Aline Marques Genú

Comparação entre mapas de solos obtidos por sensoriamento remoto espectral e pelo método convencional

Abstract – The objective of this work was to compare the use of the spectral remote sensing for producing soilmaps to the conventional method. Using a planialtimetric base map, thirty sampling points were demarcated inthe studied area. The samples were collected at 0–20, 40–60 and 80–100 cm depth in each point, all georreferenced,with the total of ninety samples in which the chemical, physical and radiometric analyses were performed. Theradiometric data were obtained in laboratory using the spectroradiometer IRIS, in the range of 400–2,500 nm.Using the analyses and interpretation of both the spectral and the planialtimetric data, a detailed spectral soilmap was obtained. For the same area, a conventional detailed map was also obtained. Four soil classes wereidentified in both maps. The produced maps presented good correlation, demonstrating that spectral data can beused as tool in soil survey. The use of spectral remote sensing, planialtimetric data and field work allows theobtention of a detailed soil map.Index terms: soil survey, radiometry, geoprocessing.

Uso de imagens de satélite na discriminação de solos desenvolvidos de basalto e arenito na região de Paraguaçu Paulista

O objetivo deste trabalho foi avaliar o potencial de discriminacao de solos, mediante informacoes espectrais obtidas por sensor remoto em satelite. Os solos apresentaram variacoes na forma da curva espectral e intensidades de reflectância. Os Nitossolos apresentaram baixa intensidade de reflectância e os Neossolos, bastante alta. Os Latossolos Vermelhos, com diferentes texturas, apresentaram aumento na intensidade de reflectância, na sequencia dos mais argilosos para os mais arenosos. Solos eutroficos apresentaram maiores intensidades de reflectância que os alicos. A analise discriminante indicou um erro geral de 0,028%. As amostras confundidas geralmente ocorreram entre os solos com caracteristicas semelhantes. A metodologia empregada na coleta de dados espectrais de satelites mostrou-se eficiente, tornando possivel discriminar os solos da regiao estudada e, assim, agilizar a confeccao de mapas de solos.

In situ separation of soil types along transects employing Vis-NIR sensors: a new view of soil evaluation

Soil components, such as organic matter, the levels and form of iron oxides, moisture and texture, influence the interaction of the soil with electromagnetic energy, so that knowledge of the energy reflected by different classes of soil is therefore of help in their discrimination. The aim of this study was to evaluate the possibility of differentiating classes of soils along two transects, by means of the field spectral behaviour of different classes, using both visual and multivariate statistical analysis. Equidistant points were marked along the transects, 100 m apart, where geo-referenced soil samples were collected from the surface layer at a depth of 0 to 0.20 m. In the area under study, ten classes of soil were described by means of laboratory analysis of surface samples and a morphological description of the profiles, with each soil being classified according to the Brazilian System of Soil Classification. For separating soil units and establishing their boundaries in the landscape three methods were used: a) traditional, evaluating the correlation between soil and landscape; b) qualitative assessment of the spectral curves; c) multivariate analysis for discrimination of the classes of soil. Comparison of these methods made possible the use of spectroradiometry in differentiating the classes of soil, with the statistical method separating a larger number of classes. It was possible to delimit the boundaries of the soil units in the area under study, as well as differences in texture, colour, total iron and organic matter between units, by varying the spectral responses of the soil samples being tested.

Espectrorradiometria de solos e comparação com sensores orbitais

The aim of this study was to characterize and compare the spectral behavior of different soil classes obtained by orbital and terrestrial sensors. For this, an area of 184 ha in Rafard (SP) Brazil was staked on a regular grid of 100x100 m and soil samples were collected and georeferenced. After that, soil spectral curves were obtained with IRIS sensor and the sample points were overlaid at Landsat and ASTER images for spectral data collection. The soil samples were classified and mean soil curves for all sensors were generated by soil classes. The soil classes were differentiated by texture, organic matter and total iron for all sensors studied, the orbital sensors despite the lower spectral resolution, maintained the characteristics of the soil and the curves of reflectance intensity.

Informações espectroeletromagnéticas e topográficas na determinação de teores de componentes do solo

The obtention of soil quantitative information by non destructive techniques, like remote sensing and digital elevation model (DEM) open a possibility of faster and cheaper evaluation on soil studies. This study aims at verifying the possibility of quantifying soil atributtes through ASTER orbital sensor data and topographic features. The study area, with 184 ha, located in Rafard County, Sao Paulo State, Brazil, was sampled in a grid way collecting 1 sample/ha. Reflectance data was obtained from ASTER image and topographic features from DEM. Then, using orbital an topographic data were generated a multiple regression equation for soil attributes. The dependent variables were selected by a forward stepwise method. After that, the models with R2 > 0.50 were tested with unknown soil samples and the estimated values (VE) and the determined values (VD) were evaluated through scatterplots. SiO2, Fe2O3, TiO2 and clay attributes were tested and, Fe2O3 and clay obtained higher values of determination coefficient. It is conclude that the models generated with spectral data and topographic information allowed the quantification of the above cited soil components.

Atributos químicos do solo associados à produtividade do trigo em um talhão com diferentes potenciais produtivos

Different yield potentials between plots and within them have been verified in areas managed under no-till (NT). Precision farming (PF) techniques can help in identifying these distinct areas, but for efficient soil fertility management in areas under long-term NT, there must be representative sampling. The aim of this study was to evaluate the influence of soil chemical properties on wheat yield in accordance with the sampling layer or depth in an area under long-term NT using zones of a plot with different yield potentials. The study was carried out at the Reserva do Iguacu (Iguacu Conservation Area), Parana, Brazil, in an area under NT for 25 years and with adoption of PF techniques for five years. Using data from yield maps of previous crops, two zones with distinct yield potentials were identified, named Z1 (higher yields) and Z2 (lower yields), in which sample grids with 16 units (50 × 50 m) were established. Wheat yield was estimated in three points per sampling unit, taking soil samples in the 0.0-0.1 and 0.1-0.2 m depths at the same points. Wheat yield was 22 % higher in Z1 as compared to Z2, in agreement with the yield maps from previous crops. Soil organic carbon contents (Corg) were higher in Z1 for both soil layers. In the 0.1-0.2 m layer, the aluminum saturation (m %) and the Al3+ contents were significantly higher in Z2. In this same layer, Z1 showed higher values of pH and base saturation (V %) and higher levels of Ca2+, Mg2+ and K+. There was positive correlation between wheat yield and Corg content in both soil layers, and considering only the 0.1-0.2 m layer, correlation was positive with pH, V % and Ca2+, Mg2+ and K+ contents, and negative with Al3+. The differences in soil fertility between Z1 and Z2 were mainly in the 0.1-0.2 m layer and were associated with the difference in wheat yield, indicating that the presence of this stratum is important for soil sampling in long-term NT areas aiming to correctly represent the status of soil fertility.