WorldView-3 is the first commercial satellite to have 16 high-resolution spectral bands that capture information in the visible and near-infrared (VNIR), and short-wave infrared (SWIR) regions of the electromagnetic spectrum (EMS). We look at how its super spectral capability sets a new standard for satellite imagery and how its benefits are being realised
After more than 40 years, the remote sensing community continues to address the two fundamental challenges when using Earth imagery at a global scale: automated information extraction and change detection. DigitalGlobe’s WorldView-3 satellite is designed to address these challenges by creating consistent datasets as well as providing unique information for agriculture, forestry and mining/geology and other applications.
Providing unique information
WorldView-3 is the first commercial satellite to have 16 high-resolution spectral bands that capture information in the visible and near-infrared (VNIR), and short-wave infrared (SWIR) regions of the electromagnetic spectrum (EMS). Operating at an altitude of 617 kilometers, the satellite provides 30-centimeter panchromatic resolution, 1.2-meter VNIR resolution, and 3.7/7.5-meter SWIR resolution, according to DigitalGlobe’s operating licenses (Department of Commerce).
WorldView-3 builds upon WorldView-2’s unique VNIR capabilities and provides eight additional spectral bands, farther into the SWIR portion of the EMS. This spectral expansion enhances WorldView-3’s capability to capture the uniqueness of each ground material’s spectral signature. Due to minimal atmospheric influence or noise in this part of the EMS, as well as an enhanced ability to differentiate among ground materials, the SWIR bands open the door for automated information extraction to save time, money, and lives.
Creating consistent imagery
Remote sensing satellites view Earth from above the atmosphere—top-of-the-atmosphere (TOA) measurements of Earth’s features. Changes in the atmosphere, sun illumination and viewing geometries during image capture result in inconsistent image data, hindering automated information extraction and change detection. Atmospheric conditions typically change during and between different imagery collections due to varying moisture levels (water vapour) and particulates (aerosols) in the atmosphere. Much research has been done trying to accurately convert the TOA measurements to surface-reflectance measurements.
The challenge has been the availability of accurate atmospheric measurements at appropriate scale, ensuring imagery can be normalized. WorldView-3 addresses this problem by becoming the first commercial imaging satellite with an atmospheric sensor as part of its payload.
During image capture, the WorldView-3 atmospheric sensor is designed to detect the presence of clouds, aerosols and water vapour at 30-meter resolution, thereby measuring the exact atmospheric conditions corresponding to every recorded image. Fig.2 shows how the atmospheric sensor has a slightly wider swath than the imaging swath.
DigitalGlobe has developed proprietary algorithms that use these atmospheric measurements to normalize WorldView-3 imagery for consistency. This normalization is called atmospheric compensation, which is especially important for information extraction, such as change detection and vegetation analysis because changes due to the atmosphere have been removed. Atmospheric compensation results in surface-reflectance image data.
Another issue impairing automated information extraction is accurately mapping cloud cover. WorldView-3’s sensors have spectral bands that range from the VNIR into the SWIR part of the EMS to accurately distinguish clouds from other bright features such as snow and ice.
THE BENEFITS OF SWIR IMAGERY
Besides offering 30 centimetre resolution panchromatic and eight-band visible and near-infrared (VNIR) imagery, WorldView-3 is licensed by the National Oceanic and Atmospheric Administration to collect short-wave infrared (SWIR) imagery in eight-bands. This allows the satellite to sense the VNIR spectrum as well as expand deeper into the infrared spectrum, than any other commercial imaging satellite, providing rich data for precisely identifying and characterizing manmade and natural materials. WorldView-3’s eight SWIR bands span the spectrum’s three atmospheric transmittance imaging windows to capture unique information for agriculture, forestry and mining/geology and other applications.
The agricultural community will benefit greatly from WorldView-3’s 16 bands. One of the main challenges facing agriculture policies is regional and global knowledge of accurate crop inventories. WorldView-3’s atmospherically compensated imagery, coupled with the 16 spectral bands, will allow for accurate crop pattern/type mapping.
As the world focuses on increasing global food security, it is critical to improve small farm productivity and yield, while decreasing costs, minimizing the environmental impact with precision agriculture practices, and better managing agriculture production and associated inventory. It is important to take corrective action early in the growing season by understanding crop conditions such as crop health and stress due to problems such as nutrient deficiency, moisture stress, and pests.
Observing soil types and conditions before, during and after a crop season is important for managing crop health. Remote sensing satellites offer a window into underlying soil conditions and how such conditions might affect vegetation.
Soil organic composition and moisture levels are assessable through the VNIR and SWIR bands. When properly monitored, such information can help users understand current and future crop potential.
One of the agricultural community’s best management practices relates to how much post-harvest crop residue is left on a field. Crop residue preserves soil moisture and prevents soil erosion during rainy months. SWIR spectral bands can be used to map and quantify how much crop residue is left behind, predicting the soil quality for future crops.
The forestry industry’s requirements are similar to the agricultural industry, which includes maintaining a detailed tree inventory of large parcels, mapping and monitoring tree health, and understanding and minimizing tree pest infestations.
WorldView-3’s spectral bands, including VNIR and SWIR, allow for tree class and species identification. Tree species have unique spectral signatures, like fingerprints, that can be extracted automatically using WorldView-3’s spectral bands (Fig.6). Stressed trees will exhibit similar symptoms as stressed crops, as green chlorophyll in the leaves is replaced by yellow and red carotenoids.
WorldView-3’s spectral bands will allow for unique mineral identification and chemical measurements. Atoms have vibrations with different frequencies, and at specific wavelengths light can stimulate the vibration. As a result, different minerals absorb specific wavelengths and reflect others.
Electronic absorptions at wavelengths less than about 1,000 nm allow analysts to identify materials containing iron. Molecular vibrational features at wavelengths between about 1,000–2,500 nm are diagnostic for materials containing anion groups such as Al-OH, Mg-OH, Fe-OH, Si-OH, carbonates, ammonium, and sulphates. Mineral spectral absorption features are particularly observed in the SWIR region.
Exposed outcrops are manifestations of potential mineral ores or sub-surface deposits. The geology and mining industries spend millions of dollars to identify potential mining sites during the exploration phase; WorldVew-3 will allow companies to cut costs and increase efficiency by narrowing the potential area before field verification is planned.
WorldView-3’s increased spectral resolution of16-bands spanning VNIR to SWIR will allow an extension of visual interpretation to machine interpretation and analyses using material spectral signatures. With the addition of WorldView-3 to its constellation, DigitalGlobe is pioneering the ability to automatically extract valuable information in the invisible part of sunlight, which carries additional spectral information.
In this interconnected global economy, understanding micro, regional, and global trends is of paramount importance for decision-makers. Being able to identify patterns and make decisions with confidence, based on the highest quality and most current visual information, is crucial for success.
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