Application of spatial environmental indicators in the assessment of degradation potential of water resources in water basins.

Changes in land use have been occurring in a continuous and disorderly way in recent decades due to rapid population growth and the growing demand for food. These constant changes result in a series of harmful effects to the environment, especially to water resources, significantly changing their availability and quality. This study aims to evaluate the degradation potential of watersheds through an evaluation of some environmental indicators using arithmetic means to construct an index called in this research "index of potential environmental degradation" (IPED). To form the IPED, the hydrographic sub-basins of the Sorocabuçu River, located in the central west of the State of São Paulo, Brazil, comprised the study area. The results showed that most hydrographic sub-basins, that is, eight units, present degradation values ranging from moderate to very high, resulting mainly from low conservation values of forests plus a use destined to the planting of temporary cultures depending on good physical conditions. On the other hand, only one sub-basin showed a low degradation value. The methodology used for the development of the IPED is easy to apply and an effective tool for environmental analyses. It may contribute to studies and forms of planning and land use management aiming the conservation of water resources and protected areas and reduction of degradation.

Spectral detection of nematodes in soybean at flowering growth stage using unmanned aerial vehicles / Detecção espectral de nematóides na soja em estádio de florescimento por meio de veículos aéreos não-tripulados

ABSTRACT: Soybean is one of the main crop species grown in the world. However, there is a decline in productivity due to the various types of stress, including the nematodes Heterodera glycines and Pratylenchus brachyurus. The objectives were to determine the best spectral band for detecting H. glycines and P. brachyurus at the beginning of flowering (R1). Soil and root sampling was conducted at nine sampling sites in each of the five nematode-infested regions, totaling 45 sampling points. Flights were made at all regions using Phantom 4 Advanced, Sequoia and 14-band customized Sentera. For H. glycines, the red spectral band best explained the variability on soil and root nematode counts as well as the second stage of juveniles in soil. For P. brachyurus, Sentera RedEdge best explained the variability in root nematode counts and Sequoia NIR best explained soil juveniles. A multiple linear regression model using spectral data for detecting P. brachyurus and H. glycines improved R² compared to simple linear regressions. At flowering growth stage (R1), soybean spectral reflectance was associated with the number of H. glycines and P. brachyurus on soil and roots using low-cost and multispectral sensors.

RESUMO: A soja é uma das principais espécies de planta cultivadas no mundo. Todavia, perdas de produtividade são ocasionadas por vários tipos de estresses, incluindo os nematoides H. glycines e P. brachyurus. Como objetivo, buscou-se determinar a melhor banda espectral para a detecção do H. glycines e P. brachyurus com o uso de modelos de regressões lineares simples e definir um modelo matemático de regressão linear múltiplo para sua detecção, no início do florescimento (R1). Para isto, foram definidos nove pontos de coleta em cinco reboleiras, totalizando 45 pontos. As coletas foram feitas em um padrão específico de distâncias, de forma a ter amostras com tipos variados de populações de nematoides. Foram realizados voos com o Phantom 4 Advanced, Sequoia e Sentera sobre cada uma das reboleiras. O comprimento de onda do vermelho melhor explicou a variabilidade dos dados para H. glycines no solo e na raiz, bem como dos juvenis de segundo estádio no solo. Para P. brachyurus, a RedEdge da Sentera foi a que explicou melhor a variabilidade dos dados para nematoide na raiz e a NIR da Sequoia a que melhor explicou para juvenis no solo. Quando se utilizou um modelo matemático para a detecção do P. brachyurus e H. glycines, percebe-se uma grande melhora no R² e p-valor com relação às regressões lineares simples. No início da floração (R1), a refletância espectral da soja foi associada ao número de H. glycines e P. brachyurus no solo e nas raízes, usando sensores de baixo custo e multiespectrais.