## 3 Datasets
### Landsat 8 Data  
The new Landsat 8 satellite, launched in February 2013, carries a two-sensor payload, the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS). The OLI sensor is able to capture eight MS bands with 30-m GSD: coastal aerosol (C, 430-450 nm), blue (B, 450-510 nm), green (G, 530-590 nm), red (R, 640-670 nm), near infrared (NIR, 850-880 nm), shortwave infrared-1 (SWIR1, 1570-1650 nm), shortwave infrared-2 (SWIR2, 2110-2290 nm) and cirrus (CI, 1360-1380 nm). In addition, Landsat 8 OLI presents one panchromatic band (P, 500-680 nm) with 15-m GSD.  
A dense time series of the Landsat 8's OLI sensor was downloaded, totally free and via the Internet, from the U.S. Landsat archive [32]. It was composed of eight free of cloud multi-temporal Landsat 8 scenes type Level 1 Terrain Corrected (L1T) in the footprint of Path 200 and Row 34, each one comprising the whole working area. The eight Landsat 8 scenes were taken with a dynamic range of 12 bits from May to November in 2013, and they were dated as follow: 23 May, 8 June, 24 June, 10 July, 26 July, 11 August, 12 September and 15 November.  
In order to use the aforementioned time series of Landsat 8 for greenhouse horticultural crop identification, it was necessary to carry out some previous processing steps. The first one was to clip the original images, both PAN and MS, according to the study area. It is noteworthy that spatial resolutions equal to or better than 8-16 m are recommended by [PERSON] _et al_. [6] to work on greenhouse detection via remote sensing. Thereby, and after clipping, eight pan-sharpened images were attained by fusing the information of PAN and MS Landsat 8 bands through applying the PANSHARP module included in Geomatica v. 2014. The pan-sharpened images were generated with a GSD of 15 m, 12-bit depth and seven bands (C, B, G, R, NIR, SWIR1 and SWIR2).  
The next processing step consisted of performing atmospheric correction by applying the ATCOR module (Geomatica v. 2014) to the eight Landsat 8 pan-sharpened images. The goal was to attain ground reflectance values. At this point, it was checked that ground reflectance values attained over greenhouses on the corrected pan-sharpened images were not significantly different from those achieved on the atmospherically corrected Landsat MS images. The results showed that the coefficient of determination (\(R^{2}\)) between ground reflectance values of pan-sharpened and MS images was always higher than 0.99 for each of the seven studied bands.  
The last process involved the rectification and co-registration of the eight images. Although all acquired Landsat 8 L1T images have been previously orthorectified and corrected for terrain relief [33], a subsequent co-registration is needed, since an extremely accurate spatial matching among multi-temporal images is crucial in this type of work [34, 35] for both pixel and object-based image analysis. The pan-sharpened RGB WV2 orthoimage with a GSD of 0.4 m was used as the reference image. Each pan-sharpened Landsat 8 image was rectified with this reference image using 50 ground control points evenly distributed over the working area and a first order polynomial transformation. The resulting RMSE2D for the geometrically-corrected images ranged from 4.42 m to 6.95 m.