1. Introduction

Environmental law enforcement agencies face the challenge of acting effectively and in a timely manner to curb actions that violate current legislation. Regarding wildfires and agricultural burning, remote sensing data enables enforcement agents to detect fire hotspots, helping prevent fire spread and allowing the delineation of burned areas for post-incident accountability.

Beyond large-scale fires, in the state of Mato Grosso do Sul, Brazil, some landowners employ fire to eliminate residual vegetation left from deforestation or for pasture clearing. In these cases, biomass is arranged into small piles or linear windrows for burning and later incorporated into the soil. However, Article 58 of Federal Decree No. 6.514/2008 classifies as an environmental infraction the “use fire in agro-pastoral areas without prior authorization from the competent authority or in contravention of the authorization granted”, punishable by a fine of BRL 3,000 per hectare or fraction thereof if no permit has been issued.

As the state-level agency responsible for environmental enforcement and management, the Environment Institute of Mato Grosso do Sul (IMASUL, in Portuguese) is tasked with identifying unauthorized burnings, including windrows, piles, native pasture, and wildfires, and take appropriate administrative sanctions against violators. To achieve this, continuous monitoring of the entire 357,125 km² territory of Mato Grosso do Sul is required—an effort made feasible only through remote sensing data. However, the current tools available pose limitations that challenge law enforcement, such as:

• Spatial resolution: Sentinel-2 imagery is commonly used for burn monitoring due to its free access, 5-day revisit time, and shortwave infrared bands ideal for fire detection. Yet, with a 10-meter pixel resolution, it fails to capture the smaller-scale piles and windrows used in these burnings.

• Temporal resolution: The Visible Infrared Imaging Radiometer Suite (VIIRS), with a spatial resolution of 375 meters, is typically used for active fire detection. However, its 12-hour revisit cycle results in significant temporal gaps, given that windrow fires can last from just a few minutes to a few hours, thus often evading detection. Furthermore, remnants of burning may be quickly incorporated into the soil, requiring prompt enforcement action before all physical evidence is lost.

To address these constraints, IMASUL’s Geoprocessing Unit (UNIGEO) has developed an automated enforcement system that integrates remote sensing techniques using Geostationary Operational Environmental Satellites (GOES) for fire detection and PlanetScope’s very high spatial resolution daily imagery for delineating burned areas.

2. Workflow

The GOES-R Series Advanced Baseline Imager (ABI) generates a Fire/Hot Spot Characterization (FDC) product that assigns a fire mask to each pixel, identifying fire categories. Although the final product has a spatial resolution of 2 km, it is produced every 10 minutes for the Americas, yielding 144 scenes per day with less than 30 minutes latency—allowing near-real-time detection.

Using a Python script, daily layers of fire pixels are generated. These pixels undergo spatiotemporal aggregation during fire events to extract information such as the date and time of first detection and the number of scenes the fire mask was assigned to each pixel. The data is then consolidated into a single monthly vector layer.

Each fire event is then analysed using PlanetScope imagery (~3.7 m resolution), provided via a partnership with the Federal Police (Brazil+ Program). Imagery from before and after the fire event is manually interpreted to delineate the burned area. In cases involving dead vegetation remnants, the linear or dotted patterns characteristic of windrows or piles can be visually distinguished (Figure 1). Once vectorised, A Fire Alert Notification (FAN) is generated for each event, containing fire data and property identification based on Brazil’s Rural Environmental Registry (CAR, in Portuguese), which holds data on all rural properties.

Each FAN undergoes a second technical review to check for valid burn authorizations issued by IMASUL. In the absence of such authorization, the burned area is validated and an administrative violation notice is issued, holding the landholder legally accountable, especially when there is evidence of a causal link—i.e., when the burning clearly aligns with common agro-pastoral practices.

3. Limitations and future perspectives

Preliminary results indicate the proposed workflow is effective for detecting and enforcing regulations against windrow burning, despite the coarse spatial resolution of GOES FDC (2 km). However, some limitations remain:

• False positives: During the evaluation of GOES FDC fire events, false positives were observed, such as fire masks assigned to areas not validated via PlanetScope imagery (Figure 2), or anomalies caused by sunglint in solar farms or water bodies.

• Cloud cover and imagery availability: Despite PlanetScope’s near-daily coverage, dense clouds or thick smoke columns can block optical sensors, impairing fire detection and burned area mapping—specially during the rainy season or intense fire episodes. Given the short duration of windrow burning, even a few consecutive cloudy days can result in missed detections if the post-burn residues are rapidly incorporated into the soil.

• Lack of omission error quantification: Since the workflow begins with GOES FDC data, fire events not detected by this product are not analysed by technicians, making it difficult to quantify undetected windrow burning events.

The next phase involves ground-truth validation through on-site inspections by environmental agents. This step is crucial not only for improving enforcement effectiveness, but also to reinforce the credibility of public institutions responsible for protecting natural resources. Establishing a robust environmental monitoring system directly contributes to law enforcement and fosters accountability, promoting sustainable land use and aligning environmental protection with socioeconomic development.

References

Brasil, Decreto nº 6.514, de 22 de julho de 2008. Dispõe sobre as infrações e sanções administrativas ao meio ambiente, Diário Oficial da União, Brasília, DF, 23 jul. 2008. [Online]. Available: https://www.planalto.gov.br/ccivil_03/_ato2007-2010/2008/decreto/d6514.htm.

European Space Agency (ESA), Sentinel-2 User Handbook, ESA Standard Document, 2021. [Online]. Available: https://sentinel.esa.int/web/sentinel/user-guides/sentinel-2-msi.

GOES-R Algorithm Working Group and GOES-R Program Office, (2018): NOAA GOES-R Series Advanced Baseline Imager (ABI) Level 2 Fire/Hot Spot Characterization (FDC). [Data set]. NOAA National Centers for Environmental Information. doi:10.7289/V5X065CR [accessed 05 Jun 2025].

NASA/NOAA, Visible Infrared Imaging Radiometer Suite (VIIRS) Data, NASA Earth Observing System Data and Information System (EOSDIS), 2023. [Online]. Available: https://earthdata.nasa.gov/viirs.

Planet Team, Planet Application Program Interface: In Space for Life on Earth. San Francisco, CA: Planet Labs PBC, 2023. [Online]. Available: https://www.planet.com.