## 4 Results and Discussion  
After creating the meta-analysis database from 490 journal articles, as described above, relevant information was extracted from the reviewed papers. Figure 5 demonstrates a typical workflow of the Landsat change detection methodology used in these studies. As shown, after data collection and preprocessing, reference data and ancillary data were used for classification and change detection, and the results are evaluated using different accuracy assessment indices. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Feature** & **Data Type** & **Description** \\ \hline Title & Free Text & Article title \\ First Author & Free Text & First author name \\ Year & Numeric & Published year \\ Source & Free Text & Published journal \\ DOI & Numeric & Article DOI \\ Study area Country & Free Text & Study area country (or region) \\ Study area size & Numeric & Study area size in square kilometers \\ Application & Free Text & Change detection application \\ Change Cause & Free Text & Cause of change (change agent) mentioned in articles \\ Data Provider & Free Text & Data download or access source \\ Total Images & Numeric & Total number of Landsat images used \\ Total Available Data & Boolean & If used all available Landsat images \\ Landsat & Categorical & Which Landsat instrument(s) used \\ Landsat Sensor & Categorical & Which Landsat sensor(s) used \\ Change Frequency & Categorical & Using more than one, one, or less than one image per year \\ Start Date & Numeric & Starting year \\ Ending Date & Numeric & Ending year \\ Duration & Numeric & Time frame \\ Images Per Year & Numeric & The average number of used images per year \\ ARD & Boolean & If used analysis ready data or surface reflectance data \\ Geometric & Free Text & Geometric correction method or standard \\ Atmospheric & Free Text & Atmospheric correction method \\ Radiometric & Free Text & Radiometric correction method \\ Cloud Removal & Free Text & Cloud, cloud shadow, and other anomalies masking method \\ Composite method & Free Text & Composite image creation method \\ Other Sensor & Free Text & Other Earth observation data \\ Ancillary Data & Free Text & Ancillary data used \\ Change Category & Categorical & Category of change detection method \\ Change Method & Free Text & Change detection method \\ Change Index & Free Text & Change metric or index \\ Computing platform & Free Text & Cloud computing platform or local computation \\ Processing Unit & Categorical & Change detection processing element \\ Ground Truth & Free Text & Reference data used for evaluation \\ CD Resolution & Numeric & Final product resolution \\ Classifier & Free Text & Classifier used \\ Classification Features & Free Text & Features used in classification \\ Classification OA & Numeric & Overall accuracy of classification \\ Assessment Indices & Free Text & Assessment indices \\ CD OA & Numeric & Change detection overall accuracy \\ \hline \hline \end{tabular}
\end{table} 
Table 1: The database features are used for meta-analysis quantitative and qualitative synthesis. Previous studies produced land cover maps to represent the state of the land cover at a specific date or period, and change detection was then implemented as a separate action or as a postprocessing activity [5]. Using this method, errors or uncertainties present in the individual land cover maps were duplicated and spread to the final change maps, resulting in incorrect attribution of change [28]. More recently, change data are integrated into land cover classification through a time series methodology implemented using a multiyear stack of Landsat data, resulting in quantitative enhancements of estimated land cover [62]. Change information is available in many forms. For example, change metrics provided by time series approaches can be used to assist in the production of sequentially integrated land cover maps. Similarly, the integration of ecological succession knowledge supports the temporal consistency of land cover maps [12, 63].