Search

High-quality height reference data are embedded in the accuracy verification processes of most remote sensing terrain applications. The Ice, Cloud, and Land elevation Satellite 2 (ICESat-2)/ATL08 terrain product has shown promising results for estimating ground heights, but it has not been fully evaluated. Hence, this study aims to assess and enhance the accuracy of the ATL08 terrain product as a height reference for the newest versions of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), the Shuttle Radar Topography Mission (SRTM), and TanDEM-X (TDX) DEMs over vegetated mountainous areas. We used uncertainty-based filtering method for the ATL08 strong and weak beams to enhance their accuracy. Then, the results were evaluated against a reference airborne LiDAR digital terrain model (DTM), by selecting 10,000 points over the entire area and comparing the accuracy of ASTER, SRTM, and TDX DEMs assessed by the LiDAR DTM to the accuracy of the ASTER, SRTM, and TDX DEMs assessed by the ATL08 strong beams, weak beams, and all beams. We also detected the impact of the terrain aspect, slope, and land cover types on the accuracy of the ATL08 terrain elevations and their relationship with height errors and uncertainty. Our findings show the accuracy of the ATL08 strong beams was enhanced by 43.91%; while the weak beams accuracy was enhanced by 74.05%. Furthermore, slope strongly influenced ATL08 height errors and height uncertainty; especially on the weak beams. The errors induced by the slope significantly decreased when the uncertainty levels were reduced to <20 m. The evaluations of ASTER, SRTM, and TDX DEMs by ATL08 strong and weak beams are close to those assessed by LiDAR DTM points within 0.6 m for the strong beams. These findings indicate that ATL08 strong beams can be used as a height reference over vegetated mountainous regions. [ABSTRACT FROM AUTHOR] more...

The service sector, including the sanitation service, currently occupies a prominent part of the economic and social development plans. The scale of development of this sector has become a criterion for measuring the progress and development in various countries of the world. Infrastructure services management has been introduced in many countries of the world including some of the leading experts in this field to ensure the sustainable development of the sanitation sector. The aim of this study is to systematically review the literature on sanitation to provide an overview of how researchers approach problem solving to achieve sustainability in sanitation services, it was also found that recent studies tend to use geographic information systems (GIS) to analyze sanitation services. Studies using GIS technology have provided maps that can be used as a decision support tool for governmental and non-governmental organizations to prioritize sanitation in underserved areas. [ABSTRACT FROM AUTHOR] more...

Earthquakes occur all around the world, causing varying degrees of damage and destruction. Earthquakes are by their very nature a sudden phenomenon and predicting them with a precise time range is difficult. Some phenomena may be indicators of physical conditions favorable for large earthquakes (e.g., the ionospheric Total Electron Content (TEC)). The TEC is an important parameter used to detect pre-earthquake changes by measuring ionospheric disturbances and space weather indices, such as the global geomagnetic index (Kp), the storm duration distribution (Dst), the sunspot number (R), the geomagnetic storm index (Ap-index), the solar wind speed (Vsw), and the solar activity index (F10.7), have also been used to detect pre-earthquake ionospheric changes. In this study, the feasibility of the 6th-day earthquake prediction by the deep neural network technique using the previous five consecutive days is investigated. For this purpose, a two-staged approach is developed. In the first stage, various preprocessing steps, namely TEC signal improvement and time-frequency representation-based TEC image construction, are performed. In the second stage, a multi-input convolutional neural network (CNN) model is designed and trained in an end-to-end fashion. This multi-input CNN model has a total of six inputs, and five of the inputs are designed as 2D and the sixth is a 1D vector. The 2D inputs to the multi-input CNN model are TEC images and the vector input is concatenated space weather indices. The network branches with the 2D inputs contain convolution, batch normalization, and Rectified Linear Unit (ReLU) activation layers, and the branch with the 1D input contains a ReLU activation layer. The ReLU activation outputs of all the branches are flattened and then concatenated. And the classification is performed via fully connected, softmax, and classification layers, respectively. In the experimental work, earthquakes with a magnitude of Mw5.0 and above that occurred in Turkey between 2012 and 2019 are used as the dataset. The TEC data were recorded by the Turkey National Permanent GNSS Network-Active (TNPGN-Active) Global Navigation Satellite System (GNSS) stations. The TEC data five days before the earthquake were marked as "precursor days" and the TEC data five days after the earthquake were marked as "normal days". In total, 75% of the dataset is used to train the proposed method and 25% of the dataset is used for testing. The classification accuracy, sensitivity, specificity, and F1-score values are obtained for performance evaluations. The results are promising, and an 89.31% classification accuracy is obtained. [ABSTRACT FROM AUTHOR] more...

Many remote sensing and geoscience applications require a highprecision terrain model. In 2022, the Forest And Buildings removed Copernicus digital elevation model (fabdem) was released, in which trees and buildings were removed at a 30 m resolution. Therefore, it was necessary to make a comprehensive evaluation of this model. This research aims to perform a qualitative and quantitative analysis of fabdem in comparison with the commonly used global dems. We investigated the effect of the terrain slope, aspect, roughness, and land cover types in causing errors in the topographic representation of all dems. The fabdem had the highest overall vertical accuracy of 5.56 m. It was the best dem in representing the terrain roughness. The fabdem and Copernicus dem were equally influenced by the slopes more than the other models and had the worst accuracy of slope representation. In the tree, built, and flooded vegetation areas of the fabdem, the mean errors in elevation have been reduced by approximately 3.34 m, 1.26 m and 1.55 m, respectively. Based on Welch's t-test, there was no significant difference between fabdem and Copernicus dem elevations. However, the slight improvements in the fabdem make it the best filtered dem to represent the terrain heights over different land cover types. [ABSTRACT FROM AUTHOR] more...

In this research, we used the Revised Universal Soil Loss Equation (RUSLE) and Geographical Information System (GIS) to predict the annual rate of soil loss in the District Chakwal of Pakistan. The parameters of the RUSLE model were estimated using remote sensing data, and the erosion probability zones were determined using GIS. The estimated length slope ( L S), crop management ( C), rainfall erosivity ( R), soil erodibility ( K), and support practice ( P) range from 0–68,227, 0–66.61%, 0–0.58, 495.99–648.68 M J / m m. t. h a − 1. y e a r − 1 , 0.15–0.25 M J / m m. t. h a − 1. y e a r − 1 , and 1 respectively. The results indicate that the estimated total annual potential soil loss of approximately 4,67,064.25 t. h a − 1. y e a r − 1 is comparable with the measured sediment loss of 11,631 t. h a − 1. y e a r − 1 during the water year 2020. The predicted soil erosion rate due to an increase in agricultural area is approximately 164,249.31 t. h a − 1. y e a r − 1 . In this study, we also used Landsat imagery to rapidly achieve actual land use classification. Meanwhile, 38.13% of the region was threatened by very high soil erosion, where the quantity of soil erosion ranged from 365487.35 t. h a − 1. y e a r − 1 . Integrating GIS and remote sensing with the RUSLE model helped researchers achieve their final objectives. Land-use planners and decision-makers use the result's spatial distribution of soil erosion in District Chakwal for conservation and management planning. [ABSTRACT FROM AUTHOR] more...

The Global Navigation Satellite System (GNSS) has significantly facilitated the detection of ionospheric irregularities. Nevertheless, the ground‐based GNSS stations are inhomogeneously distributed around the world with large gaps, especially in the vast ocean regions. This adversely affects the interpretation of the spatio‐temporal variation characteristics of the ionospheric irregularities. In this study, ionospheric irregularities over the regions of the equatorial, and low‐latitude ocean during a G4‐class strong geomagnetic storm were investigated by utilizing the spaceborne GNSS reflectometry (GNSS‐R) technique. We derived and validated the ionospheric regularities index S4R from the signal‐to‐noise ratio measurements of the spaceborne GNSS‐R. Meanwhile, we utilized the ionospheric irregularities data from ground‐based (GNSS and ionosonde) and space‐based (Swarm and FORMOSAT‐3/COSMIC) instruments to evaluate and analyze the CYGNSS‐derived S4R. All comparisons and validations conducted within this study illustrate that the spaceborne GNSS‐R measurements provide complementary data and realize the timely observation as well as confirmation of the ionospheric irregularities at the same location over the oceans. It is expected to benefit the application of spaceborne GNSS‐R in ionospheric irregularities monitoring and applications over the ocean area. Plain Language Summary: Ionospheric irregularities adversely degrade the performance of various modern technologies. Therefore, it is significant to monitor ionospheric irregularities. Since the 1990s, detecting and monitoring ionospheric irregularities have been conducted based on various instruments, especially the ground‐based GNSS (Global Navigation Satellite System) receivers. However, the ground‐based GNSS stations are unevenly distributed globally with large gaps particularly in the vast marine areas, which affects the interpretation of the spatio‐temporal variation characteristics of the ionospheric irregularities over ocean areas. This contribution developed an approach using the Cyclone global navigation satellite system spaceborne GNSS reflectometry (GNSS‐R) observations to investigate the ionospheric irregularities over the oceans in equatorial and low‐latitude regions. Meanwhile, we compared the improved approach results with the ionospheric irregularities data from ground‐based (GNSS and ionosonde) and space‐based (Swarm and FORMOSAT‐3/COSMIC). The results reveal that the ionospheric irregularities observed by ground‐based and space‐based data are consistent with CYGNSS‐derived S4R in marine areas. Key Points: An ionospheric irregularities detection method is improved by leveraging the Cyclone global navigation satellite system spaceborne GNSS reflectometry (GNSS‐R) observationsThe ionospheric irregularities observed by spaceborne GNSS‐R are comprehensively verified by GNSS, ionosonde, F3/C, and Swarm measurementsIonospheric irregularity observations using spaceborne GNSS‐R are in good consistency with other ground‐based and space‐based data [ABSTRACT FROM AUTHOR] more...

This paper presents the TDS-1 GNSS reflectometry wind Geophysical Model Function (GMF) response to GPS block types. The observables were extracted from Delay Doppler Maps (DDMs) after taking the receiver antenna gains effects and GNSS-R geometry effects into account. Since the DDM is affected by GPS EffectiveIsotropic Radiated Power (EIRP), we first investigate the sensitivity of observables to the GPS block. Additionally, the observables at high SNRs are more sensitive to wind speed, but the spatial coverage at high signal to noise ratios (SNRs) is lower, while DDMs at low SNRs have the opposite characteristics. To balance the accuracy and spatial coverage, the DDM datasets are divided into two parts: high SNR (>0 dB) and low SNR (>−10 dB and ≤0 dB) to develop wind GMF. Then, the influences of GPS block on wind speed retrieval both at high and low SNR is analyzed. Results show that the block types have impacts on wind GMF and the use of a prior GPS block can contribute to a better wind speed retrieval both at high and low SNR. Compared with ASCAT, the Root Mean Square Error (RMSE) value of wind speed retrieval at high and low SNR are 2.19 m/s and 3.13 m/s, respectively, when all TDS data are processed without distinguishing GPS block types. However, if the TDS data are separately processed and used to develop wind GMF through different blocks, both the accuracy and correlation coefficient can be improved to some extent. Finally, the influence of significant height of the swell (Hs) on SNR observables is analyzed, and it is demonstrated that there is no obvious linear or nonlinear relationship between them. [ABSTRACT FROM AUTHOR] more...

Computerized ionospheric tomography (CIT) based on Global Navigation Satellite System (GNSS) data is a worthwhile project. However, predominant issues like unevenly distributed stations, lack of data, and high‐elevation GNSS signals could affect the precise information about the ionosphere. To address this problem, many previous studies were mainly improving tomographic algorithms, rather than incorporating multisource data such as data from rapidly developed upcoming Low‐Earth‐Orbit (LEO) satellites. In this paper, the potential improvements of GNSS‐based ionospheric tomography at a global scale by combining the upcoming LEO constellations is investigated. On this basis, some numerical experiments were conducted to evaluate the performances of LEO‐augmented GNSS ionospheric tomography. Specifically, the slant total electron contents (STEC) required for ionospheric tomography from ground receivers to GNSS (including GPS, GLONASS, BDS, and Galileo) and LEO satellites are simulated by the international reference ionosphere (IRI‐2016) model during low and high solar activity in 2018 and 2014, respectively. The simulated STEC values from single‐, double‐ and quad systems of GNSS constellations were first used for ionospheric tomography. Afterward, the GNSS‐based STEC values were combined with the LEO‐based simulated STEC values. The STEC values directly derived from the IRI‐2016 model that have not been used in ionospheric tomography were used as independent references. The results showed that the GNSS + LEO solutions outperform the GNSS‐only solutions overall, the STEC values obtained by GNSS + LEO solutions are more consistent with the STEC references during both high and low years of solar activity. In comparison with the STEC references, the RMS values of the CIT‐derived STEC for GNSS‐only solutions can be decreased by 15% and 20.3% at most during low and high years of solar activity, respectively. Key Points: A method of Global Navigation Satellite System (GNSS)‐based ionospheric tomography augmented by Low‐Earth‐Orbit (LEO) satellite constellations is proposedObservations of multi‐GNSS and 192 LEO satellites are simulated for three‐dimensional ionospheric electron density reconstructionCombining LEO satellite constellations improves GNSS‐only ionospheric tomographic results [ABSTRACT FROM AUTHOR] more...

The ICE, Cloud and land Elevation Satellite-2 (ICESat-2) can provide new measurements of the Earth's elevations through photon-counting technology. Most research has focused on extracting the ground and the canopy photons in vegetated areas. Yet the extraction of the ground photons from urban areas, where the vegetation is mixed with artificial constructions, has not been fully investigated. This article proposes a new method to estimate the ground surface elevations in urban areas. The ICESat-2 signal photons were detected by the improved Density-Based Spatial Clustering of Applications with Noise algorithm and the Advanced Topographic Laser Altimeter System algorithm. The Advanced Land Observing Satellite-1 PALSAR-derived digital surface model has been utilized to separate the terrain surface from the ICESat-2 data. A set of ground-truth data was used to evaluate the accuracy of these two methods, and the achieved accuracy was up to 2.7 cm, which makes our method effective and accurate in determining the ground elevation in urban scenes. [ABSTRACT FROM AUTHOR] more...

Flash floods are among the most common natural hazards in Egyptian and Arabian deserts. In this work, we utilized two Sentinel-1 and Sentinel-2 satellite images, before and after the flash flood, SRTM, and geolocated terrestrial photos captured by volunteers. This paper aims to three substantial objectives: (1) monitoring the flash flood impacts on Wadi El-Natrun region based on free satellite data and mapping the destroyed vegetation cover; (2) the integration of the free remote sensing data, geolocated terrestrial photos, and GIS techniques, along with hydrologic and hydraulic modeling, to evaluate the impact of flash flood hazards on the study area; and (3) assistance of the decision-makers in planning the required protective works to avoid the probable flooding. Two scenarios have been applied to estimate the flash flood effect. The first scenario has relied on Sentinel-1/2 data fusion before and after the flash flood, while the second scenario has been implemented based on the integration of the Sentinel-2 images and hydrologic and hydraulic flood modeling with the help of ArcGIS software to simulate the flash flood route. The results demonstrated that although the first scenario is an efficient solution for continuous monitoring of the change in the water bodies, it is limited in the detection of the submerged vegetation area. On the other hand, the second scenario provided the flash flood route and hydrological parameters, which determine the hazard degree of the basins, thus helping the decision-maker to manage the flood risk. Moreover, the second scenario surpasses the first one by estimating the destroyed infrastructure. Consequently, the second scenario is appropriate to assess the flash flood impacts and mitigate its influence in the future. [ABSTRACT FROM AUTHOR] more...

The Northwest Pacific Ocean (NWP) is one of the most vulnerable regions that has been hit by typhoons. In September 2018, Mangkhut was the 22nd Tropical Cyclone (TC) over the NWP regions (so, the event was numbered as 1822). In this paper, we investigated the highest amplitude ionospheric variations, along with the atmospheric anomalies, such as the sea-level pressure, Mangkhut's cloud system, and the meridional and zonal wind during the typhoon. Regional Ionosphere Maps (RIMs) were created through the Hong Kong Continuously Operating Reference Stations (HKCORS) and International GNSS Service (IGS) data around the area of Mangkhut typhoon. RIMs were utilized to analyze the ionospheric Total Electron Content (TEC) response over the maximum wind speed points (maximum spots) under the meticulous observations of the solar-terrestrial environment and geomagnetic storm indices. Ionospheric vertical TEC (VTEC) time sequences over the maximum spots are detected by three methods: interquartile range method (IQR), enhanced average difference (EAD), and range of ten days (RTD) during the super typhoon Mangkhut. The research findings indicated significant ionospheric variations over the maximum spots during this powerful tropical cyclone within a few hours before the extreme wind speed. Moreover, the ionosphere showed a positive response where the maximum VTEC amplitude variations coincided with the cyclone rainbands or typhoon edges rather than the center of the storm. The sea-level pressure tends to decrease around the typhoon periphery, and the highest ionospheric VTEC amplitude was observed when the low-pressure cell covers the largest area. The possible mechanism of the ionospheric response is based on strong convective cells that create the gravity waves over tropical cyclones. Moreover, the critical change state in the meridional wind happened on the same day of maximum ionospheric variations on the 256th day of the year (DOY 256). This comprehensive analysis suggests that the meridional winds and their resulting waves may contribute in one way or another to upper atmosphere-ionosphere coupling. [ABSTRACT FROM AUTHOR] more...

In this research, we developed and evaluated a new scheme for merging soil moisture (SM) retrievals from both passive and active microwave satellite estimates, based on maximized signal-to-noise ratios, in order to produce improved SM products using least-squares theory. The fractional mean-squared-error (fMSE) derived from the triple collocation method (TCM) was used for this purpose. The proposed scheme was applied by using a threshold between signal and noise at fMSE equal to 0.5 to maintain the high-quality SM observations. In the regions where TCM is unreliable, we propose four scenarios based on the determinations of correlations between all three SM products of TCM at significance levels (i.e., p-values). The proposed scheme was applied to combine SM retrievals from Soil Moisture Active Passive (SMAP), Advanced Scatterometer (ASCAT), and Advanced Microwave Scanning Radiometer 2 (AMSR2) to produce SMAP+ASCAT and AMSR2+ASCAT SM datasets at a global scale for the period from June 2015 to December 2017. The merged SM dataset performance was assessed against SM data from ground measurements of international soil moisture network (ISMN), Global Land Data Assimilation System-Noah (GLDAS-Noah) and ERA5. The results show that the two merged SM datasets showed significant improvement over their parent products in the high average temporal correlation coefficients (R) and the lowest root mean squared difference (RMSE), compared with in-situ measurements over different networks of ISMN. Moreover, these datasets outperformed their parent products over different land cover types in most regions of the world, with a high overall average temporal R and the lowest overall average RMSE value with GLDAS and ERA5. In addition, the suggested scenarios improved SM performance in the regions with unreliable TCMs. [ABSTRACT FROM AUTHOR] more...