Advanced Land Imager Imagery Research Articles

Chronology of the 2014–2016 Eruptive Phase of Volcán de Colima and Volume Estimation of Associated Lava Flows and Pyroclastic Flows Based on Optical Multi-Sensors

The eruption at Volcán de Colima (México) on 10–11 July 2015 represents the most violent eruption that has occurred at this volcano since the 1913 Plinian eruption. The extraordinary runout of the associated pyroclastic flows was never observed during the past dome collapse events in 1991 or 2004–2005. Based on Satellite Pour l’Observation de la Terre (SPOT) and Earth Observing-1 (EO-1) ALI (Advanced Land Imager), the chronology of the different eruptive phases from September 2014 to September 2016 is reconstructed here. A digital image segmentation procedure allowed for the mapping of the trajectory of the lava flows emplaced on the main cone as well as the pyroclastic flow deposits that inundated the Montegrande ravine on the southern flank of the volcano. Digital surface models (DSMs) obtained from SPOT/6 dual-stereoscopic and tri-stereopair images were used to estimate the volumes of some lava flows and the main pyroclastic flow deposits. We estimated that the total volume of the magma that erupted during the 2014–2016 event was approximately 40 × 107 m3, which is one order of magnitude lower than that of the 1913 Plinian eruption. These data are fundamental for improving hazard assessment because the July 2015 eruption represents a unique scenario that has never before been observed at Volcán de Colima. Volume estimation provides complementary data to better understand eruptive processes, and detailed maps of the distributions of lava flows and pyroclastic flows represent fundamental tools for calibrating numerical modeling for hazard assessment. The stereo capabilities of the SPOT6/7 satellites for the detection of topographic changes and the and the availability of EO-1 ALI imagery are useful tools for reconstructing multitemporal eruptive events, even in areas that are not accessible due to ongoing eruptive activity.

Atmospheric correction of high-spatial-resolution satellite images with adjacency effects: application to EO-1 ALI data

Adjacency effects are an interesting physical phenomenon caused by multiple scattering between the atmosphere and the surface. It is necessary to remove adjacency effects in the surface reflectance retrieved from satellite data at a high spatial resolution. In this study, we propose an atmospheric correction method with adjacency effect correction to derive surface reflectance from Earth Observing-1 (EO-1) Advanced Land Imager (ALI) data. Adjacency effects are corrected using an atmospheric point spread function. An analytical expression of the atmospheric point spread function is presented based on a single scattering approximation. This method was applied to ALI imagery acquired through Watershed Airborne Telemetry Experimental Research (WATER) on 20 May 2008. Compared with the surface reflectance before the adjacency effects were corrected for, the surface reflectance after correction exhibited increased between-pixel contrast. Furthermore, the discrepancies between the surface reflectance before and after corrections decreased from the blue band to the shortwave infrared band.

Remote sensing of lake CDOM using noncontemporaneous field data

There are perhaps millions of lakes in Canada, and remote sensing is a crucial tool for making regional estimates of carbon stocks. Estimation using existing platforms has been hampered by both spatial and spectral resolution, but a new generation of sensors promises greatly improved image quality with broad-scale repeat coverage. Nearly all remote sensing studies in aquatic environments include carefully coordinated field campaigns with satellite overpasses, but this greatly limits the number of lakes that can be used in model development. We explored the opportunities and limits for combining high-quality Advanced Land Imager imagery with legacy lake samples to estimate colored dissolved organic matter (CDOM), a lake characteristic of high value in constructing lake carbon budgets. The passage of time produces somewhat greater scatter than in the standard model with timed field campaign, but there is no indication of a bias toward an incorrect model when using field samples from a variety of dates. Because many thousands of older field samples exist for Canadian lakes, existing limnological databases hold considerable value for estimating CDOM from satellite with sensors of sufficient radiometric depth and signal quality. This study reveals a substantial opportunity for creating and refining estimates of fundamental lake parameters in one of the world's great storehouses of aquatic carbon.

Detecting marine intrusion into rivers using EO-1 ALI satellite imagery: Modaomen Waterway, Pearl River Estuary, China

Because of increasing marine intrusion into the Pearl River Estuary (PRE) in China, salinity has become one of the important and necessary hydrological and water quality monitoring parameters. In this research, we examined the relationships between the reflectance from Earth Observing-1 (EO-1) Advanced Land Imager (ALI) satellite imagery and total suspended solids (TSS) based on the synchronous in situ spectra analysis of the river water, in an attempt to detect salinity using remote sensing technique. The study site was the Modaomen Waterway in the PRE, Guangdong Province, China. We found a strong negative linear relationship between in situ reflectance at 549 nm and TSS concentrations (R 2 = 0.91, p < 0.001) when the salinity of the river was less than 1.46‰. It indicates that the TSS near Pinggang and Nanzhen in Modaomen Waterway of PRE tends to be dominated by organic mater carried by the particles and this is one major reason for the inverse relation between reflectance and TSS. Meanwhile, a strong correlation was observed between salinity and TSS (R 2 = 0.70, p < 0.001). The salinity-TSS model accounted for 70% of variation in salinity and allowed the estimation of salinity with a root mean square error (RMSE) of less than 0.036‰ when the TSS concentrations were between 7.4 and 28 mg l−1. Therefore, we were able to develop a new method of detecting surface salinity of the river estuary from the calibrated EO-1 ALI reflectance data. The EO-1 ALI derived surface salinity and TSS concentrations were validated using in situ data that were collected on 18 December 2005, synchronous with EO-1 ALI satellite imagery acquisition. The results showed that the semi-empirical relationships are capable of deducing the TSS concentrations and then salinity from EO-1 ALI imagery in the PRE under low salinity. The methodology of detecting salinity from ALI imagery provides potential to monitor coastal saltwater intrusion and provides the water supply and conservancy authorities with useful spatial information to spatially understand and manage the marine intrusion.

Mapping tropical dry forest height, foliage height profiles and disturbance type and age with a time series of cloud-cleared Landsat and ALI image mosaics to characterize avian habitat

Remote sensing of forest vertical structure is possible with lidar data, but lidar is not widely available. Here we map tropical dry forest height (RMSE = 0.9 m, R 2 = 0.84, range 0.6–7 m), and we map foliage height profiles, with a time series of Landsat and Advanced Land Imager (ALI) imagery on the island of Eleuthera, The Bahamas, substituting time for vertical canopy space. We also simultaneously map forest disturbance type and age. We map these variables in the context of avian habitat studies, particularly for wintering habitat of an endangered Nearctic-Neotropical migrant bird, the Kirtland's Warbler ( Dendroica kirtlandii). We also illustrate relationships between forest vertical structure, disturbance type and counts of forage species important to the Kirtland's Warbler. The ALI imagery and the Landsat time series are both critical to the result for forest height, which the strong relationship of forest height with disturbance type and age facilitates. Also unique to this study is that seven of the eight image time steps are cloud-cleared images: mosaics of the clear parts of several cloudy scenes. We created each cloud-cleared image, including a virtually seamless ALI image mosaic, with regression tree normalization. We also illustrate how viewing time series imagery as red–green–blue composites of tasseled cap wetness ( RGB wetness composites) aids reference data collection for classifying tropical forest disturbance type and age. Our results strongly support current Landsat Program production of co-registered imagery, and they emphasize the value of seamless time series of cloud-cleared imagery.

Tracking subpixel-scale sastrugi with Advanced Land Imager

High radiometric resolution imagery from the Advanced Land Imager (ALI) can detect the spatial reflectance variations associated with sastrugi (snow dunes) on ice sheets. This is shown, in theory, by considering the appropriate SNR ratio of ALI as compared with eight-bit optical sensors and, in practice, with multitemporal ALI imagery. Comparison of ALI imagery spanning 7.5 months also shows that the reflectance pattern associated with sastrugi can persist over this interval offering the potential of their use for measuring ice sheet velocity in uncrevassed regions.