The Addition of Temperature to the TSS-RESTREND Methodology Significantly Improves the Detection of Dryland Degradation
Autor: | Arden L. Burrell, Yi Liu, Jason P. Evans |
---|---|
Rok vydání: | 2019 |
Předmět: |
Atmospheric Science
010504 meteorology & atmospheric sciences Land use 0208 environmental biotechnology Central asia 02 engineering and technology Vegetation 15. Life on land 01 natural sciences Statistical Confidence 020801 environmental engineering 13. Climate action Environmental science Degradation (geology) Ecosystem Physical geography Precipitation Computers in Earth Sciences 0105 earth and related environmental sciences |
Zdroj: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 12:2342-2348 |
ISSN: | 2151-1535 1939-1404 |
DOI: | 10.1109/jstars.2019.2906466 |
Popis: | 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-RESTRENDs) method that 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. When applied to all of the world's drylands, the inclusion of temperature improved the fit of the vegetation–climate relationship that underpins TSS-RESTREND in 98.8% of areas. The largest improvements to the fit were observed in both the cold drylands of central Asia and North America and the hot drylands of southern Australia. Including temperature also reduced the fraction of global vegetation change that could be attributed to neither climate nor land use from 25.5% to 15.5%. |
Databáze: | OpenAIRE |
Externí odkaz: |