Remote Sensing and Disaster Management. Applications.

Remote sensing technology has proven to be an effective tool for disaster management. Here are some applications of remote sensing in disaster management:

Early Warning Systems: Remote sensing data is used to monitor natural hazards such as hurricanes, typhoons, floods, and tsunamis, and provide early warning systems to the authorities, allowing them to take timely action to mitigate damage.

Damage Assessment: Remote sensing data can be used to quickly assess the extent of damage caused by a disaster. This information is useful in determining the areas that require immediate assistance and aid.

Search and Rescue: Remote sensing data can help locate stranded individuals or missing persons during a disaster. It can also be used to monitor the movement of rescue teams and assist in their deployment.

Urban Planning and Management: Remote sensing data can be used to create maps and models of urban areas, which can be used for emergency response planning and management.

Agricultural Disaster Management: Remote sensing data can be used to monitor crop conditions and detect crop damage due to natural disasters such as floods, droughts, and wildfires.

Forest Fire Management: Remote sensing data can be used to monitor forest fires and help in the planning and management of firefighting efforts.

Landslide Risk Assessment: Remote sensing data can be used to identify areas that are at high risk of landslides, allowing authorities to take preventive measures and reduce the damage caused by such disasters.

Water Management: Remote sensing data can be used to monitor water resources and predict floods and droughts, allowing authorities to manage and allocate water resources effectively.

These are some of the many applications of remote sensing in disaster management. The technology continues to evolve, and new applications are being developed every day to improve our ability to prepare for and respond to disasters

Comments

History of GIS

1. 1832 - Early Spatial Analysis in Epidemiology: - Charles Picquet creates a map in Paris detailing cholera deaths per 1,000 inhabitants. - Utilizes halftone color gradients for visual representation. 2. 1854 - John Snow's Cholera Outbreak Analysis: - Epidemiologist John Snow identifies cholera outbreak source in London using spatial analysis. - Maps casualties' residences and nearby water sources to pinpoint the outbreak's origin. 3. Early 20th Century - Photozincography and Layered Mapping: - Photozincography development allows maps to be split into layers for vegetation, water, etc. - Introduction of layers, later a key feature in GIS, for separate printing plates. 4. Mid-20th Century - Computer Facilitation of Cartography: - Waldo Tobler's 1959 publication details using computers for cartography. - Computer hardware development, driven by nuclear weapon research, leads to broader mapping applications by early 1960s. 5. 1960 - Canada Geograph...

Accuracy Assessment

Accuracy assessment is the process of checking how correct your classified satellite image is . 👉 After supervised classification, the satellite image is divided into classes like: Water Forest Agriculture Built-up land Barren land But classification is done using computer algorithms, so some areas may be wrongly classified . 👉 Accuracy assessment helps to answer this question: ✔ "How much of my classified map is correct compared to real ground conditions?" Goal The main goal is to: Measure reliability of classified maps Identify classification errors Improve classification results Provide scientific validity to research 👉 Without accuracy assessment, a classified map is not considered scientifically reliable . Reference Data (Ground Truth Data) Reference data is real-world information used to check classification accuracy. It can be collected from: ✔ Field survey using GPS ✔ High-resolution satellite images (Google Earth etc.) ✔ Existing maps or survey reports 🧭 Exampl...

Supervised Classification

Image Classification in Remote Sensing Image classification in remote sensing involves categorizing pixels in an image into thematic classes to produce a map. This process is essential for land use and land cover mapping, environmental studies, and resource management. The two primary methods for classification are Supervised and Unsupervised Classification . Here's a breakdown of these methods and the key stages of image classification. 1. Types of Classification Supervised Classification In supervised classification, the analyst manually defines classes of interest (known as information classes ), such as "water," "urban," or "vegetation," and identifies training areas —sections of the image that are representative of these classes. Using these training areas, the algorithm learns the spectral characteristics of each class and applies them to classify the entire image. When to Use Supervised Classification: - You have prior knowledge about the c...

Development and scope of Environmental Geography and Recent concepts in environmental Geography

Environmental Geography studies the relationship between humans and nature in a spatial (place-based) way. It combines Physical Geography (natural processes) and Human Geography (human activities). A. Early Stage 🔹 Environmental Determinism Concept: Nature controls human life. Meaning: Climate, landforms, and soil decide how people live. Example: People in deserts (like Sahara Desert) live differently from people in fertile river valleys. 🔹 Possibilism Concept: Humans can modify nature. Meaning: Environment gives options, but humans make choices. Example: In dry areas like Rajasthan, people use irrigation to grow crops. 👉 In this stage, geography was mostly descriptive (explaining what exists). B. Evolution Stage (Mid-20th Century) Environmental problems increased due to: Industrialization Urbanization Deforestation Pollution Geographers started studying: Environmental degradation Resource management Human impact on ecosystems The field became analytical and problem-solving...

Representation of Spatial and Temporal Relationships

In GIS, spatial and temporal relationships allow the integration of location (the "where") and time (the "when") to analyze phenomena across space and time. This combination is fundamental to studying dynamic processes such as urban growth, land-use changes, or natural disasters. Key Concepts and Terminologies Geographic Coordinates : Define the position of features on Earth using latitude, longitude, or other coordinate systems. Example: A building's location can be represented as (11.6994° N, 76.0773° E). Timestamp : Represents the temporal aspect of data, such as the date or time a phenomenon was observed. Example: A landslide occurrence recorded on 30/07/2024 . Spatial and Temporal Relationships : Describes how features relate in space and time. These relationships can be: Spatial : Topological (e.g., "intersects"), directional (e.g., "north of"), or proximity-based (e.g., "near"). Temporal : Sequential (e....

Vineesh V, Geography

Search This Blog