Technology makes Satellite Image Compatibility More Important
Tracking the news recently, it is great to see data from new satellite sensors becoming available. The USDA announced recently that it will begin using imagery from DMCii. First images from DigitalGlobe's Worldview-2 have been released. Certainly exciting times!
Technology and commercial applications typically drive sensor technology advancements to greater spatial resolution, often sacrificing spatial coverage, temporal resolution and spectral resolution. While greater spatial resolution is important and certainly a boon for applications such as Google Maps, Google Earth and other consumer oriented applications, these advancements can make it more challenging for users utilizing imagery for agricultural intelligence, environmental and resource management, land cover mapping etc. The key to many of these applications is finding the right mix of spatial, temporal and spectral resolution. With growing number of sensors available and increasing requirements for greater spatial and spectral coverage, users are increasing challenged with making trade offs in one of these areas.
For example the DMCii imagery, while providing greater combination of spatial and temporal resolution than most sensors, limits the availability of spectral bands to three, impacting the ease of crop and land cover classification, monitoring crop health and crop progress or determining attributes of such as water content or soil moisture.
Ideally every application would like to take advantage of the newest technology. So whats the solution?
More and more users are going to be required to blend imagery from multiple sources and multiple sensors for use in a single application. In order to maintain high accuracy, this blending can only be done by calibrating all the imagery used within an application to a specific level, such as top of atmosphere or surface reflectance.
Let's take a closer look at an agricultural example. Suppose I have a historical archive of P6-AWiFS or Landsat NDVI (Normalized Difference Vegetation Index) data and I wish to change to using DMCii imagery for extracting NDVI data going forward. Is my historical AWiFS or Landsat data valid for comparison with new data from DMCii imagery. The answer is no, unless both datasets have been calibrated to the same level, such as surface reflectance. Calibrating the imagery removes variations and distortion from the imagery and ensures the data is correlated to a single reference level, whether that is the top of the atmosphere or the Earth's surface.
I am an advocate of calibrating to surface reflectance, whether it is for a single scene, multiple scenes from the same sensor or multiple scenes from multiple sensors. Surface reflectance's per pixel calibration to the Earth's surface provides greater accuracy than other methodologies. However, your requirements relating to accuracy, cost and timeliness will drive your decision on which methodology best fits your needs.
Bottom line, embrace the technology advancements, but be mindful of the challenges these advancements will bring as we move forward.
If you would like to see how GDA addresses these challenges today visit our surface reflectance page.
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