Statistical Analysis of Geoscience Data

Z., Y.

doi:10.1007/978-3-030-17860-4_3

Cited by 1 publication

(2 citation statements)

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“…The statistical significance threshold to identify robust evidence that the detection of degraded pixels is affected by drought was 5% (i.e., p-value ≤0.05). The non-parametric Dunn's test with adjusted p-values via the Bonferroni method (Ma, 2019) further refined the comparison. These statistical tests were chosen because they do not require the assumption of normality in the stratified data (Boschetti et al, 2006).…”

Section: Comparison Between the Drought Severity And Land Degradationmentioning

confidence: 99%

“…These statistical tests were chosen because they do not require the assumption of normality in the stratified data (Boschetti et al, 2006). Both non-parametric tests were implemented with the R package stats In order to explore if degraded/not degraded pixels show significant differences in drought severity Ma (2019) 2. The H statistic is calculated as:…”

Section: Comparison Between the Drought Severity And Land Degradationmentioning

confidence: 99%

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Drought variability and land degradation in the Amazon River basin

et al. 2022

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The Amazon River Basin (ARB) plays an essential role in global climate regulation. Recent studies have revealed signs of increasing drought conditions in different parts of the basin. Although human activities have degraded large areas, little work has been done to assess whether prolonged drought may exacerbate land degradation. Among different methods for monitoring land degradation, the Sustainable Development Goal (SDG) indicator 15.3.1 adopted by the United Nations Convention to Combat Desertification (UNCCD) allows a comprehensive assessment of the impacts of land degradation due to its multi-factor nature and scalability. The aims of this study are twofold: 1) to assess the status of land degradation using the SDG indicator 15.3.1 from 2001 to 2020 in the Amazon basin; and 2) to explore the relationship between the detectability of land degradation using the UNCCD approach and long-term drought severity. The Standardized Precipitation Index (SPI), Standardized Precipitation-Evapotranspiration Index (SPEI), and self-calibrating Palmer Drought Severity Index (scPDSI) were used as drought indices. The results revealed 757,704 km2 (12.67% of the basin) as degraded land, which was reflected by a downward trend in land productivity dynamics followed by the combined downward trend in land productivity, Soil Organic Carbon (SOC) degradation, and land cover degradation. The largest land degradation hotspot was identified along the southwestern boundary of the Amazon River Basin. Furthermore, there was strong evidence that the detection of land degradation through SDG indicator 15.3.1 is sensitive to long-term drought, particularly when applied to rainfed croplands.

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Section: Comparison Between the Drought Severity And Land Degradationmentioning

confidence: 99%

Section: Comparison Between the Drought Severity And Land Degradationmentioning

confidence: 99%