Feature and information extraction for regions of Southeast Europe from Corona satellite images acquired in 1968

Abstract

The Corona spy programme was a series of reconnaissance satellites which delivered more than 860000 images between 1960 and 1972. Since 1995, the data are declassified and a large historic earth observation archive is made accessible to the scientific community. Despite the large volume of information and the high spatial resolution of the satellite imagery, little has been done in the last 25 years in the context of image processing of this data source, a fact which perhaps can be attributed to the technical difficulties of these primitive images such as the lack of metadata, intense spatial and radiometric distortions, low Signal-to-Noise Ratio (SNR) and a single panchromatic band. Hence, the photogrammetric challenges to extract useful information are paramount. In this study, we present recent developments arising from our efforts to map settlements and agricultural parcels over the Plovdiv region, Bulgaria from a Corona image acquired in 1968. We, overall, present initial findings from the integration of earth observation into the ERC-StG project UrbanOccupationsOETR and evaluate the usability of such primitive images in feature extraction. We compare the areas corresponding to settlements and correlate them with concurrent population census. Based on the findings, we suggest that settlements and agricultural parcels can be mapped from a Corona KH-4B image with fine radiometric quality.

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

“…In one of the very few similar studies conducted to date by Saleem et al [ 16 ] with the aim to relate population increase from 1969 to 2014 and urban growth in the Kurdistan region, a positive exponential relationship was established (R 2 = 0.89). Moreover, in a recent paper, Stratoulias and Kabadayı [ 75 ] have found an association (R 2 = 0.54, p = 0.02) between census population statistics settlement area extracted from Corona and this can act as an indication of a positive association. In the current paper, we integrated a more sophisticated image processing workflow and a larger number of samples which resulted in a good fit (R 2 = 0.76%), between population data referred to in the 1965 Bulgarian census for 30 settlements, and their settlement size as estimated in this research.…”

Remote sensing and spatial databases for investigating latent urban-rural dynamics in rural, inland districts of Southern Italy

“…The CORONA program, designed and used between the 60s and 70s of the last century, has recently been declassified allowing access for non-military purposes and users. It provides high resolution data (with a pixel size resolution up to 1.80 meters) with a wide spatial coverage (some missions have frames covering strips up to 250 km long), which can be purchased at low cost with respect to other similar products (Stratoulias, 2020). Landsat data, on the other hand, are among the first sources of medium-resolution multispectral images with global coverage: the first satellite of the Landsat mission was launched into orbit in 1972 and carried the Multispectral Scanner-MSS sensor with 80m of spatial resolution (see e.g., Irons et al, 2012;Quaranta et al, 2020).…”

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.…”