatial Science".

Deadline for manuscript submissions: 15 March 2025 | Viewed by 4448

Special Issue Editors

Prof. Dr. Zongyao Sha

E-Mail Website
Guest Editor
International School of Software, Wuhan University, Wuhan, China
Interests: geographic information system; vegetation mapping; remote sensing; spatial analysis; spatial statistics; geostatistical analysis; geospatial science; data mining; geographical analysis; digital mapping; web mapping; geo-processing
Prof. Dr. Yichun Xie

E-Mail Website
Guest Editor
Institute for Geospatial Research and Education, Eastern Michigan University, Ypsilanti, MI 48197, USA
Interests: geographic information science; spatial modelling; remote sensing theory and methodology; spatiotemporal modelling of urban growth; grassland ecosystem; coupled impacts of human dynamics and environmental change on resource management and ecosystem recovery; land-use and land-cover changes
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Climate changes and global warming have been threatening the Earth’s sustainable environment and attracting considerable attention from international agencies and scientists. One aspect that has been drawn consensus among academia is that the frequency of extreme weather events and global warming are closely correlated to the increased emissions of greenhouse gases (GHGs), with carbon dioxide (CO2) being the most significant component. Global warming has been accompanied by the rising concentration of atmospheric CO2, which has reached over 400 ppm today, while it was only 280 ppm in the preindustrial era. Facing such challenges, we must reduce the emissions of GHGs from human activities and/or enhance carbon sequestration using engineering and ecological approaches.

Measuring/quantifying carbon emissions and sequestration is a crucial step in understanding the trajectories of carbon cycling and estimating the content of atmospheric CO2 in the future. Remote sensing can be used to retrieve essential datasets required to explore carbon flux dynamics at various scales based on advanced geospatial models. This Special Issue will especially focus on novel studies on remote sensing technology and geospatial models that account for and model carbon emissions from households and industrial practices, as well as carbon sequestration (through vegetation photosynthesis) in ecosystems. We also aim to assess the impact on carbon cycling in the future by controlling emissions from human activities and improving carbon sequestration via optimized ecosystem management.

Prof. Dr. Zongyao Sha
Prof. Dr. Yichun Xie
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

  • carbon cycle
  • ecosystems
  • carbon emissions
  • vegetation carbon sequestration
  • geospatial modeling

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Published Papers (3 papers)

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Research

21 pages, 6877 KiB  
Article
Impacts of Drought and Heatwave on the Vegetation and Ecosystem in the Yangtze River Basin in 2022
by Siyuan Chen, Ruonan Qiu, Yumin Chen, Wei Gong and Ge Han
Remote Sens. 2024, 16(16), 2889; https://doi.org/10.3390/rs16162889 - 7 Aug 2024
Viewed by 1522
Abstract
In 2022, a severe drought and heatwave occurred in the middle and lower reaches of the Yangtze River Basin. Previous studies have highlighted the severity of this event, yet the relevance of soil moisture (SM), as well as vapor pressure deficit (VPD) and [...] Read more.
In 2022, a severe drought and heatwave occurred in the middle and lower reaches of the Yangtze River Basin. Previous studies have highlighted the severity of this event, yet the relevance of soil moisture (SM), as well as vapor pressure deficit (VPD) and vegetation damage, remained unclear. Here, we utilized solar-induced chlorophyll fluorescence (SIF) and various flux data to monitor the impact of drought on vegetation and analyze the influence of different environmental factors. The results indicated a severe situation of drought and heatwave in the Yangtze River Basin in 2022 that significantly affected vegetation growth and the ecosystem carbon balance. SIF and NDVI have respective advantages in reflecting damage to vegetation under drought and heatwave conditions; SIF is more capable of capturing the weakening of vegetation photosynthesis, while NDVI can more rapidly indicate vegetation damage. Additionally, the correlation of SM and SIF are comparable to that of VPD and SIF. By contrast, the differentiation in the severity of vegetation damage among different types of vegetation is evident; cropland is more vulnerable compared to forest ecosystems and is more severely affected by drought and heatwave. These findings provided important insights for assessing the impact of compound drought and heatwave events on vegetation growth. Full article
(This article belongs to the Special Issue Remote Sensing Application in the Carbon Flux Modelling)
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19 pages, 18545 KiB  
Article
Active Wildland Fires in Central Chile and Local Winds (Puelche)
by Hiroshi Hayasaka
Remote Sens. 2024, 16(14), 2605; https://doi.org/10.3390/rs16142605 - 16 Jul 2024
Viewed by 709
Abstract
Central Chile (CC, latitudes 32–40°S) experienced very active fires in 2017 and 2023. These fires burned large areas and killed many people. These unprecedented fires for CC presented a need for more defined fire weather conditions on the synoptic scale. In this paper, [...] Read more.
Central Chile (CC, latitudes 32–40°S) experienced very active fires in 2017 and 2023. These fires burned large areas and killed many people. These unprecedented fires for CC presented a need for more defined fire weather conditions on the synoptic scale. In this paper, fire weather conditions were analyzed using various satellite-derived fire data (hotspots, HSs), wind streamlines, distribution maps of wind flow and temperature, and various synoptic-scale weather maps. Results showed that local winds, known as Puelche, blew on the peak fire days (26 January 2017 and 3 February 2023). The number of HSs on these days was 2676 and 2746, respectively, about 90 times the average (30). The occurrence of Puelche winds was confirmed by streamlines from high-pressure systems offshore of Argentina to the study area in CC. The formation of strong winds and high-temperature areas associated with Puelche winds were identified on the Earth survey satellite maps. Strong winds of about 38 km h−1 and high temperatures above 32 °C with low relative humidity below 33% were actually observed at the weather station near the fire-prone areas. Lastly, some indications for Puelche winds outbreaks are summarized. This paper’s results will be used to prevent future active fire occurrences in the CC. Full article
(This article belongs to the Special Issue Remote Sensing Application in the Carbon Flux Modelling)
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17 pages, 7235 KiB  
Article
Validation of Gross Primary Production Estimated by Remote Sensing for the Ecosystems of Doñana National Park through Improvements in Light Use Efficiency Estimation
by Pedro J. Gómez-Giráldez, Jordi Cristóbal, Héctor Nieto, Diego García-Díaz and Ricardo Díaz-Delgado
Remote Sens. 2024, 16(12), 2170; https://doi.org/10.3390/rs16122170 - 15 Jun 2024
Viewed by 1629
Abstract
Doñana National Park is located in the southwest of the Iberian Peninsula, where water scarcity is recurrent, together with a high heterogeneity in species and ecosystems. Monitoring carbon assimilation is essential to improve knowledge of global change in natural vegetation cover. In this [...] Read more.
Doñana National Park is located in the southwest of the Iberian Peninsula, where water scarcity is recurrent, together with a high heterogeneity in species and ecosystems. Monitoring carbon assimilation is essential to improve knowledge of global change in natural vegetation cover. In this work, a light use efficiency (LUE) model was applied to estimate gross primary production (GPP) in two ecosystems of Doñana, xeric shrub (drought resistant) and seasonal marsh (with grasslands dependent on water hydroperiod) and validated with in situ data from eddy covariance (EC) towers installed in both ecosystems. The model was applied in two ways: (1) using the fraction of absorbed photosynthetically active radiation (FAPAR) from Sentinel-2 and meteorological data from reanalysis (ERA5), and (2) using Sentinel-2 FAPAR, reanalysis solar radiation (ERA5) and the Sentinel-2 land surface water index (LSWI). In both cases and for both ecosystems, the error values are acceptable (below 1 gC/m2) and in both ecosystems the model using the LSWI gave better results (R2 of 0.8 in marshes and 0.51 in xeric shrubs). The results also show a greater influence of the water status of the system than of the meteorological variables in this area. Full article
(This article belongs to the Special Issue Remote Sensing Application in the Carbon Flux Modelling)
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