## 3 Results
The blue cluster was mainly composed of terms related to phenology applications in agriculture (e.g., yield, food, crop classification, growth stage, sowing date, crop management, low cost), crop types (e.g., crops, wheat, maize, vineyard, soy, barley), water resource (e.g., irrigation, water use, water stress, soil moisture), crop modeling (e.g., assimilation, model result, evapotranspiration, ancillary data, sensitivity analysis), sensor and bands used (e.g., SAR - Synthetic Aperture Radar image, Rapideye, SPOT, Sentinel, MODIS products, backscattering, SWIR - Short Wave Infrared, NIR - Near Infrared, red edge), and regions like Thailandia, Northern China, and Germany. The orange cluster was mainly composed of terms related to classification methods and validation (i.e., endmember, object-oriented, support vector machine (SVM), spectral angle mapper (SAM), random forest, kappa coefficient, accuracy, field survey), spectral data characteristics (e.g., Worldview, Landsat, high spatial resolution, hyperspectral data, coarse spatial resolution, shadow, spectral response, cost efficiency), environmental resources (e.g., conservation, biodiversity, long term change, human activity, urbanization, deforestation, invasion, habitat, land cover, species distribution), and regions like Greece and Japan. Figure 3: Network mapping of the keywords most used (occurrence threshold = 20) in the rs+pheno research in 1999–2008. Color bar indicates the year in which each keyword was mainly used. Lines represent the link strength between two terms (minimum link strength = 10). Figure 4: Network mapping of the keywords most used (occurrence threshold = 20) in the rs+pheno research in 2009–2018. Color bar indicates the year in which each keyword was mainly used. Lines represent the link strength between two terms (minimum link strength = 10). Figure 5: Network mapping and clustering of terms in 1999–2008. Since it is a 3-d map, not all the terms are represented. Lines represent the link strength between two terms (minimum link strength = 10). Red cluster = phenology/climate topic; Blue cluster = classification/agriculture topic. Figure 6: Network mapping and clustering of terms in 2009–2018. Since it is a 3-d map, not all the terms are represented. Lines represent the link strength between two terms (minimum link strength = 10). Red cluster = phenology/climate topic; Blue cluster = agriculture topic; Orange cluster = classification topic. The comparison of the ten most occurment terms for 1999-2008 and 2009-2018 (Table 2) highlighted that terms like 'classification', 'accuracy','mapping', and 'temperature' were the most used one, with similar relevance and similar (relative) occurrence, in both decades. On the contrary, 'SOS', although present in both decades, in 1999-2008 was characterized by a higher relevance with respect to 2009-2018. 'LAI' was the main term in 1999-2008, but it disappeared in 2009-2018; while,'response', 'trend', and 'climate change' appeared in the last decade. It is to be noticed that the term 'NDVI' was not present in the list of ten most occurment terms. This could probably be explained by the fact that, as largely adopted, NDVI could appear not only as a single term but also as a composed term, like 'NDVI time-series', 'NDVI data', 'MODIS NDVI data', 'NDVI value', 'NDVI image', etc. As a consequence, the NDVI term occurrence is diluted into the different forms of use. The comparison of the ten most relevant terms for 1999-2008 and 2009-2018 (Table 3) showed that, apart from terms like crop type that can be recovered as crop classification and carbon flux as carbon uptake, almost all of the terms and related concepts of the first decade tended to lose their relevance in the following decade. In the first decade, the majority of the relevant terms belonged to the agriculture/classification (blue) cluster and were mainly related to crop type (rel. score = 2.14), yield (rel. score = 1.83), and growing season (e.g., July, rel. score = 2.60; May, rel.