Estimating the Optimal Threshold for Accuracy Assessment of the Global Ecosystem Dynamics Investigation (GEDI) Data in a Gentle Relief Urban Area

Barbosa, Felipe Lima Ramos; Guimarães, Renato Fontes; Júnior, Osmar Abı́lio de Carvalho; Gomes, Roberto Arnaldo Trancoso; Carvalho, Osmar Luiz Ferreira de; Lima, Thyego Pery Monteiro de

doi:10.3390/rs14153540

Cited by 3 publications

(3 citation statements)

References 52 publications

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“…Quality_flag her bir GEDI verisi için yardımcı bilgi olarak verilmektedir. Eğer quality_flag=1 ise kullanılabilir olduğuna quality_flag=0 ise kullanılamaz veri olduğunu göstermektedir (Barbosa et al 2022). Ayrıca GEDI verisinin sonuçları araştırılırken ölçümün gerçekleştiği zamanın sabah ya da gece olduğunu gösteren "solar_elevation" bilgisine göre doğruluk araştırılmıştır.…”

Section: Gedi Veri Indirme Ve Filtreleme Adımlarıunclassified

GEDI Uydu Tabanlı Lazer Altimetre Verisinin Arazi Yükseklik Tahmininin Araştırılması

NARİN,

YİLMAZ

2024

Afyon Kocatepe University Journal of Sciences and Engineering

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Global Ecosystem Dynamics Investigate (GEDI), orman örtüsü, su seviyesi ve arazi yüksekliği tahmini gibi birçok alanda yeryüzünün gözlemlenmesi için kullanılan uzay kaynaklı bir lazer altimetre sistemidir. GEDI verileri, gözlem sırasında kullanılan sensör nedeniyle atmosferik etkilerden etkilenmektedir. Çalışmamızda Türkiye’nin batısında yer alan Afyonkarahisar ili sınırları içerisindeki 55 kontrol noktası ile GEDI noktası karşılaştırmıştır. Ayrıca çalışmada GEDI verisinin hassasiyetinin daha detaylı incelenmesi için “solar_elevation” ve eğime göre karşılaştırma yapılmıştır. Karşılaştırma için doğruluk metriği olarak Karesel Ortalama Hata (KOH) kullanılmıştır. Sonuç olarak GEDI verisinin gece zamanlarında ve eğimin düşük olduğu alanlarda doğruluğunun arttığı görülmüştür. Çalışmamızda 55 nokta için arazi yüksekliği belirlemede GEDI verisi KOH’a göre 2.79 m, gece ve düşük eğimli 30 noktada ise 2.34 m başarı göstermiştir.

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Section: Gedi Veri Indirme Ve Filtreleme Adımlarıunclassified

GEDI Uydu Tabanlı Lazer Altimetre Verisinin Arazi Yükseklik Tahmininin Araştırılması

NARİN,

YİLMAZ

2024

Afyon Kocatepe University Journal of Sciences and Engineering

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“…It is set to 255 when the gray value exceeds the set threshold. The threshold segmentation methods consist of the global threshold method [31] and the local threshold method [32].…”

Section: Image Binarizationmentioning

confidence: 99%

Crack Segmentation Extraction and Parameter Calculation of Asphalt Pavement Based on Image Processing

Li,

Yin,

Zhang

2023

Sensors

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Crack disease is one of the most serious and common diseases in road detection. Traditional manual methods for measuring crack detection can no longer meet the needs of road crack detection. In previous work, the authors proposed a crack detection method for asphalt pavements based on an improved YOLOv5s model, which is a better model for detecting various types of cracks in asphalt pavements. However, most of the current research on automatic pavement crack detection is still focused on crack identification and location stages, which contributes little to practical engineering applications. Based on the shortcomings of the above work, and in order to improve its contribution to practical engineering applications, this paper proposes a method for segmenting and analyzing asphalt pavement cracks and identifying parameters based on image processing. The first step is to extract the crack profile through image grayscale, histogram equalization, segmented linear transformation, median filtering, Sauvola binarization, and the connected domain threshold method. Then, the magnification between the pixel area and the actual area of the calibration object is calculated. The second step is to extract the skeleton from the crack profile images of asphalt pavement using the Zhang–Suen thinning algorithm, followed by removing the burrs of the crack skeleton image using the connected domain threshold method. The final step is to calculate physical parameters, such as the actual area, width, segments, and length of the crack with images obtained from the crack profile and skeleton. The results show that (1) the method of local thresholding and connected domain thresholding can completely filter noise regions under the premise of retaining detailed crack region information. (2) The Zhang–Suen iterative refinement algorithm is faster in extracting the crack skeleton of asphalt pavement, retaining the foreground features of the image better, while the connected-domain thresholding method is able to eliminate the missed isolated noise. (3) In comparison to the manual calibration method, the crack parameter calculation method proposed in this paper can better complete the calculation of crack length, width, and area within an allowable margin of error. On the basis of this research, a windowing system for asphalt pavement crack detection, WSPCD1.0, was developed. It integrates the research results from this paper, facilitating automated detection and parameter output for asphalt pavement cracks.

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“…After selecting quality_flag 1 for terrain determination in all areas, a value for the RMSE = 4.03 m for 90,472 footprints was obtained, while full power & night data were selected to obtain an RMSE = 3.53 m for 22,972 footprints. [8] investigated the optimal threshold of accuracy assessment in GEDI data using the Kolmogorov-Smirnov test and other parameters in the Brasília, the capital of Brazil. They stated that a total of 7,619 GEDI data sets had an RMSE value of 5946.73 m. As a result of the methods they applied, 502 GEDI data remained and RMSE of these data decreased to 1.32 m.…”

Section: Introductionmentioning

confidence: 99%

Multi-Criteria Strategy for Estimating GEDI Terrain Height

Narin,

Lindenbergh,

Abdikan

2023

2023 10th International Conference on Recent Advances in Air and Space Technologies (RAST)

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Global Ecosystem Dynamics Investigate (GEDI) is a spaceborne laser altimeter system used for earth observation in many areas such as forest canopy, water level and terrain height estimation. GEDI data is affected by atmospheric effects due to the sensor used while observing. In this study, we propose a 7-step, multi-variable strategy for determining the elevation of the terrain with GEDI. These steps involve both different geoid models, GEDI ancillary data, and topographic features. We evaluated the effect of each step using high quality DEM data obtained by Airborne LiDAR over the central part of Puerto Rico, where building areas and forests are dominant, while the terrain has an average slope of 24%. The GEDI data of the test area consists of 3 different orbits (O06225, O07933, O08061) with different solar elevation and cloudiness rates. While the raw data of orbit O06225, obtained during a solar elevation of 8.4 and cloudy conditions, has a Root Mean Square Error (RMSE) of 418.67 m., the RMSE is reduced to 4.59 m. after applying all seven filtering steps. The raw data of orbit O07933, obtained with a solar elevation of 50.5 during cloud free conditions, has a RMSE of 10.04 m., and is reduced to a similar value of 4.8 m. as a result of the filtering steps. On the other hand, orbit O08061 was obtained with little clouds during a near-dawn solar elevation of -0.7. Its raw RMSE of 50,34 m could only be reduced to 12.41 m. by the proposed filtering procedure. It is concluded that although there are many outliers in data acquired during cloudy conditions, the accuracy of the data remaining after applying our filtering strategy can be as high as the accuracy obtained during cloud free conditions. Better results than 5 m were obtained according to the RMSE in areas with low solar elevation. In addition, it is observed that accuracy decreases strongly when the solar elevation is close to 0. Overall, it is concluded that appropriate filtering is required when determining terrain height with GEDI data.

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Estimating the Optimal Threshold for Accuracy Assessment of the Global Ecosystem Dynamics Investigation (GEDI) Data in a Gentle Relief Urban Area

Cited by 3 publications

References 52 publications

GEDI Uydu Tabanlı Lazer Altimetre Verisinin Arazi Yükseklik Tahmininin Araştırılması

GEDI Uydu Tabanlı Lazer Altimetre Verisinin Arazi Yükseklik Tahmininin Araştırılması

Crack Segmentation Extraction and Parameter Calculation of Asphalt Pavement Based on Image Processing

Multi-Criteria Strategy for Estimating GEDI Terrain Height

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