Effects of atmospheric, topographic, and BRDF correction on imaging spectroscopy-derived data products

Surface reflectance is an important data product in imaging spectroscopy for obtaining surface information. The complex retrieval of surface reflectance, however, critically relies on accurate knowledge of atmospheric absorption and scattering, and the compensation of these effects. Furthermore, illumination and observation geometry in combination with surface reflectance anisotropy determine dynamics in retrieved surface reflectance not related to surface absorption properties. To the best of authors’ knowledge, no comprehensive assessment of the impact of atmospheric, topographic, and anisotropy effects on derived surface information is available so far.This study systematically evaluates the impact of these effects on reflectance, albedo, and vegetation products. Using three well-established processing schemes (ATCOR F., ATCOR R., and BREFCOR), high-resolution APEX imaging spectroscopy data, covering a large gradient of illumination and observation angles, are brought to several processing states, varyingly affected by mentioned effects. Pixel-wise differences of surface reflectance, albedo, and spectral indices of neighboring flight lines are quantitatively analyzed in their respective overlapping area. We found that compensation of atmospheric effects reveals actual anisotropy-related dynamics in surface reflectance and derived albedo, related to an increase in pixel-wise relative reflectance and albedo differences of more than 40%. Subsequent anisotropy compensation allows us to successfully reduce apparent relative reflectance and albedo differences by up to 20%. In contrast, spectral indices are less affected by atmospheric and anisotropy effects, showing relative differences of 3% to 10% in overlapping regions of flight lines.We recommend to base decisions on the use of appropriate processing schemes on individual use cases considering envisioned data products

드론을 활용한 위성 지표반사도 산출물 공간 패턴 분석

학위논문(석사) -- 서울대학교대학원 : 농업생명과학대학 생태조경·지역시스템공학부(생태조경학), 2021.8. 조대솔.High-resolution satellites are assigned to monitor land surface in detail. The reliable surface reflectance (SR) is the fundamental in terrestrial ecosystem modeling so the temporal and spatial validation is essential. Usually based on multiple ground control points (GCPs), field spectroscopy guarantees the temporal continuity. Due to limited sampling, however, it hardly illustrates the spatial pattern. As a map, the pixelwise spatial variability of SR products is not well-documented. In this study, we introduced drone-based hyperspectral image (HSI) as a reference and compared the map with Sentinel 2 and Landsat 8 SR products on a heterogeneous rice paddy landscape. First, HSI was validated by field spectroscopy and swath overlapping, which assured qualitative radiometric accuracy within the viewing geometry. Second, HSI was matched to the satellite SRs. It involves spectral and spatial aggregation, co-registration and nadir bidirectional reflectance distribution function (BRDF)-adjusted reflectance (NBAR) conversion. Then, we 1) quantified the spatial variability of the satellite SRs and the vegetation indices (VIs) including NDVI and NIRv by APU matrix, 2) qualified them pixelwise by theoretical error budget and 3) examined the improvement by BRDF normalization. Sentinel 2 SR exhibits overall good agreement with drone HSI while the two NIRs are biased up to 10%. Despite the bias in NIR, the NDVI shows a good match on vegetated areas and the NIRv only displays the discrepancy on built-in areas. Landsat 8 SR was biased over the VIS bands (-9 ~ -7.6%). BRDF normalization just contributed to a minor improvement. Our results demonstrate the potential of drone HSI to replace in-situ observation and evaluate SR or atmospheric correction algorithms over the flat terrain. Future researches should replicate the results over the complex terrain and canopy structure (i.e. forest).원격탐사에서 지표 반사도(SR)는 지표정보를 비파괴적이고 즉각적인 방법으로 전달해주는 매개체 역할을 한다. 신뢰할 수 있는 SR은 육상 생태계 모델링의 기본이고, 이에 따라 SR의 시공간적 검증이 요구된다. 일반적으로 SR은 여러 지상 기준점(GCP)을 기반으로 하는 현장 분광법을 통해서 시간적 연속성이 보장된다. 그러나 현장 분광법은 제한적인 샘플링으로 공간 패턴을 거의 보여주지 않아, 위성 SR의 픽셀 별 공간 변동성은 잘 분석되지 않았다. 본 연구에서는 드론 기반의 초분광 영상(HSI)을 참고자료로 도입하여, 이를 이질적인 논 경관에서 Sentinel 2 및 Landsat 8 SR과 비교하였다. 우선, 드론 HSI는 현장 분광법 및 경로 중첩을 통해서 관측각도 범위 내에서 정성적인 방사 측정을 보장한다고 검증되었다. 이후, 드론 HSI는 위성 SR의 분광반응특성, 공간해상도 및 좌표계를 기준으로 맞춰졌고, 관측 기하를 통일하기 위해서 드론 HIS와 위성 SR은 각각 양방향반사율분포함수 (BRDF) 정규화 반사도 (NBAR)로 변환되었다. 마지막으로, 1) APU 행렬으로 위성 SR과 NDVI, NIRv를 포함하는 식생지수(VI)의 공간변동성을 정량화 했고, 2) 대기보정의 이론적 오차를 기준으로 SR과 VI를 픽셀별로 평가했고, 3) BRDF 정규화를 통한 개선 사항을 검토했다. Sentinel 2 SR은 드론 HSI와 전반적으로 좋은 일치를 보이나, 두 NIR 채널은 최대 10% 편향되었다. NIR의 편향은 식생지수에서 토지 피복에 따라 다른 영향을 미쳤다. NDVI는 식생에서는 낮은 편향을 보여줬고, NIRv는 도시시설물 영역에서만 높은 편향을 보였다. Landsat 8 SR은 VIS 채널에 대해 편향되었다 (-9 ~ -7.6%). BRDF 정규화는 위성 SR의 품질을 개선했지만, 그 영향은 부수적이었다. 본 연구에서는 평탄한 지형에서 드론 HSI가 현장 관측을 대체할 수 있고, 따라서 위성 SR이나 대기보정 알고리즘을 평가하는데 활용될 수 있다는 것을 보였다. 향후 연구에서는 산림으로 대상지를 확대하여, 지형과 캐노피 구조가 드론 HSI 및 위성 SR에 미치는 영향을 분석할 필요가 있다.Chapter 1. Introduction 1 1.1 Background 1 Chapter 2. Method 3 2.1 Study Site 3 2.2 Drone campaign 4 2.3 Data processing 4 2.3.1 Sensor calibration 5 2.3.2 Bidirectional reflectance factor (BRF) calculation 7 2.3.3 BRDF correction 7 2.3.4 Orthorectification 8 2.3.5 Spatial Aggregation 9 2.3.6 Co-registration 10 2.4 Satellite dataset 10 2.4.2 Landsat 8 12 Chapter 3. Result and Discussion 12 3.1 Drone BRF map quality assessment 12 3.1.1 Radiometric accuracy 12 3.1.2 BRDF effect 15 3.2 Spatial variability in satellite surface reflectance product 16 3.2.1 Sentinel 2B (10m) 17 3.2.2 Sentinel 2B (20m) 22 3.2.3 Landsat 8 26 Chapter 4. Conclusion 28 Supplemental Materials 30 Bibliography 34 Abstract in Korean 43석

Theoretical Evaluation of Anisotropic Reflectance Correction Approaches for Addressing Multi-Scale Topographic Effects on the Radiation-Transfer Cascade in Mountain Environments

Research involving anisotropic-reflectance correction (ARC) of multispectral imagery to account for topographic effects has been ongoing for approximately 40 years. A large body of research has focused on evaluating empirical ARC methods, resulting in inconsistent results. Consequently, our research objective was to evaluate commonly used ARC methods using first-order radiation-transfer modeling to simulate ASTER multispectral imagery over Nanga Parbat, Himalaya. Specifically, we accounted for orbital dynamics, atmospheric absorption and scattering, direct- and diffuse-skylight irradiance, land cover structure, and surface biophysical variations to evaluate their effectiveness in reducing multi-scale topographic effects. Our results clearly reveal that the empirical methods we evaluated could not reasonably account for multi-scale topographic effects at Nanga Parbat. The magnitude of reflectance and the correlation structure of biophysical properties were not preserved in the topographically-corrected multispectral imagery. The CCOR and SCS+C methods were able to remove topographic effects, given the Lambertian assumption, although atmospheric correction was required, and we did not account for other primary and secondary topographic effects that are thought to significantly influence spectral variation in imagery acquired over mountains. Evaluation of structural-similarity index images revealed spatially variable results that are wavelength dependent. Collectively, our simulation and evaluation procedures strongly suggest that empirical ARC methods have significant limitations for addressing anisotropic reflectance caused by multi-scale topographic effects. Results indicate that atmospheric correction is essential, and most methods failed to adequately produce the appropriate magnitude and spatial variation of surface reflectance in corrected imagery. Results were also wavelength dependent, as topographic effects influence radiation-transfer components differently in different regions of the electromagnetic spectrum. Our results explain inconsistencies described in the literature, and indicate that numerical modeling efforts are required to better account for multi-scale topographic effects in various radiation-transfer components.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Global retrieval of bidirectional reflectance and albedo over land from EOS MODIS and MISR data: Theory and algorithm

This paper describes the theory and the algorithm to be used in producing a global bidirectional reflectance distribution function (BRDF) and albedo product from data to be acquired by the moderate resolution imaging spectroradiometer (MODIS) and the multiangle imaging spectroradiometer (MISR), both to be launched in 1998 on the AM-I satellite platform as part of NASA's Earth Observing System (EOS). The product will be derived using the kernel-driven semiempirical Ambrals BRDF model, utilizing five variants of kernel functions characterizing isotropic, volume and surface scattering. The BRDF and the albedo of each pixel of the land surface will be modeled at a spatial resolution of I km and once every 16 days in seven spectral bands spanning the visible and the near infrared. The BRDF parameters retrieved and recorded in the MODIS BRDF/albedo product will be intrinsic surface properties decoupled from the prevailing atmospheric state and hence suited for a wide range of applications requiring characterization of the directional anisotropy of Earth surface reflectance. A set of quality control flags accompanies the product. An initial validation of the Ambrals model is demonstrated using a variety of field-measured data sets for several different land cover types

Anisotropic-Reflectance Correction of Multispectral Satellite Imagery in Complex Mountain Terrain

The utilization of satellite imagery acquired over rugged terrain is problematic because of anisotropic reflectance. A variety of environmental factors, such as the atmosphere and the topography, cause significant variation in the irradiant and radiant flux. Consequently, satellite imagery must be radiometric ally corrected to account for these variations which influence the at-satellite spectral response. In mountain terrain, the topographic effect is very pronounced, and satellite imagery must be normalized utilizing various techniques. The purpose of this research was to evaluate various implementations of the Minnaert correction technique which were designed to account for the influence of topography and land cover on sensor response. Specifically, a local and land cover stratification procedure was developed and tested to compute multiple Minnaert constants. SPOT HRV satellite imagery of the Nanga Parbat Himalaya was used because the topography is extreme, and the study area represents an excellent location for testing anisotropic-reflectance correction procedures. The SPOT-3 NIR image was used in the analysis as the atmospheric influence was minimal. A digital elevation model (DEM) was generated using SPOT-3 panchromatic stereopairs. The DEM was used to produce estimates of slope and slope aspect for accounting for variations in the local direct irradiant flux. Four subimages were selected to evaluate the spectral variance for two homogeneous areas and two heterogeneous areas. Effective anisotropic-reflectance correction should result in a decrease in spectral variation over homogeneous land cover and increased spectral variation among heterogeneous land cover areas. Descriptive statistics and semivariogram analysis was used for evaluation of the original and normalized images. Results indicated that the Cosine-correction method produced high radiance values throughout the image regardless of land cover. This over-correction was found wherever there were steep slopes, and is the result of not accounting for the correct magnitude of the surface irradiance. The Minnaert-correction procedure, using a global Minnaert constant, appeared to produce better results, however, global-regression analysis revealed results that did not accurately characterize the degree of anistropy for various land cover classes. M innaert correction based upon land-cover stratification produced statistically valid results, such that both topography and land cover effects on the radiant flux were generally accounted for. The window-based approach produced images that appeared to reduce the topographic effect, although overcorrection still occurred, and statistical results were invalid for small window sizes. These results indicated that the Minnaert-Correction procedure has the potential to be used to reduce the topographic effect in rugged terrain, if scale-dependent variation in the topography and land-cover characteristics can be locally evaluated to compute Minnaert constants. Furthermore, the diffuse-irradiant and adjacent-terrain irradiant flux need to be considered as overcorrection is problematic in complex terrain. More research on dynamic spatial-partitioning of the topography and spectral variation is therefore warrented

Detecting soil erosion in semi-arid Mediterranean environments using simulated EnMAP data

Soil is an essential nature resource. Management of this resource is vital for sustainability and the continued functioning of earths atmospheric, hydrospheric and lithospheric functioning. The assessment and continued monitoring of surface soil state provides the information required to effectively manage this resource. This research used a simulated Environmental Mapping and Analysis Program (EnMAP) hyperspectral image cube of an agricultural region in semi- arid Mediterranean Spain to classify soil erosion states. Multiple Endmember Spectral Mixture Analysis (MESMA) was used to derive within pixel fractions of eroded and accumulated soils. A Classification of the soil erosion states using the scene fraction outputs and digital terrain information. The information products generated in this research provided an optimistic outlook for the applicability of the future EnMAP sensor for soil erosion investigations in semi-arid Mediterranean environments. Additionally, this research verifies that the launch of the EnMAP satellite sensor in 2018 will provide the opportunity to further improve the monitoring of earth finite soil resources.NSERC create AMETHYST , Alberta Terrestrial Imaging Centre

Procedures for the analysis and use of multiple view angle image data

It is recognised that the majority of vegetative cover types have anisotropic reflectance characteristics that are largely a function of their canopy geometry. Several studies have made attempts at formulating methods for the use of data remotely sensed from off-nadir directions. The best of these methods attempt to utilise the "extra" information implicitly contained in off-nadir image datasets. In this study, an attempt is made to extract information concerning agro-physical parameters of a number of vegetative cover types using imagery acquired by an airborne sensor, the Daedalus Airborne Thematic Mapper (ATM). It is also recognised in the literature that the nature of spatial variance in images is related to the size and distribution of the objects in the scene and the sampling characteristics of the sensor. In previous work this relationship has been explored by examining scenes using images of varying spatial resolutions, using a number of measurements of spatial variance. The underlying trend of these measurements is then used to interpret the nature of the objects in the scene. No previous work exists which attempts to utilise the change in variance of images acquired at different off-nadir view angles. In this study, the understanding of this relationship is developed by examining the change in variance of a number of vegetative cover types from multiple view angle image datasets. The geometry of the ATM sensor is derived to allow an understanding of the sampling characteristics of the instrument. Two important geometric factors are established: first, the area of the ground resolution element increases with view angle, which effectively reduces spatial resolution at off-nadir angles; and second, overlap between adjacent ground resolution elements increases with view angle, increasing the spatial auto-correlation between these samples. The effects of illumination, atmosphere and topography can all influence variance in an image. A parametric procedure for normalising multiple view angle (and therefore multitemporal) datasets for these factors is developed, based upon the production of reflectance images using a sky radiance model of the spectral and spatial distributions of irradiance, ground measurements of irradiance, and a digital terrain model of the study site. Finally, it is shown that image variance is likely to decrease at off-nadir view angles, the magnitude of this decrease being related to the sensor geometry and (more importantly) the geometry of the canopy. By a simple statistical analytical procedure it is possible to construct broad classes within which the nature of the canopy can be classified

How forward‐scattering snow and terrain change the Alpine radiation balance with application to solar panels

Rough terrain in mid- and high latitudes is often covered with highly reflective snow, giving rise to a very complex transfer of incident sunlight. In order to simplify the radiative transfer in weather and climate models, snow is generally treated as an isotropically reflecting material. We develop a new model of radiative transfer over mountainous terrain, which considers for the first time the forward scattering properties of snow. Combining ground-measured meteorological data and high resolution digital elevation models, we show that the forward scattering peak of snow leads to a strong local redistribution of incident terrain reflected radiation. In particular, the effect of multiple terrain reflections is enhanced. While local effects are large, area-wide albedo is only marginally decreased. In addition, we show that solar panels on snowy ground can clearly benefit from forward scattering, helping to maximize winter electricity production