Wie kann Fernerkundung helfen, Waldbrände zu erkennen und zu verhindern?

Early detection is a major factor in controlling Wildfire spread. The second factor is response to this. The infamous CampFire event in Paradise, California was first noticed at 6:30 but not reported to the local fire authorities until 8:20 am. Actual containment action came even later. Rapidly spreading Wildfires, such as the August 8 Lahaina, Maui, cause horrific loss of life and property. The lack of early detection and notification of the people affected are heart-breaking.

- Leveraging remote sensing, I actively monitor wildfire-prone areas, ensuring rapid detection and response. - My expertise in image processing aids in interpreting data to discern subtle signs of wildfires. - Collaborating with emergency services, I help strategize effective containment measures. - Through continuous professional development, I refine my skills to enhance fire detection accuracy. - My work not only detects but also aids in preventing the spread of wildfires, safeguarding ecosystems.

Fire is easier to map if using highly temporal dataset such as MODIS or VIIRS which capture data everyday comlared to Landsat ot Sentinel-2. Using burn ratio such as NBR, you can threshold the fire using certain value.

La teledetección juega un papel vital en la detección y prevención de incendios forestales, permitiendo monitorear vastas áreas en casi tiempo real. Los sensores infrarrojos y térmicos son capaces de identificar fuentes de calor y columnas de humo, alertando de incendios en etapas tempranas. Estos datos se procesan y transmiten a agencias de emergencia, mejorando la respuesta y la planificación de evacuaciones. Además, la teledetección complementa otros métodos, como reportes humanos o sensores terrestres, proporcionando una cobertura más amplia y efectiva para la prevención de incendios.

This is a wonderful use-case for Remote Sensing using Satellites, Aircraft, Drones, In-place ground sensors, etc. Space and aerial applications have been in practice for quite a while already and the availability, technology and ability to process and use the data quickly is improving. For example, manned aircraft are in the air during and after thunder storms and scan entire states in a flight looking for lightening strikes in many states. Thousands of enlarged fires are extinguished each year with this method. Drones are currently in used during and post active fire events to detect movement of fire line as well as flareups in areas that were thought extinguished. Thermal and SWIR sensors are the most common sensors currently

In my experience, remote sensing is pivotal for wildfire management. By analyzing satellite data, I've helped pinpoint fire outbreaks before they escalate. This proactive approach is crucial for deploying resources efficiently and safeguarding vulnerable ecosystems from extensive damage.

Manned aircraft and long endurance drones are showing themselves very effective in fire monitoring during the night while the fire crews and equipment are resting. This data captured at night is made into a specific map formats for the fire crews early in the morning to understand where the fire is as they send out crews in the morning. TFR's are in place during fires, so the fire airspace manager is in charge of the airspace and these operations within the TFR are not FAA managed.

Remote sensing tracks wildfires by capturing infrared radiation, detecting heat sources, and monitoring smoke plumes via satellites like Landsat or Sentinel-2. Indicators include sudden increases in temperature in specific areas, visible flames, and the emergence of smoke columns. These anomalies, especially in vegetated regions, signal potential fire outbreaks. Remote sensing also identifies fire scars post-blaze, aiding in damage assessment and ecosystem recovery monitoring. Real-time observations facilitate timely intervention, enabling authorities to prioritize firefighting efforts, safeguard communities, and mitigate environmental impacts caused by wildfires.

1/2: Agree with Daniel especially the long-enduring fixed-wing drones because copter drones typically suffer from speed and endurance. Manned-aircraft emmits lots of CO2e. For example, it's worth noting that a traditional DHC-2T aircraft consumes nearly 4,000 liters of fuel to provide reconnaissance over one million hectares (or 10,000 km2), resulting in an emission of ~9,885 kg (less than 10 tons) of Carbon Dioxide equivalent (CO2e). In stark contrast, a fixed-wing drone with fuel injection tractor propeller, produces a mere 21.5 kg of CO2e for the same area, significantly reducing its environmental footprint. A DHC-2T can't fly 30+ hours straight and can't fly into smokes or at night. Satellite imaging qualities are coarse,

2/2: low resolution due to high altitude, have limited frequency, large volume datasets, slow processing, prone to cloud blockage and smokes, passing overhead once or twice a day, limited flexibility and availability, dependence on spectral radiance, reduced temperature tensitivity, conversion challenges and practical limitations, and expensive. According to LAND Info satellite images can go up to $34 US per square kilometer plus additional fees for post processing (i.e. GeoEye-1 satellite images cost $25 US/sq.km if minimum order quantity is met).

Satellite images aid in early wildfire identification and prediction by detecting smoke plumes, heat signatures, and vegetation changes. Infrared sensors spot thermal signatures, revealing active fires through smoke and clouds. Heat maps highlight areas with rising temperatures, indicating potential wildfires. Monitoring vegetation health identifies fire-prone regions, while real-time imagery tracks fire growth and weather conditions. This data contributes to early warning systems and facilitates effective response, minimizing damage and protecting lives. With SatSure's KaleidEO capability of onboard processing, the live fire updates can be provided to first responders & local communities.

La banda SWIR en sensores como Landsat y Sentinel-2 es esencial para mapear incendios debido a su capacidad para detectar la humedad en la vegetación y el suelo, incluso en presencia de humo. Esto permite evaluar con precisión la gravedad del incendio y el área quemada, así como los cambios en la vegetación. Además, comparar datos antes y después del incendio ayuda a medir la recuperación y resiliencia del ecosistema. Esta información es crucial para planificar la rehabilitación, compensar daños y diseñar estrategias de mitigación efectivas, proporcionando una visión detallada del impacto y facilitando una gestión ambiental más informada y proactiva.

As a remote sensing professional, I harness advanced technology to map wildfires. My expertise in interpreting satellite data aids in early detection, enabling swift action. Through meticulous analysis, I contribute to effective disaster management and ecological restoration, ensuring a safer environment.

With our fixed-wing drones equipped with Overwatch Imaging sensors, fire mapping is a click away. We focus on early detection of hotspots as small as 10'x10', providing real-time heat detection displayed on a user interface with geolocated imagery layered over Google Earth terrain maps. Within 5min, a mosaic is generated, stitching image data in-flight to create a single, multispectral composite. 10min, Fire Mapper outputs are generated, processing image data to produce a transfer-optimized map with vector point polygons delineating fire boundaries and heat intensity. Within 15min, a publication-ready map is created by operators using Overwatch and GIS tools, ensuring accuracy and transfer to the ground within 1/2hr of the initial fly-over.

Due to the SWIR being sensitive to surface and canopy moisture, the addition of this spectral band on sensors such as Landsat and Sentinel-2 make these useful sensors for fire scar mapping, aided by the fact that this band range is less sensitive to small particles (smoke plumes). There is also a correlation between spectral change and burn severity, however this can be saturated and is dependent on accurate baselining. As with all multispectral analysis, this is dependent on cloud and haze. There are applications of SAR to fire mapping, however this is not as straightforward and requires more expert guidance.

In my experience, remote sensing is pivotal for wildfire management. By analyzing data trends, I've developed models that predict fire risks with high accuracy. This proactive approach enables efficient resource allocation, ensuring rapid response and minimizing potential damage.

La predicción de incendios implica cruzar más de una fuente de información espacial para determinar las zonas más propensas a tener incendios forestales, estas áreas deben ser compartidas a través de mapas con las autoridades locales para construir estrategias de prevención, reacción y mitigación. Una forma de entender cuales son esas áreas potenciales de incendios son aquellas en donde el contenido de agua en el suelo o humedad del suelo sea muy baja, representando algún mínimo histórico junto con una anomalía o pico de alta temperatura. Entendiendo cuando estos dos datos se encuentran en un área especifica nos dará indicios de zonas potenciales

Wildfires can be predicted by monitoring vegetation health, moisture content, and thermal anomalies. Indices like NDVI analyze vegetation vigor and dryness, crucial for fire risk evaluation. Thermal infrared sensors detect temperature changes, identifying hotspots in drought-affected areas prone to ignition. Additionally, monitoring weather patterns, terrain characteristics, and historical fire data aids in predictive modeling. Integrating these factors through satellites like Landsat or Sentinel-2 enables the creation of fire risk maps, helping authorities anticipate fire-prone regions. This proactive approach enhances preparedness, allowing for preemptive measures to mitigate potential wildfire outbreaks.

Forest fire often happen in dried vegetation. Using moisture indices such as NDMI and MNDWI, you could quantify the amount of water in the plant. Adding neigborhood analysis, it will identify the cluster on which forest fire have higher potential.

Detecting and preventing wildfires is one of the well-known and widely used applications of remote sensing. Thermal imaging satellites like NASA's MODIS, VIIRS, and ESA’s Sentinel-3 provide crucial data for detecting active wildfires through real-time monitoring. Additionally, higher spatial resolution multispectral and hyperspectral sensors onboard commercial and public satellites aid in fire behaviour modelling, post-fire assessment, and resource allocation, which are vital for prevention. ESA’s Copernicus Emergency Management Service (EMS) and NASA’s Fire Information for Resource Management System (FIRMS) platforms integrate data from multiple satellites and play a significant role in wildfire detection and prevention.