Figure 1 - uploaded by Ulrich Beisl
Content may be subject to copyright.
Viewing geometry for a line scan sensor. For frame sensors the area of constant view zenith angle is a circle and still has a varying view azimuth (cf. Figure 2).
Source publication
The image quality of photogrammetric images is influenced by various effects from outside the camera. One effect is the scattered
light from the atmosphere that lowers contrast in the images and creates a colour shift towards the blue. Another is the changing
illumination during the day which results in changing image brightness within an image blo...
Context in source publication
Similar publications
Context. Various solar features can be seen in emission or absorption on maps of the Sun in the millimetre and submillimetre wavelength range. The recently installed Atacama Large Millimetre/submillimetre Array (ALMA) is capable of observing the Sun in that wavelength range with an unprecedented spatial, temporal and spectral resolution. To interpr...
Citations
... To correct the angular dependency, the observed direct reflectance was pixel-wise multiplied by the anisotropy correction factor anc (θ i ,θ v ,φ) , which is defined by the nadir reflectance to the predicted reflectance under the same incident zenith in Equation (4) [26,34]: ...
... To correct the angular dependency, the observed direct reflectance was pixel-wise multiplied by the anisotropy correction factor anc (θ i ,θ v ,φ) , which is defined by the nadir reflectance to the predicted reflectance under the same incident zenith in Equation (4) [26,34]: The solar irradiance was generally stable. The beginning low values belong to the DLS adaption period, covering 10-15 images that were discarded during processing. ...
... To correct the angular dependency, the observed direct reflectance was pixel-wise multiplied by the anisotropy correction factor anc (θ i ,θ v ,ϕ) , which is defined by the nadir reflectance to the predicted reflectance under the same incident zenith in Equation (4) [26,34]: ...
For grape canopy pixels captured by an unmanned aerial vehicle (UAV) tilt-mounted RedEdge-M multispectral sensor in a sloped vineyard, an in situ Walthall model can be established with purely image-based methods. This was derived from RedEdge-M directional reflectance and a vineyard 3D surface model generated from the same imagery. The model was used to correct the angular effects in the reflectance images to form normalized difference vegetation index (NDVI) orthomosaics of different view angles. The results showed that the effect could be corrected to a certain scope, but not completely. There are three drawbacks that might restrict a successful angular model construction and correction: (1) the observable micro shadow variation on the canopy enabled by the high resolution; (2) the complexity of vine canopies that causes an inconsistency between reflectance and canopy geometry, including effects such as micro shadows and near-infrared (NIR) additive effects; and (3) the resolution limit of a 3D model to represent the accurate real-world optical geometry. The conclusion is that grape canopies might be too inhomogeneous for the tested method to perform the angular correction in high quality.
... Such corrections are performed with software packages such as ATCOR [13] and FLAASH which incorporates MODTRAN [12]. Similar corrections using radiative transfer properties have been applied to airborne ADS40 imagery [14]. ...
An alternative technique for shadow detection and abundance is presented for high spatial resolution imagery acquired under clear sky conditions from airborne/spaceborne sensors. The method, termed Scattering Index (SI), uses Rayleigh scattering principles to create a diffuse skylight vector as a shadow reference. From linear algebra, the proportion of diffuse skylight in each image pixel provides a per pixel measure of shadow extent and abundance. We performed a comparative evaluation against two other methods, first valley detection thresholding (extent) and physics-based unmixing (extent and abundance). Overall accuracy and F-score measures are used to evaluate shadow extent on both Worldview-3 and ADS40 images captured over a common scene. Image subsets are selected to capture objects well documented as shadow detection anomalies, e.g., dark water bodies. Results showed improved accuracies and F-scores for shadow extent and qualitative evaluation of abundance show the method is invariant to scene and sensor characteristics. SI avoids shadow misclassifications by avoiding the use of pixel intensity and the associated limitations of binary thresholding. The method negates the need for complex sun-object-sensor corrections, it is simple to apply, and it is invariant to the exponential increase in scene complexity associated with higher-resolution imagery.
... This avoids the use of complex atmospheric models that require the atmospheric state data that are not usually available. Thanks to the usage of the irradiance sensor, we are able to obtain accurate surface reflectivity [3]. In addition, sunglint introduces a reflectivity contribution coming from the water surface that does not provide any information about the properties of the water. ...
The bathing water quality is an essential issue because of the consequences for the public health of the coastline users that make an extensive recreational use of it, even more in tourist areas. Overpopulation of coastlines generates large volumes of wastewater that must be treated as a prior step to its discharge into the coastal outfalls. In order to carry out a control of the wastewater treatment and discharge process, it is necessary to monitor the discharge points through a systematic and costly in-situ sampling analyzed in laboratory for the detection of bacterial pathogens. This requirement of bathing water monitoring made clear thanks to the European directive 2006/7/CE of February 15, 2006. This complex and slow procedure does not allow obtaining early alerts of the presence of pathogens because the biological bacterial analysis method require a minimum of three days. We propose, the use of a hyperspectral camera aboard a drone in order to monitor the bathing water by using the Radiative Transfer Model (RTM) to obtain indicators of the presence of bacterial pathogens. In this way, this paper presents the first preliminary results of our study.
... R k (θ i , θ r , ϕ) j can be presented using the vertical reflectance of the object at the specific solar illumination angle, R k (θ i t , 0, 0), and the anisotropy factor, ani f (θ i , θ r , ϕ) j . The anisotropy factor is derived as the ratio of the modelled directional and vertical reflectance, ρ model (θ i , θ r , ϕ) j and ρ model (θ i t , 0, 0), respectively [43]: ...
... In our current implementation, we use the simple empirical BRDF model developed by Walthall et al. [44] and Nilson and Kusk [45]. Previously, the model was used by Beisl et al. [43,46] with 1D pushbroom and 2D frame format images. The 3-parameter model, ρ model (θ r , ϕ), is feasible for data collected during a short period of time (Equation (3)), but an extended version, ρ model (θ i , θ r , ϕ), is used for cases with a varying sun zenith angle (Equation (4)): ...
Unmanned airborne vehicles (UAV) equipped with novel, miniaturized, 2D frame format hyper- and multispectral cameras make it possible to conduct remote sensing measurements cost-efficiently, with greater accuracy and detail. In the mapping process, the area of interest is covered by multiple, overlapping, small-format 2D images, which provide redundant information about the object. Radiometric correction of spectral image data is important for eliminating any external disturbance from the captured data. Corrections should include sensor, atmosphere and view/illumination geometry (bidirectional reflectance distribution function—BRDF) related disturbances. An additional complication is that UAV remote sensing campaigns are often carried out under difficult conditions, with varying illumination conditions and cloudiness. We have developed a global optimization approach for the radiometric correction of UAV image blocks, a radiometric block adjustment. The objective of this study was to implement and assess a combined adjustment approach, including comprehensive consideration of weighting of various observations. An empirical study was carried out using imagery captured using a hyperspectral 2D frame format camera of winter wheat crops. The dataset included four separate flights captured during a 2.5 h time period under sunny weather conditions. As outputs, we calculated orthophoto mosaics using the most nadir images and sampled multiple-view hyperspectral spectra for vegetation sample points utilizing multiple images in the dataset. The method provided an automated tool for radiometric correction, compensating for efficiently radiometric disturbances in the images. The global homogeneity factor improved from 12–16% to 4–6% with the corrections, and a reduction in disturbances could be observed in the spectra of the object points sampled from multiple overlapping images. Residuals in the grey and white reflectance panels were less than 5% of the reflectance for most of the spectral bands.
... However, radiometric correction methods are rare when using aerial photogrammetric images due to the special features of photogrammetric data acquisition, such as the wide field of view, varying flying heights, the frame image format, and varying sensor exposure settings (Read and Graham, 2002;Ryan and Pagnutti, 2009;Beisl, 2012). Also the relatively wide multispectral channels of photogrammetric sensors and the lack of channels in the shortwave infrared region (1-3 µm) require adaptation of the traditionally used atmospheric correction algorithms (Richter, 2008). ...
Full thesis available from the following link:
http://urn.fi/URN:ISBN:978-951-711-295-6
... La corrección radiométrica de una imagen aérea pasa por aplicar, en primer lugar, los parámetros de calibración radiométrica del sensor obtenidos en laboratorio, seguida de la corrección atmosférica, y finalmente la corrección BRDF [Hefe06]. Sin embargo, pocos fabricantes de cámaras digitales y Sw de Fotogrametría tienen implementados procedimientos de corrección radiométrica rigurosos [UBeis06,UBeis08,UBeis12], considerando soluciones interactivas basadas en criterios puramente visuales, tanto en el postproceso de las imágenes del vuelo, como en la generación de mosaicos de ortofotografías. ...
Determining NDVI data continuity of Sentinel-2A MSI and
Landsat 8 OLI with three or five days visiting time have a
significant contribution in long-term time series of forest
monitoring [1]. Current study tried to examine the NDVI data
continuity between Sentinel-2A and Landsat 8 OLI at the
maximum growing season in the Çamliyayla forest district,
Turkey. Landsat 8 OLI L1TP, Landsat 8 OLI level L1T, and
Sentinel-2A level L1C were acquired. Pearson correlation
coefficient, boxplots, cross calibration, and regression
statistical analysis were used to determine the consistency
between two NDVI data sets. NDVI maps were generated
after implementing necessary preprocessing operations on
images including different atmospheric methods DOS1, and
Sen2Cor, and geo-shift corrections. Results showed
correlation coefficient was approximately greater than 0.8
which reveals good consistency between two data set. Highest
correlation coefficient between Landsat 8 OLI NDVI and
Sentinel-2A NDVI obtained 0.89 (
< 0.0) by DOS
atmospheric correction approach. Findings imply that Landsat
8 OLI NDVI is almost consistent with Sentinel-2A NDVI
data. Finally, Landsat 8 OLI NDVI and Sentinel-2A NDVI
can be used as a complementary data that was one of the ESA
mission aims [2–5]and it can be considered as a valuable data
source for consistently doing time series forest monitoring. In
further investigation, other vegetation indices continuity for
other forest types and different tree species types is
recommended.
This work presents an assessment on the correlation between CyGNSS-derived Global Navigation Satellite Systems Reflectometry (GNSS-R) bistatic reflectivity rl and SMAP-derived brightness temperature BT, over land surfaces. This parametric-study is performed as a function of Soil Moisture Content (SMC), vegetation opacity τ, and albedo ω. Several target areas are selected to evaluate potential differentiated geophysical effects on “active” (as many transmitters as navigation satellites are in view), and passive approaches. Although microwave radiometry has potentially a better sensitivity to SMC, the spatial resolution is poor ~ 40 km. On the other hand, GNSS-R bistatic coherent radar footprint is limited by half of the first Fresnel zone which provides about ~ 150 m of spatial resolution (depending on the geometry). The synergetic combination of both techniques could provide advantages with respect to active monostatic Synthetic Aperture Radar (SAR).
Sea surface wind speed plays an essential role for the investigation of several oceanic applications. This parameter can be estimated through Synthetic Aperture Radar (SAR) images using Geophysical Model Functions (GMFs) approaches i.e. CMOD.5 empirical method. However, SAR data suffer from an inherent dilemma called Speckle Noise that complicates the visual interpretation of the image and causes a bad estimation of parameters. In order to mitigate the adverse effects of this multiplicative noise, several approaches have been proposed especially SAR filtering approach. This paper deals with adapting speckle noise reduction while applying SAR despeckling process for wind speed retrieval. It aims estimate wind speed using CMOD.5 empirical method from SAR images in VV-polarization. This will be done, in a first step, without the filtering process and then, by adding two mainly used filters in the scientific community: Lee filter and NL-SAR filter. In fact, all published works in this field, do not address SAR despeckling process for wind speed estimation. After referring to the Advanced Scattrometer (ASCAT) Data measurements used for validation, numerical results on Sentinel-1 data showed that the the filtering step's adoption allows an accurate estimation of wind speed. Thus, Speckle noise reduction stage is essential for a better wind speed estimation .
The BRDF (Bi-directional Reflectance Distribution Function) describes the scattering properties of the surface as a function of the incidence direction, viewing geometry and wave length, and typically depends on the land-cover type being observed. In our work a laser scanning point cloud should be assigned multispectral values from aerial images. Since each laser point is covered by up to nine images, i.e. in general by nine different colour vectors, a unique set of colour vectors is sought for through radiometric correction by applying an optimal BRDF. As BRDF the widely used linear semi-empirical modified Walthall model has been chosen, for which the parameters should be determined by least squares adjustment. For the evaluation mostly uniform areas of four different object classes, such as road surfaces, lawn and grass area, trees and high vegetation, and roof tops, were used. It could be shown that the simple Walthall model yields acceptable results.
