The objective of this study was to develop and calibrate a photovoltaic-powered soil moisture sensor (SMS) for irrigation management. Soil moisture readings obtained from the sensor were compared with gravimetric measurements. An automated SMS was used in two trials: (i) okra crop (Abelmoschus esculentus) and (ii) chili pepper (Capsicum frutescens). All sensors were calibrated and automated using an Arduino Mega board with C++. The soil moisture data were subjected to descriptive statistical analysis. The data recorded by the equipment was correlated with the gravimetric method. The determination coefficient (R²), Pearson correlation (r), and root mean square error (RMSE) were adopted as criteria for equipment validation. The results show that our SMS achieved an R² value of 0.70 and an r value of 0.84. Notably, there was a striking similarity observed between SMS and gravimetric data, with RMSE values of 3.95 and 4.01, respectively. The global model developed exhibited highly efficient outcomes with R² (0.98) and r (0.99) values. The applicability of the developed SMS facilitates irrigation management with accuracy and real-time monitoring using digital data. The automation of the SMS emerges as a real-time and precise alternative for performing irrigation at the right moment and in the correct amount, thus avoiding water losses.

Thematic maps of land cover and use can assist in the environmental monitoring of semiarid regions, mainly due to the advent of climate change, such as drought, and pressures from anthropic activities, such as the advance of urban areas. The use of geotechnologies is key for its effectiveness and low operating cost. The objective was to evaluate and understand the spatiotemporal dynamics of the loss and gain of land cover and use in a region of the Brazilian semiarid region, and identify annual trends from changing conditions over 36 years (1985 to 2020), using cloud remote sensing techniques in Google Earth Engine (GEE). Thematic maps of land cover and land use from MapBiomas Brazil were used, evaluated by Mann–Kendall trend analysis. The Normalized Difference Vegetation Index (NDVI) was also determined from the digital processing of about 800 orbital images (1985 to 2020) from the Landsat series of satellites. The trend analysis for land cover and use detected, over time, the loss of forest areas and water bodies, followed by the advance of exposed soil areas and urban infrastructure. The modification of native vegetation directly influences water availability, and agricultural activities increase the pressure on water resources, mainly in periods of severe drought. The NDVI detected that the period from 2013 to 2020 was most affected by climatic variability conditions, with extremely low average values. Thematic maps of land cover and use and biophysical indices are essential indicators to mitigate environmental impacts in the Brazilian semiarid region.

A caatinga apresenta uma diversidade de fisionomias e um enorme quadro de degradação, sendo importantes os estudos relacionados a fitossociologia para a caracterização da vegetação. O objetivo deste trabalho foi realizar um estudo de florística e fitossociologia em um fragmento florestal de caatinga no município de Serra do Mel no Rio Grande do Norte. Para realização do estudo foi realizado um levantamento da vegetação adotando-se a Amostragem Inteiramente Aleatória, onde foram marcadas 10 unidades amostrais de 20 x 20 m (400 m²). Foram amostrados todos os indivíduos florestais arbustivos-arbóreos vivos com CAP ≥ 6 cm. Foram avaliados todos os parâmetros fitossociológicos da estrutura horizontal e vertical, a diversidade florística das espécies através do Índice de Shannon-Weaver (H’), dominância de Simpson (C) e equabilidade de Pielou (J’). No levantamento foram encontradas 7 famílias, 12 gêneros e 12 espécies. As famílias com maior número de espécies e de indivíduos foram a Fabaceae e Euphorbiaceae. Croton blanchetianus, Mimosa tenuiflora, Bauhinia forficata, Mimosa ophthalmocentra e Poincianella pyramidalis foram as espécies que assumiram maior importância na área de estudo sob os aspectos fitossociológicos. A área do presente estudo apresenta baixa diversidade de espécies se comparada com outros fragmentos florestais de caatinga já estudados. Palavras-chave: Estrutura; Diversidade; Caatinga. FLORISTIC-PHYTOSOCIOLOGICAL CHARACTERIZATION OF THE WOODY COMPONENT IN A CAATINGA FRAGMENT IN SERRA DO MEL, RIO GRANDE DO NORTE, BRAZIL   ABSTRACT: The caatinga presents a diversity of physiognomies and a huge degradation picture, being important the studies related to phytosociology for the characterization of the vegetation. The aim of this work was to carry out a floristic and phytosociological study in a forest fragment of caatinga in Serra do Mel, Rio Grande do Norte. To carry out the study, a survey of the vegetation was performed adopting the Random Sampling, where 10 sample units of 20 x 20 m (400 m²) were marked. All living shrubby-arboreal forest individuals with CAP ≥ 6 cm were sampled. All phytosociological parameters of horizontal and vertical structure, floristic diversity of species was evaluated through Shannon-Weaver Index (H'), Simpson dominance (C) and Pielou equability (J'). The analytic survey found 7 families, 12 genera and 12 species. The families with the largest number of species and individuals were Fabaceae and Euphorbiaceae. Croton blanchetianus, Mimosa tenuiflora, Bauhinia forficata, Mimosa ophthalmocentra and Poincianella pyramidalis were the most important species in the study area under phytosociological aspects. The area of the present study presents low species diversity compared to other forest fragments of caatinga already studied. Keywords: Phytosociology; diversity; Caatinga.

Northeast Brazil (NEB), particularly its semiarid region, represents an area highly susceptible to the impacts of climate change, including severe droughts, and intense anthropogenic activities. These stresses may be accelerating environmental degradation and desertification of soil in NEB. The main aim of this study was to gain geospatial insights into the biophysical parameters of surface energy balance and actual evapotranspiration on a multi-temporal scale, aiming to detect and analyze the spectral behavioral patterns of areas vulnerable to degradation processes, based on thematic maps at the surface, for NEB and mainly the semiarid region of NEB from 2000 to 2019. Geospatial data from 8-day MODIS sensor products were used, such as surface reflectance (Terra/MOD09A1 and Aqua/MYD09A1), surface temperature (Terra/MOD11A2 and Aqua/MYD11A2), and actual evapotranspiration (Terra/MOD16A2 and Aqua/MYD16A2), version 6. Therefore, in this study, pixel-to-pixel values were processed by calculating the average pixel statistics for each year. From the reflectance product, digital processing of the surface albedo and spectral vegetation indices was also carried out, using computational programming scripts and machine learning algorithms developed via the Google Earth Engine (GEE) platform. The study also presents a seasonal analysis of these components and their relationships over 20 years. Through vegetation indices and statistical correlations, a new predictive model of actual evapotranspiration was developed. The quantitative and spatiotemporal spectral patterns of the parameters were assessed through descriptive statistics, measures of central tendency and dispersion, and statistical error analyses and correlation indices. Thematic maps highlighted the pixel-to-pixel results, with patterns of high temperature distribution mainly in the central and northeastern part of NEB and the semiarid region of NEB, highlighting the formation of persistent heat islands over time. Meanwhile, in these areas, the maps of actual evapotranspiration showed a drastic reduction due to the lesser availability of energy. Over time, the semiarid region of NEB presented areas with little and/or no vegetation cover, which were highly well-defined between the years 2012 and 2019, confirming that these areas are extremely vulnerable to degradation and desertification processes due to significant loss of vegetative and water resilience. The components of energy balance were highly interconnected to climatological and environmental conditions, showing the severe results of drought and accentuation of the water deficit in NEB, presenting a greater condition of aridity in the semiarid region of NEB over time.

Seasonally Dry Tropical Forests (SDTFs) are situated in regions prone to significant water deficits. This study aimed to evaluate and quantify the dynamics and spatial patterns of vegetation and water bodies through the analysis of physical–hydrological indices for a remnant of FTSD between 2013 and 2021. Basal area, biomass, and tree number were monitored in 80 permanent plots located in two areas of an SDTF remnant with different usage histories. To assess vegetation and water resource conditions, geospatial parameters NDVI, NDWIveg, NDWI, and MNDWI were estimated for the period from 2013 to 2021. The observed patterns were evaluated by simple linear regression, principal component analysis (PCA), and principal component regression (PCR). Area 2 presented higher values of basal area, biomass, and number of trees. In area 1, there was an annual increase in basal area and biomass, even during drought years. The NDVI and NDWIveg indicated the vulnerability of vegetation to the effects of droughts, with higher values recorded in 2020. NDWI and MNDWI detected the water availability pattern in the study area. Physical–hydrological indices in the dynamics of tree vegetation in dry forests are influenced by various factors, including disturbances, soil characteristics, and precipitation patterns. However, their predictive capacity for basal area, biomass, and tree number is limited, highlighting the importance of future research incorporating seasonal variability and specific local conditions into their analyses.