dc.contributor.author |
Tsele, Philemon
|
|
dc.contributor.author |
Ramoelo, Abel
|
|
dc.contributor.author |
Qabaqaba, Mcebisi
|
|
dc.contributor.author |
Mafanya, Madodomzi
|
|
dc.contributor.author |
Chirima, Johannes George
|
|
dc.date.accessioned |
2023-04-20T10:32:22Z |
|
dc.date.issued |
2022 |
|
dc.description |
DATA AVAILABILITY STATEMENT : We understand that the publication of the data is becoming a good practice in research. However, we
plan to share all our data in future, but at this stage we are still going to further analyse it for locally par-
ameterized types of models, looking at both empirical and the inversion of the physically-based models. |
en_US |
dc.description |
The Sentinel-2 data used in this study were downloaded from the European Space Agency Copernicus Open Access Hub. |
en_US |
dc.description.abstract |
The Sentinel-2 Level 2 Prototype Processor (SL2P) allows the generation of biophysical estimates at high spatiotemporal resolution from Sentinel-2 imagery and could be a solution for generating products in natural environments. This study validated the SL2P estimates of leaf area index (LAI), fractional vegetation cover (FVC) and canopy chlorophyll content (CCC) over the savanna and grassland environments using field measurements. The performance of the SL2P estimates in Marakele and Golden Gate Highlands National Parks were comparatively poor and linearly biased coupled with moderate-to-high errors. The SL2P estimates in the two study sites had low accuracy with relative root mean squared error’s in the range 61.63% to 85.26% and possible systematic underestimations with pBias's ranging from 32.17% to 63.16%. These findings gave insight about the performance of the SL2P estimates over the considered heterogenous environments, and suggest the need for extensive validation and re-calibration of the system using long-term field measurements. |
en_US |
dc.description.department |
Geography, Geoinformatics and Meteorology |
en_US |
dc.description.embargo |
2023-06-17 |
|
dc.description.librarian |
hj2023 |
en_US |
dc.description.uri |
https://www.tandfonline.com/loi/tgei20 |
en_US |
dc.identifier.citation |
Philemon Tsele, Abel Ramoelo, Mcebisi Qabaqaba, Madodomzi
Mafanya & George Chirima (2022) Validation of LAI, chlorophyll and FVC biophysical
estimates from sentinel-2 level 2 prototype processor over a heterogeneous savanna and
grassland environment in South Africa, Geocarto International, 37:26, 14355-14378, DOI:
10.1080/10106049.2022.2087756. |
en_US |
dc.identifier.issn |
1010-6049 (print) |
|
dc.identifier.issn |
1752-0762 (online) |
|
dc.identifier.other |
10.1080/10106049.2022.2087756 |
|
dc.identifier.uri |
http://hdl.handle.net/2263/90405 |
|
dc.language.iso |
en |
en_US |
dc.publisher |
Taylor and Francis |
en_US |
dc.rights |
© 2022 Informa UK Limited, trading as Taylor & Francis Group. This is an electronic version of an article published in Geomicrobiology Journal, vol. 37, no. 26, pp. 14355-14378, 2022. doi : 10.1080/10106049.2022.2087756. Geomicrobiology Journal is available online at : https://www.tandfonline.com/loi/tgei20. |
en_US |
dc.subject |
Sentinel-2 level 2 prototype processor (SL2P) |
en_US |
dc.subject |
Leaf area index (LAI) |
en_US |
dc.subject |
Fractional vegetation cover (FVC) |
en_US |
dc.subject |
Canopy chlorophyll content (CCC) |
en_US |
dc.subject |
Error analysis |
en_US |
dc.title |
Validation of LAI, chlorophyll and FVC biophysical estimates from sentinel-2 level 2 prototype processor over a heterogeneous savanna and grassland environment in South Africa |
en_US |
dc.type |
Postprint Article |
en_US |