Information Extraction and Population Estimates of Settlements from Historic Corona Satellite Imagery in the 1960s

Abstract

The Corona satellite program was a historic reconnaissance mission which provided high spatial resolution panchromatic images during the Cold War era. Nevertheless, and despite the historic uniqueness and importance of the dataset, efforts to extract tangible information from this dataset have primarily focused on visual interpretation. More sophisticated approaches have been either hampered or unrealized, often justified by the primitive quality of this early satellite product. In the current study we attempt to showcase the usability of Corona imagery outside the context of visual interpretation. Using a 1968 Corona image acquired over the city municipality of Plovdiv, Bulgaria, we reconstruct a panchromatic 1.8 m spatial resolution georegistered image with a relative displacement Root Mean Square Error (RMSE) of 6.616 (for x dimension) and 1.886 (for y dimension) and employ segmentation and texture analysis to discern agricultural parcels and settlements’ footprints. Population statistics of this past era are retrieved from national census and related to settlements’ footprints. An exponential relationship between the two variables was identified by applying a semi-log regression. The high adjusted R2 value found (76.54%) indicates that Corona images offer a unique opportunity for population data analysis of the past. Overall, we showcase that the Corona images’ usability extends beyond the visual interpretation, and features of interest extracted through image analysis can be subsequently used for further geographical and historical research.

Using CORONA Imagery to Study Land Use and Land Cover Change—A Review of Applications

“…Our results showed that except for present-day Russia and China, CORONA imagery was also commonly used in India and Nepal; the Middle East (Iraq, Iran and Syria); Northern and Western Africa (Egypt, Mali and Senegal); and Central and Eastern Europe (Poland and Romania) [26,28,30,[42][43][44][52][53][54][55][56][57][58]. Some of these countries (e.g., Poland and Romania) have good coverage of CORONA imagery due to the goals of the program and the importance of the countries during the Cold War era [59][60][61]. One of the reasons that probably pushed researchers to use CORONA in several countries listed here is the poor availability of comparable aerial data that are not easily accessible via online archives, although they exist [5]: for instance, aerial data for Poland acquired in the 1950s or the 1960s.…”

Estimation of loss in arable land and irrigation requirements using high‐resolution imagery and Google Earth Engine

“…CORONA imagery has been used because it offers unique insights to monitor changes at a high resolution of approximately 2–4 ft (0.6–1.2 m) per pixel using images pertaining to the 1960s (Fekete, 2020). The effective utilization of declassified high‐resolution CORONA data, alongside modern high‐resolution imagery, has proven valuable in mapping temporal land use changes, particularly tracking changes in the agriculture sector (Casana, 2020; Hamp‐Adams, 2020; Maurer et al, 2019; Stratoulias & Grekousis, 2021). The GeoEye data obtained were already georeferenced, but to ensure spatial overlap among all datasets, it was necessary to georeference the images to a consistent projection system (Danielson & Gesch, 2011; Neteler & Mitasova, 2013).…”

“…High‐resolution satellite data offer advantages over traditional methods in mapping and monitoring vegetation status and water balance due to their cost‐effectiveness, temporal resolution and wide geographical coverage (Peña‐Barragán et al, 2011). The utilization of declassified high‐resolution CORONA data, in conjunction with contemporary high‐resolution imagery, has proven effective in mapping temporal land use changes (Casana, 2020; Maurer et al, 2019), particularly in monitoring transformations in agricultural land use, including changes in irrigation practices (Hamp‐Adams, 2020; Stratoulias & Grekousis, 2021). Furthermore, these types of analysis are augmented with the use of cloud‐based platforms, such as G EE, as they enable advanced analysis and processing of geospatial data at a planetary scale with extensive collection of satellite imagery and powerful computing capabilities (Orimoloye et al, 2021; Tamiminia et al, 2020; Zhang et al, 2022).…”

Agricultural Land Abandonment in Bulgaria: A Long-Term Remote Sensing Perspective, 1950–1980

“…To our knowledge, agricultural land abandonment or rural depopulation in Bulgaria has not been studied from a remote sensing perspective, if we leave aside our preliminary work [22,23] and a follow-up study inspired and shaped by our work to a more considerable extent than it has been mentioned in acknowledgement [24]. These studies were also limited to their early satellite imagery.…”