dc.contributor.author |
Bonnet, Wessel
|
|
dc.contributor.author |
Cho, Moses Azong
|
|
dc.contributor.author |
Masemola, Cecilia
|
|
dc.date.accessioned |
2024-11-20T06:48:16Z |
|
dc.date.available |
2024-11-20T06:48:16Z |
|
dc.date.issued |
2024-08 |
|
dc.description.abstract |
An effective methodology is needed to simulate soil spectra on a large scale. The brightness-shape-moisture (BSM) radiative transfer model (RTM) is used to simulate soil spectra for different semiarid and arid biomes within Southern Africa based on hyperspectral imagery obtained from the Hyperion satellite. Such simulation based on hyperspectral data is especially relevant in light of newer hyperspectral missions, such as Prisma providing ongoing data streams. In this particular study, Hyperion’s data are cleaned using the SUREHYP procedure, segmented using the simple linear iterative clustering (SLIC) algorithm, filtered to exclude photosynthetic and senescent vegetation, and parameterized via a Hyperion band calibrated BSM model lookup table to obtain simulation parameter distributions for different biomes. This provides a means to better simulate soil spectra using each biome’s obtained parameter distributions in the BSM forward model. |
en_US |
dc.description.department |
Plant Production and Soil Science |
en_US |
dc.description.librarian |
hj2024 |
en_US |
dc.description.sdg |
SDG-15:Life on land |
en_US |
dc.description.sponsorship |
The CSIR and the National Research Foundation New Earth Observation Frontiers innovation funding mechanism. |
en_US |
dc.description.uri |
https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=36 |
en_US |
dc.identifier.citation |
W. Bonnet, M.A. Cho and C. Masemola, "Defining Brightness-Shape-Moisture Soil Parameters for Southern Africa From Hyperion Hyperspectral Imagery," in IEEE Transactions on Geoscience and Remote Sensing, vol. 62, pp. 1-8, 2024, Art no. 5527808, doi: 10.1109/TGRS.2024.3446246. |
en_US |
dc.identifier.issn |
0196-2892 (print) |
|
dc.identifier.issn |
1558-0644 (online) |
|
dc.identifier.other |
10.1109/TGRS.2024.3446246. |
|
dc.identifier.uri |
http://hdl.handle.net/2263/99192 |
|
dc.language.iso |
en |
en_US |
dc.publisher |
Institute of Electrical and Electronics Engineers |
en_US |
dc.rights |
© Copyright 2024 IEEE - All rights reserved, including rights for text and data mining and training of artificial intelligence and similar technologies. |
en_US |
dc.subject |
Atmospheric modeling |
en_US |
dc.subject |
Mathematical models |
en_US |
dc.subject |
Hyperspectral imaging |
en_US |
dc.subject |
Biological system modeling |
en_US |
dc.subject |
Absorption |
en_US |
dc.subject |
Soil moisture |
en_US |
dc.subject |
Soil properties |
en_US |
dc.subject |
Southern Africa |
en_US |
dc.subject |
Hyperion |
en_US |
dc.subject |
Brightness-shape-moisture (BSM) |
en_US |
dc.subject |
Radiative transfer model (RTM) |
en_US |
dc.subject |
Simple linear iterative clustering (SLIC) |
en_US |
dc.subject |
SDG-15: Life on land |
en_US |
dc.title |
Defining brightness-shape-moisture soil parameters for southern Africa from hyperion hyperspectral imagery |
en_US |
dc.type |
Postprint Article |
en_US |