## 4 Results and Discussion
### Data and Sensors  
Landsat data can be accessed through several different sources, which are displayed in Figure 10. As expected, USGS, the official Landsat data provider, is the main source of Landsat change detection data in the reviewed papers. USGS is accessed through online repositories, such as EarthExplorer, GloVis, and the Earth Resources Observation and Science (EROS) Center science-processing architecture (ESPA) on-demand interface, which provides all historical global data processed at different levels of geometric and \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Change Agent** & **Change Magnitude** & **Number of Studies** \\ \hline \multirow{8}{*}{**Category**} & \multirow{8}{*}{**Category**} & Deforestation & Abrupt/Gradual & 149 \\  & & Urban expansion & Gradual & 102 \\  & & Human Activities & Abrupt/Gradual & 47 \\  & & Agriculture expansion & Gradual & 30 \\  & & Population growth & Gradual & 21 \\  & & Afforestation & Gradual & 20 \\  & & Industrial & Abrupt & 11 \\  & & Economic & Abrupt & 7 \\  & & Disturbance & Abrupt/Gradual & 6 \\  & & Mining & Gradual & 5 \\  & & Harvest & Abrupt & 4 \\  & & Dam & Abrupt & 3 \\ \hline \multirow{8}{*}{**Category**} & \multirow{8}{*}{**Category**} & Insect & Gradual & 9 \\  & & Fire & Abrupt & 8 \\ \cline{1-1}  & & Climate change & Gradual & 7 \\ \cline{1-1}  & & Desertification & Gradual & 7 \\ \cline{1-1}  & & Drought & Gradual & 6 \\ \cline{1-1}  & & Earthquake & Abrupt & 4 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Change agents in Landsat change detection studies. Figure 9: The geographic distribution of Landsat change detection studies for different applications. radiometric standards. Google Earth Engine (GEE, [[https://eartheengine.google.com](https://eartheengine.google.com)]([https://eartheengine.google.com](https://eartheengine.google.com))) also provides online access to all Landsat data and products. By using GEE, users do not require any storage infrastructure when downloading data. GEE is mostly used to access algorithms and to apply those algorithms to image datasets and other spatial data at a range of geographical scales. Amazon Web Services (AWS, [[https://aws.amazon.com/earth](https://aws.amazon.com/earth)]([https://aws.amazon.com/earth](https://aws.amazon.com/earth))) provides another private solution to access data. AWS offers clients admittance to an assortment of datasets (e.g., Sentinels, MODIS, Landsat, and elevation datasets) on a cloud-based platform. The versatility of this serverless computing platform supports code snippets from C#, Python, Node.js, and Java. AWS makes Landsat images accessible to anybody to utilize through Amazon Simple Storage Service (S3). All Landsat-8 images from 2015 are accessible alongside a selection of cloud-free images from 2013 and 2014. Additionally, all daily Landsat data are made available within hours of production. AWS reported 500 million global requests for Landsat data within the first 150 days of the launch of Landsat on AWS in March 2015. Using AWS, [PERSON] et al. (2020), for example, applied a dense time series of Landsat-8 and Sentinel-2 imagery at continent-scale to quantify the nature and magnitude of seasonality changes and to estimate the timing of vegetation phenophase transitions [71]. Figure 11 shows the number of studies that used data derived from different Landsat sensors. As illustrated, Landsat TM, with its reliable and consistent radiometry, 30 m spatial resolution, and an extensive historical catalog spanning from 1982 to 2012, is the most commonly used sensor in the reviewed studies. For monitoring changes prior to this time,  
Figure 10: Data sources of Landsat imagery in the reviewed studies. Landsat MSS is the only available data source with 60 m spatial resolution, though it has relatively challenging preprocessing steps. Landsat ETM+ data are used in relatively few studies due to the SLC failure and are usually replaced with Landsat TM data.