The Addition of Temperature Significantly Improves the Detection of Land Degradation in Cold Drylands Using the TSS-RESTREND Methodology

Cold drylands make up 20% of the world's water limited regions. This paper presents a modification to the Time Series Segmented – RESidual TRENDs (TSS-RESTREND) method which allows for the use of temperature as an additional explanatory variable along with precipitation. TSS-RESTREND was performed over Mongolia both with and without temperature. The addition of temperature reduced the number of pixels that fail the significance tests built into the TSS-RESTREND method from 17% to below 5%. It also improved the statistical confidence in almost all areas. Furthermore, the direction of change is consistent with previous findings that looked at vegetation trends over the same study region.

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