Wie kann man Fernerkundungsdaten nutzen, um Waldbrände zu verhindern?

Any information system that reads, manipulates, writes, manages and visualizes geospatial data is GIS. Geospatial data may be in the raster or vector format. Any other file format with geographic coordinates can be imported to GIS.

#GIS is the #GIFTED_EYE of Planet. Its the logical answer to hidden numerics inside the biosphere. Its is a book having earth's surface and upper atmosphere rythem notes. Coming to its defination, GIS is a set of rules that covers: 1.Gathering of Raw Earth information 2.Processing 3.Organization 4.Visualization Reinvention of tools and methodologies to address these 4 points is also GIS.

I'll mention two techniques: i) Thermal Imaging: Thermal infrared sensors on drones or satellites can detect heat signatures of wildfires before visible smoke appears enabling timely intervention. ii) Smoke detection: Studies have revealed that detecting smoke through satellite imagery is possible. The presence of smoke can be identified by utilizing specific image pre-processing and analysis techniques. As a result, remote sensing data can be used to monitor changes in atmospheric conditions, enabling us to locate areas at a higher risk of fires.

Es preciso resaltar que la PREVENECIÖN busca evitar que se generen riesgos por incendios forestales, sobre la base de datos de identificación de focos de calor, registro de incendios pasados, la caracterización de las especies forestales y la aplicación de herramientas de teledetección, nos permitan desarrollar politicas y programas para fortalecer la cultura de prevención con los actores territoriales y los sistemas de alerta temprana que coadyuven a gestionar los incendios forestales y retroalimetar permanentemente las politicas y acciones para prevenir y reducir los riesgos por incendios forestales

Remote sensing data can be invaluable in preventing wildfires through several means: -Early Detection: Identifies heat signatures and changes in vegetation patterns. -Monitoring Fuel Conditions: Tracks vegetation health, moisture content, and fuel loads. -Mapping Vulnerable Areas: Creates detailed maps based on terrain and historical data. -Fire Weather Forecasting: Enhances prediction of conditions conducive to wildfire spread. -Fire Behavior Prediction: Integrates data into models to predict wildfire behavior. -Post-fire Assessment: Evaluates damage, regeneration, and erosion risks for rehabilitation efforts.

You can use thermal remote sensing data that monitor the area more than daily like MODIS and VIIRS. This data can easily detech hotspot at any given moment.

By gaining more insights in the frequency, spread and intensity of fires either through post or active fire data, such as Modis, GoES, etc, we are able to plan, prepare and predict the behaviour of fires.

Optical data can be used in various ways to prevent wildfires. We can gather valuable information about the land cover, vegetation, and changes in the environment by analyzing these images. This data helps us identify areas with high fuel density, such as dense vegetation or dry grass, which are more prone to wildfires. We can also monitor vegetation health and moisture content, which can indicate the risk of fire ignition. With this information, we can implement proactive measures like targeted vegetation management, early warning systems, and strategic firebreak placement to prevent wildfires.

Optical remote sensing data can help prevent wildfires by detecting changes in vegetation health and monitoring potential fire risks. For example, satellite images can identify areas with dry vegetation or abnormal heat patterns, signaling higher fire danger. By analyzing these images, authorities can prioritize preventive measures such as controlled burns, forest management, or public awareness campaigns in high-risk areas. Additionally, real-time monitoring allows for early detection of wildfires, enabling rapid response efforts to contain them before they escalate, ultimately reducing the risk of extensive damage and loss of life.

There is no better way than thermal payloads on drone or compact thermal drones. Satellite can be used if the spatial resolution is good (<100 m/px) and which are expensive and if you have a cloudy day, just forget about it ! Monitoring the fire propagation and advising the water planes pilots of the direction of fire propagation can be such a helpful info to calm down the fire and stop its propagation !

Thermal bands and SAR imagery are the only imagery products that can penetrate wildfire smoke to capture burn scars and fire activity (given SWIR bands here and there). It's pivotal to target areas affected and predict movement.

Many wildfires starts with failures on power lines masts. Thermal imaging is very good technology to inspect and qualify for maintenance masts and poles that shows overheating insulators.

Thermal data is the information obtained from sensors that capture heat or infrared radiation, such as satellites, drones, or cameras. Thermal data can help prevent wildfires by: Detecting fire or hot spots in real-time, and alerting the authorities or fire-fighting services. Monitoring the vegetation, fuel, and moisture conditions of an area, and assessing the fire risk or fire behavior. Evaluating the damage and recovery of a burned area, and planning for restoration or mitigation measures.

A compreensão dos dados obtidos por sensores que captam informações térmicas são de grande importância na prevenção e identificação de incêndios florestais. A partir destas informações é possível identificar anomalias que podem indicar a ocorrência de incêndios. Além disso, a integração com outros sensores permitem o mapeamento de cicatrizes e até mesmo analisar a severidade das queimadas. Uma ressalva que deve ser feita é que devesse buscar imagens obtidas de sensores que consigam captar anomalias termais condizentes com as temperaturas atingidas por queimadas ou incêndios.

Using remote sensing, it's like having special heat-detecting eyes in the sky to prevent wildfires. Thermal data acts like a hotspot detector, pointing out areas prone to catching fire. What many miss is its ability to track persistent heat, predicting flare-ups even after the flames are out, making wildfire prevention more effective.

Radar data, acting like a digital radar system, reveals terrain conditions. An often unnoticed advantage is its capability to see through smoke and dust, offering clear views in challenging conditions. This enhances early detection and response to potential wildfires.

Remote sensing aids wildfire prevention through early detection, monitoring, and risk assessment with satellite imagery, thermal sensors, and GIS integration.

Les données radar, souvent collectées par des satellites radar à synthèse d'ouverture (SAR), sont utiles pour évaluer la structure de la végétation et détecter les changements. Ces données peuvent pénétrer à travers le feuillage dense, permettant une observation même par temps couvert. En analysant les données radar, on peut cartographier la structure du couvert végétal, évaluer la biomasse forestière et détecter d'éventuelles anomalies qui pourraient indiquer un risque d'incendie. Les données radar sont particulièrement précieuses pour les régions tropicales où la couverture nuageuse peut compliquer l'utilisation d'autres types de données.

Radar data is pivotal in wildfire prevention: - Vegetation Density Mapping - prior events - Early Detection of Smoldering Fires - Mapping Terrain and Topography - All-Weather Surveillance --> capability to penetrate through clouds

Radar data is crucial in preventing wildfires through its ability to penetrate smoke, clouds, and vegetation cover. This enables the detection of terrain changes and identification of potential fire risks. For instance, interferometric synthetic aperture radar (InSAR) can monitor ground deformation, revealing subtle shifts that may precede wildfires. Additionally, radar can be employed to assess fuel moisture content, aiding in evaluating the flammability of vegetation. Integrating radar data with other sources enhances early warning systems, facilitating timely intervention measures such as targeted fire prevention campaigns, vegetation management, and resource allocation for firefighting efforts.

My opinion is Lidar data offers detailed 3D information on vegetation structure and density, aiding in identifying high-risk fire areas. Additionally, Lidar-derived elevation data helps model terrain features, such as slope and aspect, which are crucial for predicting fire behavior.

LiDAR data can provide functional reporting and utility vegetation management services. Such insights help utilities to prioritise vegetation encroachments, power lines. When a power line falls down, whether it’s caused by a falling tree or another reason, it remains energized until the utility company shuts it off. If vegetation on the ground comes in contact with the high-voltage downed conductor, it can spark a fire. Tree, Vegetation Contact: Even if a power line doesn’t collapse, contact with a tree branch or other vegetation can cause a fire over time.

O LiDAR aerotransportado gera dados tridimensionais da floresta, permitindo a caracterização do sub-bosque presente e a mensuração estimada do material combustível existente.

Lidar data is valuable in wildfire prevention by providing detailed 3D information about the landscape. It can be used to create highly accurate terrain models and identify fine-scale features such as vegetation density and structure. By analyzing lidar data, authorities can assess fuel load, potential fire pathways, and areas susceptible to rapid fire spread. This information is crucial for developing effective fire management strategies, including prescribed burns and creating defensible spaces. Lidar can also aid in assessing canopy height and structure, contributing to a more comprehensive understanding of the landscape factors influencing fire behavior.

Lidar data can be used to determine the vertical structure of forests. This makes it possible to see whether there is a lot of combustible material near the ground in a forest. The risk of forest fires increases with the presence of the “fuel”, and forest fire risk maps can be derived from lidar data.

It is possible to use GIS tools such as hotspot analysis to identify areas of persistent fire occurrence (& even changes in occurrence patterns across time & space). These areas can then be prioritised for fire prevention

GIS prevents wildfires by mapping vulnerable areas, but overlooked is its role in analyzing historical fire data to predict future risks. Additionally, GIS helps coordinate firefighting resources efficiently, often underappreciated. By integrating weather patterns, it aids in timely evacuation planning, a critical but underestimated aspect of wildfire prevention.

Prevenir talvez não seja o melhor termo, creio que o GIS auxilia mais no conhecimento sobre o território, no mapeamento das áreas de maiores risco ou mais susceptíveis a incêndios. Por sensoriamento remoto, por exemplo, pode-se mapear o estresse hídrico, saúde da vegetação, ações de antropização ou mudanças significativas nas áreas. Analisar dados históricos e entender quais eram as condições que favoreceram os eventos naquele momento. O ideal é ter um monitoramento sistemático que traga o retrato da realidade com uma frequência suficiente para se planejar e tomar ações. Neste ponto de maturidade sim é possível falar de ações de prevenção.

You can use GIS to identify at risk areas such as peat bogs , mature forests , recently cut or burnt over areas and then put in place measures to safe guard these areas- such as access roads, resources for fire fighters

The more important thing about understand the wildfires is that we are analizing a situation that present a multivariable approach, the only way to trate with a complex problem with multiple reasons is through of analysis and manage of the data and information, the most valuable data in this geographic problems is spacial data, so the GIS are the most powerful system to get, interpret and analyze Information to take decisions and create predictive models of the nature phenomenons

Nowadays, GIS (Geographic Information System) tools and remote sensing data play important role in disaster risk reduction/management, including wildfire prevention, risk reduction, preparedness, and response. Especially, satellite images are essential to modern wildfire monitoring, analysis, and early warning systems. In GIS, it is possible to integrate various spatial datasets such as land cover, vegetation types, soil, elevation, slope, aspect, and weather patterns to create comprehensive wildfire hazard maps. Adding anthropogenic elements, such as buildings, roads, arable lands, infrastructure, etc., we can also obtain fire risk maps.

Thermal, Radar, and Lidar data are most effective to detect wildfire and assess the post-wildfire impact. Spectral and temporal resolution of the data play an important role in this application.

O uso de novas ferramentas de SIG precisam e devem ser utilizados para o monitoramento preventivo e mitigatório de incêndios florestais. Um exemplo disso é o uso de dashboards dinâmicos com informações quantitativas e qualitativas (Qt de focos, FRP, data e hora de detecção) além de informações úteis de localização como rede viária, hidrografia, localidades, etc. A integração dos dados permite as autoridades responsáveis aumentar sua assertividade na tomada de decisão.

By the use of classification areas prone to wildfires can be analyzed and actively monitored by lidar and thermal to eradicate wildfires before it happens

Además del uso de las tecnologías previamente mencionadas en el artículo, yo utilizaría información histórica sobre los incendios forestales que se hayan presentado previamente en la zona de estudio. Con está información podría identificar fácilmente los lugares en donde la tendencia muestre un mayor riesgo a que ocurra un evento como éste, y así poder adoptar alguna tecnología como la LiDAR o los datos térmicos para tratar de predecir los posibles incendios que se puedan presentar.