Temporal patterns of active fire density and its relationship with a satellite fuel greenness index by vegetation type and region in Mexico during 2003-2014

Background: Understanding the temporal patterns of fire occurrence and their relationships with fuel dryness is key to sound fire management, especially under increasing global warming. At present, no system for prediction of fire occurrence risk based on fuel dryness conditions is available in Mexico. As part of an ongoing national-scale project, we developed an operational fire risk mapping tool based on satellite and weather information. Results: We demonstrated how differing monthly temporal trends in a fuel greenness index, dead ratio (DR), and fire density (FDI) can be clearly differentiated by vegetation type and region for the whole country, using MODIS satellite observations for the period 2003 to 2014. We tested linear and non-linear models, including temporal autocorrelation terms, for prediction of FDI from DR for a total of 28 combinations of vegetation types and regions. In addition, we developed seasonal autoregressive integrated moving average (ARIMA) models for forecasting DR values based on the last observed values. Most ARIMA models showed values of the adjusted coefficient of determination (R2 adj) above 0.7 to 0.8, suggesting potential to forecast fuel dryness and fire occurrence risk conditions. The best fitted models explained more than 70% of the observed FDI variation in the relation between monthly DR and fire density. Conclusion: These results suggest that there is potential for the DR index to be incorporated in future fire risk operational tools. However, some vegetation types and regions show lower correlations between DR and observed fire density, suggesting that other variables, such as distance and timing of agricultural burn, deserve attention in future studiesAntecedentes: Una adecuada planificación del manejo del fuego requiere de la comprensión de los patrones temporales de humedad del combustible y su influencia en el riesgo de incendio, particularmente bajo un escenario de calentamiento global. En la actualidad en México no existe ningún sistema operacional para la predicción del riesgo de incendio en base al grado de estrés hídrico de los combustibles. Un proyecto de investigación nacional actualmente en funcionamiento, tiene como objetivo el desarrollo de un sistema operacional de riesgo y peligro de incendio en base a información meteorológica y de satélite para México. Este estudio pertenece al citado proyecto Resultados: Se observaron en el país distintas tendencias temporales en un índice de estrés hídrico de los combustibles basado en imágenes MODIS, el índice “dead ratio” (DR), y en las tendencias temporales de un ìndice de densidad de incendios (FDI), en distintos tipos de vegetación y regiones del país. Se evaluaron varios modelos lineales y potenciales, incluyendo términos para la consideración de la autocorrelación temporal, para la predicción de la densidad de incendios a partir del índice DR para un total de 28 tipos de vegetación y regiones. Se desarrollaron además modelos estacionales autoregresivos de media móvil (ARIMA en inglés) para el pronóstico del índice DR a partir de los últimos valores observados. La mayoría de los modelos ARIMA desarrollados mostraron valores del coeficiente de determinación ajustado (R2 adj) por encima de 0.7 to 0.8, sugiriendo potencial para ser empleados para un pronóstico del estrés hídrico de los combustibles y las condiciones de riesgo de ocurrencia de incendio. Con respecto a los modelos que relacionan los valores mensuales de DR con FDI, la mayoría de ellos explicaron más del 70% de la variabilidad observada en FDI. Conclusiones: Los resultados sugirieron potencial del índice DR para ser incluido en futuras herramientas operacionales para determinar el riesgo de incendio. En algunos tipos de vegetación y regiones se obtuvieron correlaciones más reducidas entre el índice DR y los valores observados de densidad de incendios, sugiriendo que el papel de otras variables tales como la distancia y el patrón temporal de quemas agrícolas debería ser explorado en futuros estudiosFunding for this work was provided by CONAFOR-CONACYT Project 252620 “Development of a Fire Danger System for Mexico.” This work was also cofinanced by the Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria and European Social Fund (Dr. E. Jiménez grant)S

Monitoring holopelagic Sargassum spp. along the Mexican Caribbean coast: understanding and addressing user requirements for satellite remote sensing

Massive influxes of holopelagic Sargassum spp. (Sargassum natans and S. fluitans) have been causing major economic, environmental and ecological problems along the Caribbean coast of Mexico. Predicting the arrival of the sargassum as an aid to addressing these problems is a priority for the government, coastal communities and the society; both mitigating the impacts and providing opportunities for its use. Lack of data concerning precise locations and times of sargassum beachings means that public and private funds are being spent inefficiently and most actions are reactive. The dynamic nature of sargassum beachings/influxes render conventional ground-based monitoring insufficient. Earth observation and cloud-based processing services offer tools to track, quantify and understand sargassum beaching remotely in a frequent, systematic and reliable manner with the temporal and spatial resolutions required for its management. In order to find the right solutions to address this problem, in this paper the needs and requirements of stakeholders are taken into consideration for the development of an Earth observation-based service to monitor sargassum along the Mexican Caribbean coast. Routine monitoring of sargassum over a large area will be cost effective and help mitigate the negative effects of sargassum influxes. The combination of imagery from Planet, specifically their SuperDove systems that provide daily data at 3 m spatial resolutions, with the freely available EU Copernicus data would be useful for many different stakeholders and potential users. A prototype of the service is presented, based on the main user requirements. The system would enable public and private organizations to allocate resources appropriately in affected areas quickly and efficiently, thereby minimizing economic, social and environmental impacts and enhancing the resilience of local communities. It would also assist the sargassum industry in the collection of fresh algae for onward processing. The system could easily be implemented for similar types of environmental monitoring in the Greater Caribbean and beyond

Fernerkundungs- und GIS-gestützte Optimierung des Bewässerungsfeldbaus am Amu-Darja-Unterlauf und in seinem Delta

Die Arbeit illustriert die wissenschaftliche Anwendung der Satellitenfernerkundung und von GIS-Verfahren für die Optimierung des Bewässerungsfeldbaus im Unterlauf des Amu-Darja und in seinem Delta. Ziel ist die Senkung des agrarischen Wasserverbrauchs durch alternative Landnutzungsmodelle und die Schaffung eines Monitoring-Instruments für die ökologische Entwicklung der Region

Morphological changes in the Aral Sea. Satellite imagery and water balance model.

The Aral Sea, once the worlds fourth largest lake, has suffered a dramatic loss of both area and volume, as a result of greatly reduced river inflow brought about by increasing irrigation (mainly of cotton and rice) along the two rivers, Amu Darja and Syr Darja, that flow into it. The ecological consequences are severe and have been discussed in a variety of scientific publications (Micklin, 1991 and 2000, Giese, 1998, Letolle, & Mainguet, 1996). Satellite images have helped to monitor and document the desiccation process and to describe the associated morphological changes. This includes changes of the water body itself as well as the related changes of the surrounding environment and plant communities, such as the newly formed desert areas like the so-called Aral Kum. Low spatial resolution data such as NOAA-AVHRR has proven to be valuable to monitor the desiccation on a frequent basis. The use of high resolution satellite data has been limited for morphological change studies due to higher costs (Resurs-MSU-SK/E, Landsat-TM) and only partial coverage of the lake surface. New satellite systems such as Terra-MODIS are useful because of full coverage of the lake, easy access on a daily basis and provision to researchers at no cost. Besides remote sensing data, GIS modelling techniques have proven to be a useful tool for forecasting the desiccation process of the Aral Sea under specific circumstances. Several probable water inflow scenarios have been assumed to forecast the future desiccation of the lake. Further investigations will include automatic change detection and automated monitoring of the desiccation process