Aplicação da Lei de Newcomb-Benford em dados de queimadas, desmatamento e precipitação pluvial no Estado do Maranhão

Abstract

The current technological transformation elevates data management to a central position in innovation and decision-making. Data, more than mere information, are strategic tools that, when organized and visualized, enable the analysis of complex phenomena. The accuracy and veracity of this data are crucial in a digital environment, and the concept of Big Data illustrates a dynamic system that impacts everything from environmental monitoring to precision agriculture. Despite its abundance, the correct interpretation and coherence of t his information are major challenges. The tripod of Data, Information, and Knowledge is the foundation of modern advances, driven by information technology. A fundamental analytical tool for ensuring data authenticity is the Newcomb-Benford Law, also known as the Law of the First Digit. This statistical concept describes a distribution pattern where smaller digits appear more frequently as the first digits in natural number sets. Originally used in accounting audits to detect fraud and manipulation, its sensitivity to small variations makes it valuable in various areas of data science, including environmental investigations. Natural phenomena, such as hydrological and geophysical processes, tend to follow the Benford distribution, allowing for the verificati on of the integrity of large sets of environmental data, such as earthquake records and river flow. In the context of Maranhão, where fires and deforestation are critical environmental challenges, often linked to agribusiness, satellite monitoring has been essential. Applying Benford's Law to these environmental data can help detect inconsistencies and manipulations, providing more accurate diagnoses of damage and aiding in the formulation of conservation strategies. Deforestation and fires directly impact local hydrology, altering the water cycle. Therefore, the aforementioned research sought to investigate the application of Newcomb-Benford's Law to rainfall, fires, and deforestation data in Maranhão, evaluating its effectiveness in verifying the authenticity of environmental information. Identifying patterns and anomalies will allow correlating the analyzed data with the observed impacts on the region's natural systems, contributing to more effective conservation strategies. The results achieved demonstrat ed that the precipitation data presented greater compliance with the Newcomb-Benford Law, which reinforces its natural origin and the little interference in its generation. In contrast, the fire data obtained from Google Earth Engine exhibited considerable deviations from the expected distribution, with the digits "2" and "3" predominating as the first digits, which may indicate structural biases in the measurement methods or the need for data collection revisions. Similarly, the deforestation data from Global Forest Watch also showed noticeable deviations, although statistical analyses using the Z-test and Kolmogorov-Smirnov test indicated that these data adhere to Benford's Law.