Legacy product - no abstract available

Legacy product - no abstract available

How much easier it would be to map and quantify the key elements of the hydrological cycle if the Earth's surface was transparent! Unfortunately, this is not the case and it is this very inability to penetrate to sufficient depths to map and quantify groundwater components of the hydrological cycle that currently necessitates the integration of satellite- airborne- and ground observations. In Australia, important advances have been made in the last 3 years in quantifying key elements of the hydrological cycle. This has been achieved in part through the increased use of Landsat, MODIS, SPOT, hyperspectral, NOAA and LiDAR datasets to improve the mapping and quantification of surface water, evapotranspiration, soil moisture and recharge and discharge. However, significant limitations remain in using satellite-based platforms alone for quantifying catchment water balances, surface-groundwater interactions, groundwater resource estimation and managing groundwater dependent ecosystems. Increasingly, the need to map the key elements of the hydrological cycle to calibrate water balance models and for environmental management, is leading to the development of more holistic systems approaches, involving the integration of satellite-, airborne and ground-based techniques and measurements. One example is in the River Murray Corridor (RMC) in SE Australia, where previous attempts to assess the water needs for iconic floodplain wetland ecosystems, based largely on satellite-based measurements, did not adequately take into account sub-surface soil conditions and groundwater quality and processes. In floodplain environments such as the River Murray Floodplain, the factors that govern tree health are invariably complex, and include a wide range of biophysical and biogeochemical factors.

Legacy product - no abstract available

Legacy product - no abstract available

No abstract available

We measured the light absorption properties of two naturally occurring Australian hydrocarbon oils, a Gippsland light crude oil and a North West Shelf light condensate. Using these results in conjunction with estimated sensor environmental noise thresholds, the theoretical minimum limit of detectability of each oil type (as a function of oil thickness) was calculated for both the hyperspectral HYMAP and multispectral Quickbird sensors. The Gippsland crude oil is discernable at layer thickness of 20 micro metres or more in the Quickbird green channel. The HYMAP sensor was found to be theoretically capable of detecting a layer of Gippsland crude oil with a thickness of 10 micro metres in approximately six sensor channels. By contrast, the North West Shelf light condensate was not able to be detected by either sensor for any thickness up to 200 icro metres. Optical remote sensing is therefore not applicable for detecting diagnostic absorption features associated with this light condensate oil type, which is considered representative for the prospective Australian Northwest Shelf area. We conclude that oil type is critical to the applicability of optical remote sensing for natural oil slick detection and identification. We recommend that a sensor- and oil-specific sensitivity study should be conducted prior to applying optical remote sensors for oil exploration. The oil optical properties were obtained using two different laboratory methods, a reflectance-based approach and transmittance-based approach. The reflectance-based approach was relatively complex to implement, but was chosen in order to replicate as closely as possible real world remote sensing measurement conditions of an oil film on water. The transmittance-based approach, based upon standard laboratory spectrophotometric measurements was found to generate results in good agreement with the reflectance-based approach. Therefore, for future oil- and sensor-specific sensitivity studies, we recommend the relatively accessible transmittance-based approach, which is detailed in this paper.

Legacy product - no abstract available

This document defines the Computer Compatible Tape (CCT) format for raw, quicklook, bulk-corrected (georeferenced) system-corrected and precision processed Landsat Thematic Mapper (TM) imagery data acquired from the Landsat 4, Landsat 5 and subsequent satellites.

DIGITAL NUMBER TO RADIANCE CALIBRATION CONSTANTS FOR ACRES LANDSAT MULTISPECTRAL SCANNER DATA