Top Cited

1
Abstract:
In China, traditional methodology on early detection of natural terrain to landslides is challenging as zones most prone to slope failure are usually inaccessible due to high location and dense vegetation. This can lead to underestimation of potential landslide events to the degree of wrongly identifying unstable areas as stable. This paper provides a solution for these cases by proposing an integrated space-air-ground investigation system that allows for the early detection, real-time prediction, and warning of catastrophic geohazards. Firstly, high-resolution optical images and interferometric synthetic aperture radar (InSAR) data from satellites are employed to obtain a global panorama of a region, highlighting these problematic locations; yet results are detailed enough to provide reliable estimates of deformations at particular points along time spans of days and weeks. As consequence, it makes the compilation of long displacement time-histories feasible, contributing to the understanding of long-term landslide-driving phenomena in regions where it has been underestimated. This is called the general investigation. Then, detailed assessments can be done through the deve-lopment of unmanned aerial vehicles (UAV) for elaborating high-resolution relief maps and photogrammetric representations based on both visual images and light laser detection and ranging (LiDAR) data. The system finally allows for precise tagging of locations that warrant real-time site monitoring of displacements using global navigation satellite system (GNSS) and crack gauges, validating expecting behavior of these critical, but previously hidden hazardous locations. The overall approach makes it possible to establish a four-level comprehensive early warning system, which meets the urgent needs of the country and promotes a practical and operational application of such system in the field of geohazard prevention.
2
Abstract:
The distribution pattern of urban facility POIs usually forms clusters (i.e. "hot spots") in local geographic space. The kernel density estimation (KDE), which has been usually utilized for expressing these spatial characteristics, is one of the most popular visualization tools. Considering the missing of quantitative statistical inference assessment in KDE, this paper proposes a novel method to detect the hot spots of urban facility POIs. First, this method computes the attribute value of geographic unit with the "distance decay effect", then by adopting the statistical index of Getis-Ord Gi*, we analysis the local spatial cluster characteristics of urban facilities. Comparing this method with the conventional spatial autocorrelation based on the Quadrat clustering, the attribute value of kernel density computing can preserve the local information of data, and the spatial cluster characteristics of urban facilities can reflect the continuity characteristics of urban services, for that the KDE considers the regional impact based on the First Law of Geography. The actual data experiment for analyzing the financial POIs' distribution patterns indicates that this approach is effective to extract the hot spots of urban facility POIs in city areas.
3
4
Abstract:
Change detection for remote sensing imagery is the process to determine difference of the same object or phenomenon at different times. Real-time automatic change detection technology is of great significance for excavating potential of image data and maintaining the current situation of geospatial data. With the development of remote-sensing earth observation technology, varieties of remote-sensing sensors for different tasks have emerged. Change detection is also diversified with the coming up of multi-resolution remote-sensing data, with advanced theories and techniques developed for continuously different sensors. This paper reviews the development of multi-temporal remote sen-sing image change detection technologies and summarizes the classification system of multi-temporal remote sensing image change detection. And the latest developments in change detection research are summarized from three aspects:pre-processing, change detection strategies and accuracy assessment. This paper also points out the challenges that change detection is facing and possible countermeasures, in the hope of deepening the research into change detection technology for remote sensing images.
5
Abstract:
As the most frequent and devastating geohazard next to earthquakes, landslides are widely distributed in mountainous areas of west China, which makes early detection of landslides a vital task for geologic disaster prevention. Although time series SAR interferometry (InSAR) based on repeat-pass satellite SAR observations has shown a great potential in landslide detection, its performance is usually limited by factors such as vegetation coverage, which leads to low reliability of detection results. Aiming at this problem, we carry out a case study by employing the coherent scatterer InSAR (CSI) method to successfully detect 17 unstable slopes in Danba County in the upper reach of Dadu River Basin from archived ALOS PALSAR and ENVISAT ASAR datasets. The effectiveness and advantage of the CSI method are demonstrated by comparisons with other observation data as well as validation against field survey. And, major impact factors for the performance of time series InSAR analysis in landslide investigations and future research topics of high priority are summarized.
6
Abstract:
Based on the DMSP/OLS nighttime light data for the years 1993-2012 and spatial analysis methods including standard deviational ellipse and rank-size distribution, this paper systematically analyzes the spatial structure and spatiotemporal dynamics of the urban system in countries along B & R (The Belt and Road Initiative). We found that nighttime light increased in most countries along B & R. These fast growing countries are undergoing economic reforms and post-war reconstruction, while nighttime light reduction occurs in areas of social and economic unrest. The trend of size distribution of nighttime light in B&R is continuous spatial expansion, and the center of the nighttime light is moving to southeast Asia. The nighttime light distribution in the top 2000 urban places in B&R follows the rank-size distribution, thus urban land distribution is more concentrated than the past. The high rank cities are fairly well developed, but the development of the small cities is lagging behind. The general distribution trend toward, concentration is stronger than decentralization in B&R.
7
Abstract:
Since 2017, many serious geological disasters have been reported, including the 2017 mountain collapse at high altitudes in Xinmo Village in Mao County, Sichuan Province, and the 2018 Baige landslide in Jinsha River, most of which are of great destructive power and hard to detect in advance. It is worth noting that although the geohazard prevention has been carried out extensively across the whole country which is supported by the state, many of these geological disasters occur outside the potential geohazard points estimated in advance. The early identification of these undetectable geohazards points remains a big challenge and a crucial task in current geohazard prevention work. In this paper, the characteristics of interferometric synthetic aperture radar (InSAR) and its inherited limitations are summarized. Based on the integrated remote sensing technologies (including optical, SAR/InSAR and LiDAR), the key observation concept with three forms "morphology, deformation, situation" is proposed. Through the integration of a range of remote sensing technologies, the locations of potential geohazards will be identified qualitatively, and their associated movements will be monitored quantitatively. Finally, a series of thoughts and recommendations are provided to guide our future work for the early detection of serious geological hazards.
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