Search Results (6)

Declassified Keyhole imagery partially provides multi-temporal coverage that can support land-use change analysis. However, the volume of commercial (paid) Keyhole data is much larger than that of free imagery, and the extent to which commercial data can enhance the application of Keyhole imagery for land-use change analysis remains unknown. In this work, the full archive of Keyhole images for China was obtained from the USGS to identify regions with repeated coverage automatically by using the ArcPy library in Python. The years from 1960 to 1984 were divided into five 5-year periods (T1, 1960~1964; T2, 1965~1969; T3, 1970~1974; T4, 1975~1979; and T5, 1980~1984). The Keyhole images’ metadata, including resolution, acquisition time, and image extent, were utilized to classify the images into meter level (C1), five-meter level (C2), and ten-meter level (C3). The spatial distributions of combinations of imagery at different resolutions for each period and the repeated coverage of imagery at each resolution across the five periods were investigated to extract repeated-coverage regions. The coverage proportions were nearly 100% for C1 imagery for the T3, T4, and T5 periods; C2 for T1 and T2; and C3 for T1 and T3. The T3 period featured extensive coverage at all three resolutions (66%). The T1 period was mainly covered by C2/C3 (93%), and T4 had C1/C3 coverage (68%). In contrast, T2 relied primarily on C2 imagery (100%), and T5 was only covered by C1 (96%). For C1 imagery, land-use changes in almost all areas in China in the T3/T4/T5 time span could be detected, and for C2 and C3 images, the corresponding time spans were T1/T2 and T1/T3. Although this study focused on repeated-coverage area detection within China, the methodology and Python codes provided allow for the implementation of an automated process for land-use change detection from the 1960s to the 1980s in other regions worldwide. Full article

Keyhole imagery, acquired between the 1960s and 1980s, offers a unique opportunity to study land use changes prior to the era of modern remote sensing. This study evaluates the potential of free-download Keyhole imagery within China to detect land use changes over five 5-year periods (1960–1984). Using metadata and spatial analysis tools in Python 3.12, we classified images into three resolution categories (meter-level, five-meter-level, and ten-meter-level) and analyzed their spatial distribution and repeated coverage. Results show that 26.5%, 58.9%, and 34.0% of areas were capable of detecting at least one land-use change event for the respective resolution categories. The T3 period (1970–1974) exhibited the greatest diversity of imagery combinations among the five periods. However, uneven spatial and temporal coverage, particularly in western and rural regions, limits the ability of free Keyhole imagery to conduct continuous multi-temporal analysis, and collaboration with paid Keyhole imagery could fill gaps in coverage and improve the accuracy of land use change detection. The study highlights the potential of Keyhole imagery for historical land use research while underscoring the need for methodological refinements to address data limitations. The shared Python scripts and metadata processing techniques could also support other land-use change research using Keyhole imagery globally. Full article

Rapid global urbanization during the late 20th and early 21st centuries has induced substantial land cover changes, posing significant threats to the United Nations Educational, Scientific and Cultural Organization’s (UNESCO) World Heritage Sites. In this study, we investigated the spatio-temporal change in urban development in response to land use transformations in the world cultural heritage site (CHS) of Taxila, Pakistan, to check the possible threats faced by the site. Land transfer matrices were used to assess the land cover change (LCC) between 1990 and 2024. Support vector machine and Getis–Ord Gi techniques were employed for LCC classification and spatial pattern interpretation, respectively, which were later evaluated by the high spatial resolution imagery of KH-9 (Keyhole-9), Google Earth Pro and Gaofen-2. The results indicate a significant increase in built-up area from 23.68 km² to 78.5 km², accompanied by a substantial rise in bare land from 8.56 km² to 26.5 km² between 1990 and 2024, which is quite irregular. LCC transformations were notable, with 13.1 km² of cropland and 44.8 km² vegetation being converted into 4.4 km² of built-up area and 14.5 km² into bare land during the 1990 to 2024 period. Getis–Ord Gi analysis observed a high Z-score value and showed low to high clustering patterns in the proximity of the Sarakhola and Bhir Mound sites from 1990 to 2024. Furthermore, high spatial resolution imagery indicates the loss of the core zone of the Sarakhola site from 0.0168 to 0.0032 km² from 2004 to 2024, which was the major threat to its outstanding universal venue (OUV) status. The findings of the current study indicate that the CHS under study is facing an alarming situation for conservation due to rapid urban development and encroachment. Therefore, local government should strictly implement the heritage law and revisit their policies to promote conservation efforts to maintain the authenticity and integrity of this world CHS. Full article

In March 1966, M_s 6.8 and 7.2 earthquakes occurred in Xingtai, North China, resulting in widespread soil liquefaction that caused severe infrastructure damage and economic losses. Using Keyhole satellite imagery combined with aerial images and fieldwork records, we interpreted and identified 66,442 liquefaction points and analyzed the coseismic liquefaction distribution characteristics and possible factors that influenced the Xingtai earthquakes. The interpreted coseismic liquefaction was mainly concentrated above the IX-degree zone, accounting for 80% of all liquefaction points. High-density liquefaction zones (point density > 75 pieces/km²) accounted for 22% of the total liquefaction points. Most of the interpreted liquefaction points were located at the region with a peak ground acceleration (PGA) of >0.46 g. The liquefaction area on 22 March was significantly larger than that on 8 March. The region of liquefaction was mainly limited by sandy soil conditions, water system conditions, and seismic geological conditions and distributed in areas with loose fine sand and silt deposits, a high water table (groundwater level increases before both mainshocks corresponding to the liquefaction intensive regions), rivers, and ancient river channels. Liquefaction exhibited a repeating characteristic in the same region. Further understanding of the liquefaction characteristics of Xingtai can provide a reference for the prevention of liquefaction in northern China. Full article

Earth observation (EO) data can provide large scale, high-resolution, and transferable methodologies to quantify the sprawl and vertical development of cities and are required to inform disaster risk reduction strategies for current and future populations. We synthesize the evolution of Bishkek, Kyrgyzstan, which experiences high seismic hazard, and derive new datasets relevant for seismic risk modeling. First, the urban sprawl of Bishkek (1979–2021) was quantified using built-up area land cover classifications. Second, a change detection methodology was applied to a declassified KeyHole Hexagon (KH-9) and Sentinel-2 satellite image to detect areas of redevelopment within Bishkek. Finally, vertical development was quantified using multi-temporal high-resolution stereo and tri-stereo satellite imagery, which were used in a deep learning workflow to extract buildings footprints and assign building heights. Our results revealed urban growth of 139 km² (92%) and redevelopment of ~26% (59 km²) of the city (1979–2021). The trends of urban growth were not reflected in all the open access global settlement footprint products that were evaluated. Building polygons that were extracted using a deep learning workflow applied to high-resolution tri-stereo (Pleiades) satellite imagery were most accurate (F1 score = 0.70) compared to stereo (WorldView-2) imagery (F1 score = 0.61). Similarly, building heights extracted using a Pleiades-derived digital elevation model were most comparable to independent measurements obtained using ICESat-2 altimetry data and field-measurements (normalized absolute median deviation < 1 m). Across different areas of the city, our analysis suggested rates of building growth in the region of 2000–10,700 buildings per year, which when combined with a trend of urban growth towards active faults highlights the importance of up-to-date building stock exposure data in areas of seismic hazard. Deep learning methodologies applied to high-resolution imagery are a valuable monitoring tool for building stock, especially where country-level or open-source datasets are lacking or incomplete. Full article

The Kofun period of the history of Japan—between the 3rd and the 7th century AD—bears its name from the construction of huge, earth mound tombs called Kofun. Among them, the largest have a keyhole shape and are attributed to the first, semi-legendary emperors. The study of the orientation of ancient tombs is usually a powerful tool to better understand the cognitive aspects of religion and power in ancient societies. This study has never been carried out in Japan due to the very large number of Kofun and to the fact that access to the perimeter is usually forbidden. For these reasons, to investigate Kofun orientations, simple tools of satellite imagery are used here. Our results strongly point to a connection of all Kofun entrance corridors with the arc of the sky where the Sun and the Moon are visible every day of the year; additionally, these show an orientation of the keyhole Kofun to the arc of the rising/shining Sun, the goddess that the Japanese emperors put at the mythical origin of their dynasty. Full article