## 4 Discussion  
### Publication Trends  
Rs+pheno studies have significantly increased in number over the last decade and, as also for other disciplines (e.g., [42; 43]), the USA and China are the leading countries in terms of the number of papers. The main peaks may be recognized in correspondence with some critical dates: around 1980 (one year after the publication of the seminal work of [44] about the use of red and NIR for monitoring vegetation), 1985-86 (after Landsat-5 launch in 1984 and the year of the publications of [45] about LAI, and [46] about NDVI for remotely sensed phenology), 1995 (one year after the pivotal work of [20] about the extraction of phenological metrics from NDVI annual profile), 1999 (in 1997, the Kyoto protocol about global warming was signed), 2002-05 (Landsat-7 was launched in 1999, MODIS in 2000, and the EVI was proposed for the first time by [15]), 2008-09 (after the publication of [6] about plant phenology, shifting in response to global change using NDVI data), and 2015 (in 2011, 30 years of Landsat archive became freely available [47]; in 2013, Landsat-8 was launched, and, in 2015, Sentinel-2 was launched).  
In this framework, MODIS can be considered the most common satellite used in rs+pheno studies, covering almost all the topics identified, thanks to its very high temporal resolution (twice a day, with a 8- to 16-day and 1-month composite), moderate spatial resolution (250 m), large availability of ready-to-use products, and consistent coverage all over the world. On the contrary, Landsat represents the series of satellites that allows the larger temporal archive since the early 1980s and hence the larger time span for rs+pheno studies; while Sentinel-2 (launched in 2015) is the emerging technology in rs+pheno research, thanks to its high spatial resolution (10 m) and high temporal resolution (every 5 days). Based on such satellites, several ways of integrating the proposed remote sensing VIs into phenological modeling analysis have been suggested through time, e.g., for studying anomalies in spring and autumn phenology [48; 49], analyzing the effects of warmer temperatures on the incidence and severity of frost damage [50; 51], exploring the role of phenology in fire dynamics [52; 53], combining multi-resolution products [54; 55], smoothing satellite time-series data [56; 57], integrating remotely sensed phenology data and climate [58; 59]. While NDVI and EVI represent the most agreed VIs in rs+pheno studies, LAI and FAPAR, although largely used as inputs in crop modeling studies [60; 61; 62], remain only partially adopted.  
The most journals used in rs+pheno studies are characterized by high impact factor (>4) and high H-index (>100), and, apart from RS, by a 30-years long history of rs+pheno publications. Yet, the journals mostly involved are largely biased towards remote sensing applications in ecology and/or biology rather than towards pure ecology and/or biology. This evidence demonstrates how rs+pheno is foremost considered as a subset of remote sensing science rather than a branch of phenology. As an example, the RSE journal also covers ecology and biology but not without remote sensing techniques. Purely ecological/biological journals are only partially used to publish rs+pheno studies. This may be interpreted as that, unlike traditional phenology, rs+pheno is not considered yet as a well-established branch of ecology. Finally, it is to be noticed that the first most-publishing purely ecological journals in rs+pheno were AFM and GCB (or International Journal of Biometeorology--data not shown here), both with a clear climate-based target. However, in the last decade, journals like EI (or Ecological Modeling and Science of the Total Environment--data not shown here), with a wider ecological perspective, have increasingly been used, suggesting a progressive tendency towards a less technical approach, and a new clearance for remotely sensed phenology.