Improved Surface Reflectance from Remote Sensing Data with Sub-Pixel Topographic Information

Roupioz, Laure; Nerry, Françoise; Li, Jia; Menenti, Massimo

doi:10.3390/rs61110356

Cited by 24 publications

(24 citation statements)

References 29 publications

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“…The impact of incident radiations reflected by the surrounding inclined surfaces has been highlighted in several studies [71][72][73][74]. As working at the square kilometer, the integration of sub-pixel topography may also improve the results as shown in [75].…”

Section: Discussionmentioning

confidence: 99%

Estimation of Daily Solar Radiation Budget at Kilometer Resolution over the Tibetan Plateau by Integrating MODIS Data Products and a DEM

Roupioz

Nerry

et al. 2016

Remote Sensing

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Considering large and complex areas like the Tibetan Plateau, an analysis of the spatial distribution of the solar radiative budget over time not only requires the use of satellite remote sensing data, but also of an algorithm that accounts for strong variations of topography. Therefore, this research aims at developing a method to produce time series of solar radiative fluxes at high temporal and spatial resolution based on observed surface and atmosphere properties and topography. The objective is to account for the heterogeneity of the land surface using multiple land surface and atmospheric MODIS data products combined with a digital elevation model to produce estimations daily at the kilometric level. The developed approach led to the production of a three-year time series (2008)(2009)(2010) of daily solar radiation budget at one kilometer spatial resolution across the Tibetan Plateau. The validation showed that the main improvement from the proposed method is a higher spatial and temporal resolution as compared to existing products. However, even if the solar radiation estimates are satisfying on clear sky conditions, the algorithm is less reliable under cloudy sky condition and the albedo product used here has a too coarse temporal resolution and is not accurate enough over rugged terrain.

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Section: Discussionmentioning

confidence: 99%

Estimation of Daily Solar Radiation Budget at Kilometer Resolution over the Tibetan Plateau by Integrating MODIS Data Products and a DEM

Roupioz

Nerry

et al. 2016

Remote Sensing

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“…Optical data collected by satellites is influenced by the atmospheric conditions between the satellite and the surface of the Earth, which can degrade the quality of the optical images 30,31 . In order to obtain the actual spectral characteristics of ground features, the ENVI quick atmospheric correction module 32 was used to remove the effects of the atmosphere in the images.…”

Section: Methodsmentioning

confidence: 99%

Could Vegetation Index be Derive from Synthetic Aperture Radar? – The Linear Relationship between Interferometric Coherence and NDVI

Bai

Fang

Gao

et al. 2020

Sci Rep

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Due to many factors in the physical properties of the ground surface, the corresponding interferometric coherence values change dynamically over time. Among these factors, the roles of the vegetation and its temporal variation have not yet been revealed so far. In this paper, synthetic aperture radar (Sentinel-1) data and optical remote sensing (Landsat TM) images over four whole seasons are employed to reveal the relationship between the interferometric coherence and the normalized difference vegetation index (NDVI) at five sites that have ground deformation due to mining in Henan province, China. The result showed: (1) As for the village area with few vegetation cover, the related coherence values are significantly higher than that in the farm land area with high densities of vegetation in the spring and summer, which indicates that the subsidence by mining in few vegetation cover area is easier to be monitored; (2) Linear regression coefficients (R 2) between the interfereometric coherence values and the NDVI values is 0.62, which indicate the interferometric coherence values and the nDVi values change reversely in both farm land and village areas over the year. it suggests months between November and March with lower NDVI value are more suitable for deformation detecting. Therefore, the interfereometric coherence values can be used to detect the density of vegetation, while NDVI values can be reference for elucidating when the traditional differential interferometric synthetic aperture radar (DInSAR) could be effectively used. DInSAR leverages the phase difference between two correlated synthetic aperture radar (SAR) images to accurately detect large scale surface displacements and is widely used for mine deformation monitoring 1-4. However, as the technique suffers from a number of limitations, including spatial decorrelation, thermal noise, Doppler centroid shift, and temporal decorrelation, it is not appropriate in certain situations 5-7. Some research address the limitations of traditional DInSAR disturbed by the agricultural activities, especially the high density of crop vegetation, in the test of the polarimetric InSAR (POLInSAR) technique for its ability to increase interferometric coherence 8,9. Therefore, it is necessary to elucidate the deformation monitoring conditions under which the traditional DInSAR can be effectively used. The coherence is also taken as the main parameter in target classification 10,11 , forest change detection 12-14 , and lake study 15,16. The extent of temporal changes in the scatterers is a key factor affecting interferometric coherence 11,17. In DInSAR deformation measurements, the interferometric coherence is used for selecting the stable scatterers to achieve better accuracy 5. Compared with other scatterers, vegetation has a larger impact on SAR image coherence. In the seasons when vegetation is growing, the temporal decorrelation phenomena is

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“…The pixel-level topographic effect dominates the reflectance of the solo slope through the alteration of local incidence and viewing geometry, as well as the distribution of the illuminated irradiance [20,29]. However, this effect is relatively small for the composite slope BRDF, and the sub-pixel level topographic effects become the primary factors, which include the shadow, distribution of sub-topographic slope and aspect statistic, and the redistribution of radiation within a remote sensing pixel [4,31].…”

Section: Model Building Procedures and Scientific Problemsmentioning

confidence: 99%

“…Consequently, dominant BRDF modeling over rugged terrain occurs on an infinite slope surface [17,20,21,27]. However, the focus of low resolution remote sensing data is not the topography influence at the pixel level, but the topography influence at the sub-pixel level [29][30][31]. There should be a robust relationship between these two different anisotropic reflectance resolution.…”

Section: Introductionmentioning

confidence: 99%

Characterizing Land Surface Anisotropic Reflectance over Rugged Terrain: A Review of Concepts and Recent Developments

et al. 2018

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Rugged terrain, including mountains, hills, and some high lands are typical land surfaces around the world. As a physical parameter for characterizing the anisotropic reflectance of the land surface, the importance of the bidirectional reflectance distribution function (BRDF) has been gradually recognized in the remote sensing community, and great efforts have been dedicated to build BRDF models over various terrain types. However, on rugged terrain, the topography intensely affects the shape and magnitude of the BRDF and creates challenges in modeling the BRDF. In this paper, after a brief introduction of the theoretical background of the BRDF over rugged terrain, the status of estimating land surface BRDF properties over rugged terrain is comprehensively reviewed from a historical perspective and summarized in two categories: BRDFs describing solo slopes and those describing composite slopes. The discussion focuses on land surface reflectance retrieval over mountainous areas, the difference in solo slope and composite slope BRDF models, and suggested future research to improve the accuracy of BRDFs derived with remote sensing satellites.

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Improved Surface Reflectance from Remote Sensing Data with Sub-Pixel Topographic Information

Cited by 24 publications

References 29 publications

Estimation of Daily Solar Radiation Budget at Kilometer Resolution over the Tibetan Plateau by Integrating MODIS Data Products and a DEM

Estimation of Daily Solar Radiation Budget at Kilometer Resolution over the Tibetan Plateau by Integrating MODIS Data Products and a DEM

Could Vegetation Index be Derive from Synthetic Aperture Radar? – The Linear Relationship between Interferometric Coherence and NDVI

Characterizing Land Surface Anisotropic Reflectance over Rugged Terrain: A Review of Concepts and Recent Developments

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