Review of shadow detection and de-shadowing methods in remote sensing

Shahtahmassebi, AmirReza; Yang, Ning; Wang, Ke; Moore, Nathan; Shen, Zhangquan

doi:10.1007/s11769-013-0613-x

Cited by 141 publications

(94 citation statements)

References 69 publications

(141 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Shadow detection answers the question where and to what extent shadow occurs in an image [28]. Shadow compensation on the other hand encompasses methods that can be used to reduce or avoid the impact of shadow cover on mapping [29]. A considerable number of shadow detection and compensation techniques have been developed for remote sensing but most focus on high resolution multispectral data.…”

Section: Introductionmentioning

confidence: 99%

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

Priem

Canters

2016

Remote Sensing

View full text Add to dashboard Cite

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.

show abstract

Section: Introductionmentioning

confidence: 99%

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

Priem

Canters

2016

Remote Sensing

View full text Add to dashboard Cite

show abstract

“…The current methods for shadow detection can be divided into three types [11][12][13]: (1) property-based methods [9,[13][14][15][16][17][18][19][20]; (2) geometrical methods [14,[17][18][19][20]; and (3) machine learning methods [15,16,21,22].…”

Section: Introductionmentioning

confidence: 99%

An Automatic Shadow Detection Method for VHR Remote Sensing Orthoimagery

Wang

Yuan

et al. 2017

Remote Sensing

View full text Add to dashboard Cite

Abstract:The application potential of very high resolution (VHR) remote sensing imagery has been boosted by recent developments in the data acquisition and processing ability of aerial photogrammetry. However, shadows in images contribute to problems such as incomplete spectral information, lower intensity brightness, and fuzzy boundaries, which seriously affect the efficiency of the image interpretation. In this paper, to address these issues, a simple and automatic method of shadow detection is presented. The proposed method combines the advantages of the property-based and geometric-based methods to automatically detect the shadowed areas in VHR imagery. A geometric model of the scene and the solar position are used to delineate the shadowed and non-shadowed areas in the VHR image. A matting method is then applied to the image to refine the shadow mask. Different types of shadowed aerial orthoimages were used to verify the effectiveness of the proposed shadow detection method, and the results were compared with the results obtained by two state-of-the-art methods. The overall accuracy of the proposed method on the three tests was around 90%, confirming the effectiveness and robustness of the new method for detecting fine shadows, without any human input. The proposed method also performs better in detecting shadows in areas with water than the other two methods.

show abstract

“…Especially in the mountainous environment, shadows frequently occur in terrain areas with steep slopes (Giles, 2001;Dare, 2005). As a result, the accuracy of land cover/ use mapping procedure over steep mountainous terrain is often low (Dorren et al, 2003;Shahtahmassebi et al, 2013). In Taiwan, the landscape is often characterized as alpine terrain, thus using very high resolution images for land cover/ use mapping will be severely affected by the shadow problem.…”

Section: Introductionmentioning

confidence: 99%

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.

View full text Add to dashboard Cite

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.

show abstract

Review of shadow detection and de-shadowing methods in remote sensing

Cited by 141 publications

References 69 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

An Automatic Shadow Detection Method for VHR Remote Sensing Orthoimagery

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

Contact Info

Product

Resources

About