Empirical methods to compensate for a view-angle-dependent brightness gradient in AVIRIS imagery

Kennedy, Robert E.; Cohen, Warren B.; Takao, Gen

doi:10.1016/s0034-4257(97)00111-9

Cited by 66 publications

(43 citation statements)

References 21 publications

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“…perpendicular to the flight direction, due to a variety of disturbing effects (e.g. Kennedy et al, 1997;Schiefer et al, 2006). With regard to the derivation of the fluorescence signal the following effects have to be considered.…”

Section: First Regional Map Of Fluorescence Derived From Hyper Airbormentioning

confidence: 99%

CEFLES2: the remote sensing component to quantify photosynthetic efficiency from the leaf to the region by measuring sun-induced fluorescence in the oxygen absorption bands

et al. 2009

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Abstract. The CEFLES2 campaign during the Carbo Europe Regional Experiment Strategy was designed to provide simultaneous airborne measurements of solar induced fluorescence and CO 2 fluxes. It was combined with extensive ground-based quantification of leaf-and canopy-level processes in support of ESA's Candidate Earth Explorer Mission of the "Fluorescence Explorer" (FLEX). The aim of this campaign was to test if fluorescence signal detected from an airborne platform can be used to improve estimates of plant mediated exchange on the mesoscale. Canopy fluorescence was quantified from four airborne platforms using a combination of novel sensors: (i) the prototype airborne sensor AirFLEX quantified fluorescence in the oxygen A and B bands, (ii) a hyperspectral spectrometer (ASD) measured reflectance along transects during 12 day courses, (iii) spatially high resolution georeferenced hyperspectral data cubes containing the whole optical spectrum and the thermal region were gathered with an AHS sensor, and (iv) the first employment of the high performance imaging spectrometer HYPER delivered spatially explicit and multi-temporal transects across the whole region. During three measurement periods in April, June and September 2007 structural, functional and radiometric characteristics of more than 20 different vegetation types in the Les Landes region, Southwest France, were extensively characterized on the ground. The campaign concept focussed especially on quantifying plant mediated exchange processes (photosynthetic electron transport, CO 2 uptake, evapotranspiration) and fluorescence emission. The comparison between passive sun-induced fluorescence and active laser-induced fluorescence was performed on a corn canopy in the daily cycle and under desiccation stress. Both techniques show good agreement in detecting stress induced fluorescence change at the 760 nm band. On the large scale, airborne and ground-level measurements of fluorescence were compared on several vegetation types supporting the scaling of this novel remote sensing signal. The multi-scale design of the four airborne radiometric measurements along with extensive ground activities fosters a nested approach to quantify photosynthetic efficiency and gross primary productivity (GPP) from passive fluorescence.

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Section: First Regional Map Of Fluorescence Derived From Hyper Airbormentioning

confidence: 99%

CEFLES2: the remote sensing component to quantify photosynthetic efficiency from the leaf to the region by measuring sun-induced fluorescence in the oxygen absorption bands

et al. 2009

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“…Sensors with a large total field of view are typically affected by changes in the sensor view angle (Kennedy et al, 1997). To determine the magnitude of these effects, the digital numbers (DN) representing coniferous forest were plotted against image pixel number in the across scan direction (Fig.…”

Section: Image Data and Processingmentioning

confidence: 99%

Remote sensing of forest biophysical variables using HyMap imaging spectrometer data

Schlerf¹,

Atzberger²,

Hill³

2005

Remote Sensing of Environment

278

171

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This study systematically evaluated linear predictive models between vegetation indices (VI) derived from radiometrically corrected airborne imaging spectrometer (HyMap) data and field measurements of biophysical forest stand variables (n=40). Ratio-based and soil-linerelated broadband VI were calculated after HyMap reflectance had been spectrally resampled to Landsat TM channels. Hyperspectral VI involved all possible types of two-band combinations of ratio VI (RVI) and perpendicular VI (PVI) and the red edge inflection point (REIP) computed from two techniques, inverted Gaussian Model and Lagrange Interpolation. Cross-validation procedure was used to assess the prediction power of the regression models. Analyses were performed on the entire data set or on subsets stratified according to stand age. A PVI based on wavebands at 1088 nm and 1148 nm was linearly related to leaf area index (LAI) (R 2 =0.67, RMSE=0.69 m 2 m À2 (21% of the mean); after removal of one forest stand subjected to clearing measures: R 2 =0.77, RMSE=0.54 m 2 m À2 (17% of the mean). A PVI based on wavebands at 885 nm and 948 nm was linearly related to the crown volume (VOL) (R 2 =0.79, RMSE=0.52). VOL was derived from measured biophysical variables through factor analysis (varimax rotation). The study demonstrates that for hyperspectral image data, linear regression models can be applied to quantify LAI and VOL with good accuracy. For broadband multispectral data, the accuracy was generally lower. It can be stated that the hyperspectral data set contains more information relevant to the estimation of the forest stand variables LAI and VOL than multispectral data. When the pooled data set was analysed, soil-line-related VI performed better than ratio-based VI. When age classes were analysed separately, hyperspectral VI performed considerably better than broadband VI. Best hyperspectral VI in relation with LAI were typically based on wavebands related to prominent water absorption features. Such VI are related to the total amount of canopy water; as the leaf water content is considered to be relatively constant in the study area, variations of LAI are retrieved. D

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“…For UAV-, air-and spaceborne systems a number of correction methods have been developed. These include the use of image statistic based methods for flat terrain [42] and physical or semi-empirical models such as for the processing of MODIS data [43]. Lately, a more generic BRDF correction method was introduced, which builds on a surface cover characterization [44].…”

Section: Discussionmentioning

confidence: 99%

Angular Dependency of Hyperspectral Measurements over Wheat Characterized by a Novel UAV Based Goniometer

et al. 2015

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Abstract:In this study we present a hyperspectral flying goniometer system, based on a rotary-wing unmanned aerial vehicle (UAV) equipped with a spectrometer mounted on an active gimbal. We show that this approach may be used to collect multiangular hyperspectral data over vegetated environments. The pointing and positioning accuracy are assessed using structure from motion and vary from σ = 1° to 8° in pointing and σ = 0.7 to 0.8 m in positioning. We use a wheat dataset to investigate the influence of angular effects on the NDVI, TCARI and REIP vegetation indices. Angular effects caused significant variations on the indices: NDVI = 0.83-0.95; TCARI = 0.04-0.116; REIP = 729-735 nm. Our analysis highlights the necessity to consider angular effects in optical sensors when observing vegetation. We compare the measurements of the UAV goniometer to the angular modules of the SCOPE radiative transfer model. Model and measurements are in high accordance OPEN ACCESSRemote Sens. 2015, 7 726(r 2 = 0.88) in the infrared region at angles close to nadir; in contrast the comparison show discrepancies at low tilt angles (r 2 = 0.25). This study demonstrates that the UAV goniometer is a promising approach for the fast and flexible assessment of angular effects.

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Empirical methods to compensate for a view-angle-dependent brightness gradient in AVIRIS imagery

Cited by 66 publications

References 21 publications

CEFLES2: the remote sensing component to quantify photosynthetic efficiency from the leaf to the region by measuring sun-induced fluorescence in the oxygen absorption bands

CEFLES2: the remote sensing component to quantify photosynthetic efficiency from the leaf to the region by measuring sun-induced fluorescence in the oxygen absorption bands

Remote sensing of forest biophysical variables using HyMap imaging spectrometer data

Angular Dependency of Hyperspectral Measurements over Wheat Characterized by a Novel UAV Based Goniometer

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