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 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 (

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 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 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.