ABSTRACT
The availability of extremely high resolution images offers an unprecedented opportunity to use such images to monitor, maintain and ultimately preserve and rehabilitate the natural environment throughout the life cycle of oil and gas projects. The variety of images available range from optical images such as Landsat ETM1 imagery (14.25 meter/pixel), IKONOS2 imagery (1 meter/pixel) and QuickBird3 imagery (0.6 meter/pixel). These optical images have sufficient spatial and spectral resolution to detect different vegetation types (e.g. old growth vs. new plantations), cleared vegetation caused by logging or human habitat expansion, burned areas due to fire and vegetation stress caused by spills from oil pipelines or storage vessels. These images are also useful for identifying potential pollutant sources such as abandoned wells, old drilling pits or other remediation targets, as well as potential pollutant receptors. Areas which have perpetual cloud cover, such as South Sumatra, of Indonesia, can be monitored using Synthetic Aperture Radar (e.g. European Space Agency's Synthetic Aperture Radar and RadarSat International of Canada). Although a typical SAR does not have the spectral resolution of optical sensors, it does have the advantage of seeing through clouds. The radar backscatter is sensitive to surface roughness and Dielectric Constant which can be used quite effectively to discriminate major vegetation types.
These images, when combined with normal GIS tools, take us beyond simple monitoring, to generating predictive tools for planning future sites for drilling wells and placement of facilities such as pipelines and roads. This paper will focus on the use of these techniques for oil spill response planning in South Sumatra, while taking note of other applications of remote sensing and GIS to oil and gas operations in the regional environment.
Efficient Identification of Corn Cultivation Area with Multitemporal Synthetic Aperture Radar and Optical Images in the Google Earth Engine Cloud Platform
