ABSTRACT Desertification is the degradation process caused by climatic conditions and human activities that results in loss of soil productivity and decline in vegetation growth in the long term. Several indices related to vegetation, soil and climate are used to monitor desertification, but few studies explore qualitative and quantitative aspects of indices on desertification on spatial and hierarchical scale. This study aims to identify and measure indices related to increased risk of desertification on global, local and hierarchical scales using multinomial logistic regression models. Images from TM, ETM+ and OLI sensor from 1997 to 2018 in the end of dry and rainy seasons were used to quantify NDVI, TGSI, albedo, temperature, aridity index, evapotranspiration and precipitation on global spatial scale (Irauçuba Centro Norte) and local spatial scale (Miraíma, Canindé, Irauçuba and Santa Quitéria). GISD was calculated by geometric mean of weighted indices and segmented into 8 classes of susceptibility to desertification (hierarchical scale). The results showed that the best models were obtained on local scale and for the end of the rainy season. Temperature proved to be the most important variable for increased risk of desertification on global, local and hierarchical scales. Therefore, the increase in the risk of desertification in the studied areas is due to human activities of deforestation, overgrazing and fire. These factors contributed to reduction of vegetation cover and increase in temperature, changing the microclimatic, which led to decline in precipitation and worsening of desertification. term TM ETM 199 201 NDVI TGSI albedo temperature index Norte Miraíma, Miraíma (Miraíma Canindé Quitéria. Quitéria . Quitéria) scale) season Therefore deforestation fire microclimatic 19 20 1 2

ABSTRACT Careful implementation of a filtration system is essential for maintaining the operation of an irrigation system. Failure to maintain a filtration system can have a negative eff ect on irrigation pressure and uniformity. To avoid this problem, it is important to clean the filters, which can be done either manually or automatically. Predicting the correct time to clean the filters helps maintain the pressure and efficiency of the system. The aim of this study was to model backwash pressure as a function of water quality and the filter inlet pressure load using artificial neural networks. The characteristics of the water were determined using sensors to measure the pH (hydrogen potential), turbidity, total dissolved solids (TDS), and temperature. A pressure transducer was used to quantify the drop in pressure and the need to clean the filters. To predict the need for cleaning the irrigation filters, a hydraulic structure was constructed that included a screen filtration system with a mesh size of 120, cleaned by backwashing. The need for cleaning estimated by the multilayer perceptron feedforward artificial neural networks with 2-4-1 architecture performed well in modelling the temporal evolution of the pressure load in the screen filtration system (120 mesh), whereas adjusting the pressure load based on the water quality characteristics (pH, turbidity, total dissolved solids and temperature) performed poorly. uniformity problem automatically hydrogen potential, potential , potential) turbidity TDS, TDS (TDS) temperature 120 backwashing 241 2 4 1 2-4- (12 mesh, mesh) pH, (pH poorly (TDS 12 24 2-4 (1 2- (

ABSTRACT Knowledge of soil water dynamics is essential for establishing appropriate methods of irrigation management. Water dynamics in unsaturated soils is a complex process that can be explained by the Richards equation. As this is a non-linear differential equation, there is no analytical solution, but requires the use of the finite element method, for example, to obtain solutions, where simulations using numerical modelling make it possible to predict the the flow of water from the soil. As such, the aim of this study was to evaluate a 2D numerical model in simulating water distribution and wet bulb formation resulting from a subsurface irrigation system, in addition to validating the generated model. The Pearson correlation coefficient (r), the coefficient of determination (R2) and the root-mean-square error (RMSE) were calculated. For each treatment, both during and after irrigation, the model showed a small relative error, high values for R2 and a positive correlation with the field data. It was concluded that the model is applicable to the design and management of subsurface irrigation systems, varying the installation depth of the drip tube, the spacing between emitters and the soil moisture, giving good results for the various simulated scenarios. equation nonlinear non linear solution method example solutions such D system r, r , (r) R (R2 rootmeansquare root mean square RMSE (RMSE calculated treatment data systems tube moisture scenarios (r (R

ABSTRACT Understanding organic carbon and predominant humic fractions in the soil allows contributes to soil quality management. Conventional fractionation techniques require time, excessive sampling, and high maintenance costs. In this study, predictive models for organic carbon in humic substances (HS) were evaluated using hyperspectral data as an alternative to chemical fractionation and quantification by wet digestion. Twenty-nine samples of Neossolos Flúvicos (Fluvents) - A1, and 36 samples of Cambissolos (Inceptisols) - A2 were used. The samples were also analyzed jointly, creating a third sample group - A1&A2. Untransformed spectral reflectance factors were obtained using the FieldSpec Pro FR 3 hyperspectral sensor (350–2500 nm). Pre-processing techniques were employed, including Savitzky–Golay smoothing and first- and second-order derivative analysis. After selecting variables using the Backward method, which removes spectral variables that are not statistically significant for the regression. Estimation models were built by Principal Components Regression (PCR) and Partial Least Squares Regression (PLSR). The spectral data were evaluated individually for soil classes A1 and A2, and jointly for A1&A2. The PLSR was more efficient than PCR, especially for the estimation models that used the first derivative of reflectance employing the three sample groups. For samples of A1, the best estimate was seen for humic acid (RPD = 6.09) and humin (RPD = 2.38); for A2, the best models estimated the OC in fulvic acid (RPD = 2.35) and humin (RPD = 2.51); and for the joint spectral data (A1&A2), the prediction was robust for humin only (RPD = 2.01). The most representative wavelengths were observed using the first derivative with PLSR and PCR, centred on the region between 1600 and 1800 nm. The first-derivative of reflectance calculated more-robust predictive models using PLSR than PCR. The best predictions occurred for organic carbon associated with humic acid in Neossolos Flúvicos, with fulvic acid in Cambissolos, and with humin in both soil classes. management time sampling costs study HS (HS digestion Twentynine Twenty nine Fluvents (Fluvents A Inceptisols (Inceptisols A1A2 AA A1&A2 350–2500 3502500 350 2500 (350–250 nm . nm) Preprocessing Pre processing employed SavitzkyGolay Savitzky Golay secondorder second order analysis method regression PCR (PCR PLSR. (PLSR) groups RPD 6.09 609 6 09 2.38 238 2 38 2.38) 2.35 235 35 2.51 251 51 2.51) A1&A2, , (A1&A2) 2.01. 201 2.01 01 2.01) 160 180 firstderivative morerobust A1A A1&A 350–250 350250 250 (350–25 (PLSR 6.0 60 0 2.3 23 2.5 25 5 (A1&A2 20 2.0 16 18 350–25 35025 (350–2 6. 2. (A1&A 1 350–2 3502 (350– 350– (350 (35 (3 (

Abstract Plant community succession is generally approached with phytosociological methods, but field surveys are time-consuming, expensive, and limited to several of sites. Remote sensing offers an efficient and economical way to analyze vegetation on large extensions and in inaccessible areas. Most studies addressing remote sensing and tree community succession refer to forest physiognomies. We investigated whether structural changes that occur in non-forest physiognomies are identified by multispectral sensor images (OLI-Landsat). Thirteen 0.1-ha plots were set up in Caatinga fragments aging 10-15, 20-25, 30-35, 40-45 and >50 years to calculate the total density of individuals (TD), mean canopy height (H), total basal area (G) and total aboveground biomass (AGB). We performed correlation analyses between these structural descriptors and eight remote sensing variables (reflectance data and spectral indices) obtained from Landsat images at the end of the rainy season and during the dry season. Blue and short-wave infrared reflectances were negatively correlated with mean height, basal area and biomass, regardless of the analyzed scene (coefficients between -0.58 and -0.79). The litter layer (a non-photosynthetic vegetation component) and the soil exposure are important factors influencing the spectral data. methods timeconsuming, timeconsuming time consuming, consuming time-consuming expensive sites areas nonforest non OLILandsat. OLILandsat OLI . (OLI-Landsat) 0.1ha 01ha ha 0.1 0 1 1015, 1015 10 15, 15 10-15 2025, 2025 20 25, 25 20-25 3035, 3035 30 35, 35 30-35 4045 40 45 40-4 50 >5 TD, TD , (TD) H, H (H) G (G AGB. AGB (AGB) reflectance indices shortwave short wave coefficients 0.58 058 58 -0.5 0.79. 079 0.79 79 -0.79) a nonphotosynthetic photosynthetic component (OLI-Landsat 1ha 01 0. 101 10-1 202 2 20-2 303 3 30-3 404 4 40- 5 > (TD (H (AGB 0.5 05 -0. 07 0.7 7 -0.79 10- 20- 30- -0 -0.7 -

RESUMO O objetivo deste trabalho foi avaliar os teores assimilados de elementos minerais, características de produtividade e qualidade do fruto de melão amarelo ‘Goldex’ fertirrigado com diferentes doses de nitrogênio e potássio em dois anos de cultivo na região da Chapada do Apodi-CE. O delineamento foi em blocos ao acaso em esquema fatorial 4x3 com quatro doses de nitrogênio (0%, 50%, 100%, 150% da dose recomendada) e três doses de potássio (0%, 100%, 150% da dose recomendada). Na parte aérea do melão, os maiores níveis de adubação nitrogenada (N Fert.) e potássica (K Fert.) proporcionaram um aumento do teor assimilado de nitrogênio (N) até 48 DAT e redução do teor assimilado de potássio (K) no final do ciclo (62 DAT). A produção máxima de massa seca da parte foi de 3,23 t ha−1 com uma adubação de 150 e 100 kg ha−1 de N e K, respectivamente. A produtividade de fruto comercial média obtida nos dois anos de cultivo foi 34,68 t ha−1 chegando a um valor máximo de 40,28 t ha−1 em adubação de 150 kg ha−1 de N e K. O teor de sólidos solúveis totais aumentou em função do aumento da N Fert. e K Fert. apresentando máximo valor 8,07 °Brix. Os modelos indicaram que o fator K Fert. foi determinante no aumento desta variável. Em futuros estudos é necessário aumentar as concentrações dos dois fatores a fim de otimizar a viabilidade máxima da produtividade e °Brix.

ABSTRACT The objective of this study was to evaluate the assimilated contents of mineral elements, yield characteristics and fruit quality of ‘Goldex’ yellow melon fertigated with different doses of nitrogen (N) and potassium (K) in two years of cultivation in the region of Apodi Plateau-CE. The design was randomized blocks in a 4x3 factorial scheme with four N doses (0%, 50%, 100%, 150% of the recommended dose) and three K doses (0%, 100%, 150% of the recommended dose). In the shoots of the melon plant, the highest levels of N (N Fert.) and K (K Fert.) fertilization promoted an increase in the assimilated N content up to 48 DAT and a reduction in the assimilated K content at the end of the cycle (62 DAT). The maximum shoot dry mass production was 3.23 t ha−1 with a fertilization of 150 and 100 kg ha−1 of N and K, respectively. The average marketable fruit yield obtained in the two years of cultivation was 34.68 t ha−1, reaching a maximum value of 40.28 t ha−1 under 150 kg ha−1 N and K fertilization. Total soluble solids increased as a function of the increase in N Fert. and K Fert., with a maximum value of 8.07 °Brix. The models indicated that the K Fert. factor was decisive in the increase of this variable. In future studies it is necessary to increase the concentrations of the two factors in order to optimize the maximum viability of yield and °Brix.

RESUMO Os métodos capacitivos de determinação da umidade do solo apresentam grande praticidade e aplicabilidade no meio agrícola, porém sofrem influência do tipo de solo, temperatura e salinidade. Nesse trabalho, teve-se como objetivo a verificação do desempenho do Sensor Capacitivo de Umidade em Meios Porosos submetido a meios salinos. O sensor avaliado foi desenvolvido na Universidade Federal do Ceará e fornece medições e frequência elétrica relativas à umidade do solo. O sensor capacitivo de meios porosos foi submetido a soluções salinas, em diferentes concentrações de cloreto de potássio (KCl), e observou-se que os eletrodos do sensor apresentam sensibilidade à salinidade, quando inserido em soluções aquosas com salinidade de até 4 dS/m de condutividade elétrica. Como alternativa, foram testados ajustes de seu circuito RC (resistor-capacitor) como alternativa para atenuar o efeito da salinidade nas medições, quando foi possível gerar leituras em frequência elétrica de kHz a MHz relativos à umidade do solo. Posteriormente foram feitos testes em solo de textura arenosa em diferentes condições de umidade e salinidade. Não foram observadas diferenças significativas quanto à utilização de diferentes resistores no circuito RC montado para atenuação do efeito da salinidade nas medições realizadas pelo sensor, seja em solução ou em solo.

ABSTRACT Capacitive methods for determining soil moisture are extremely practical and easily applied in the agricultural environment, but are influenced by temperature, salinity and the type of soil. In this study, the aim was to verify the performance of the Capacitive Moisture Sensor for Porous Media when subjected to saline media. The sensor under evaluation was developed at the Federal University of Ceará, and provides measurements and electrical frequencies related to soil moisture. The capacitive sensor for porous media was subjected to saline solutions with different concentrations of potassium chloride (KCl), when it was seen that the sensor electrodes appear sensitive to salinity when inserted in saline aqueous solutions with an electrical conductivity of up to 4 dS/m. Adjustments to the RC (resistor-capacitor) circuit were tested as an alternative to lessen the effect of salinity on the measurements, and it was possible to generate readings related to soil moisture in electrical frequencies ranging from kHz to MHz. Tests were then carried out in a sandy soil under different conditions of moisture and salinity. No significant differences were seen when using different resistors in the RC circuit that was constructed to lessen the effects of salinity on the measurements taken by the sensor, whether in solution or in the soil.

RESUMO Os remotely piloted aircrafts - RPAs, estão firmados no mercado como poderosa ferramenta de aquisição de imagens aéreas, facilitando os mapeamentos para diversos fins. Assim, objetivou-se avaliar a qualidade dos processos a partir da geração de produtos digitais georreferenciados com diferentes quantidades de pontos de controle (GCPs), utilizando Controle Estatístico de Processos (CEP) e Padrão de Exatidão Cartográfico (MAS) em ortomosaico produzido com imagens de RPA. Foi utilizado um RPA multirrotor para aquisição de imagens aéreas em área de 2 hectares. Posteriormente foi gerado ortomosaico por meio do software PhotoScan, georreferenciado com oito, cinco e três GCPs (Pontos de controles). Os erros de posicionamento foram submetidos ao CEP para avaliar a qualidade dos processos e os ortomosaicos foram qualificados pelo MAS. Os resultados são promissores, tendo em vista os erros de posicionamento menores que 0,1 m nos ortomosaicos gerados, classificados como padrão “A” de Exatidão Cartográfica. Os Controles Estatísticos de Processos demonstraram níveis aceitáveis de erros, indicando grande acurácia para levantamentos desta natureza. As elevadas precisões obtidas nos mapeamentos indicam que imagens aéreas obtidas por meio de RPAs podem ser utilizadas em levantamentos topográficos, contanto que se respeitem os padrões de erros e controle de processos, atestando a qualidade dos resultados.

ABSTRACT Remotely piloted aircraft (RPA) are established in the market as a powerful tool for acquiring aerial images and facilitating mapping for various purposes. The aim of this study was to evaluate the quality of processes originating from the generation of georeferenced digital products employing a differing number of ground control points (GCP), using Statistical Process Control (SPC) and Mapping Accuracy Standards (MAS) in an orthomosaic produced with images from an RPA. A multirotor RPA was used to acquire aerial images over an area of 2 hectares. An orthomosaic was later generated using the PhotoScan software, and georeferenced with eight, five and three GCP (ground control points). Positioning errors were submitted to SPC to evaluate the quality of each process, and the orthomosaics were qualified by MAS. The results are promising, in view of the positioning errors of less than 0.1 m in the generated orthomosaics, which are classified as Mapping Accuracy Standards class ‘A’. Statistical Process Control showed acceptable levels of error, indicating the high accuracy of surveys of this nature. The precision obtained when mapping shows that aerial images obtained by means of RPA can be used in topographic surveys as long as error standards and process control are observed, attesting to the quality of the results.

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 Os dados de sensoriamento remoto são essenciais para se avaliar processos de natureza dinâmica em sistemas aquáticos continentais, tais como a eutrofização e o aumento da concentração de sedimentos suspensos. Portanto, objetivou-se desenvolver modelos para estimar as concentrações de clorofila-a a partir de dados de sensoriamento remoto em águas continentais da região semiárida brasileira. A área de estudo corresponde ao reservatório Orós, localizado no estado do Ceará. O desenvolvimento dos modelos baseou-se em medidas realizadas em 20 pontos amostrais. Foram coletadas amostras de água no reservatório para a análise das seguintes variáveis: i) clorofila-a, condutividade elétrica, pH, turbidez; ii) medições ópticas in situ da transparência da água e da radiância espectral. As medidas de radiância foram realizadas utilizando-se espectrorradiômetro ASD FieldSpec®3 Hi-Res. Posteriormente, os dados espectrais foram transformados em reflectância e utilizados para testar o desempenho de diversos modelos de estimativa de clorofila-a disponíveis na literatura. Os resultados indicaram que para o modelo de três bandas o valor máximo do coeficiente de determinação (R2) de 0,88 foi obtido utilizando-se as bandas espectrais: λ1 = 660 nm, λ2 = 690 nm, e λ3 = 717 nm. O modelo de duas bandas espectrais apresentou melhor desempenho (R2= 0,87) para as bandas espectrais λ1 = 660 nm e λ2 = 690 nm. Os modelos apresentaram um erro médio absoluto de 5,35 e 5,00 µg L-1, respectivamente para os modelos de três e duas bandas espectrais. Os modelos desenvolvidos são confiáveis, indicando que esta variável limnológica pode ser quantificada a partir dos dados de sensoriamento remoto de campo com elevado grau de confiabilidade.

ABSTRACT Remote-sensing data are essential to evaluate dynamic processes such as eutrophication and increases in the concentration of suspended sediments in continental aquatic systems. The aim of this study, therefore, was to develop models to estimate chlorophyll-a concentrations from remote-sensing data in continental waters of the Brazilian semi-arid region. The study area corresponds to the Orós reservoir, located in the state of Ceará. The models were developed based on measurements taken at 20 sampling points. Water samples were collected from the reservoir to i) analyse the chlorophyll-a, electrical conductivity, pH and turbidity; ii) take optical measurements in situ of water transparency and spectral radiance. Radiance measurements were carried out using an ASD FieldSpec®3 Hi-Res spectroradiometer. The spectral data were later transformed into reflectance values and used to test the performance of several models found in the literature for estimating chlorophyll-a. The results showed that for the three-band model, the maximum value for the coefficient of determination (R2), of 0.88, was obtained using the λ1 = 660 nm, λ2 = 690 nm and λ3 = 717 nm spectral bands. The model employing two spectral bands presented the best performance (R2 = 0.87) in the λ1 = 660 nm and λ2 = 690 nm bands. An absolute mean error of 5.35 and 5.00 µg L-1 was found for the three- and two-band models respectively. The developed models are reliable, showing that chlorophyll-a concentrations can be quantified from remote-sensing field data with a high degree of accuracy.

RESUMO A textura tem grande importância no manejo dos solos, pois influencia fortemente o comportamento físico-hídrico e químico dos solos. É necessário, portanto, a determinação de tal textura, sendo a razão de bandas espectrais, uma alternativa rápida e precisa para este fim. O objetivo deste trabalho foi avaliar o uso de dados espectrais, adquiridos pelo sensor aerotransportado ProSpecTIR-VS, com resolução espacial de 1 m, na seleção de duas bandas para composição de um Índice por Diferença Normalizada, que permita estimar os atributos texturais do solo, além de elaborar o mapa textural do solo na imagem. Foram coletadas 64 amostras em áreas inseridas no perímetro irrigado Jaguaribe-Apodi, que se localiza na Chapada do Apodi, Bacia do Baixo Jaguaribe, cujas classes predominantes são Cambissolos. As amostras foram coletadas em solo exposto, tendo como base as imagens hiperespectrais do sensor aerotransportado ProSpecTIR-VS. O Índice por Diferença Normalizada (NDI) foi construído, realizando-se todas as possíveis relações normalizadas de bandas e os melhores índices foram selecionados com base no coeficiente de determinação (R²). Os resultados mais promissores de R² foram obtidos na estimativa da areia, com as bandas 1045 e 1323 nm, com R² de 0.5. Os baixos valores de R² podem ser explicados pela interferência na resposta espectral por materiais que estavam na superfície do solo, como resto de cultura, cascalho e da vegetação. A elaboração do mapa de areia utilizando o melhor modelo resultou em 82.1% dos pixels com valores entre 20 e 60% de areia, enquadrando-se entre mínimo e máximo dos teores de areia das amostras de solos.

ABSTRACT Texture is of great importance in soil management, as it strongly influences the physical, hydraulic and chemical behaviour of soils. It is therefore necessary to determine texture, with the spectral band ratio being a fast and precise alternative method for this purpose. The aim of this study was to evaluate the use of spectral data, acquired by the ProSpecTIR-VS airborne sensor with a spatial resolution of 1 m, in selecting two bands for building a Normalised Difference Index that allows the textural attributes of the soil to be estimated, besides preparing a texture map of the soil in the image. Sixty-four samples were collected from several areas inserted in the Jaguaribe-Apodi irrigated perimeter, which is located in the Chapada do Apodi, in the Lower Jaguaribe Basin, where the predominant soil classes are Cambisols. The samples were collected from exposed soil, based on the hyperspectral images of the ProSpecTIR-VS airborne sensor. The Normalised Difference Index (NDI) was constructed, carrying out all possible normalised band ratios, with the best indices selected based on the coefficient of determination (R²). The most promising results for R² were obtained when estimating sand in the 1045 and 1323 nm bands, with an R² of 0.5. The low values for R² can be explained by interference in the spectral response from materials on the soil surface, such as crop residue, gravel and vegetation. Preparing the sand map using the best model resulted in 82.1% of the pixels having values between 20 and 60% sand, falling between the minimum and maximum sand content of the soil samples.

RESUMO O estudo minucioso de dados hiperespectrais pode ser um forte aliado para o diagnóstico nutricional de plantas e otimizam o manejo de insumos agrícola. Este estudo caracterizou as variações dos fatores de reflectância em folhas de algodoeiro (Gossypium hirsutum L.) da cultivar BRS 293, submetidas a diferentes níveis de adubação de N e K. Foram cultivadas 166 plantas submetidos a quatro doses de N e K, com vinte repetições e seis controles. Cada tratamento se referiu a um nível de adubação: 50, 75, 100 e 125% da quantidade recomendada para ambos macronutrientes em cada etapa do ciclo fenológico. O espectrorradiômetro utilizado em laboratório foi o FieldSpec Pro FR 3® com resolução espectral de 1 nm e cuja faixa de operação se estende de 350 a 2500 nm. Em ambos os tratamentos, a ACP permitiu identificar os comprimentos de onda agrupados em parâmetros como o brilho, a clorofila e a umidade das folhas. A adubação de N e K provocou alterações significativas nos fatores, onde a maior diferenciação entre as doses se deu aos 790 e 1198 nm. Os comprimentos entre 550 e 700 nm e em 1390 e 1880 nm se mostraram, respectivamente, as mais promissoras para explicar a variância dos níveis nutricionais de N e K sobre a cultura do algodoeiro.

ABSTRACT The detailed study of hyperspectral data that optimise the management of agricultural inputs can be a powerful ally in the nutrient diagnosis of plants. This study characterised variations in the reflectance factors of cotton leaves (Gossypium hirsutum L.) of the BRS 293 cultivar, submitted to different levels of N and K fertilisation. A total of 166 plants were submitted to four doses of N and K, with twenty replications and six controls. Each treatment represents one level of fertilisation: 50, 75, 100 and 125% of the recommended amount of both macronutrients at each stage of the phenological cycle. The spectroradiometer used in the laboratory was the FieldSpec Pro FR 3® with a spectral resolution of 1 nm and an operating range that extends from 350 to 2500 nm. In both treatments, PCA allowed wavelengths to be idenbtified grouped by such parameters as brightness, chlorophyll and leaf moisture. The N and K fertilisation caused significant changes in the factors, where the greatest difference between doses was seen at 790 and 1198 nm. The wavelengths between 550 and 700 nm and at 1390 and 1880 nm were, respectively, the most promising for explaining the variance in nutrient levels of N and K in cotton.

RESUMO Em virtude do crescimento exponencial no volume de dados considerados nas tomadas de decisões inteligentes, o sensoriamento remoto hiperespectral (SRH) tem indubitavelmente trazido maior domínio sobre os cultivos agrícolas porque ultrapassa o paradigma de pouca informação disponível sobre os alvos. Nesta revisão do estado da arte do SRH foram agrupadas visões complementares sobre o uso de sensores e técnicas analíticas na agricultura desta última década. Foram citadas tecnologias de ponta e as tendências de pesquisa associadas a cada nível de coleta de dados. Ainda há muito a avançar nas ciências agrárias, no entanto, os profissionais da agricultura de precisão estão devotados aos insights de aplicações valiosas com a maior disponibilidade de dados hiperespectrais. Neste sentido, esta revisão está organizada da seguinte maneira: A seção 1 contextualiza o leitor e conceitua fundamentos para o sensoriamento remoto. A segunda seção discorre sobre os tipos de sensores e suas resoluções. A seção 3 traz quatro subseções que apresentam aplicações recentes destas tecnologias segundo o nível de aquisição. Finalmente, a quarta seção oferece ao leitor a discussão sobre as tendências positivas alcançadas no manejo de vegetação, solos e corpos hídricos nos últimos dez anos, bem como as necessidades e desafios para a próxima década.

ABSTRACT In view of the exponential growth in the volume of data that is considered in intelligent decision-making, hyperspectral remote sensing (HRS) has, without doubt, brought greater dominance over agricultural crops as it goes beyond the paradigm of little information being available about the targets. In this review of the state of the art of HRS, complementary views on the use of sensors and analytical techniques in agriculture over the last decade are grouped together. State-of-the-art technologies, and research trends associated with each level of data collection are cited. There is still a long way to go in the agricultural sciences; however, specialists in precision agriculture are devotees of the valuable insights offered with the increased availability of hyperspectral data. In this respect, this review is organised as follows: Section 1 helps the reader to contextualise and conceptualise the basics of remote sensing; the second section discusses the types of sensors and their resolutions; section 3 presents four subsections that show recent applications of these technologies according to their level of acquisition; finally, the fourth section offers the reader a discussion on the positive trends achieved in managing vegetation, soils and waterbodies over the last ten years, as well as the needs and challenges of the next decade.

RESUMO Um dos procedimentos mais eficazes na avaliação de áreas degradadas tem sido o uso do sensoriamento remoto. Este trabalho objetivou avaliar a dinâmica temporal do NDVI e da precipitação pluviométrica na detecção de degradação dos recursos naturais em uma região semiárida do Brasil. A área estudada localiza-se a oeste do município de Tauá, estado do Ceará, com predomínio de floresta caatinga arbustiva. As informações de precipitação foram obtidas junto à FUNCEME. Foram adquiridas 10 imagens (estação seca) de uma série histórica de 27 anos (1985-2011) do sensor TM/LANDSAT5, posteriormente convertidas em reflectância de superfície por meio da extensão FLAASH/ENVI e obtidas os índices NDVI, segmentados em 6 classes conforme o uso e ocupação do solo. Os valores médios das classes de NDVI foram submetidos à análise estatística e confrontados pelo Teste T (p<0,05) e matriz de correlação de Pearson. Observou-se que nos anos com precipitação pluviométrica acima da média histórica (1985-1993 e 1996-2004) houve significativo acréscimo de áreas degradas representadas por baixo NDVI (entre 0 e 0,4), decorrentes do avanço de terras incorporadas à agricultura de subsistência. No entanto, em períodos de estiagem (1993-1996 e 2004-2011), constatou-se comportamento inverso, caracterizado pela regeneração natural do estrato arbustivo-arbóreo em decorrência do abandono das áreas agrícolas, comportamento evidenciado por incrementos de até 1.807% da classe de NDVI moderadamente alta (entre 0,6 e 0,8). Portanto, a dinâmica espaço-temporal do NDVI e da precipitação pluviométrica contribuíram para detecção de evidências do processo de degradação do bioma caatinga numa área no município de Tauá, estado do Ceará.

ABSTRACT One of the most effective procedures in the evaluation of degraded areas has been the use of remote sensing. The aim of this work was to evaluate the temporal dynamics of the NDVI and rainfall in detecting the degradation of natural resources in a semi-arid region of Brazil. The area under study is located to the west of the district of Tauá, in the State of Ceará, with a predominance of shrub-like caatinga forest. Rainfall data was obtained from FUNCEME. Ten images (dry season) were acquired from a 27-year historical series (1985-2011) from the TM/LANDSAT5 sensor, later converted to surface reflectance using the FLAASH/ENVI extension; NDVI indices were obtained and divided into six classes corresponding to land usage and occupation. The mean values of the NDVI classes were submitted to statistical analysis and compared by T-test (p<0.05) and the Pearson correlation matrix. It was found that in the years with rainfall above the historical average (1985-1993 and 1996-2004) there was a significant increase in degraded areas, represented by low values for the NDVI (between 0 and 0.4), due to more land being used for subsistence farming. However, during periods of drought (1993-1996 and 2004-2011), the opposite behaviour was seen, characterised by the natural regeneration of the woody stratum due to agricultural areas being abandoned; behaviour that was evidenced by increases of up to 1,807% in the moderately high class of the NDVI (between 0.6 and 0.8). The spatial and temporal dynamics of the NDVI and the rainfall therefore played a part in detecting evidence of the process of degradation of the caatinga biome in an area of the district of Tauá, in the State of Ceará.

RESUMO Devido à necessidade de monitoramento da tensão da água no solo de forma contínua, o método do perfil instantâneo é considerado trabalhoso, sendo necessário muito tempo e, principalmente, mão de obra na instalação e manutenção. O objetivo deste trabalho é avaliar a possibilidade de utilização de sensores capacitivos no método do perfil instantâneo em substituição aos tensiômetro em uma área do Perímetro Irrigado Baixo Acaraú. O experimento foi realizado em um ARGISSOLO VERMELHO-AMARELO Eutrófico. Os sensores foram instalados a 15; 30; 45 e 60 cm da superfície e alimentados por painéis fotovoltaicos, com gerenciador de energia para carregamento de baterias e fornecimento noturno de energia. Os registros dos sensores capacitivos foram coletados a cada cinco minutos e armazenados em placa de aquisição de dados. Dispondo-se das medidas simultâneas de umidade do solo obtidas pelos sensores, e do potencial total da água no solo, pela curva de retenção de água no solo, foi possível a determinação, para cada período, da condutividade hidráulica em função do conteúdo volumétrico de água, através da equação de Richards. Ao final do experimento pode-se concluir pela vantagem da utilização dos sensores capacitivos no método do perfil instantâneo como alternativa ao uso do tensiômetro. As principais vantagens do uso de sensores capacitivos foi a de tornar o método menos trabalhoso e possibilitar a leitura da umidade em maiores tensões nos solos de textura arenosa.

ABSTRACT Due to the need to monitor soil water tension continuously, the instantaneous profile method is considered laborious, requiring a lot of time, and especially manpower, to set up and maintain. The aim of this work was to evaluate the possibility of using capacitive sensors in place of tensiometers with the instantaneous profile method in an area of the Lower Acaraú Irrigated Perimeter. The experiment was carried out in a Eutrophic Red-Yellow Argisol. The sensors were installed 15, 30, 45 and 60 cm from the surface, and powered by photovoltaic panels, using a power manager to charge the battery and to supply power at night. Records from the capacitive sensors were collected every five minutes and stored on a data acquisition board. With the simultaneous measurement of soil moisture obtained by the sensors, and the total soil water potential from the soil water retention curve, it was possible to determine the hydraulic conductivity as a function of the volumetric water content for each period using the Richards equation. At the end of the experiment, the advantage of using capacitive sensors with the instantaneous profile method was confirmed as an alternative to using a tensiometer. The main advantages of using capacitive sensors were to make the method less laborious and to allow moisture readings at higher tensions in soils of a sandy texture.