A Comparison of 4 Shadow Compensation Techniques for Land Cover Classification of Shaded Areas from High Radiometric Resolution Aerial Images

Wu, Shou-Tsung; Hsieh, Yi-Ta; Chen, Chaur-Tzuhn; Chen, Jan-Chang

doi:10.1080/07038992.2014.979488

Cited by 17 publications

(11 citation statements)

References 21 publications

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“…Here, a DSM and other LiDAR derived features such as sky view factor are used to model different irradiance components which are in turn entered in a non-linear spectral correction model. Direct classification or classification of shaded areas using shaded material training data is a shadow compensation technique that has been applied with relative success for classifying multispectral imagery [38] but remains remarkably unexplored for hyperspectral data. This approach relies on the idea that radiances received from shaded areas are still material dependent and assumes that a significant amount of class related spectral information is still present in shadow [28].…”

Section: Introductionmentioning

confidence: 99%

Synergistic Use of LiDAR and APEX Hyperspectral Data for High-Resolution Urban Land Cover Mapping

Priem

Canters

2016

Remote Sensing

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Land cover mapping of the urban environment by means of remote sensing remains a distinct challenge due to the strong spectral heterogeneity and geometric complexity of urban scenes. Airborne imaging spectroscopy and laser altimetry have each made remarkable contributions to urban mapping but synergistic use of these relatively recent data sources in an urban context is still largely underexplored. In this study a synergistic workflow is presented to cope with the strong diversity of materials in urban areas, as well as with the presence of shadow. A high-resolution APEX hyperspectral image and a discrete waveform LiDAR dataset covering the Eastern part of Brussels were made available for this research. Firstly, a novel shadow detection method based on LiDAR intensity-APEX brightness thresholding is proposed and compared to commonly used approaches for shadow detection. A combination of intensity-brightness thresholding with DSM model-based shadow detection is shown to be an efficient approach for shadow mask delineation. To deal with spectral similarity of different types of urban materials and spectral distortion induced by shadow cover, supervised classification of shaded and sunlit areas is combined with iterative LiDAR post-classification correction. Results indicate that height, slope and roughness features contribute to improved classification accuracies in descending order of importance. Results of this study illustrate the potential of synergistic application of hyperspectral imagery and LiDAR for urban land cover mapping.

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Section: Introductionmentioning

confidence: 99%

Synergistic Use of LiDAR and APEX Hyperspectral Data for High-Resolution Urban Land Cover Mapping

Priem

Canters

2016

Remote Sensing

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“…In an optical image, shadows are formed by obstructing direct light. The lower DN values in the shadow areas cause partial or total loss of radiometric information in the affected areas (Dare, 2005;Yuan, 2008;Zhou et al, 2009), the loss of radiometric information is the absence of direct light (Adeline et al, 2013;Wu et al, 2014 In addition, the mean DN values of all plots for the R, G, and B bands in the non-shadow area are non-vegetation>water bodies>vegetation, whereas those in the shadow area are water bodies>non-vegetation>vegetation (Table 3 and Table 4) (Figure 2). Regardless of shadow or non-shadow, the DN values for vegetation in the NIR band are significantly highest than water bodies and non-vegetation, indicating that NIR effectively reflects vegetation conditions (Table 3 and Table 4) (Figure 2).…”

Section: Spectral Characteristics Of the Shadow Areamentioning

confidence: 99%

“…Under these conditions, target objects in a shadow area are irradiated by the scattered light and reflected light from the surrounding environment (Chakraborti, 2007;Makarau et al, 2011;Adeline et al, 2013;Wu et al, 2014). Conversely, target objects in a non-shadow area not only receive scattered and reflected light, but also direct light.…”

Section: Introductionmentioning

confidence: 99%

“…In recent years, airborne multispectral aerial image devices have produced high radiometric resolution data (12-bit or higher), providing more radiometric details for potential use in classification or interpretation of land cover of shadow areas (Wu et al 2014). High radiometric resolution data offers great possibilities for the observation of the spectral characteristics of shadow area and solving the shadow problem .…”

Section: Introductionmentioning

confidence: 99%

“…However, few studies focused on how high radiometric resolution data was dealt with the shadow problem (Wu et al 2014), and worked on classifying or interpreting the land cover of shadow areas in remote sensing images (Zhou et al 2009;Wu et al 2014). Even, fewer ones are analyzing the spectral properties in the shadow areas.…”

Section: Introductionmentioning

confidence: 99%

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Analyzing Spectral Characteristics of Shadow Area From Ads-40 High Radiometric Resolution Aerial Images

Hsieh¹,

Wu²,

Chen³

et al. 2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Commission VII, WG VII/4KEY WORDS: Shadow, shadow spectra, ADS-40, high radiometric resolution ABSTRACT:The shadows in optical remote sensing images are regarded as image nuisances in numerous applications. The classification and interpretation of shadow area in a remote sensing image are a challenge, because of the reduction or total loss of spectral information in those areas. In recent years, airborne multispectral aerial image devices have been developed 12-bit or higher radiometric resolution data, including Leica ADS-40, Intergraph DMC. The increased radiometric resolution of digital imagery provides more radiometric details of potential use in classification or interpretation of land cover of shadow areas. Therefore, the objectives of this study are to analyze the spectral properties of the land cover in the shadow areas by ADS-40 high radiometric resolution aerial images, and to investigate the spectral and vegetation index differences between the various shadow and non-shadow land covers. According to research findings of spectral analysis of ADS-40 image: (i) The DN values in shadow area are much lower than in nonshadow area; (ii) DN values received from shadowed areas that will also be affected by different land cover, and it shows the possibility of land cover property retrieval as in nonshadow area; (iii) The DN values received from shadowed regions decrease in the visible band from short to long wavelengths due to scattering; (iv) The shadow area NIR of vegetation category also shows a strong reflection; (v) Generally, vegetation indexes (NDVI) still have utility to classify the vegetation and non-vegetation in shadow area. The spectral data of high radiometric resolution images (ADS-40) is potential for the extract land cover information of shadow areas.

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Comparison of manual and automated shadow detection on satellite imagery for agricultural land delineation

Tarko

Bruin

Bregt

2018

International Journal of Applied Earth Observation and Geoinfor

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A Comparison of 4 Shadow Compensation Techniques for Land Cover Classification of Shaded Areas from High Radiometric Resolution Aerial Images

Cited by 17 publications

References 21 publications

Synergistic Use of LiDAR and APEX Hyperspectral Data for High-Resolution Urban Land Cover Mapping

Synergistic Use of LiDAR and APEX Hyperspectral Data for High-Resolution Urban Land Cover Mapping

Analyzing Spectral Characteristics of Shadow Area From Ads-40 High Radiometric Resolution Aerial Images

Comparison of manual and automated shadow detection on satellite imagery for agricultural land delineation

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