En México, la CONAFOR es el organismo público responsable del monitoreo y cuantificación anual de los incendios de vegetación, aunque estos incendios también pueden registrarse a través de los puntos de calor del sensor MODIS. Los estados de Guanajuato y Querétaro se ubican en el centro del país, principalmente sobre el Desierto Chihuahuense, que ha sufrido los últimos años de sequía severa y extensa. El objetivo de este artículo es evaluar cuantitativa y comparativamente, los incendios de vegetación históricos reportados por CONAFOR con respecto a MODIS, entre los años 2000 y 2024, en los estados de Querétaro y Guanajuato. Las comparaciones entre los registros de los incendios de CONAFOR y MODIS fueron realizadas con respecto a su tendencia temporal, datos climáticos (temperatura y precipitación), patrones espaciales, puntos calientes (hotspots) y fríos (cold spots), y tipos de vegetación. En ambos estados se encontró una tendencia general al aumento en el número de incendios de vegetación con el tiempo, aunque no necesariamente de la superficie quemada; donde la mayor cantidad de incendios se registró entre marzo y abril, relacionados con la temporada más seca del año, confirmada por el aumento de la temperatura y el descenso de la precipitación. Los hotspots se concentraron en el norte y suroeste de ambos estados, mientras que los coldspots mostraron diferencias dependiendo de la fuente de datos y del estado. La correlación entre hotspots y coldspots de ambas fuentes de datos fue ligeramente positiva. Los hotspots coincidieron espacialmente con algunos municipios donde hay producción intensiva de agave para mezcal y tequila, y donde se ha reportado que los hornos de carbón pueden estar condicionando la incidencia de incendios. Los tipos de vegetación más afectados durante todo el periodo de tiempo estudiado fueron el bosque de encino y la selva baja caducifolia. El estudio de la dinámica temporal de los incendios de vegetación en Guanajuato y Querétaro reveló varios patrones fundamentales, aunque dependiendo de la fuente de datos, pueden mostrar discrepancias, por lo que la integración de múltiples fuentes de información es crucial para mejorar la precisión y comprensión de la dinámica de estos incendios.

This study assessed the potential of the ASCAT SSM 6.25 km product for agricultural drought monitoring across Mexico. The drought monitoring in Mexico currently relies on precipitation-based indices, without considering the use of in situ soil moisture observations and satellite-derived soil moisture products. To evaluate the performance, cross-validation was performed between ASCAT, ERA5-Land, and ESA CCI soil moisture products for assessing correlations under varying climatic and land cover conditions. Furthermore, drought indicators, including SMAPI and SPEI, were calculated and compared against the SPI from the Mexican Drought Monitor to evaluate the assessment during drought events. Results showed strong potential of ASCAT SSM in central and northeastern Mexico, while arid regions exhibited low correlation due to subsurface scattering effects. Otherwise, soil moisture anomalies derived from ASCAT aligned well with precipitation anomalies outside arid zones. In conclusion, ASCAT SSM 6.25 km demonstrates significant potential for integration into Mexico’s drought monitoring systems as drought indicators based on ASCAT effectively captured precipitation deficits and drought conditions, mirroring SPI patterns reported by national monitoring agencies.

The rise in global temperatures has become a concern as every year reaches new record high temperatures and heat wave occurrences are more common. Alongside with this, worldwide population has also increased, resulting in highly urbanized areas where mitigation and adaptation to extreme heat has only just started to be considered in order to improve citizens quality of life and health. The Monterrey Metropolitan Area is characterized by semi-arid climate conditions which pose significant environmental challenges related to environmental resilience and recently, extreme heat conditions. In this research, the heat wave occurrences of 2023 and 2024 in Monterrey were evaluated using the Heat Index (HI) metric, information from the Air Quality and Climate Monitoring Network of Nuevo León and satellite temperature imagery from the Mexican National Meteorological Service in order to determine the most vulnerable areas and the health threats that high temperatures may cause. The results indicate that Heat Index values depend on relative humidity percentages besides temperature, as higher humidity levels are linked to an increase in HI. The Monterrey Metropolitan Area can experience HI of more than 30°C, making the risk of heat stress most likely to occur. It is recommended to the population to be extremely cautious if exposed to the heat for long periods of time and to avoid outdoor activities if possible if the Heat Index exceeds the 41°C.

Synthetic Aperture Radar (SAR) imagery provides robust Earth observation capabilities under all-weather and day-night conditions; however, its side-looking geometry introduces geometric distortions that must be corrected through orthorectification. A Digital Elevation Model (DEM) is central to this correction, and its vertical accuracy directly affects the geolocation precision of SAR products. This study evaluates the influence of DEM accuracy on Sentinel-1 Ground Range Detected (GRD) imagery within an urban district of Ankara, Türkiye. Six DEMs were analyzed, including four publicly available models (SRTM 1″, SRTM 3″, ALOS AW3D30, and YÜKPAF) and two InSAR-derived DEMs generated from Sentinel-1 Single Look Complex (SLC) pairs. Vertical accuracy was assessed using 495 ICESat-2 ATL08 elevation points, while horizontal accuracy was evaluated against high-precision Ground Control Points (GCPs) from the HGM Küre platform. Results show that Copernicus DEM achieved the highest vertical accuracy (RMSE 2.2 m), while YÜKPAF delivered the best horizontal geolocation performance (RMSE 8.2 m). Conversely, InSAR-derived DEMs exhibited lower accuracy due to coherence loss and phase unwrapping errors, with horizontal RMSE values exceeding 15 m. Findings highlight the strong dependence of SAR geolocation performance on DEM quality and emphasize the importance of selecting reliable elevation data to ensure spatial fidelity in geospatial applications.