Using shadows in high-resolution imagery to determine building height

Comber, Alexis; Umezaki, Masahiro; Zhou, Rena; Ding, Ying; Li, Yang; Fu, Hua; Jiang, Hongwei; Tewkesbury, Andrew P.

doi:10.1080/01431161.2011.635161

Cited by 38 publications

(27 citation statements)

References 6 publications

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“…Our research used a somewhat similar approach of using a ratio of shadow and nonshadow regions to score pixels based on the likelihood of being within a saguaro shadow. The shadow method differs from Comber et al 6 and Shettigara and Sumerling 7 in that this research attempted to detect feature presence but not to estimate feature height. In addition, the aerial imagery used in this research contains a range of acquisition dates and times, while Comber et al 6 and Shettigara and Sumerling 7 used singular satellite imagery scenes.…”

Section: Introductionmentioning

confidence: 92%

“…Although shadows are often treated as unwanted noise in remote sensing research, they can be useful in object identification and feature measurement. Comber et al 6 presented a method for measuring the heights of buildings in satellite imagery by analyzing neighboring areas of high reflectance contrast. Shettigara and Sumerling 7 employed tree heights and shadows as calibration data to estimate building heights based on building shadows.…”

Section: Introductionmentioning

confidence: 99%

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Mapping saguaro cacti using digital aerial imagery in Saguaro National Park

Carter

Leeuwen

2018

J. Appl. Rem. Sens.

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Population research on the saguaro cactus (Carnegiea gigantea) has historically been limited to repeat monitoring efforts in small plots with areas of 1 to 4 hectares. Large extent saguaro censuses of areas >2.59 km 2 have not been undertaken. This research developed an automated shadow detection method for mapping mature saguaros in digital aerial imagery using saguaro shadows as proxies for saguaro locations. The shadow method detected 446,092 saguaro shadows in aerial imagery of 231 km 2 of the Saguaro National Park (SNP) near Tucson, Arizona. The results were validated against saguaro location data in 11 small plots provided by SNP staff. The shadow method correctly identified 58% of mature saguaros in these 11 plots. Twenty-one percent of the saguaros in the plots did not produce a shadow signature in the imagery. Fieldwork was conducted in two plot locations to investigate reasons why these mature saguaros failed to produce shadow signatures in the aerial imagery, which showed that vegetation interference, rocky slopes, and shadow alignments were the primary factors that precluded shadow signatures from appearing in the imagery. This research provides a methodology for automated large-area saguaro mapping, which will be useful in long-term population monitoring and saguaro ecology research.

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Section: Introductionmentioning

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Mapping saguaro cacti using digital aerial imagery in Saguaro National Park

Carter

Leeuwen

2018

J. Appl. Rem. Sens.

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“…The method overestimates the shadow lengths of buildings, resulting in large errors in calculated H B . In [11], the number of a building's storeys as well as its length and shape were inferred based on the identification of shadow areas. In the absence of detailed validation, it appears that the empirical nature of the rule-based classification may only be practical for the presented cases.…”

Section: Previous Workmentioning

confidence: 99%

A Shadow-Overlapping Algorithm for Estimating Building Heights From VHR Satellite Images

Kadhim

Mourshed

2018

IEEE Geosci. Remote Sensing Lett.

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Building height is a key geometric attribute for generating 3-D building models. We propose a novel four-stage approach for automated estimation of building heights from their shadows in very high resolution (VHR) multispectral images. First, a building's actual shadow regions are detected by applying ratio-band algorithm to the VHR image. Second, 2-D building footprint geometries are identified using graph theory and morphological fuzzy processing techniques. Third, artificial shadow regions are simulated using the identified building footprint and solar information in the image metadata at predefined height increments. Finally, the difference between the actual and simulated shadow regions at every height increment is computed using Jaccard similarity coefficient. The estimated building height corresponds to the height of the simulated shadow region that resulted in the maximum value for Jaccard index. The algorithm is tested on seven urban sites in Cardiff, U.K. with various levels of morphological complexity. Our method outperforms the past attempts, and the mean error is reduced by at least 21%.

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“…Shadow is considered as noise in some of the remote sensing existing literature [130], and considerable studies have been conducted to develop methods for detection and reduction or removal of shadow in remotely sensed imagery (for more details [131][132][133]). Nevertheless, one may employ shadows in the image as a valuable source of contextual information for enhancing the quality of tree identification tasks, as they provide a three-dimensional clue (i.e., proportional to width and height of the feature) on the existence of a tree feature adjacent to/in proximity to the shadow.…”

Section: Masking Candidate Tree Crown Land Covermentioning

confidence: 99%

Mapping the Individual Trees in Urban Orchards by Incorporating Volunteered Geographic Information and Very High Resolution Optical Remotely Sensed Data: A Template Matching-Based Approach

et al. 2018

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This paper presents a collective sensing approach that integrates imperfect Volunteered Geographic Information (VGI) obtained through Citizen Science (CS) tree mapping projects with very high resolution (VHR) optical remotely sensed data for low-cost, fine-scale, and accurate mapping of trees in urban orchards. To this end, an individual tree crown (ITC) detection technique utilizing template matching (TM) was developed for extracting urban orchard trees from VHR optical imagery. To provide the training samples for the TM algorithm, remotely sensed VGI about trees including the crowdsourced data about ITC locations and their crown diameters was adopted in this study. A data quality assessment of the proposed approach in the study area demonstrated that the detected trees had a very high degree of completeness (92.7%), a high thematic accuracy (false discovery rate (FDR) = 0.090, false negative rate (FNR) = 0.073, and F 1 score (F 1 ) = 0.918), and a fair positional accuracy (root mean square error (RMSE) = 1.02 m). Overall, the proposed approach based on the crowdsourced training samples generally demonstrated a promising ITC detection performance in our pilot project.

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Using shadows in high-resolution imagery to determine building height

Cited by 38 publications

References 6 publications

Mapping saguaro cacti using digital aerial imagery in Saguaro National Park

Mapping saguaro cacti using digital aerial imagery in Saguaro National Park

A Shadow-Overlapping Algorithm for Estimating Building Heights From VHR Satellite Images

Mapping the Individual Trees in Urban Orchards by Incorporating Volunteered Geographic Information and Very High Resolution Optical Remotely Sensed Data: A Template Matching-Based Approach

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