Targets, methods, and sites for assessing the in-flight spatial resolution of electro-optical data products

Pagnutti, Mary; Blonski, Slawomir; Cramer, Michael; Helder, Dennis L.; Holekamp, Kara; Honkavaara, Eija; Ryan, Robert

doi:10.5589/m10-078

Cited by 31 publications

(40 citation statements)

References 15 publications

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“…Conversely, the modulation transfer function (MTF) has historically been a widely-used figure of merit with the value of the MTF at the Nyquist frequency, often forming the system design requirement for sensors. An excellent overview of these measures and their development can be found in [8]. Because ESF and the line spread function (LSF) are often more intuitive than MTF, the results developed in this paper will focus largely on the ESF measurement and its derivative, LSF, as an assessment of the spatial quality of the TIRS instrument.…”

Section: Sensor Spatial Performancementioning

confidence: 99%

“…For the most part, these can be classified by the type of target that is being used: edge targets, point targets, line targets and pulse targets [8,11]. Although not used universally, edge targets are probably the most widely utilized type of on-orbit targets, as both man-made and natural objects can be identified as suitable edge targets.…”

Section: Sensor Spatial Performancementioning

confidence: 99%

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Pre- and Post-Launch Spatial Quality of the Landsat 8 Thermal Infrared Sensor

et al. 2015

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Abstract:The Thermal Infrared Sensor (TIRS) for the Landsat 8 platform was designed and built at NASA Goddard Space Flight Center (GSFC). TIRS data will extend the data record for thermal observations from the heritage Landsat sensors, dating back to the launch of Landsat 4 in 1982. The two-band (10.9 and 12.0 μm) pushbroom sensor with a 185 km-wide swath uses a staggered arrangement of quantum well infrared photodetector (QWIPs) arrays. The required spatial resolution is 100 m for TIRS, with the assessment of crop moisture and water resources being science drivers for that resolution. The evaluation of spatial resolution typically relies on a straight knife-edge technique to determine the spatial edge response of a detector system, and such an approach was implemented for TIRS. Flexibility in the ground calibration equipment used for TIRS thermal-vacuum chamber testing also made possible an alternate strategy that implemented a circular target moved in precise sub-pixel increments across the detectors to derive the edge response. On-orbit, coastline targets were developed to evaluate the spatial response performance. Multiple targets were identified that produced similar results to one another. Even though there may be a slight bias in the point spread function (PSF)/modulation transfer function (MTF) estimates towards poorer performance using this approach, it does have the ability to track relative changes for

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Section: Sensor Spatial Performancementioning

confidence: 99%

Section: Sensor Spatial Performancementioning

confidence: 99%

Pre- and Post-Launch Spatial Quality of the Landsat 8 Thermal Infrared Sensor

et al. 2015

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“…A plethora of methods were developed to assess the PSF or the direction line spread functions (LSF) pre-launch or on orbit from remote sensing imagery (see Pagnutti et al [65] for a review). Post-launch methods rely on the presence of highly contrasted targets on the ground that can be knife edges (edge methods) [66][67][68][69], a straight and narrow long object (pulse methods) [66] or a point source (impulse methods) [70].…”

Section: Effective Spatial Resolutionmentioning

confidence: 99%

Sentinel-2’s Potential for Sub-Pixel Landscape Feature Detection

et al. 2016

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Land cover and land use maps derived from satellite remote sensing imagery are critical to support biodiversity and conservation, especially over large areas. With its 10 m to 20 m spatial resolution, Sentinel-2 is a promising sensor for the detection of a variety of landscape features of ecological relevance. However, many components of the ecological network are still smaller than the 10 m pixel, i.e., they are sub-pixel targets that stretch the sensor’s resolution to its limit. This paper proposes a framework to empirically estimate the minimum object size for an accurate detection of a set of structuring landscape foreground/background pairs. The developed method combines a spectral separability analysis and an empirical point spread function estimation for Sentinel-2. The same approach was also applied to Landsat-8 and SPOT-5 (Take 5), which can be considered as similar in terms of spectral definition and spatial resolution, respectively. Results show that Sentinel-2 performs consistently on both aspects. A large number of indices have been tested along with the individual spectral bands and target discrimination was possible in all but one case. Overall, results for Sentinel-2 highlight the critical importance of a good compromise between the spatial and spectral resolution. For instance, the Sentinel-2 roads detection limit was of 3 m and small water bodies are separable with a diameter larger than 11 m. In addition, the analysis of spectral mixtures draws attention to the uneven sensitivity of a variety of spectral indices. The proposed framework could be implemented to assess the fitness for purpose of future sensors within a large range of applications.

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“…The GSD was calculated as the geometric mean of the ground sampled distance based on a projection of the pixel pitch distance to the ground [12,20]. The GSD was computed in inches in both the X and Y dimensions (the along-scan and cross-scan directions, respectively), and we calculated their geometric mean.…”

Section: Niirs Estimation Using the Giqementioning

confidence: 99%

Estimation of the Image Interpretability of ZY-3 Sensor Corrected Panchromatic Nadir Data

Li¹,

Luo²,

Zhu³

2014

Remote Sensing

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Image quality is important for taking full advantage of satellite data. As a common indicator, the National Imagery Interpretability Scale (NIIRS) is widely used for image quality assessment and provides a comprehensive representation of image quality from the perspective of interpretability. The ZY-3 (Ziyuan-3) satellite is the first civil high resolution mapping satellite in China, which was established in 2012. So far, there has been no reports on adopting NIIRS as the common indicator for the quality assessment of that satellite image data. This lack of a common quality indicator results in a gap between satellite data users around the world and those in China regarding the understanding of the quality and usability of ZY-3 data. To overcome the gap, using the general image-quality equation (GIQE), this study evaluates the ZY-3 sensor-corrected (SC) panchromatic nadir (NAD) data in terms of the NIIRS. In order to solve the uncertainty resulting from the exceeding of the ground sample distance (GSD) of ZY-3 data (2.1 m) in GIQE (less than 2.03 m), eight images are used to establish the relationship between the manually obtained NIIRS and the GIQE predicted NIIRS. An adjusted GIQE is based on the relationship and verified by another five images. Our study demonstrates that the method of using adjusted GIQE for calculating NIIRS can be used for the quality assessment of ZY-3 satellite images and reveals that the NIIRS value of ZY-3 SC NAD data is about 2.79.

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Targets, methods, and sites for assessing the in-flight spatial resolution of electro-optical data products

Cited by 31 publications

References 15 publications

Pre- and Post-Launch Spatial Quality of the Landsat 8 Thermal Infrared Sensor

Pre- and Post-Launch Spatial Quality of the Landsat 8 Thermal Infrared Sensor

Sentinel-2’s Potential for Sub-Pixel Landscape Feature Detection

Estimation of the Image Interpretability of ZY-3 Sensor Corrected Panchromatic Nadir Data

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