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

Autor: Mahsa Shahbandeh, Dominik Kaim, Jacek Kozak
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Remote Sensing, Vol 15, Iss 11, p 2793 (2023)
Druh dokumentu: article
ISSN: 2072-4292
DOI: 10.3390/rs15112793
Popis: CORONA spy satellites offer high spatial resolution imagery acquired in the 1960s and early 1970s and declassified in 1995, and they have been used in various scientific fields, such as archaeology, geomorphology, geology, and land change research. The images are panchromatic but contain many details of objects on the land surface due to their high spatial resolution. This systematic review aims to study the use of CORONA imagery in land use and land cover change (LULC) research. Based on a set of queries conducted on the SCOPUS database, we identified and examined 54 research papers using such data in their study of LULC. Our analysis considered case-study area distributions, LULC classes and LULC changes, as well as the methods and types of geospatial data used alongside CORONA data. While the use of CORONA images has increased over time, their potential has not been fully explored due to difficulties in processing CORONA images. In most cases, study areas are small and below 5000 km2 because of the reported drawbacks related to data acquisition frequency, data quality and analysis. While CORONA imagery allows analyzing built-up areas, infrastructure and individual buildings due to its high spatial resolution and initial mission design, in LULC studies, researchers use the data mostly to study forests. In most case studies, CORONA imagery was used to extend the study period into the 1960s, with only some examples of using CORONA alongside older historical data. Our analysis proves that in order to detect LULC changes, CORONA can be compared with various contemporary geospatial data, particularly high and very high-resolution satellite imagery, as well as aerial imagery.
Databáze: Directory of Open Access Journals
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