Subjects: Geosciences >> Geography submitted time 2022-02-21 Cooperative journals: 《干旱区科学》
Carlos R PINHEIRO JUNIOR
Conan A SALVADOR
Tiago R TAVARES
Marcel C ABREU
Hugo S FAGUNDES
Wilk S ALMEIDA
Eduardo C SILVA NETO
Lúcia H C ANJOS
Marcos G PEREIRA
Abstract：Soils (Leptosols or Epileptic Regosols) with lithic contact at a depth of 50 cm occupy almost 20% of the Brazilian semi-arid region. These lithic soils are susceptible to erosion due to faster saturation of water-holding capacity during rainfall, which accelerates the beginning of runoff. However, erosion traits of lithic soils in the semi-arid region of Brazil are less studied. The aim of this study was to characterize the soil and landscape attributes in areas with Neossolos Litlicos (Entisols) in the Ca atinga biome to identify region of high susceptibility to erosion. Results showed that the soils were characterized by a sandy texture, soil structure with poor development and low content of organic carbon. These attributes increase susceptibility to erosion and reduce water storage capacity, especially in the states of Cear and Sergipe. In these states, the content of rock fragments in the soil reaches 790 g/kg. High contents of silt and fine sand, high silt/clay ratio, predominance of Leptosols and strong rainfall erosivity were observed in Piau and northwestern Cear. A very high degree of water erosion was observed in the states of Pernambuco and Paraba. Despite the low degree of erosion observed in the state of Bahia, it is highly susceptible to erosion due to the predominance of very shallow soils, rugged relief and high values of rainfall erosivity. Lower vulnerability was observed in the state of Alagoas because of its more smoothed relief, greater effective soil depth, thicker A horizon of soil and lower rainfall erosivity. In general, the characteristics that intensify the susceptibility to erosion in the Caatinga biome are those soil structures with poor development or without aggregation, low contents of organic carbon, high contents of silt and fine sand, high values of silt/clay ratio and rugged relief in some regions. This study collected information contributing to a better characterization of soils with lithic contact in the semi-arid region of Brazil. In addition, regions with a higher susceptibility to erosion were identified, revealing insights that could help develop strategies for environmental risk mitigation.
Subjects: Geosciences >> Geography submitted time 2021-01-15 Cooperative journals: 《干旱区科学》
Robson B de LIMA
Patrícia A B BARRETO-GARCIA
Alessandro de PAULA
Jhuly E S PEREIRA
Flávia F de CARVALHO
Silvio H M GOMES
Abstract：The volumetric variability of dry tropical forests in Brazil and the scarcity of studies on the subject show the need for the development of techniques that make it possible to obtain adequate and accurate wood volume estimates. In this study, we analyzed a database of thinning trees from a forest management plan in the Contendas de Sincorá National Forest, southwestern Bahia State, Brazil. The data set included a total of 300 trees with a trunk diameter ranging from 5 to 52 cm. Adjustments, validation and statistical selection of four volumetric models were performed. Due to the difference in height values for the same diameter and the low correlation between both variables, we do not suggest models which only use the diameter at breast height (DBH) variable as a predictor because they accommodate the largest estimation errors. In comparing the best single entry model (Hohenald-Krenn) with the Spurr model (best fit model), it is noted that the exclusion of height as a predictor causes the values of 136.44 and 0.93 for Akaike information criterion (AIC) and adjusted determination coefficient (R2 adj), which are poorer than the second best model (Schumacher-Hall). Regarding the minimum sample size, errors in estimation (root mean square error (RMSE) and bias) of the best model decrease as the sample size increases, especially when a larger number of trees with DBH≥15.0 cm are randomly sampled. Stratified sampling by diameter class produces smaller volume prediction errors than random sampling, especially when considering all trees. In summary, the Spurr and Schumacher-Hall models perform better. These models suggest that the total variance explained in the estimates is not less than 95%, producing reliable forecasts of the total volume with shell. Our estimates indicate that the bias around the average is not greater than 7%. Our results support the decision to use regression methods to build models and estimate their parameters, seeking stratification strategies in diameter classes for the sample trees. Volume estimates with valid confidence intervals can be obtained using the Spurr model for the studied dry forest. Stratified sampling of the data set for model adjustment and selection is necessary, since we find significant results with mean error square root values and bias of up to 70% of the total database.
Subjects: Geosciences >> Geography submitted time 2023-06-13 Cooperative journals: 《干旱区科学》
Janisson B de JESUS
Tatiana M KUPLICH
Íkaro D de C BARRETO
Fernando L HILLEBRAND
Cristiano N da ROSA
Abstract： The Caatinga biome is an important ecosystem in the semi-arid region of Brazil. It has significantly degraded due to human activities and is currently a region undergoing desertification. Thus, monitoring the variation in the Caatinga biome has become essential for its sustainable development. However, traditional methods for estimating aboveground biomass (AGB) are time-consuming and destructive. Remote sensing, such as optical and radar imaging, can estimate and correlate with vegetation. Nevertheless, radar imaging is still a novelty to be applied in estimating the AGB of this biome, which is an area with little research. Therefore, this study aimed to use Sentinel-1 images to estimate the AGB of the Caatinga biome in Sergipe State (northeastern Brazil) and to verify its influencing factors. Nineteen sample plots (30 m×30 m) were selected, and the stems of individuals with a circumference at breast height (1.3 m above the ground) equal to or greater than 6.0 cm were measured, and the AGB through an allometric equation was estimated. The Sentinel-1 images from 3 different periods (green, intermediate, and dry periods) were used to consider the phenological conditions of the Caatinga biome. All the pre-processing and extraction of attributes (co-polarized VV (vertical transmit and vertical receive), cross-polarized VH (vertical transmit and horizontal receive), and band ratio VH/VV backscatter, radar vegetation index, dual polarization synthetic aperture radar (SAR) vegetation index (DPSVI), entropy (H), and alpha angle (α)) were performed with Sentinel's Application Platform. These attributes were used to estimate the AGB through simple and multiple linear regressions and evaluated by the coefficients of determination (R2), correlation (r), and root mean squared error (RMSE). The results showed that the attributes individually had little ability to estimate the AGB of the Caatinga biome in the three periods. Combined with multiple regression, we found that the intermediate period presented the equation with the best results among the observed and estimated variables (R2=0.73; r=0.85; RMSE=8.33 Mg/hm2), followed by the greenness period (R2=0.72; r=0.85; RMSE=8.40 Mg/hm2). The attributes contributing to these equations were VH/VV, DPSVI, H, α, and co-polarized VV for the green period and cross-polarized VH for the intermediate period. The study showed that the Sentinel-1 images could be used to estimate the AGB of the Caatinga biome in the green and intermediate phenological periods since the SAR attributes highly correlated with the estimated variable (i.e., AGB) through multiple linear equations.
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