Remote Sensing for Vegetation Mapping and Its Application in Carbon Budget
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: closed (6 November 2022) | Viewed by 18926
Special Issue Editors
Interests: global burned area extraction; land surface reflectance retrieval; thermal infrared remote sensing; vegetation parameters (leaf area index, biomass) mapping
Interests: forest and burned area mapping; spatial photogrammetry; image registration; land-cover change; noctilucent remote sensing
Special Issues, Collections and Topics in MDPI journals
Interests: landsat surface temperature retrieval; local climate zone classification
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Deforestation typically releases carbon from the terrestrial biosphere to the atmosphere as CO2 (carbon dioxide), while recovering vegetation in abandoned agricultural or logged land removes CO2 from the atmosphere and sequesters it in vegetation biomass and soil carbon. Carbon budget estimation from vegetation dynamics receives a great deal of scientific attention. The key state variables and parameters of vegetation, i.e., the forest cover and its change, the content of chlorophyll, biomass, tree height, forest burned area, and leaf area index, have impacts on the vegetation carbon budget. Combining remote sensing and ecological modeling reveals a promising avenue in vegetation carbon budget investigation. This Special Issue seeks the most recent research on gaining the key vegetation parameters using the SAR interferometry, multispectral lidar, hyperspectral remote sensing, and unmanned aerial vehicle remote sensing incorporated into an ecological process model with a carbon budget model, to evaluate the spatio-temporal dynamics of both carbon storage and carbon budget of vegetation, assessing the influence of these vegetation parameters on vegetation carbon storage.
Prof. Dr. Zhaoming Zhang
Dr. Tengfei Long
Dr. Mengmeng Wang
Guest Editors
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Keywords
- airborne lidar for 3D vegetation mapping
- tree height retrieval
- vegetation classification using hyperspectral remote sensing
- forest cover and forest change mapping
- vegetation parameters (chlorophyll content, biomass, leaf area index) mapping
- forest burned area mapping
- forest carbon storage
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