Improper use of land resources may result in severe soil salinization. Timely monitoring and early warning of soil salinity is in urgent need for sustainable development. This paper addresses the possibility and potential of Advanced Land Imager (ALI) for mapping soil salinity. In situ field spectra and soil salinity data were collected in the Yellow River Delta, China. Statistical analysis demonstrated the importance of ALI blue and near infrared (NIR) bands for soil salinity. A partial least square regression (PLSR) model was established between soil salinity and ALI-convolved field spectra. The model estimated soil salinity with a R2 (coefficient of determination), RPD (ratio of prediction to deviation), bias, standard deviation (SD) and root mean square error (RMSE) of 0.749, 3.584, 0.036 g∙kg−1, 0.778 g∙kg−1 and 0.779 g∙kg−1. The model was then applied to atmospherically corrected ALI data. Soil salinity was underestimated for moderately (soil salinity within 2–4 g∙kg−1) and highly saline (soil salinity >4 g∙kg−1) soils. The underestimates increased with the degree of soil salinization, with a maximum value of ~4 g∙kg−1. The major contribution for the underestimation (>80%) may result from data inaccuracy other than model ineffectiveness. Uncertainty analysis confirmed that improper atmospheric correction contributed to a very conservative uncertainty of 1.3 g∙kg−1. Field sampling within remote sensing pixels was probably the major source responsible for the underestimation. Our study demonstrates the effectiveness of PLSR model in retrieving soil salinity from new-generation multi-spectral sensors. This is very valuable for achieving worldwide soil salinity mapping with low cost and considerable accuracy.
1 November 2016 in ISPRS Journal of Photogrammetry and Remote Sensing
Compound drought–heatwaves (CDHWs) accelerate the warming and drying of soils, triggering soil compound drought–heatwaves (SCDHWs) that jeopardize the health of soil ecosystems. Nevertheless, the behavior of these events worldwide and their responses to climatic warming are underexplored. Here, we show a global escalation in the frequency, duration, peak intensity, and severity of SCDHWs, as well as an increase in affected land area, from 1980 to 2023. The increasing trends, which are particularly prominent since the early 2000 s, and projected to persist throughout this century, are dominated by summertime SCDHWs and enhanced by El Niño. Intensive soil warming as well as climatologically lower soil temperatures compared to air temperatures lead to localized hotspots of escalating SCDHW severity in northern high latitudes, while prolonged duration causes such hotspots in northern South America. Transformation of natural ecosystems, particularly forests and wetlands, to cropland as well as forest degradation substantially enhance the strength of SCDHWs. Global SCDHWs consistently exhibit higher frequencies, longer durations, greater severities, and faster growth rates than CDHWs in all aspects from 1980 to 2023. They are undergoing a critical transition, with droughts replacing heatwaves as the primary constraint. We emphasize the significant intensification of SCDHWs in northern high latitudes as well as the prolonged duration of SCDHWs in the Southern Hemisphere, posing an underrated threat to achieving carbon neutrality and food security goals.