Abstract Studies around the world show an increase in global average temperatures, with a consequent increase in extreme events and changes in the distribution of precipitation, causing a decrease in agricultural production and changes in planting areas. This study analyzed the exposure to climate risk that the coffee crop in the region of Alta Mogiana/SP, Brazil has been presenting in the past thirty years (1991-2021). Time series of daily data of maximum and minimum temperature and precipitation were used. By the statistical tests we observed a trend of increase in maximum temperatures daily of approximately 1.4°C and minimum daily of 0.8°C in the municipalities of the region and a trend towards a decrease in precipitation of 0.9 mm daily, indicating greater exposure of the coffee crop in the region to climate risk and increased vulnerability for the coffee producer. In view of these analyses, a literature review was carried out, suggesting agroforestry systems and mechanical irrigation as the most promising strategies to manage climate risk in coffee plantations. In addition, drought-resistant cultivars, training courses for farmers, increased rural insurance, and nutritional control of the plants can also be considered efficient options for climate exposure in coffee plantations from Alta Mogiana.

ABSTRACT This study used spectral data integrated with the agrometeorological model by Doorenbos and Kassam to estimate soybean grain productivity in the state of Mato Grosso, Brazil. In the developed model, spectral data were used instead of meteorological data and biophysical parameters of the crop. For this purpose, the products of real and potential evapotranspiration (MOD16), normalized difference vegetation index – NDVI (MOD13Q1), and leaf area index (MOD15A2H) from the MODIS satellite were used, in addition to sunstroke data obtained by using the visible channel from the satellite GOES IMAGER. The results obtained showed that, with the proposed methodology, it was possible to follow the development of soybean cultivation throughout the cycle and to estimate production and productivity in the study area. Willmott's agreement index was 0.99 and 0.96 and Pearson's correlation coefficient was 0.99 and 0.84 for production and productivity, respectively.