Spatial Mapping of Thermal Anomalies and Change Detection in the Sierra Madre Occidental, Mexico, from 2000 to 2024

Sandoval Sarahi and Escobar-Flores Jonathan Gabriel ()
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Sandoval Sarahi: SECIHTI, Instituto Politécnico Nacional, Durango 34220, DG, Mexico
Escobar-Flores Jonathan Gabriel: CIIDIR Durango, Instituto Politécnico Nacional, Durango 34220, DG, Mexico

Land, 2025, vol. 14, issue 8, 1-19

Abstract: We quantified monthly changes in land surface temperature (LST) over the Sierra Madre Occidental (SMO) in Mexico from 2000 to 2024 using MODIS satellite imagery (MOD11B3). The SMO is the longest continuous mountain complex in Mexico, covering an area of 251,648 km 2 . It is an area of great importance for biodiversity conservation, as it is home to numerous endemic flora and fauna species. The Intergovernmental Panel on Climate Change (IPCC) has stated that high mountain areas are among the regions most affected by climate change and are a key element of the water cycle. We calculated an anomaly index by vegetation type in the SMO and applied change detection to spatially identify where changes in LST had taken place. The lowest LST values were in December and January (20 to 25 °C), and the highest LST values occurred in April, May, and June (>40 °C). Change detection applied to the time series showed that the months with the highest positive LST changes were May to July, and that November was notable for increases of up to 5.86 °C. The time series that showed the greatest changes compared to 2000 was the series for 2024, where LST increases were found in all months of the year. The maximun average increase was 6.98 °C from 2000 to June 2005. In general, LST anomalies show a pattern of occurrence in the months of March through July for the three vegetation types distributed in the Sierra Madre Occidental. In the case of the pine forest, which is distributed at 2000 m above sea level, and higher, it was expected that there would be no LST anomalies; however, anomalies were present in all time series for the spring and early summer months. The LST values were validated with in situ data from weather stations using linear regression models. It was found that almost all the values were related, with R 2 > 0.60 ( p < 0.001). In conclusion, the constant increases in LST throughout the SMO are probably related to the loss of 34% of forest cover due to forest fires, logging, land use changes, and increased forest plantations.

Keywords: temperate forest; land surface temperature; MODIS; remote sensing (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
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