The objective of this research is to select the best orbital sensor for rainfall estimates (monthly and annual scales) and to analyze the frequency and magnitude of extreme rainfall events and their trends and disruptions based on the use of satellite rainfall product data for the Cananeia–Iguape Coastal System (CICS). Data from four satellite rainfall products were used to identify the correspondence with seven points on the surface of the study area. Statistical metrics were used to identify the best satellite rainfall product. After identifying the sensor with the best performance in estimating orbital precipitation, extreme events were identified by the Standardized Precipitation Index (SPI) on a one-month (SPI-1), three-month (SPI-3), and twelve-month (SPI-12) scale. Trend and rupture detection in the time series were performed using different statistical techniques (Mann–Kendall, Pettitt, Standard Normal Homogeneity Test, or Buishand test). Among the satellite rainfall products, CHIRPS had the best measurements for the analyzed points on the surface. The year 1983 was characterized as very rainy, also marked by the occurrence of El Niño, and was marked by the rupture of the rains at all points (IDs 1, 2, 3, 4, 5, 6, and 7) analyzed in the month of June. The decrease in monthly rainfall was more significant in the months of February (at points IDs 1, 2, 3, 5, and 7) and April (IDs 1, 3, 5, and 7). Decreased rainfall may cause CICS mangrove shrinkage. These results showed the importance of studying rainfall in an area with mangroves in order to understand the dynamics of vegetation in the face of climate change.

Extensive urbanization around the world has resulted in the consumption of massive vegetated areas and natural resources. To this end, one strategy for urban development is to consolidate urban areas. In Balneário Camboriú/SC, Brazil, this trend has transformed the city into a vertical built-up area on its coastal strip, accommodating a large amount of buildings both in terms of quantity and number of floors. This research aims to quantify the thermo-hygrometric fluctuation on the waterfront of Balneário Camboriú, in negative radiation balance. To acquire the data on air temperature (Ta) and relative humidity (RH), two mobile transects and measuring at two fixed points were made in a situation of negative radiation balance on 26 August 2019, in the winter period of the Southern Hemisphere. The collection work began at 06:00:00 a.m. (before sunrise, the peak of the negative radiation balance), on Atlântica Avenue (waterfront) and Brasil Avenue (parallel to the waterfront). It was verified that the Ta varied from 16.0 °C to 19.0 °C, and the RH remained over 80% during the entire route. At the meteorological shelters, the temperature presented a variation from 14.4 °C to 17.7 °C, and the RH ranged from 79.6% to 91.3% between the two points. The spatial variability in the Ta and RH along the paths travelled and at the fixed points is directly related to the land cover, represented especially by the buildings’ verticalization and data collection time.

The objective of this article is to investigate the possible correlations between vegetation indices and surface temperature in the Cananéia–Iguape Coastal System (CICS), in São Paulo (Brazil). Vegetation index data from MODIS orbital products were used to carry out this work. The Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) were acquired from the MODIS/Aqua sensor (MYD13Q1) and the leaf area index (LAI) from the MODIS/Terra (MOD15A2H). Surface temperature data were acquired from MODIS/Aqua (MYD11A2). The data were processed using Google Earth Engine and Google Colab. The data were collected, and spatial and temporal correlations were applied. Correlations were applied in the annual and seasonal period. The annual temporal correlation between vegetation indices and surface temperature was positive, but statistically significant for the LAI, with r = 0.43 (90% significance). In the seasonal period, positive correlations occurred in JFM for all indices (95% significance). Spatially, the results of this research indicate that the largest area showed a positive correlation between VI and LST. The hottest and rainiest periods (OND and JFM) had clearer and more significant correlations. In some regions, significant and clear correlations were observed, such as in some areas in the north, south and close to the city of Iguape. This highlights the complexity of the interactions between vegetation indices and climatic attributes, and highlights the importance of considering other environmental variables and processes when interpreting changes in vegetation. However, this research has significantly progressed the field, by establishing new correlations and demonstrating the importance of considering climate variability, for a more accurate understanding of the impacts on vegetation indices.