ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume X-4-2024
https://doi.org/10.5194/isprs-annals-X-4-2024-21-2024
https://doi.org/10.5194/isprs-annals-X-4-2024-21-2024
18 Oct 2024
 | 18 Oct 2024

Estimating Soil Salinity Using HISUI Hyperspectral Data in the Western Australian Wheatbelt

Emiko Ariyasu and Satomi Kakuta

Keywords: Arid, Map, Electrical Conductivity, Salt-affected, SWIR, Remote sensing

Abstract. Soil salinity, caused by natural and anthropogenic factors, significantly impacts agricultural productivity, ecosystems, and global biodiversity. To mitigate severe salinity levels, it is necessary to detect early the salt-affected land for implementing solutions, such as adequate irrigation and cultivation of salt-tolerant crops. Before launching spaceborne hyperspectral sensor, Hyperspectral Imager Suite, (HISUI) developed by Japanese Ministry of Economy Trade and Industry, Kobayashi et al. (2010 and 2013) developed methods utilizing airborne hyperspectral data from HyMap to estimate soil salinity in wheatbelt region of Western Australia as a previous study. This paper aims to assess the feasibility of estimating soil salinity with HISUI in the same study area, following the past approach. Also, the goal is to estimate low soil salinity levels as same as the past objectives. As a result, past approach could not be fully applied in spaceborne hyperspectral sensor, caused by atmospheric effect in SWIR region. However, absorption of soil salinity in SWIR regions could be detected by HISUI. In the soil index, the NDSI (Normalized Difference Soil Index) showed higher accuracy than the Soil Index (SI) developed in previous studies. Then, the lowest values of RMSE were less than 100 mS/m in NDSI. As a result, HISUI data could not leach to map soil salinity at lower levels in this study. However, it showed the potential to estimate it with higher accuracy using hyperspectral data.