Leaks from accidents or damage to pipelines that transport liquid petroleum hydrocarbons (PHC) such as gasoline and diesel are harmful to the environment as well as to human health, and may be hard to detect by inspection mechanisms alone when they occur in small volumes or persistently. In the present study, we aim to identify spectral anomalies in two plant species (Brachiaria brizantha and Neonotonia wightii) linked to contamination effects at different developmental phases of these plants. To do so, we used spectroscopy and remote sensing approaches to detect small gasoline and diesel leaks by observing the damage caused to the vegetation that covers simulated pipelines. We performed a contamination test before and after planting using gasoline and diesel volumes that varied between 2 and 16 L/m³ soil, in two experimental designs: (i) single contamination before planting, and (ii) periodic contaminations after planting and during plant growth. We collected the reflectance spectra from 35 to approximately 100 days after planting. We then compared the absorption features positioned from the visible spectral range to the shortwave infrared and the spectral parameters in the red edge range of the contaminated plants to the healthy plants, thus confirming the visual and biochemical changes verified in the contaminated plants. Despite the complexity in the indirect identification of soil contamination by PHCs, since it involves different stages of plant development, the results were promising and can be used as a reference for methods of indirect detection from UAVs (Unmanned Aerial Vehicles), airplanes, and satellites equipped with hyperspectral sensors.

A agricultura familiar representa um pilar fundamental da estrutura econômica e social do Brasil, sendo responsável por uma parte significativa da produção nacional de alimentos e desempenhando um papel crucial na promoção da segurança alimentar no País. Na Região Metropolitana do Vale do Rio Cuiabá e Entorno, este segmento é representado por cerca de 28.000 famílias residentes no meio rural, organizadas em 10.547 estabelecimentos agropecuários. Seu fortalecimento depende do apoio de políticas públicas capazes de compreender especificidades regionais e criar mecanismos eficientes de desenvolvimento e consolidação do setor. Neste contexto, a Empresa Mato-Grossense de Pesquisa, Assistência e Extensão Rural (EMPAER) e a Embrapa estabeleceram uma parceria para desenvolver uma plataforma digital capaz de integrar dados de diversas dimensões territoriais. O objetivo foi caracterizar a região de forma abrangente e, principalmente, disponibilizar ferramentas de análise inteligente que auxiliem na formulação de políticas públicas e na orientação de investimentos locais. A solução foi estruturada a partir do conceito de inteligência territorial estratégica, que prevê a organização temática de dados espaciais em cinco grandes quadros: natural, agrário, agrícola, de infraestrutura e socioeconômico. Espera-se que a plataforma possa ser utilizada para subsidiar ações de gestão territorial de organizações públicas e privadas por meio da tipificação dos municípios da região em função dos seus potenciais ambientais e produtivos, apoiando instituições de pesquisa, órgãos de planejamento, gestão e de assistência técnica rural.

Family farming is a cornerstone of Brazil's economic and social structure. It accounts for a significant portion of the national food production and plays a crucial role in promoting food security in the country. In the Metropolitan Region of the Cuiabá River Valley and Surroundings, this segment encompasses approximately 28,000 families residing in rural areas, organized into 10,547 agricultural establishments. The strengthening of family farming depends on its support by public policies which are capable of understanding regional specificities and creating effective mechanisms for the development and consolidation of the sector. In this context, a partnership was established between the Mato Grosso Company of Rural Research, Assistance, and Extension (EMPAER) and Embrapa, to develop a digital platform that integrates data across different territorial dimensions, aiming to characterize the region and, above all, provide analytical tools to support public policy and local investment decisions. This solution was based on the strategic territorial intelligence concept, which thematically organizes spatial data into five major frameworks: natural, agrarian, agricultural, infrastructural, and socioeconomic. We expect the platform to support territorial management efforts by public and private organizations by classifying the region’s municipalities according to their environmental and production potential. This, in turn, will assist research institutions and organizations responsible for rural planning, management, and technical assistance.