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

Changes of glacier area in the Austrian alps between 1973 and 1992 derived from Landsat data

Data from Landsat satellite sensors are used to obtain an inventory of 165 Austrian glaciers and their temporal change. Applications and modifications of existing remote sensing algorithms for glacier clas- sification are discussed. A trend analysis of the glacier area from a Landsat MSS scene (208/27, Sep. 13, 1973) and two TM scenes (193/27, Sep. 30, 1985 and Sep. 17,1992) reveals: - Glaciers with areas below l km2, usually excluded from direct observations, shrank significantly by 25 percent between 1973 and 1992. -- There is a strong decrease of glacier area between 1985 and 1992 for glaciers of all sizes. - Decrease depends on exposition, with highest values found for glaciers exposed to the south and east. - Accumulation and ablation zones of glaciers are distinguishable by remote sensing, so that the annual net mass balance may be estimated remotely

A new method to determine multi-angular reflectance factor from lightweight multispectral cameras with sky sensor in a target-less workflow applicable to UAV

A new physically based method to estimate hemispheric-directional reflectance factor (HDRF) from lightweight multispectral cameras that have a downwelling irradiance sensor is presented. It combines radiometry with photogrammetric computer vision to derive geometrically and radiometrically accurate data purely from the images, without requiring reflectance targets or any other additional information apart from the imagery. The sky sensor orientation is initially computed using photogrammetric computer vision and revised with a non-linear regression comprising radiometric and photogrammetry-derived information. It works for both clear sky and overcast conditions. A ground-based test acquisition of a Spectralon target observed from different viewing directions and with different sun positions using a typical multispectral sensor configuration for clear sky and overcast showed that both the overall value and the directionality of the reflectance factor as reported in the literature were well retrieved. An RMSE of 3% for clear sky and up to 5% for overcast sky was observed

Validation of a simplified model to generate multispectral synthetic images

A new procedure to assess the quality of topographic correction (TOC) algorithms applied to remote sensing imagery was previously proposed by the authors. This procedure was based on a model that simulated synthetic scenes, representing the radiance an optical sensor would receive from an area under some specific conditions. TOC algorithms were then applied to synthetic scenes and the resulting corrected scenes were compared with a horizontal synthetic scene free of topographic effect. This comparison enabled an objective and quantitative evaluation of TOC algorithms. This approach showed promising results but had some shortcomings that are addressed herein. First, the model, originally built to simulate only broadband panchromatic scenes, is extended to multispectral scenes in the visible, near infrared (NIR), and short wave infrared (SWIR) bands. Next, the model is validated by comparing synthetic scenes with four Satellite pour l'Observation de la Terre 5 (SPOT5) real scenes acquired on different dates and different test areas along the Pyrenees mountain range (Spain). The results obtained show a successful simulation of all the spectral bands. Therefore, the model is deemed accurate enough for its purpose of evaluating TOC algorithms.The authors gratefully acknowledge the financial support provided by the Public University of Navarre (UPNA). Part of the research presented in this paper is funded by the Spanish Ministry of Economy and Competitiveness in the frame of the ESP2013-48458-C4-2-P project

Vliv atmosférické a topografické korekce na přesnost odhadu množství chlorofylu ve smrkových lesních porostech

Odstraňování efektů zemské atmosféry (tzv. atmosférická korekce) je jednou z klíčových součástí předzpracování obrazových dat dálkového průzkumu Země používaných pro kvantitativní nebo semi-kvantitativní analýzu. Přestože v současné době existuje velké množství robustních výpočetních technik kvantitativního odhadu různých parametrů zemského povrchu, vliv atmosférické korekce na výsledky těchto odhadů zpravidla není brán dostatečně v úvahu. Hlavním cílem této práce je zhodnocení vlivu použití různých technik atmosférické korekce na přesnost kvantitativního odhadu množství chlorofylu v lesních porostech smrku ztepilého (Picea abies). Obsah chlorofylu byl určován na podkladě výpočtu vybraných vegetačních indexů, které jsou na obsah chlorofylu citlivé (ANCB650-720, MSR, N718, TCARI/OSAVI a D718/D704). Hodnoty těchto indexů byly simulovány pomocí kombinace modelů radiativního transferu PROSPECT a DART. Výsledné odhady obsahu chlorofylu byly na závěr validovány pomocí výsledků laboratorního stanovení obsahu chlorofylu v odebraných vzorcích smrkových jehlic. Kromě toho byl v rámci práce odvozen nový index pro hodnocení podobnosti dvou srovnávaných spekter nazvaný normalized Area Under Difference Curve (nAUDC). V rámci této práce byla testována potenciální možnost náhrady standardní atmosférické korekce...Removal of atmospheric effects (atmospheric correction) is an essential step in a pre-processing chain of all remotely sensed image data used for any quantitative or semi-quantitative analysis. Although there are many robust computing techniques allowing quantitative estimation of various parameters of the Earth's surface, the influence of atmospheric correction on the accuracy of such estimation is usually not taken into account at all. The main focus of this thesis is to assess the influence of the use of different atmospheric correction techniques on the Norway spruce (Picea abies) canopy chlorophyll content estimation accuracy. Canopy chlorophyll content was estimated using values of chlorophyll sensitive vegetation indices (ANCB650-720, MSR, N718, TCARI/OSAVI and D718/D704) simulated by a coupling of PROSPECT and DART radiative transfer models and validated by a ground-truth dataset. A new spectral similarity index called normalized Area Under Difference Curve (nAUDC) was developed to allow mutual comparison of two spectra originating from hyperspectral datasets corrected by different atmospheric correction methods. Potential substitutability of the standard physically-based ATCOR-4 atmospheric correction by the empirical correction based on the data acquired by the downwelling irradiance...Department of Applied Geoinformatics and CartographyKatedra aplikované geoinformatiky a kartografiePřírodovědecká fakultaFaculty of Scienc

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

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