The surface albedo plays an important role in the exchanges of energy and mass in the planetary boundary layer. Therefore, changes in albedo affect the balance of radiation and energy at the surface, which can be detected with its monitoring. Albedo determination has been performed through various sensors, but there is not yet any publication dealing with albedo calculation procedures using OLI (Operational Land Imager) - Landsat 8 images. The objective of the study is to present the procedures for computing the albedo with OLI images and map it in irrigated areas of the São Gonçalo Irrigated District, PB, Brazil. Images of the year 2013, path 215 and row 65, were selected. The data necessary for calculating the albedo were extracted from each image metadata: additive and multiplicative terms of radiance and reflectance, and sun elevation angle. There were large differences between the albedo values of irrigated plots, water bodies and native vegetation. The albedo obtained with OLI images provides a higher degree of differentiation of the various types of land use, due to the substantial increase in the radiometric resolution of this new sensor.

The Caatinga is the largest nucleus of Seasonally Dry Tropical Forests (SDTF) in the Neotropics. The leafing patterns of SDTF vegetation are adapted to the current environmental and climate variability, but the impacts of climate change tend to alter plants’ phenology. Thus, it is necessary to characterise phenological parameters and evaluate the relationship between vegetation and environmental drivers. From this information, it is possible to identify the dominant forces in the environment that trigger the phenological dynamics of the Caatinga. In this way, remote sensing represents an essential tool to investigate the phenology of vegetation, particularly as it has a long series of vegetation monitoring and allows relationships with different environmental drivers. This study has two objectives: (i) estimate phenological parameters using an Enhanced Vegetation Index (EVI) time-series over 20 years, and (ii) characterise the relationship between phenologic dynamics and environmental drivers. TIMESAT software was used to determine four phenological parameters: Start Of Season (SOS), End Of Season (EOS), Length Of Season (LOS), and Amplitude (AMPL). Boxplots, Pearson’s, and partial correlation coefficients defined relationships between phenologic dynamics and environmental drivers. The non-parametric test of Fligner–Killeen was used to test the interannual variability in SOS and EOS. Our results show that the seasonality of vegetation growth in the Caatinga was different in the three experimental sites. The SOS was the parameter that presented the greatest variability in the days of the year (DOY), reaching a variation of 117 days. The sites with the highest SOS variability are the same ones that showed the lowest EOS variation. In addition, the values of LOS and AMPL are directly linked to the annual distribution of rainfall, and the longer the rainy season, the greater their values are. The variability of the natural cycles of the environmental drivers that regulate the ecosystem’s phenology and the influence on the Caatinga’s natural dynamics indicated a greater sensitivity of the phenologic dynamics to water availability, with precipitation being the limiting factor of the phenologic dynamics. Highlights: The EVI time series was efficient in estimating phenological parameters. The high variability of the start of season (SOS) occurred in sites with low variability of end of the season (EOS) and vice versa. The precipitation and water deficit presented a higher correlation coefficient with phenological dynamics. Length of Season (LOS) and amplitude (AMPL) are directly linked to the annual distribution of rainfall.

Apesar de ser o único bioma brasileiro cujos limites estão restritos ao território nacional, pouca atenção tem sido dada à conservação da diversificada paisagem da Caatinga. Em virtude da carência de dados de campo para monitorar os parâmetros biofísicos da Caatinga em região semiárida do Nordeste brasileiro, este trabalho teve como objetivo avaliar a dinâmica espaço-temporal por meio de técnicas e produtos de Sensoriamento Remoto. A área de estudo compreendeu a Unidade de Conservação do Parque Nacional da Furna Feia e suas adjacências, situada entre os municípios de Mossoró e Baraúna (RN, Brasil). Utilizaram-se seis imagens orbitais do TM LANDSAT 5, órbita 216 e ponto 63, no período de 2007 a 2010. Com auxílio da ferramenta Sistema de Informação Geográfica se implementaram os algoritmos com geração das cartas temáticas expressando a variabilidade dos parâmetros de albedo da superfície, NDVI e temperatura de superfície. Os resultados obtidos não só foram consistentes com dados da literatura para os diferentes usos do solo e variações climáticas. Além de demonstrar o potencial das geotecnologias, a compreensão da dinâmica dos padrões espaciais e temporais dos processos biofísicos de interação solo-planta-atmosfera da Caatinga no Semiárido.

Field-based soil moisture measurements are cumbersome. Thus, remote sensing techniques are needed because allows field and landscape-scale mapping of soil moisture depth-averaged through the root zone of existing vegetation. The objective of the study was to evaluate the accuracy of an empirical relationship to calculate soil moisture from remote sensing data of irrigated soils of the Apodi Plateau, in the Brazilian semiarid region. The empirical relationship had previously been tested for irrigated soils in Mexico, Egypt, and Pakistan, with promising results. In this study, the relationship was evaluated from experimental data collected from a cotton field. The experiment was carried out in an area of 5 ha with irrigated cotton. The energy balance and evaporative fraction (Λ) were measured by the Bowen ratio method. Soil moisture (θ) data were collected using a PR2 - Profile Probe (Delta-T Devices Ltd). The empirical relationship was tested using experimentally collected Λ and θ values and was applied using the Λ values obtained from the Surface Energy Balance Algorithm for Land (SEBAL) and three TM - Landsat 5 images. There was a close correlation between measured and estimated θ values (p<0.05, R² = 0.84) and there were no significant differences according to the Student t-test (p<0.01). The statistical analyses showed that the empirical relationship can be applied to estimate the root-zone soil moisture of irrigated soils, i.e. when the evaporative fraction is greater than 0.45.