A spatial-spectral approach for visualization of vegetation stress resulting from pipeline leakage

Hydrocarbon leakage into the environment is a major problem with large economic and environmental impacts. Traditional methods for investigating seepage and pollution, such as drilling, are time consuming, destructive and expensive. Remote sensing has proved to be a tool that offers a non-destructive investigation method and has a significant added value to traditional methods. Optical remote sensing has been extensively tested for exploration of onshore hydrocarbon reservoirs and detection of hydrocarbons at the Earth's surface. Theoretically, remote sensing is a suitable tool for direct and indirect detection of the presence of hydrocarbons in the environment. In this research we investigate a leaking pipeline through analysis of hyperspectral imagery (HyMap). Due to inhomogeneous field cover, variations between fields turned out to be much larger than infield variations related to pollution issues. To overcome this problem a spatial-spectral normalization procedure was developed using moving kernels to enhance pollution related anomalies. The final results shows local anomalies which are likely related to hydrocarbon pollution.