Mark van der Meijde

Thermal Infrared Spectrometer for Earth Science Remote Sensing Applications—Instrument Modifications and Measurement Procedures

In this article we describe a new instrumental setup at the University of Twente Faculty ITC with an optimized processing chain to measure absolute directional-hemispherical reflectance values of typical earth science samples in the 2.5 to 16 μm range. A Bruker Vertex 70 FTIR spectrometer was chosen as the base instrument. It was modified with an external integrating sphere with a 30 mm sampling port to allow measuring large, inhomogeneous samples and quantitatively compare the laboratory results to airborne and spaceborne remote sensing data. During the processing to directional-hemispherical reflectance values, a background radiation subtraction is performed, removing the effect of radiance not reflected from the sample itself on the detector. This provides more accurate reflectance values for low-reflecting samples. Repeat measurements taken over a 20 month period on a quartz sand standard show that the repeatability of the system is very high, with a standard deviation ranging between 0.001 and 0.006 reflectance units depending on wavelength. This high level of repeatability is achieved even after replacing optical components, re-aligning mirrors and placement of sample port reducers. Absolute reflectance values of measurements taken by the instrument here presented compare very favorably to measurements of other leading laboratories taken on identical sample standards.

A Spatial-Spectral Approach for Visualization of Vegetation Stress Resulting from Pipeline Leakage

Hydrocarbon leakage into the environment has large economic and environmental impact. Traditional methods for investigating seepages and their resulting pollution, such as drilling, are destructive, time consuming and expensive. Remote sensing is an efficient tool that offers a non-destructive investigation method. Optical remote sensing has been extensively tested for exploration of onshore hydrocarbon reservoirs and detection of hydrocarbons at the Earths surface. In this research, we investigate indirect manifestations of pipeline leakage by way of visualizing vegetation anomalies in airborne hyperspectral imagery. Agricultural land-use causes a heterogeneous landcover; variation in red edge position between fields was much larger than infield red edge position variation that could be related to hydrocarbon pollution. A moving and growing kernel procedure was developed to normalzie red edge values relative to values of neighbouring pixels to enhance pollution related anomalies in the image. Comparison of the spatial distribution of anomalies with geochemical data obtained by drilling showed that 8 out of 10 polluted sites were predicted correctly while 2 out of 30 sites that were predicted clean were actually polluted.

Impact of DEM source and resolution on topographic seismic amplification

Abstract The impact of topographic attributes on the uneven distribution of seismic response and associated devastation has frequently been observed and documented during seismic events, but has rarely been investigated at a regional scale. Existing numerical and experimental techniques applied to explore the impact of topographic attributes in the aggravation of seismic response, have been limited to isolated and/or synthetic hills and ridges. Predicting the realistic regional impact of topographic seismic response is strongly dependent on the resolution and accuracy of regional topographic information. This study evaluates the topographic attributes and seismic parameters computed from multi-resolution and source DEMs, to investigate the impact of data source and resolution on the derived topographic seismic response. Methodologies are developed to readily derive the spatial distribution of relevant topographic attributes and seismic parameters, utilizing the multi-resolution and source DEMs. The impact of DEM source and resolution on slope gradient, relative height of terrain and shear wave velocity ( V S 30 ) are addressed. It is observed that, even though, relatively coarse resolution DEMs underestimate the critical sites of steep slope gradient and the lower V S 30 zones, this has limited impact on the derived normalized topographic aggravation factor. The free and easily accessible DEMs provide an opportunity for reasonable prediction of topographic seismic response, especially in near-real time. The slope gradient is observed to be the most sensitive topographic attribute to amplified seismic response, followed by the relative height.

Evaluating the feasibility of multitemporal hyperspectral remote sensing for monitoring bioremediation

Abstract In recent years, several studies focused on the detection of hydrocarbon pollution in the environment using hyperspectral remote sensing. Particularly the indirect detection of hydrocarbon pollution, using vegetation reflectance in the red edge region, has been studied extensively. Bioremediation is one of the methods that can be applied to clean up polluted sites. So far, there have been no studies on monitoring of bioremediation using (hyperspectral) remote sensing. This study evaluates the feasibility of hyperspectral remote sensing for monitoring the effect of bioremediation over time. Benzene leakage at connection points along a pipeline was monitored by comparing the red edge position (REP) in 2005 and 2008 using HyMap airborne hyperspectral images. REP values were normalized in order to enhance local variations caused by a change in benzene concentrations. 11 out of 17 locations were classified correctly as remediated, still polluted, or still clean, with a total accuracy of 65%. When only polluted locations that were remediated were taken into account, the (users) accuracy was 71%.

Adjusting Spectral Indices for Spectral Response Function Differences of Very High Spatial Resolution Sensors Simulated from Field Spectra

The use of data from multiple sensors is often required to ensure data coverage and continuity, but differences in the spectral characteristics of sensors result in spectral index values being different. This study investigates spectral response function effects on 48 spectral indices for cultivated grasslands using simulated data of 10 very high spatial resolution sensors, convolved from field reflectance spectra of a grass covered dike (with varying vegetation condition). Index values for 48 indices were calculated for original narrow-band spectra and convolved data sets, and then compared. The indices Difference Vegetation Index (DVI), Global Environmental Monitoring Index (GEMI), Enhanced Vegetation Index (EVI), Modified Soil-Adjusted Vegetation Index (MSAVI2) and Soil-Adjusted Vegetation Index (SAVI), which include the difference between the near-infrared and red bands, have values most similar to those of the original spectra across all 10 sensors (1:1 line mean 1:1R2 > 0.960 and linear trend mean ccR2 > 0.997). Additionally, relationships between the indices’ values and two quality indicators for grass covered dikes were compared to those of the original spectra. For the soil moisture indicator, indices that ratio bands performed better across sensors than those that difference bands, while for the dike cover quality indicator, both the choice of bands and their formulation are important.

Investigation of Remote Sensing for Potential Use in Dike Inspection

Dikes are critical barriers against storm surges, sea level rise, and flooding by rivers. Monitoring of these structures is most often done by visual inspection. This paper investigates remote sensing as a tool to facilitate the dike inspection process for grass-covered dikes. Two inspection criteria were considered, namely soil moisture and the quality of the dike cover. Four types of remote sensing data were used, obtained in a ground-based campaign with hand-held sensors. These were thermal, visible, multispectral, and hyperspectral remote sensing data. Relationships were found between the remote sensing data and the inspection criteria. In particular, afternoon thermal remote sensing data showed a negative correlation to soil moisture and broadband multispectral remote sensing data, especially using the near-infrared band, showed a negative correlation to dike cover quality. Limitations for the use of thermal remote sensing are also discussed.

Study of Volcanic Activity at Different Time Scales Using Hypertemporal Land Surface Temperature Data

We apply a method for detecting subtle spatiotemporal signal fluctuations to monitor volcanic activity. Whereas midwave infrared data are commonly used for volcanic hot spot detection, our approach utilizes hypertemporal longwave infrared-based land surface temperature (LST) data. Using LST data of the second-generation European Meteorological Satellites, we study (a) a paroxysmal, 1 day long eruption of Mount Etna (Italy); (b) a prolonged, 6 month period of effusive and lateral lava flows of the Nyamuragira volcano (Democratic Republic of Congo); and (c) intermittent activity in the permanent lava lake of Nyiragongo (Democratic Republic of Congo) over a period of 2 years (2011-2012). We compare our analysis with published ground-based observations and satellite-based alert systems; results agree on the periods of increased volcanic activity and quiescence. We further apply our analysis on mid-infrared and long-infrared brightness temperatures and compare the results. We conclude that our study enables the use of LST data for monitoring volcanic dynamics at different time scales, can complement existing methodologies, and allows for use of long time series from older sensors that do not provide midwave infrared data.