# Retrieval of Similar Evolution Patterns from Satellite Image Time Series +
## 3 Experiments  
The proposed method for the retrieval of specific spatio-temporal patterns in SITS was tested on series of Landsat images captured at different periods of time and over different locations. In all application scenarios described hereafter, all of the available spectral bands were taken into consideration, namely green, red, blue, Near Infrared and two Short-Wave Infrared bands. Moreover, the spatial resolution of the Landsat sensor was 30 m.  
The first series consists of a short time series of 10 images acquired between 1984 and 1993 (i.e., an image is acquired each year), over Bucharest, Romania, and regions surrounding the city. The size of the images is \(1702\times 1975\) pixels and the captures were taken in different seasons of the years. Several samples of the time series, along with their acquisition moments, are shown in Figure 4. In this case, the task was to determine similar changes that occurred during the formation of three accumulation lakes near Bucharest, namely Dridu, Mihailesti, and Morii. Two of these lakes evolved similarly, whereas the third one went through several modifications over the time period mentioned above.  
The second dataset is formed of 13 Landsat images of \(1250\times 400\) pixels capturing the Dobrogea region, Romania, between 6 May 2000 and 9 September 2001. Some images from the dataset, together with the corresponding timespan, are shown in Figure 5. In May 2000, the heavy rain led to the swelling of Danube river which caused floods in this region (Figure 5a). A rapid assessment of the area affected by floods is necessary in this type of situation. Therefore, the application considered in this case was oriented towards the delimitation of areas affected by floods.  
The third time series spans a longer period of time than the previous time series, almost 28 years between 14 September 1984 and 27 October 2011, and contains 88 multispectral images of \(700\times 700\) pixels. The location is still Bucharest, Romania and surrounding regions, but the area captured by the SITS is smaller than in the previous case. The first and last images from the long-term SITS, along with the corresponding temporal distribution of the acquisitions, are shown in Figure 6. In general, long-term SITS acquisition is characterized by irregular temporal sampling with data captured under different meteorological (e.g., precipitation, clouds, season) and illumination conditions. These issues make the query-by-example retrieval in long-term SITS a challenging task to accomplish if other types of distance measure (e.g., Euclidean distance) are used to assess the degree of similarity between the temporal sequences. There are two main applications where the information extracted from long-term SITS shows its potential, namely land cover and land use mapping. These two applications impact the sustainable management of the natural resources, urban planning, and agriculture.  
Figure 4: Short Landsat SITS comprised of 10 images captured between 1984–1993. Only four representative images (i.e., containing specific changes) of the series are shown: (**a**) 1984, (**b**) 1987, (**c**) 1988, (**d**) 1992. The distribution of the acquisition moments is shown in (**e**).  
Figure 5: Dobrogea Landsat SITS comprised of 13 images captured between 6 May 2000 and 14 September 2001, in the Dobrogea region. Four images of the series are shown, namely: (**a**) 6 May 2000, (**b**) 22 May 2000, (**c**) 9 July 2000, and (**d**) 29 October 2000. The distribution of the acquisition moments is shown in (**e**).  
In all cases, the user was asked to select a single evolution in the area of interest and then the proposed algorithm was applied to identify other spatio-temporal evolutions with similar spectro-temporal signatures.