João Alírio

Remote Sensing data are used across various fields, and their selection must consider the study's objectives, sensor capabilities, and different resolutions. In urban climate investigations, such as the Urban Heat Island (UHI), thermal sensors estimate Land Surface Temperature (LST), but freely available products have low spatial resolution. This study proposes a methodology to resample MODIS LST from 1 km to 10 m (MODIS_LST_1km and MODIS_LST_10m, respectively), between 2018 and 2023, in different seasons, along the border between Portugal and Spain. We used Google Earth Engine to calculate MODIS_LST_1km and the Normalized Difference Vegetation Index (NDVI) from Sentinel-2. We resampled the NDVI to 1 km and calculated a regression equation for each data when images from both products were available. We applied the resulting equation using NDVI with a 10 m (original resolution) to obtain MODIS_LST_10m. We validated the results with Landsat-8 LST (Landsat_LST) data through Spearman correlation in R software. Additionally, we analyzed the correlation between NDVI and the Enhanced Vegetation Index (EVI) from Landsat-8 with MODIS_LST_10m to assess whether higher temperatures corresponded to areas with low vegetation. The model showed good explainability, especially in summer, and validation with Landsat-8 was also more significant in summer (ρ between 0.736 and 0.895). The correlations between MODIS_LST_10m with EVI and NDVI were negative on most dates, indicating higher temperatures in less vegetated areas. For future studies, we plan to test other sensors/satellites, such as Sentinel-3, to reinforce the robustness of this methodology.

Assessing biodiversity in protected areas is essential for effective conservation management. However, conventional methods for estimating species richness can lead to inaccurate assessments of biodiversity in these regions. To address this, we present a complementary approach to assess potential species richness at a 1 km resolution in the special conservation area of Montesinho/Nogueira (SAC-MN; Portugal), based on a spatial and temporal estimates of species richness trends over time (2001–2021). We compiled 10,190 species occurrence records from four taxonomic groups: amphibians, reptiles, birds, and mammals. We created correlative ecological niche models (MaxEnt) with a time series of satellite-remote sensing variables (SRS-ENMs) using Google Earth Engine (GEE). We calculated annual potential species richness (PSR) maps by stacking the SRS-ENMs and identified positive and negative trends with the Mann–Kendall test. Each species’ ecological niche model revealed unique patterns of habitat suitability within SAC-MN over time. The eastern and western boundaries of SAC-MN revealed an increase in PSR, while the central area indicated PSR declines. Each group displayed different trends in PSR: birds and mammals were more similar between them than amphibians and reptiles. This approach provides ecologists and conservationists with valuable tools to evaluate PSR and trends over time, offering crucial insights for decision-makers and stakeholders to support local biodiversity conservation efforts.

The Urban Heat Island (UHI) effect refers to the temperature difference between urban and surrounding rural areas, with higher temperatures in urban areas, especially after sunset. The Surface Urban Heat Island (SUHI), a proxy for UHI, can be evaluated using Remote Sensing (RS) data by calculating the Land Surface Temperature (LST). Bragança (Portugal) has an in situ network, with 23 sensors installed in 2011, classified into seven different Local Climate Zones (LCZs), to measure Air Temperature (T_air). The primary objectives of this study were to: i) calculate the LST using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data available on Google Earth Engine (GEE) from 2000-2023 at these 23 points, divided into spring/summer (a); and autumn/winter (b); ii) calculate and analyze the Intensity of SUHI (SUHI_int) (2000-2023), using LST, based on the temperature difference recorded at each sensor compared to the average temperature at the Rural Areas (RCD) sensors, and evaluate the thermal behavior in the LCZs; iii) calculate the UHI (UHI_int), using T_air data; and iv) correlate SUHI_int and UHI_int (2011-2023). As a result, 17 images from (a) and four from (b) were processed, and the highest LST medians were associated with classes featuring anthropogenic elements in both, with (a) being more heterogeneous. Comparisons between SUHI_int and UHI_int, were obtained in 13 days, only from (a). The highest median temperature values were in anthropogenic classes. The correlation between SUHI_int and UHI_int was "strong" (74%) and "very strong" (26%), confirming their similarity in thermal behaviour.

In this work, we present and describe a spectral library (SL) with 15 vascular plant species from Montesinho Natural Park (MNP), a protected area in Northeast Portugal. We selected species from the vascular plants that are characteristic of the habitats in the MNP, based on their prevalence, and also included one invasive species: Alnus glutinosa (L.) Gaertn, Castanea sativa Mill., Cistus ladanifer L., Crataegus monogyna Jacq., Frangula alnus Mill., Fraxinus angustifolia Vahl, Quercus pyrenaica Willd., Quercus rotundifolia Lam., Trifolium repens L., Arbutus unedo L., Dactylis glomerata L., Genista falcata Brot., Cytisus multiflorus (L’Hér.) Sweet, Erica arborea L., and Acacia dealbata Link. We collected spectra (300–2500 nm) from five records per leaf and leaf side, which resulted in 538 spectra compiled in the SL. Additionally, we computed five vegetation indices from spectral data and analysed them to highlight specific characteristics and differences among the sampled species. We detail the data repository information and its organisation for a better understanding of the data and to facilitate its use. The SL structure can add valuable information about the selected plant species in MNP, contributing to conservation purposes. This plant species SL is publicly available in Zenodo platform.

The special area of conservation Montesinho/Nogueira (SAC-MN) is a key area for biodiversity conservation in the Iberian Peninsula. Covering an area of approximately 1081 km² in the northeast of Portugal mainland, the SAC-MN is home to a wide range of species, including several endemic and endangered species and priority habitats. Despite its ecological significance and importance for conservation, there is a lack of publicly available biodiversity data, which urges the need to create a comprehensive and up-to-date biodiversity dataset for the SAC-MN. To bridge the knowledge gap on biodiversity in SAC-MN, we undertook a thorough data collection process, including species occurrence records and conservation status information at regional (Portugal) and European levels, from multiple sources. We collected and compiled this information for five major taxonomic groups (amphibians, birds, flora - vascular plants, mammals and reptiles) in SAC-MN, resulting in a total of 31,871 records with 1,312 documented species. In addition, we developed an easy-to-navigate web-based geographic information system (Web GIS). In this article, we present an in-depth report on the process of compiling and preparing data, as well as the development and design of our Web GIS to increase awareness and enhance understanding of the importance of preserving biodiversity in SAC-MN.

The special area of conservation Montesinho/Nogueira (PTCON0002) is a key area for conserving biodiversity in the Iberian Peninsula. Covering an area of approximately 1081 km² in the northeast of Portugal mainland, the PTCON0002 is home to a wide range of biodiversity, including several endemic and endangered species, and priority habitats. Despite its ecological significance and importance for conservation, there is a lack of publicly available biodiversity data, which urges the need to create a comprehensive and up-to-date biodiversity dataset for the PTCON0002. To bridge the knowledge gap on biodiversity in PTCON0002, we undertook a thorough data collection process, such as species occurrence records and conservation status information at regional (Portugal) and European levels, from multiple sources. We collected and compiled this information for PTCON0002 resulting in a total of 31 871 records with 1 312 documented species. In addition, we developed an easy-to-navigate web-based geographic information system (Web GIS). In this article, we present an in-depth report on the process of compiling and preparing data, as well as the development and design of our Web GIS to increase awareness and enhance understanding of the importance of preserving biodiversity in PTCON0002.