Direct Georeferencing of Ultrahigh-Resolution UAV Imagery

Turner, Darren; Lucieer, Arko; Wallace, Luke

doi:10.1109/tgrs.2013.2265295

Cited by 339 publications

(256 citation statements)

References 16 publications

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“…Dandois and Ellis [34] and Turner et al [40] provide a detailed description of the software and workflow. Briefly, the software uses the SfM approach for 3D reconstruction from overlapping collection of photographs.…”

Section: Processing Of Aerial Photographsmentioning

confidence: 99%

Aboveground Biomass Estimation Using Structure from Motion Approach with Aerial Photographs in a Seasonal Tropical Forest

Ota

Ogawa

Shimizu

et al. 2015

Forests

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Abstract:We investigated the capabilities of a canopy height model (CHM) derived from aerial photographs using the Structure from Motion (SfM) approach to estimate aboveground biomass (AGB) in a tropical forest. Aerial photographs and airborne Light Detection and Ranging (LiDAR) data were simultaneously acquired under leaf-on canopy conditions. A 3D point cloud was generated from aerial photographs using the SfM approach and converted to a digital surface model (DSMP). We also created a DSM from airborne LiDAR data (DSML). From each of DSMP and DSML, we constructed digital terrain models (DTM), which are DTMP and DTML, respectively. We created four CHMs, which were calculated from (1) DSMP and DTMP (CHMPP); (2) DSMP and DTML (CHMPL); (3) DSML and DTMP (CHMLP); and (4) DSML and DTML (CHMLL). Then, we estimated AGB using these CHMs. The model using CHMLL yielded the highest accuracy in four CHMs (R 2 = 0.94) and was comparable to the model using CHMPL (R 2 = 0.93). The model using CHMPP yielded the lowest accuracy (R 2 = 0.79). In conclusion, AGB can be estimated from CHM derived from aerial photographs using the SfM approach in the tropics. However, to accurately estimate AGB, we need a more accurate DTM than the DTM derived from aerial photographs using the SfM approach.

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Section: Processing Of Aerial Photographsmentioning

confidence: 99%

Aboveground Biomass Estimation Using Structure from Motion Approach with Aerial Photographs in a Seasonal Tropical Forest

Ota

Ogawa

Shimizu

et al. 2015

Forests

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“…The output of the SfM stage is a sparse, unscaled 3D point cloud in arbitrary units along with camera models and orientation [29,30,34,37]. The 3D point cloud can be registered to a projected coordinate system by identifying and incorporating ground control points in the bundle adjustment [26,27,29,38]. A dense image matching algorithm is then employed to extract a dense 3D point cloud from the images [29,[34][35][36][39][40][41][42].…”

Section: Introductionmentioning

confidence: 99%

Poppy Crop Height and Capsule Volume Estimation from a Single UAS Flight

et al. 2017

Self Cite

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Abstract:The objective of this study was to estimate poppy plant height and capsule volume with remote sensing using an Unmanned Aircraft System (UAS). Data were obtained from field measurements and UAS flights over two poppy crops at Cambridge and Cressy in Tasmania. Imagery acquired from the UAS was used to produce dense point clouds using structure from motion (SfM) and multi-view stereopsis (MVS) techniques. Dense point clouds were used to generate a digital surface model (DSM) and orthophoto mosaic. An RGB index was derived from the orthophoto to extract the bare ground spaces. This bare ground space mask was used to filter the points on the ground, and a digital terrain model (DTM) was interpolated from these points. Plant height values were estimated by subtracting the DSM and DTM to generate a Crop Height Model (CHM). UAS-derived plant height (PH) and field measured PH in Cambridge were strongly correlated with R 2 values ranging from 0.93 to 0.97 for Transect 1 and Transect 2, respectively, while at Cressy results from a single flight provided R 2 of 0.97. Therefore, the proposed method can be considered an important step towards crop surface model (CSM) generation from a single UAS flight in situations where a bare ground DTM is unavailable. High correlations were found between UAS-derived PH and poppy capsule volume (CV) at capsule formation stage (R 2 0.74), with relative error of 19.62%. Results illustrate that plant height can be reliably estimated for poppy crops based on a single UAS flight and can be used to predict opium capsule volume at capsule formation stage.

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“…The AGISOFT Photoscan Professional software, which implements modern SfM algorithms, was used to generate a point cloud from the RGB photographs. Detailed descriptions of the Photoscan workflow can be found, for example, in [20,21]. …”

Section: Aerial Image Acquisitionmentioning

confidence: 99%

Forest Stand Inventory Based on Combined Aerial and Terrestrial Close-Range Photogrammetry

Mikita

Janata

Surový

2016

Forests

107

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Abstract:In this article we introduce a new method for forest management inventories especially suitable for highly-valued timber where the precise estimation of stem parameters (diameter, form, and tapper) plays the key role for market purposes. The unmanned aerial system (UAS)-based photogrammetry is combined with terrestrial photogrammetry executed by walking inside the stand and the individual tree parameters are estimated. We compare two automatic methods for processing of the point clouds and the delineation of stem circumference at breast height. The error of the diameter estimation was observed to be under 1 cm root mean square error (RMSE) and the height estimation error was 1 m. Apart from the mentioned accuracy, the main advantage of the proposed work is shorter time demand for field measurement; we could complete both inventories of 1 hectare forest stand in less than 2 h of field work.

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Direct Georeferencing of Ultrahigh-Resolution UAV Imagery

Cited by 339 publications

References 16 publications

Aboveground Biomass Estimation Using Structure from Motion Approach with Aerial Photographs in a Seasonal Tropical Forest

Aboveground Biomass Estimation Using Structure from Motion Approach with Aerial Photographs in a Seasonal Tropical Forest

Poppy Crop Height and Capsule Volume Estimation from a Single UAS Flight

Forest Stand Inventory Based on Combined Aerial and Terrestrial Close-Range Photogrammetry

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