Comparison of different resolutions of six free online DEMs with GPS elevation data on a new 6th of October City, Egypt

Aziz, Khaled Mahmoud Abdel; Rashwan, Karim Samir

doi:10.1007/s12517-022-10845-5

Cited by 4 publications

(2 citation statements)

References 10 publications

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“…Furthermore, combination of Landsat‐8 OLI and Sentinel‐2 MSI data for initial assessment of SOC may be an interesting topic (Velazquez et al, 2022). In terms of used DEM with a resolution of 30 m derived from SRTM (USGS, 2018), application of other DEMs i.e., NASADEM 1 arc‐second and ASTER 1 arc‐second may provide an improved result (Aziz & Rashwan, 2022). Furthermore, despite the fact that XGBoost Tree is unaffected by multicollinearity of the predictor variables, it is also suggested to detect the multicollinearity and to omit the highly correlated predictors which may change the results of modelling.…”

Section: Resultsmentioning

confidence: 99%

Digital assessments of soil organic carbon storage using digital maps provided by static and dynamic environmental covariates

Shirazi

Shahbazi

Rezaei

et al. 2023

Soil Use and Management

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Understanding the vertical and lateral distribution of soil organic carbon (SOC) and soil organic carbon density (SOCD) is indispensable for soil use and environmental management because of their vital role in soil quality assessments. Primarily, they are needed in calculating soil organic carbon storage (SOCS). The objective of this research was to provide digital maps of SOC and SOCD variation as well as their uncertainties at multiple standardized depths (H1: 0–5, H2: 5–15, H3: 15–30, H4: 30–60 and H5: 60–100 cm) using a parsimonious model with optimized terrain‐related attributes and satellite‐derived data. SOCS were evaluated at soil subgroup levels. An area of about 808 km2 with varying elevation, plant cover and lithology from the Miandoab region, West Azerbaijan Province, Iran was selected as a case study area. A total of 386 soil samples were collected from 104 profiles comprising various soil genetic horizons. A continuous spline function was then fitted to the target properties in advance of creating a dataset at five standard depth intervals (following the GlobalSoilMap project). These were then grouped into three classes including top (H1), middle (H2, H3 and H4) and bottom (H5) depths to ease interpretation. Static and dynamic covariates (30‐m resolution) were derived from a digital elevation model (DEM) and a suite of Landsat‐8 spectral imageries, respectively. Four candidate models including stepwise multiple linear regression (SMLR), random forest (RF), cubist (CU) and extreme gradient boosting (XGBoost) Tree were tested in this study. Finally, the digital maps at 30‐m resolution of SOC and SOCD and their uncertainties were prepared using the best‐fit model and the bootstrapping method, respectively. Four soil subgroups (Gypsic Haploxerepts, Typic Calcixerepts, Typic Haploxerepts and Xeric Haplocalcids) were identified across the study area. The covariates had variable contributions on the evaluated models. The XGBoost Tree model generally outperformed other models for prediction of SOC and SOCD (R2 = 0.60, on average). Regardless of soil subgroups, the uncertainty analysis showed that the SOCD map had a low prediction interval range value indicating high accuracy. Additionally, the highest SOCS and SOCD was observed at the top followed by middle and bottom depths in the study area. All subgroups exhibited a decreasing trend of SOCD with increasing depth. A similar trend was also observed for SOCS. The highest SOCD (on average) was observed in Gypsic Haploxerepts (4.71 kg C/m2) followed by Typic Calcixerepts (4.46 kg C/m2), Typic Haploxerepts (4.45 kg C/m2) and Xeric Haplocalcids (4.40 kg C/m2). Overall, the SOCS normalized by area within soil order boundaries was greater in Inceptisols than Aridisols across the study area. The findings of this study provide critical information for sustainable management of soil resources in the area for agricultural production and environmental health in the Miandoab region of Iran.

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Section: Resultsmentioning

confidence: 99%

Digital assessments of soil organic carbon storage using digital maps provided by static and dynamic environmental covariates

Shirazi

Shahbazi

Rezaei

et al. 2023

Soil Use and Management

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“…On the other hand, research also has shortcomings in terms of the use of spatial data. For example, land elevation data has a fairly old year of data, and there is a possibility of resolution bias which causes it to be less accurate, as stated in the research [28].…”

Section: Discussionmentioning

confidence: 99%

Mitigation Control on Industrial Allotment Area Plan based on Tsunami Hazard Prone Zoning Area in Purworejo Regency, Central Java

Kusuma,

Ratiningsih

2024

IOP Conf. Ser.: Earth Environ. Sci.

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Purworejo district has determined an industrial allotment area of 922,238 hectares along the south coast. Meanwhile, the coast of Purworejo Regency is part of the southern coast of Java Island and has the potential to be affected by tsunamis. Tsunami disaster events in the south of Java Island recorded run-up of up to 15,7 meters and recent research shows a potential run-up of 34 meters. The study aimed to identify tsunami hazard zones and directions of control based on modelling of inundation potential. The determination of the hazard zone was conducted through spatial classification analysis, while the direction of mitigation control was formulated by descriptive analysis. The high tsunami hazard zone in the 15,7 meters run-up scenario covers 0,33% of the industrial allotment area and the high tsunami hazard zone in the 20 meters run-up scenario covers 3,47% of the industrial allotment area so that the direction of mitigation included strengthening foundations and adapting buildings, providing disaster infrastructure, optimizing regional protection functions, and limiting building density. The high tsunami hazard zone in the 34 meters run-up scenario covers 99,12% of the industrial allotment area so that directional mitigation control is the displacement of the entire industrial allotment area.

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Assessing the control factors upon glacial valley development in southernmost Patagonia (Fuegian Andes of Argentina)

Oliva,

Cioccale,

Rabassa

2023

Geomorphology

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Comparison of different resolutions of six free online DEMs with GPS elevation data on a new 6th of October City, Egypt

Cited by 4 publications

References 10 publications

Digital assessments of soil organic carbon storage using digital maps provided by static and dynamic environmental covariates

Digital assessments of soil organic carbon storage using digital maps provided by static and dynamic environmental covariates

Mitigation Control on Industrial Allotment Area Plan based on Tsunami Hazard Prone Zoning Area in Purworejo Regency, Central Java

Assessing the control factors upon glacial valley development in southernmost Patagonia (Fuegian Andes of Argentina)

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