5 resultados para Geoenvironmental cartography

em Scielo Saúde Pública - SP


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Map units directly related to properties of soil-landscape are generated by local soil classes. Therefore to take into consideration the knowledge of farmers is essential to automate the procedure. The aim of this study was to map local soil classes by computer-assisted cartography (CAC), using several combinations of topographic properties produced by GIS (digital elevation model, aspect, slope, and profile curvature). A decision tree was used to find the number of topographic properties required for digital cartography of the local soil classes. The maps produced were evaluated based on the attributes of map quality defined as precision and accuracy of the CAC-based maps. The evaluation was carried out in Central Mexico using three maps of local soil classes with contrasting landscape and climatic conditions (desert, temperate, and tropical). In the three areas the precision (56 %) of the CAC maps based on elevation as topographical feature was higher than when based on slope, aspect and profile curvature. The accuracy of the maps (boundary locations) was however low (33 %), in other words, further research is required to improve this indicator.

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ABSTRACT The semiarid region of northeastern Brazil has a large area occupied by Planosols, where in the State of Pernambuco these soils are mainly used for livestock farming and subsistence crops. The knowledge on these soils is limited, which compromises the understanding on their behavior, potentialities and limitations.This study aimed to analyze morphological, chemical, physical and mineralogical attributes of Planosols developed under different geoenvironmental conditions. Morphological descriptions and chemical, physical and mineralogical analyses were performed in four profiles of Planosols along a rainfall gradient. An increase in rainfall allowed for an increase in the clay content in the Bt horizon and a reduction in ESP, EC, Na+, CEC, S, pH (water and KCl) and soil density. Horizons A and E were thicker in Planosols in more humid environments. The increase in ESP associated with the presence of expansive minerals (smectite and vermiculite) allowed the development of a prismatic structure in Haplic Planosols and a columnar structure in Natric Planosols. The mineralogical assembly is indicative of poorly weathered soils. The mineralogical assemblies of the silt and clay fractions were similar in the different geoenvironments, while higher contents of easily alterable minerals were observed in the composition of the sand fraction in environments with a drier climate.

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One of the first scientific maps of the Amazon region, The Course of the Amazon River (Le Cours de La Rivière des Amazones), was constructed by Nicolas Sanson, a French cartographer of the seventeenth century, and served as the prototype for many others. The evaluation of this chart, until now, has been that it is a very defective map, a sketch based on a historical account, according to the opinion of La Condamine. Thus, the aim of the present work was to prove that the map of the Amazon River traced by Nicolas Sanson is a scientific work, a map that presents precise geographic coordinates considering its time, shows a well-determined prime meridian, and also employs a creative methodology to deduce longitudes from latitudes and distances that had been covered. To show such characteristics, an analysis of the accuracy of the map was made by comparing its latitudes and longitudes with those of a current map. We determined the prime meridian of this map and analyzed the methodology used for the calculation of longitudes. The conclusion is that it is actually a good map for the time, particularly considering the technology and the limited information that Sanson had at his disposal. This proves that the negative assertion of La Condamine is unfounded.

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Since different pedologists will draw different soil maps of a same area, it is important to compare the differences between mapping by specialists and mapping techniques, as for example currently intensively discussed Digital Soil Mapping. Four detailed soil maps (scale 1:10.000) of a 182-ha sugarcane farm in the county of Rafard, São Paulo State, Brazil, were compared. The area has a large variation of soil formation factors. The maps were drawn independently by four soil scientists and compared with a fifth map obtained by a digital soil mapping technique. All pedologists were given the same set of information. As many field expeditions and soil pits as required by each surveyor were provided to define the mapping units (MUs). For the Digital Soil Map (DSM), spectral data were extracted from Landsat 5 Thematic Mapper (TM) imagery as well as six terrain attributes from the topographic map of the area. These data were summarized by principal component analysis to generate the map designs of groups through Fuzzy K-means clustering. Field observations were made to identify the soils in the MUs and classify them according to the Brazilian Soil Classification System (BSCS). To compare the conventional and digital (DSM) soil maps, they were crossed pairwise to generate confusion matrices that were mapped. The categorical analysis at each classification level of the BSCS showed that the agreement between the maps decreased towards the lower levels of classification and the great influence of the surveyor on both the mapping and definition of MUs in the soil map. The average correspondence between the conventional and DSM maps was similar. Therefore, the method used to obtain the DSM yielded similar results to those obtained by the conventional technique, while providing additional information about the landscape of each soil, useful for applications in future surveys of similar areas.

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This paper aims to assess the effectiveness of ASTER imagery to support the mapping of Pittosporum undulatum, an invasive woody species, in Pico da Vara Natural Reserve (S. Miguel Island, Archipelago of the Azores, Portugal). This assessment was done by applying K-Nearest Neighbor (KNN), Support Vector Machine (SVM) and Maximum Likelihood (MLC) pixel-based supervised classifications to 4 different geographic and remote sensing datasets constituted by the Visible, Near-Infrared (VNIR) and Short Wave Infrared (SWIR) of the ASTER sensor and by digital cartography associated to orography (altitude and "distance to water streams") of which the spatial distribution of Pittosporum undulatum directly depends. Overall, most performed classifications showed a strong agreement and high accuracy. At targeted species level, the two higher classification accuracies were obtained when applying MLC and KNN to the VNIR bands coupled with auxiliary geographic information use. Results improved significantly by including ecology and occurrence information of species (altitude and distance to water streams) in the classification scheme. These results show that the use of ASTER sensor VNIR spectral bands, when coupled to relevant ancillary GIS data, can constitute an effective and low cost approach for the evaluation and continuous assessment of Pittosporum undulatum woodland propagation and distribution within Protected Areas of the Azores Islands.