ABSTRACT The rational exploitation of the land requires planning its agricultural use, which can be supported by the agricultural land suitability (ALS) assessment. The scheme to assess ALS proposed by Food Agricultural Organization (FAO) has been adopted in Brazil based on guiding charts for subtropical, humid tropical and semi-arid tropical climate. However, the guiding chart used for the semi-arid region has dramatically limited the ALS in drylands on which rainfed agriculture has been practiced. In this study, an adequation for the ALS assessment regarding the edaphoclimatic conditions of semi-arid region was proposed to improve the representation of agricultural areas and to allow a better planning of soil conservation practices. The ALS of the south region of Ceará State (Brazil) was assessed according to the FAO scheme and its initial adaptation to the Brazilian conditions; subsequently, this assessment was obtained by two adequations. Adequation I disregarded the limiting factor of water availability, while adequation II, besides disregarding the factor of water availability, established new limits for the classes of effective soil depth. The adequations resulted in an increase of 177.19 % in the areas with regular suitability for crops to the detriment of areas with restricted suitability for crops and areas with suitability only for pasture or grazing lands. The adequations increased the agricultural suitability in 41.26 % of the area of the mapping units, and 16.77 % of them were due to the modifications related to the effective soil depth, while the other 26.35 % were due to the changes related to water availability. The results related to water availability were equivalent to those observed through the dynamic analysis of land-use and cover associated with the rainfall, which demonstrated an increase in the areas for rainfed agriculture and a reduction in fallow and pasture areas in the years with rainfall within the climatic normality. The areas considered suitable for crop production with the adequation of the scheme may be included in soil conservation programs. use (ALS (FAO subtropical semiarid semi arid climate However practiced study practices (Brazil subsequently II depth 17719 177 19 177.1 lands 4126 41 26 41.2 units 1677 16 77 16.7 2635 35 26.3 landuse normality programs 1771 17 1 177. 412 4 2 41. 167 7 16. 263 3 26.

ABSTRACT Brazilian palm swamps (veredas) are fundamentals in the hydrological balance of watercourses in the Brazilian savanna (Cerrado). The “sponge effect” of their soils is the main factor controlling local hydrology, storing rainwater, and functioning as headwaters. The restricted knowledge of these tropical ecosystems has led to increased losses, poor preservation, and reduction in their ecosystem services. Veredas have become refuges surrounded by croplands, often drained and inappropriately managed. This study shows the impacts of anthropization on soil processes and properties of a vereda in an agricultural area. Two soil profiles were selected and characterized as preserved and anthropized, respectively upstream and downstream of the studied vereda. Morphological, physical, chemical and microbiological properties were analyzed. Principal Components Analysis (PCA) was applied to synthesize the data and provide evidence of the main properties and underlying processes that most responded to the degradation action. The arrangement of this analysis shows three main distinguish drivers: one joining the properties related to the humification of organic matter and relative accumulation of mineral matter versus accumulation of organic matter; the second with properties related to soil chemical reactivity; and the third reflecting the mineralization of organic matter. Our results suggest that the anthropic action has strongly caused the organic carbon reduction (~22 %). After 20 years, the anthropized soil presents not only a great decline in carbon stock (~14 kg m-2), but also strong impacts on several other ecologic functions, such as water holding capacity. Veredas are complex and fragile environments, and they should be fully protected to maintain their ecosystem services.

RESUMO O processo de desertificação causa redução da vegetação e degradação do solo. A ausência de técnicas de visualização e ampla dimensão espaço - temporal dos dados dificultam a identificação da desertificação e a rápida tomada de decisão por equipes multidisciplinares. O Scatter Plot 2D é uma análise visual e bidimensional das reflectâncias das bandas do vermelho (630 - 690 nm) e do infravermelho próximo (760 - 900 nm) para visualizar a resposta espectral da vegetação. Nesse sentido, a hipótese deste trabalho é que a visualização das reflectâncias da vegetação através do Scatter Plot 2D permitirá inferir a ocorrência de desertificação. Neste estudo o objetivo foi identificar áreas desertificadas e caracterizar a dinâmica espacial e temporal da vegetação e do solo nos períodos secos (FS) e chuvosos (FC), de 2000 a 2008 usando o Scatter Plot 2D. Foram utilizados o 2D Scatter Plot do Envi® 4.8 e as reflectâncias das bandas 3 e 4 do sensor TM5 em comunidades do núcleo de Irauçuba (Ceará, Brasil). Foram observadas as densidades de concentração das reflectâncias dos pixels de vegetação em relação ao infravermelho próximo. Todas as comunidades em todos os períodos de avaliação apresentaram concentrações de pixels com reflectâncias inferiores a 0,4 (40%), indicando pouco desenvolvimento da vegetação e posterior degradação, causadas pelo desmatamento, uso do fogo e sobre pastejo. Portanto o Scatter Plot 2D foi capaz de mostrar a vegetação com baixas reflectâncias no infravermelho próximo entre os anos de 2000 a 2008 em épocas secas e chuvosas, permitindo inferir a ocorrência da desertificação.

ABSTRACT The desertification process causes soil degradation and a reduction in vegetation. The absence of visualisation techniques and the broad spatial and temporal dimension of the data hampers the identification of desertification and rapid decision-making by multidisciplinary teams. The 2D Scatter Plot is a two-dimensional visual analysis of reflectances in the red (630 - 690 nm) and near-infrared (760 - 900 nm) bands to visualise the spectral response of the vegetation. The hypothesis of this study is that visualising the reflectances of the vegetation by means of a 2D scatter plot will allow desertification to be inferred. The aim of this study was to identify desertified areas and characterise the spatial and temporal dynamics of the vegetation and soil during dry (DP) and rainy (RP) periods between 2000 and 2008, using a 2D scatter plot. The 2D scatter plot generated by the Envi® 4.8 software and the reflectances in bands 3 and 4 of the TM5 sensor were used within communities in the Irauçuba hub (Ceará, Brazil). The concentration densities of the near-infrared reflectances of the vegetation pixels were observed. Each community presented pixel concentrations with reflectances of less than 0.4 (40%) during each of the periods under evaluation, indicating little vegetation development, with further degradation caused by deforestation, the use of fire and overgrazing. The 2D scatter plot was able to show vegetation with low reflectance in the near infrared during both dry and rainy periods between 2000 and 2008, thereby inferring the occurrence of desertification.

RESUMO O Hidrograma Unitário (HU) é o método mais popular para aplicações relacionadas a cheias. Existem vários modelos conceituais e geomorfológicos baseados no HU e acoplados a diferentes discretizações espaciais. No entanto, existem poucos estudos sobre a avaliação de modelos de HU de acordo com abordagens semi-distribuídas. O objetivo deste estudo foi avaliar a influência da modelagem concentrada e semi-distribuída na aplicabilidade do HU do Soil Conservation Service (HU SCS) e do HU Instantâneo de Clark (HUI de Clark) na estimativa de hidrogramas de cheias. Os procedimentos metodológicos foram conduzidos no Hydrologic Modeling System (HEC-HMS) utilizando os eventos chuva-vazão de uma bacia hidrográfica monitorada no sul do Brasil. As principais conclusões foram: a) o HUIC na abordagem semi-distribuída proporcionou desempenho ligeiramente superior; b) o HUIC foi capaz de estimar efetivamente os hidrogramas de escoamento superficial direto mesmo para eventos de chuva de longa duração; c) o HU SCS apresentou hidrogramas mais precisos para modelagem concentrada; d) o algoritmo de Nelder e Mead pode ter aplicação limitada.

ABSTRACT The Unit Hydrograph (UH) is the most popular method for flood related applications. There are several conceptual and geomorphological models based on UH and coupled with different spatial discretizations. However, there are few studies concerning the evaluation of UH models according to semi-distributed approaches. This study aimed to assess the influence of lumped and semi-distributed modeling on the applicability of Soil Conservation Service UH (SCS UH) and Clark’s Instantaneous UH (Clark’s IUH) for estimation of flood hydrographs. The methodological procedures were conducted in the Hydrological Modeling System (HEC-HMS) using rainfall-runoff events of a gauged watershed in Southern Brazil. The main conclusions were: a) CIUH under the semi-distributed approach provided slightly superior performance; b) CIUH was able to effectively estimate the direct surface runoff hydrographs even for long duration rainfall events; c) SCS UH presented more accurate hydrographs for lumped modeling; d) the Nelder and Mead algorithm may have limited application.

ABSTRACT When the harvesting of sugarcane involves a mechanized process, plant residues remain on the soil surface, which makes proximal and remote sensing difficult to monitor. This study aimed to evaluate, under laboratory conditions, differences in the soil spectral behavior of surface layers Quartzipsamment and Hapludox soil classes due to increasing levels of sugarcane’s dry (DL) and green (GL) leaf cover on the soil. Soil cover was quantified by supervised classification of the digital images (photography) taken of the treatments. The spectral reflectance of the samples was obtained using the FieldSpec Pro (350 to 2500 nm). TM-Landsat bands were simulated and the Normalized Difference Vegetation Index (NDVI) and soil line were also determined. Soil cover ranged from 0 to 89 % for DL and 0 to 80 % for GL. Dry leaf covering affected the features of the following soil constituents: iron oxides (480, 530 and 900 nm) and kaolinite (2200 nm). Water absorption (1400 and 1900 nm) and chlorophyll (670 nm) were determinant in differentiating between bare soil and GL covering. Bands 3 and 4 and NDVI showed pronounced variations as regards differences in soil cover percentage for both DL and GL. The soil line allowed for discrimination of the bare soil from the covered soil (DL and GL). High resolution sensors from about 50 % of the DL or GL covering are expected to reveal differences in soil spectral behavior. Above this coverage percentage, soil assessment by remote sensing is impaired.

Atualmente, o espectro de reflectância do solo é uma informação subutilizada em processos de classificação. Sendo assim, os objetivos deste trabalho foram avaliar as relações entre os espectros de solos e seus atributos físicos e químicos, identificar padrões espectrais para cada classe de solo e por fim analisar o uso da classificação numérica de perfis, conciliada a dados espectrais, na distinção de solos. Para tanto, foram estudados 20 perfis da região de Piracicaba, SP, sendo descritos morfologicamente e classificados até o 3¼ nível categórico do SiBCS. Amostras foram coletadas dos horizontes pedogenéticos e foram submetidas às análises granulométrica e química. Posteriormente, o comportamento espectral de cada solo foi obtido e submetido à análise por componentes principais. Os escores dos componentes principais foram utilizados em análise de correlação linear com pH, matéria orgânica, P, K, Ca, Mg, Al, CTC, V% e m%. Além da interpretação dos três primeiros componentes principais, foram estabelecidas relações desses com as classes de solo definidas pelo SiBCS. Ainda, a classificação numérica dos perfis foi procedida a partir do algoritmo OSACA, utilizando os dados espectrais como base. A relação entre a classificação do SiBCS e a classificação numérica, foi determinada pelo índice de Informação Mútua Normalizada (IMN) e o Coeficiente de Incerteza (U). Foram encontradas correlações significativas entre os escores dos componentes principais e a areia (0,78), a argila (-0,74), a cor do solo e o teor de Al (0,73). A representação gráfica dos componentes principais e sua interpretação visual indicou diferenças no comportamento espectral das classes de solo, principalmente entre os Argissolos e as demais classes. Já a classificação numérica dos perfis, com base nos espectros dos solos, obteve valores para os índices de informação mútua normalizada e coeficiente de incerteza de 0,74 e 0,64, respectivamente. Esses valores indicam que a classificação numérica possui boa relação com a estabelecida pelo SiBCS, sendo capaz, por exemplo, de distinguir Argissolos de classes como Latossolos e Nitossolos. Além disso, observou-se que tal técnica não é capaz de diferenciar Latossolos e Nitossolos Vermelho férricos; no entanto, Cambissolos foram agrupados corretamente. A técnica evidenciou-se eficiente, demonstrando sua aplicabilidade em processos de classificação de solo.

Considering that information from soil reflectance spectra is underutilized in soil classification, this paper aimed to evaluate the relationship of soil physical, chemical properties and their spectra, to identify spectral patterns for soil classes, evaluate the use of numerical classification of profiles combined with spectral data for soil classification. We studied 20 soil profiles from the municipality of Piracicaba, State of São Paulo, Brazil, which were morphologically described and classified up to the 3rd category level of the Brazilian Soil Classification System (SiBCS). Subsequently, soil samples were collected from pedogenetic horizons and subjected to soil particle size and chemical analyses. Their Vis-NIR spectra were measured, followed by principal component analysis. Pearson's linear correlation coefficients were determined among the four principal components and the following soil properties: pH, organic matter, P, K, Ca, Mg, Al, CEC, base saturation, and Al saturation. We also carried out interpretation of the first three principal components and their relationships with soil classes defined by SiBCS. In addition, numerical classification of the profiles based on the OSACA algorithm was performed using spectral data as a basis. We determined the Normalized Mutual Information (NMI) and Uncertainty Coefficient (U). These coefficients represent the similarity between the numerical classification and the soil classes from SiBCS. Pearson's correlation coefficients were significant for the principal components when compared to sand, clay, Al content and soil color. Visual analysis of the principal component scores showed differences in the spectral behavior of the soil classes, mainly among Argissolos and the others soils. The NMI and U similarity coefficients showed values of 0.74 and 0.64, respectively, suggesting good similarity between the numerical and SiBCS classes. For example, numerical classification correctly distinguished Argissolos from Latossolos and Nitossolos. However, this mathematical technique was not able to distinguish Latossolos from Nitossolos Vermelho férricos, but the Cambissolos were well differentiated from other soil classes. The numerical technique proved to be effective and applicable to the soil classification process.

O sensoriamento remoto representa um importante potencial na avaliação do ambiente, contudo, ainda existe a necessidade de entender melhor as relações entre atributos do solo e dados espectrais. O objetivo do trabalho foi analisar descritivamente o comportamento espectral de alguns perfis de solos da região de Piracicaba, Estado de São Paulo, utilizando o espectrorradiômetro de laboratório (400 a 2500 nm). Procurou-se ainda, avaliar as relações entre energia eletromagnética refletida com atributos químicos, físicos e mineralógicos dos solos, verificando as variações espectrais das amostras ao longo dos perfis e suas relações com classificação e discriminação dos solos. Observou-se que solos mais arenosos refletiram mais, com curvas espectrais de aspecto ascendente, ao contrário dos solos argilosos. A banda centrada em 1900 nm discriminou solos com mineralogia 2:1 dos de 1:1 e oxídicos. Foi possível detectar a presença de caulinita, gibbsita e dos óxidos de ferro (hematita e goethita) presentes nos solos pelos aspectos descritivos das curvas, feições de absorção e intensidade de reflectância; e que existe uma relação entre níveis de intemperismo e informações espectrais. A avaliação dos dados espectrais de amostras dos horizontes superficiais e subsuperficiais permitiu caracterizar e discernir a variabilidade analítica do perfil, auxiliando na discriminação e classificação dos solos.

Remote sensing has a high potential for environmental evaluation. However, a necessity exists for a better understanding of the relations between the soil attributes and spectral data. The objective of this work was to analyze the spectral behavior of some soil profiles from the region of Piracicaba, São Paulo State, using a laboratory spectroradiometer (400 to 2500 nm). The relations between the reflected electromagnetic energy and the soil physical, chemical and mineralogical attributes were analyzed, verifying the spectral variations of soil samples in depth along the profiles with their classification and discrimination. Sandy soil reflected more, presenting a spectral curve with an ascendant form, opposite to clayey soils. The 1900 nm band discriminated soil with 2:1 mineralogy from the 1:1 and oxidic soils. It was possible to detect the presence of kaolinite, gibbsite, hematite and goethite in the soils through the descriptive aspects of curves, absorption features and reflectance intensity. A relation exists between the weathering stage and spectral data. The evaluation of the superficial and subsuperficial horizon samples allowed characterizing and discriminating the analytical variability of the profile, helping to soil distinguishing and classification.

O objetivo deste trabalho foi avaliar o desempenho preditivo do submodelo espectral do modelo JONG, com a inserção de variáveis espectrais que considerassem a densidade de biomassa do dossel e as contribuições dos diferentes solos subjacentes. Índices calculados pela diferença e razão simples - entre as bandas 4 e 3, 4 e 5, 4 e 7, do sensor orbital ETM+/Landsat 7 - foram sugeridos para representar a contribuição espectral dos solos subjacentes e a influência das diferenças estruturais dos dosséis. A parametrização da componente espectral foi implementada por regressão linear múltipla e, em seguida, foi comparada aos dados de biomassa obtidos em campo. As variáveis espectrais que melhor expressaram as variações da disponibilidade inicial de forragem foram a fração solo (modelo linear de mistura espectral) e a razão entre as bandas 4 e 7. A componente espectral do modelo JONG, com a nova parametrização, apresenta sensibilidade para eliminar as influências do solo e dossel na disponibilidade inicial de biomassa e facilita a interpretação dos resultados, em razão da relação entre as variáveis espectrais selecionadas.

The objective of this work was to evaluate the predictive performance of the JONG model's spectral submodel, with the insertion of variables considering contributions of different underlying soils and canopy densities. Indices calculated by subtraction and simple ratio between 4 and 3, 4 and 5, 4 and 7 bands, of Landsat 7/ETM+ sensor - were suggested in order to represent the spectral contribution of the different underlying soils and the influence of canopy structural differences. The spectral component parameterization was implemented by multiple linear regression and, then, it was compared to the biomass data measured in the field. Spectral variables that better describe the variations of initial biomass availability and soil spectral contributions were the soil fraction (spectral mixture linear model), and ratio between 4 and 7 bands. The spectral component of the JONG model, with the new parameterization, showed sensibility in eliminating the canopy and soil influences in the biomass initial availability and, also, improved the interpretation of results due to the relationship between selected spectral variables.