Detection of Geothermal Anomalies in Hydrothermal Systems Using ASTER Data: The Caldeiras da Ribeira Grande Case Study (Azores, Portugal)

ABSTRACT: Current-day volcanic activity in the Azores archipelago is characterized by seismic events and secondary manifestations of volcanism. Remote sensing techniques have been widely employed to monitor deformation in volcanic systems, map lava flows, or detect high-temperature gas emissions. However, using satellite imagery, it is still challenging to identify low-magnitude thermal changes in a volcanic system. In 2010, after drilling a well for geothermal exploration on the northern flank of Fogo Volcano on São Miguel Island, a new degassing and thermal area emerged with maximum temperatures of 100 °C. In the present paper, using the ASTER sensor, we observed changes in the near-infrared signals (15 m spatial resolution) six months after the anomaly emerged. In contrast, the thermal signal (90 m spatial resolution) only changed its threshold value one and a half years after the anomaly was recognized. The results show that wavelength and spatial resolution can influence the response time in detecting changes in a system. This paper reiterates the importance of using thermal imaging and high spatial resolution images to monitor and map thermal anomalies in hydrothermal systems such as those found in the Azores.info:eu-repo/semantics/publishedVersio

Monitoring Glyphosate-Based Herbicide Treatment Using Sentinel-2 Time Series—A Proof-of-Principle

In this paper we aim to show a proof-of-principle approach to detect and monitor weed management using glyphosate-based herbicides in agricultural practices. In a case study in Germany, we demonstrate the application of Sentinel-2 multispectral time-series data. Spectral broadband vegetation indices were analysed to observe vegetation traits and weed damage arising from herbicide-based management. The approach has been validated with stakeholder information about herbicide treatment using commercial products. As a result, broadband NDVI calculated from Sentinel-2 data showed explicit feedback after the glyphosate-based herbicide treatment. Vegetation damage could be detected after just two days following of glyphosate-based herbicide treatment. This trend was observed in three different application scenarios, i.e., during growing stage, before harvest and after harvest. The findings of the study demonstrate the feasibility of satellite based broadband NDVI data for the detection of glyphosate-based herbicide treatment and, e.g., the monitoring of latency to harvesting. The presented results can be used to implement monitoring concepts to provide the necessary transparency about weed treatment in agricultural practices and to support environmental monitoring

Vegetation Phenology as a Function of Plant Functional Type and Urbanization

Urban land cover contributes to higher temperatures in urban areas compared to adjacent rural areas, which can cause an earlier start of the growing season for urban vegetation. Variations in plant community characteristics between urban and rural areas also produce intra-urban differences in vegetation phenophases, although few studies have investigated differences in phenology between plant functional types in multiple urban environments. In this study I used an exploratory analysis based on the Landsat Phenology Algorithm and weather station data to quantify differences in leaf-onset dates for different plant functional types in the New York City Metropolitan Area. The results demonstrate that Landsat can be used to identify urban-rural variations in leaf-onset for different plant functional types, and that these variations are driven by different climate variables depending on plant functional type. Furthermore, results from such analyses suggest that long-term changes in leaf onset vary across different plant functional types—i.e., grasslands may be advancing at a different rate than forests