Satellite Remote Sensing of Savannas: Current Status and Emerging Opportunities
Abdi, Abdulhakim M. LU
; Brandt, Martin
; Abel, Christin
LU
and Fensholt, Rasmus
(2022)
In Journal of Remote Sensing
2022.
- Abstract
- Savannas cover a wide climatic gradient across large portions of the Earth’s land surface and are an important component of the terrestrial biosphere. Savannas have been undergoing changes that alter the composition and structure of their vegetation such as the encroachment of woody vegetation and increasing land-use intensity. Monitoring the spatial and temporal dynamics of savanna ecosystem structure (e.g., partitioning woody and herbaceous vegetation) and function (e.g., aboveground biomass) is of high importance. Major challenges include misclassification of savannas as forests at the mesic end of their range, disentangling the contribution of woody and herbaceous vegetation to aboveground biomass, and quantifying and mapping fuel... (More)
- Savannas cover a wide climatic gradient across large portions of the Earth’s land surface and are an important component of the terrestrial biosphere. Savannas have been undergoing changes that alter the composition and structure of their vegetation such as the encroachment of woody vegetation and increasing land-use intensity. Monitoring the spatial and temporal dynamics of savanna ecosystem structure (e.g., partitioning woody and herbaceous vegetation) and function (e.g., aboveground biomass) is of high importance. Major challenges include misclassification of savannas as forests at the mesic end of their range, disentangling the contribution of woody and herbaceous vegetation to aboveground biomass, and quantifying and mapping fuel loads. Here, we review current (2010–present) research in the application of satellite remote sensing in savannas at regional and global scales. We identify emerging opportunities in satellite remote sensing that can help overcome existing challenges. We provide recommendations on how these opportunities can be leveraged, specifically (1) the development of a conceptual framework that leads to a consistent definition of savannas in remote sensing; (2) improving mapping of savannas to include ecologically relevant information such as soil properties and fire activity; (3) exploiting high-resolution imagery provided by nanosatellites to better understand the role of landscape structure in ecosystem functioning; and (4) using novel approaches from artificial intelligence and machine learning in combination with multisource satellite observations, e.g., multi-/hyperspectral, synthetic aperture radar (SAR), and light detection and ranging (lidar), and data on plant traits to infer potentially new relationships between biotic and abiotic components of savannas that can be either proven or disproven with targeted field experiments. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/96785df3-0b8b-475d-8bec-1f58c8a519af
- author
- Abdi, Abdulhakim M.
LU
; Brandt, Martin
; Abel, Christin
LU
and Fensholt, Rasmus
- organization
- publishing date
- 2022-06-17
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Savannas, Forests, Dryland ecosystems, Remote sensing, Earth observation, Global change ecology
- in
- Journal of Remote Sensing
- volume
- 2022
- article number
- 9835284
- pages
- 20 pages
- publisher
- American Association for the Advancement of Science (AAAS)
- external identifiers
-
- scopus:85141110199
- ISSN
- 2694-1589
- DOI
- 10.34133/2022/9835284
- language
- English
- LU publication?
- yes
- id
- 96785df3-0b8b-475d-8bec-1f58c8a519af
- date added to LUP
- 2022-11-02 12:00:48
- date last changed
- 2024-01-04 04:05:52
@article{96785df3-0b8b-475d-8bec-1f58c8a519af,
abstract = {{Savannas cover a wide climatic gradient across large portions of the Earth’s land surface and are an important component of the terrestrial biosphere. Savannas have been undergoing changes that alter the composition and structure of their vegetation such as the encroachment of woody vegetation and increasing land-use intensity. Monitoring the spatial and temporal dynamics of savanna ecosystem structure (e.g., partitioning woody and herbaceous vegetation) and function (e.g., aboveground biomass) is of high importance. Major challenges include misclassification of savannas as forests at the mesic end of their range, disentangling the contribution of woody and herbaceous vegetation to aboveground biomass, and quantifying and mapping fuel loads. Here, we review current (2010–present) research in the application of satellite remote sensing in savannas at regional and global scales. We identify emerging opportunities in satellite remote sensing that can help overcome existing challenges. We provide recommendations on how these opportunities can be leveraged, specifically (1) the development of a conceptual framework that leads to a consistent definition of savannas in remote sensing; (2) improving mapping of savannas to include ecologically relevant information such as soil properties and fire activity; (3) exploiting high-resolution imagery provided by nanosatellites to better understand the role of landscape structure in ecosystem functioning; and (4) using novel approaches from artificial intelligence and machine learning in combination with multisource satellite observations, e.g., multi-/hyperspectral, synthetic aperture radar (SAR), and light detection and ranging (lidar), and data on plant traits to infer potentially new relationships between biotic and abiotic components of savannas that can be either proven or disproven with targeted field experiments.}},
author = {{Abdi, Abdulhakim M. and Brandt, Martin and Abel, Christin and Fensholt, Rasmus}},
issn = {{2694-1589}},
keywords = {{Savannas; Forests; Dryland ecosystems; Remote sensing; Earth observation; Global change ecology}},
language = {{eng}},
month = {{06}},
publisher = {{American Association for the Advancement of Science (AAAS)}},
series = {{Journal of Remote Sensing}},
title = {{Satellite Remote Sensing of Savannas: Current Status and Emerging Opportunities}},
url = {{http://dx.doi.org/10.34133/2022/9835284}},
doi = {{10.34133/2022/9835284}},
volume = {{2022}},
year = {{2022}},
}