Feasibility study and optimization of image tasking in the context of the European Union CAP CwRS

Vajsova, Blanka; Åstrand, Pär Johan; Oddone, Axel; Ellis, George A.

doi:10.1117/12.974665

Cited by 2 publications

(5 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Note that Aguilar et al [ 7 ] reported RMSE 2D values of 0.89 pixels and 1.10 pixels in the orientation phase of two WV2 ORS2A single images with an off-nadir angle of 10° and 22.4°, respectively. In addition, and according to Vajsová et al [ 16 ], the corresponding ground spatial resolution of Deimos-2 images with an off-nadir angle of 35° would be 1.9 m. In this way, the update of the GSD could improve the expected RMSE 2D to 0.66 pixels (1.255/1.9).…”

Section: Discussionmentioning

confidence: 95%

“…The RMSE 2D values attained from the direct geopositioning approach were always lower than the nominal circular error 90% (CE90) of 100 m (equivalent to approximately 65.9 m as RMSE 2D ) specified for Deimos-2 L1B products without GCPs’ support [ 16 ]. However, these direct geopositioning errors provided by Deimos-2 were almost four times higher than those obtained for the Maxar’s (old DigitalGlobe) VHR satellite constellation, where the CE90 for WV2 ORS2A product turns out to be 10.2 m (6.7 m in terms of RMSE 2D ) [ 46 ].…”

Section: Discussionmentioning

confidence: 99%

“…There are only a few published works dealing with pansharpening methods [ 14 ] or image classification [ 15 ] from Deimos-2 imagery. Regarding the geometric capabilities of the Deimos-2 level 1B (L1B) product, a technical report was published by the Joint Research Centre (JRC) in the frame of control with the remote sensing program of the European Common Agriculture Policy [ 16 ]. In this work, Vajsová et al [ 16 ] used ground points (GPs) with variable accuracies (from 0.05 m to 0.90 m measured as root mean square error in one direction, RMSE 1D ).…”

Section: Introductionmentioning

confidence: 99%

“…Regarding the geometric capabilities of the Deimos-2 level 1B (L1B) product, a technical report was published by the Joint Research Centre (JRC) in the frame of control with the remote sensing program of the European Common Agriculture Policy [ 16 ]. In this work, Vajsová et al [ 16 ] used ground points (GPs) with variable accuracies (from 0.05 m to 0.90 m measured as root mean square error in one direction, RMSE 1D ). Probably due to this poor GP support, they did not find differences between RPC0 and RPC1 sensor models when orthorectifying Deimos-2 images.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Geometric Accuracy Assessment of Deimos-2 Panchromatic Stereo Pairs: Sensor Orientation and Digital Surface Model Production

Aguilar

Jiménez-Lao

Nemmaoui

et al. 2020

Sensors

View full text Add to dashboard Cite

Accurate elevation data, which can be extracted from very high-resolution (VHR) satellite images, are vital for many engineering and land planning applications. In this way, the main goal of this work is to evaluate the capabilities of VHR Deimos-2 panchromatic stereo pairs to obtain digital surface models (DSM) over different land covers (bare soil, urban and agricultural greenhouse areas). As a step prior to extracting the DSM, different orientation models based on refined rational polynomial coefficients (RPC) and a variable number of very accurate ground control points (GCPs) were tested. The best sensor orientation model for Deimos-2 L1B satellite images was the RPC model refined by a first-order polynomial adjustment (RPC1) supported on 12 accurate and evenly spatially distributed GCPs. Regarding the Deimos-2 based DSM, its completeness and vertical accuracy were compared with those obtained from a WorldView-2 panchromatic stereo pair by using exactly the same methodology and semiglobal matching (SGM) algorithm. The Deimos-2 showed worse completeness values (about 6% worse) and vertical accuracy results (RMSEZ 42.4% worse) than those computed from WorldView-2 imagery over the three land covers tested, although only urban areas yielded statistically significant differences (p < 0.05).

show abstract

Section: Discussionmentioning

confidence: 95%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Geometric Accuracy Assessment of Deimos-2 Panchromatic Stereo Pairs: Sensor Orientation and Digital Surface Model Production

Aguilar

Jiménez-Lao

Nemmaoui

et al. 2020

Sensors

View full text Add to dashboard Cite

show abstract

“…In comparison to ground-based measurements, satellite sensor systems are capable of surmounting spatial constraints to a large extent, and very high spatial coverage of data. At the same time, many remote sensing data are also high resolution, such as the commercial satellite WorldView-4 with up to 0.31 m spatial resolution [20]. But, in the case of trace gas observations, the resolution of various remote sensing products varies considerably and is generally low due to the limitations of current satellite sensor technology.…”

mentioning

confidence: 99%

An Improved Geographically and Temporally Weighted Regression for Surface Ozone Estimation From Satellite-Based Precursor Data

Wang,

Xue,

Sun

et al. 2023

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

View full text Add to dashboard Cite

It is very essential to resolve the issues of atmospheric ozone pollution and health impact evaluation about high spatial resolution and accurate near-surface ozone concentration. Nevertheless, the existing remotely-sensed ozone products could not meet the demands of high spatial resolution monitoring. For this purpose, this study using surface ozone precursor (the surface nitrogen dioxide concentration and formaldehyde concentration) data developed an improved geographically and temporally weighted regression (IGTWR) method to estimate the surface ozone concentration. This method calculated a generalized distance between sample points in that multidimensional space constructed using the longitude, latitude, day, and normalized difference vegetation index (NDVI). Next, the surface ozone precursor data were as independent variables to retrieve the daily ozone concentrations. The contribution of the proposed model is that the NDVI data was introduced as the underlaying factor to explain the heterogeneity of underlaying conditions and indicated ozone concentration more accurately to improve estimation accuracy. And then the ground station observations were used to validate the estimated ground-level ozone concentration results. Based on the cross-validation results of all test data, the model estimated the root mean squared error (RMSE) and the correlation coefficient (R 2 ) of surface ozone are 9.456 µg /m 3 and 0.983, respectively. The results demonstrate that it is feasible to estimate surface ozone concentrations using data from the TROPOMI sensor and an improved geographically weighted regression model. Index Terms-Improved geographically and temporally weighted regression (IGTWR), satellite-based precursor data, surface ozone, tropospheric monitoring instrument (TROPOMI). I. INTRODUCTIONITH the pursuit of sustainable development in modern society, air pollution, especially groundlevel ozone (O3) pollution, is receiving increasing attention from governments and people in general. Unlike the upper-level ozone known as the "Earth's umbrella", surface

show abstract

Feasibility study and optimization of image tasking in the context of the European Union CAP CwRS

Cited by 2 publications

References 0 publications

Geometric Accuracy Assessment of Deimos-2 Panchromatic Stereo Pairs: Sensor Orientation and Digital Surface Model Production

Geometric Accuracy Assessment of Deimos-2 Panchromatic Stereo Pairs: Sensor Orientation and Digital Surface Model Production

An Improved Geographically and Temporally Weighted Regression for Surface Ozone Estimation From Satellite-Based Precursor Data

Contact Info

Product

Resources

About