Application Oriented Quality Evaluation of Gaofen-7 Optical Stereo Satellite Imagery

Tian, J.; Zhuo, Xiangyu; Yuan, Xiangtian; Henry, Corentin; d’Angelo, Pablo; Krauss, Thomas F.

doi:10.5194/isprs-annals-v-1-2022-145-2022

Cited by 7 publications

(5 citation statements)

References 17 publications

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“…By analyzing the change information within each building polygon, object-based damage assessment reports can be generated. Therefore, connected component analysis is employed in this study to extract information for each irregular block and its internal contents [35].…”

Section: Buildings Floor Level Damage Assessmentmentioning

confidence: 99%

“…Given the substantial volume of collapsed buildings to locate and classify, relying solely on manual labor is not a viable option. To overcome this challenge, Tian and Wang utilized image segmentation methodologies to accomplish automated extraction and batch processing of building footprints [21,35]. Initially, non-building regions such as vegetation, bare land, and shadows were extracted, followed by the masking of these regions to retain only the building areas and achieve more accurate assessment of building damages.…”

Section: Introductionmentioning

confidence: 99%

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Rapid Fine-Grained Damage Assessment of Buildings on a Large Scale: A Case Study of the February 2023 Earthquake in Turkey

Hong,

Zhang,

Tong

et al. 2024

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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High resolution stereo satellite images (HRSSIs) have the potential to provide accurate height and volume information, playing a crucial role in assessing building collapses during various natural disasters. However, the time-consuming process of 3D reconstruction, inadequate vertical accuracy of digital surface model (DSM), and concentrated clustering of buildings pose challenges for collapse assessment focused on buildings. Therefore, we present an improved approach for rapid fine-grained assessment of building collapses. Firstly, accurate and consistent positioning parameters for HRSSIs are obtained through the combined block adjustment using laser altimetry points (LAPs), ensuring the generation of DSMs with vertical accuracy exceeding 2m. Next, a set of rapid 3D reconstruction techniques are introduced, achieving a significant eight-fold improvement in generating DSMs. Subsequently, we deploy an automated workflow for batch processing and registration of open-source building footprints, enabling accurate extraction of building height changes from dual-time DSMs. Finally, based on the building change image, a large-scale GIS image of building floor-level collapses is generated using connected component detection and threshold classification strategies. These findings have far-reaching implications for post-disaster emergency response, damage assessment, and expeditious reconstruction efforts. In our study, we processed an 800 square kilometer area in Kahramanmaras Province, Turkey, generating dual-time DSMs within one hour. This enabled the assessment of floor-level collapses for a total of 48,092 buildings within the area. Validation was conducted on 361 houses in the city center, utilizing Google Street View images as ground truth. Remarkably, our approach achieved a high accuracy rate of 93.27% in floorlevel assessment.

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Section: Buildings Floor Level Damage Assessmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Rapid Fine-Grained Damage Assessment of Buildings on a Large Scale: A Case Study of the February 2023 Earthquake in Turkey

Hong,

Zhang,

Tong

et al. 2024

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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“…It can effectively acquire 20 km wide front-view panchromatic stereoscopic images with a 0.8 m resolution, rear-view panchromatic stereoscopic images with a 0.65 m resolution, and multi-spectral images with a 2.6 m resolution [38]. Currently, the Gaofen-7 satellite is mainly used for natural resource survey monitoring and global geo-information resource construction [39]. It also provides high-precision satellite remote sensing images for the fields of urban and rural development as well as national survey statistics.…”

Section: Data Sourcesmentioning

confidence: 99%

“…resource construction [39]. It also provides high-precision satellite remote sensing images for the fields of urban and rural development as well as national survey statistics.…”

Section: Datasetsmentioning

confidence: 99%

An Information Extraction Method for Industrial and Commercial Rooftop Photovoltaics Based on GaoFen-7 Remote Sensing Images

Tao,

He,

Wang

et al. 2023

Remote Sensing

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With the increasing global focus on renewable energy, distributed rooftop photovoltaics (PVs) are gradually becoming an important form of energy generation. Effective monitoring of rooftop PV information can obtain their spatial distribution and installed capacity, which is the basis used by management departments to formulate regulatory policies. Due to the time-consuming and labor-intensive problems involved in manual monitoring, remote-sensing-based monitoring methods are getting more attention. Currently, remote-sensing-based distributed rooftop PV monitoring methods are mainly used as household rooftop PVs, and most of them use aerial or satellite images with a resolution higher than 0.3 m; there is no research on industrial and commercial rooftop PVs. This study focuses on the distributed industrial and commercial rooftop PV information extraction method based on the Gaofen-7 satellite with a resolution of 0.65 m. First, the distributed industrial and commercial rooftop PV dataset based on Gaofen-7 satellite and the optimized public PV datasets were constructed. Second, an advanced MANet model was proposed. Compared to MANet, the proposed model removed the downsample operation in the first stage of the encoder and added an auxiliary branch containing the Atrous Spatial Pyramid Pooling (ASPP) module in the decoder. Comparative experiments were conducted between the advanced MANet and state-of-the-art semantic segmentation models. In the Gaofen-7 satellite PV dataset, the Intersection over Union (IoU) of the advanced MANet in the test set was improved by 13.5%, 8.96%, 2.67%, 0.63%, and 0.75% over Deeplabv3+, U2net-lite, U2net-full, Unet, and MANet. In order to further verify the performance of the proposed model, experiments were conducted on optimized public PV datasets. The IoU was improved by 3.18%, 3.78%, 3.29%, 4.98%, and 0.42%, demonstrating that it outperformed the other models.

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“…Previous work (Tian et al, 2022, Luo et al, 2021 has evaluated the quality of the Gaofen-7 data from the application-oriented aspects, including 3D modeling, building extraction, and road extraction, but no detailed evaluation of the underlying elevation models is performed. Detection of tectonic faults based on GF-7 digital elevation models was investigated in (Zhu et al, 2023), and the geolocation accuracy and quality of the elevation model was evaluated in this context.…”

Section: Introductionmentioning

confidence: 99%

Geometric Evaluation of Gaofen-7 Stereo Data

d’Angelo,

Tian

2023

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. China’s first sub-metre stereo satellite, GaoFen-7, was launched on 7 November 2019. One of the main criteria for a stereo mapping satellite is the geometric accuracy of the images. In this paper, we present a systematic evaluation of the geometry accuracy of Gaofen-7 on two scenes over the centre of Munich, Germany. The geometry accuracy is evaluated in a three-step workflow: 1) direct georeferencing accuracy; 2) image orientation using bundle adjustment with ground control points; 3) height accuracy of the generated digital surface model (DSM). In addition to dense LiDAR point clouds, ground control points were measured in the field. These were used as references. The results show that RPC bundle adjustment with 0 order bias correction is sufficient to achieve sub-metre absolute accuracy. The height accuracy of the generated digital surface models varies with land cover type, ranging from 0.9m (NMAD) in open areas to 4.5m in urban areas.

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Application Oriented Quality Evaluation of Gaofen-7 Optical Stereo Satellite Imagery

Cited by 7 publications

References 17 publications

Rapid Fine-Grained Damage Assessment of Buildings on a Large Scale: A Case Study of the February 2023 Earthquake in Turkey

Rapid Fine-Grained Damage Assessment of Buildings on a Large Scale: A Case Study of the February 2023 Earthquake in Turkey

An Information Extraction Method for Industrial and Commercial Rooftop Photovoltaics Based on GaoFen-7 Remote Sensing Images

Geometric Evaluation of Gaofen-7 Stereo Data

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