Abstract
With uninterrupted space-based data collection since 1972, Landsat plays a key role in systematic monitoring of the Earth’s surface, enabled by an extensive and free, radiometrically consistent, global archive of imagery. Governments and international organizations rely on Landsat time series for monitoring and deriving a systematic understanding of the dynamics of the Earth’s surface at a spatial scale relevant to management, scientific inquiry, and policy development. In this study, we identify trends in Landsat-informed change detection studies by surveying 50 years of published applications, processing, and change detection methods. Specifically, a representative database was created resulting in 490 relevant journal articles derived from the Web of Science and Scopus. From these articles, we provide a review of recent developments, opportunities, and trends in Landsat change detection studies. The impact of the Landsat free and open data policy in 2008 is evident in the literature as a turning point in the number and nature of change detection studies. Based upon the search terms used and articles included, average number of Landsat images used in studies increased from 10 images before 2008 to 100,000 images in 2020. The 2008 opening of the Landsat archive resulted in a marked increase in the number of images used per study, typically providing the basis for the other trends in evidence. These key trends include an increase in automated processing, use of analysis-ready data (especially those with atmospheric correction), and use of cloud computing platforms, all over increasing large areas. The nature of change methods has evolved from representative bi-temporal pairs to time series of images capturing dynamics and trends, capable of revealing both gradual and abrupt changes. The result also revealed a greater use of nonparametric classifiers for Landsat change detection analysis. Landsat-9, to be launched in September 2021, in combination with the continued operation of Landsat-8 and integration with Sentinel-2, enhances opportunities for improved monitoring of change over increasingly larger areas with greater intra- and interannual frequency.
Highlights
The world’s population has increased from 2.6 billion at the beginning of the 1950s to7.7 billion at present and is predicted to reach ~9.7 billion by 2050
60% of all land cover change is directly related to anthropogenic activities such as agricultural and industrial development, and 40% is indirectly linked to human activity, such as climate change [3,4]
After creating the meta-analysis database from 490 journal articles, as described above, relevant information was extracted from the reviewed papers
Summary
The world’s population has increased from 2.6 billion at the beginning of the 1950s to7.7 billion at present and is predicted to reach ~9.7 billion by 2050. Population growth is known to be the greatest driver of land cover change, via alterations to land use, globally [1]. Global land cover is deeply intertwined with the environment and climate, and changes to one will impact the other via several interacting feedback loops [2]. 60% of all land cover change is directly related to anthropogenic activities such as agricultural and industrial development, and 40% is indirectly linked to human activity, such as climate change [3,4]. Knowing how humans use and alter the landscape is often more crucial for planning and management purposes than the land cover itself [5]. Land use change related to processes such as industrialization, urbanization, desertification, Remote Sens.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
