Geovisualization

Cartography is the science and art of map-making, involving the representation of spatial data in a visual format. Thematic maps, a key aspect of cartography, are designed to emphasize specific data patterns related to geographic areas. Different types of thematic maps serve various analytical and communicative purposes.

Thematic Maps

1. Choropleth Map

A choropleth map represents data within predefined geographic boundaries (such as countries, states, or districts) using color gradients. Darker or more intense colors typically indicate higher values, while lighter colors represent lower values.

Key Characteristics:
- Aggregates data within administrative boundaries.
- Uses color intensity to show variations.
- Suitable for representing ratios, densities, or percentages.
Example: A population density map where darker shades indicate more densely populated states.

2. Choroschematic Map

A choroschematic map simplifies spatial data using symbols instead of detailed geographic accuracy. These maps focus on the general spatial distribution of data rather than precise boundaries.

Key Characteristics:
- Uses simplified symbols instead of exact borders.
- Helps in showing broad spatial relationships.
- Often used for land use, economic zones, or general trends.
Example: A land use map that shows forests, agricultural areas, and urban zones using different symbols.

3. Chorochromatic Map

A chorochromatic map displays categorical or qualitative data by assigning different colors to different categories. It does not rely on predefined administrative boundaries but rather on the distribution of distinct features.

Key Characteristics:
- Represents qualitative data (not numerical).
- Uses different colors to distinguish between categories.
- Independent of political or administrative boundaries.
Example: A language distribution map where different colors represent regions speaking different languages.

4. Isopleth Map

An isopleth map visualizes continuous data distribution by connecting points of equal value with contour lines. Unlike choropleth maps, isopleth maps do not rely on administrative boundaries, making them ideal for showing natural phenomena.

Key Characteristics:
- Represents continuous data without boundary constraints.
- Uses isolines to connect areas of equal value.
- Ideal for climatic, elevation, and environmental data.
Example: A weather map showing isobars (lines of equal atmospheric pressure) or an elevation map with contour lines.

Key Differences:

Type	Data Representation	Boundary Dependence	Example Use
Choropleth	Aggregated numerical data	Bound to administrative regions	Population density map
Choroschematic	Simplified symbols for spatial patterns	Less detailed, broad trends	Land use distribution
Chorochromatic	Categorical/qualitative data using color	Not restricted by administrative boundaries	Language distribution
Isopleth	Continuous data with equal-value lines	No predefined boundaries	Weather maps with isobars

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Natural Disasters

A natural disaster is a catastrophic event caused by natural processes of the Earth that results in significant loss of life, property, and environmental resources. It occurs when a hazard (potentially damaging physical event) interacts with a vulnerable population and leads to disruption of normal life . Key terms: Hazard → A potential natural event (e.g., cyclone, earthquake). Disaster → When the hazard causes widespread damage due to vulnerability. Risk → Probability of harmful consequences from interaction of hazard and vulnerability. Vulnerability → Degree to which a community or system is exposed and unable to cope with the hazard. Resilience → Ability of a system or society to recover from the disaster impact. 👉 Example: An earthquake in an uninhabited desert is a hazard , but not a disaster unless people or infrastructure are affected. Types Natural disasters can be classified into geophysical, hydrological, meteorological, clim...

Types of Remote Sensing

Remote Sensing means collecting information about the Earth's surface without touching it , usually using satellites, aircraft, or drones . There are different types of remote sensing based on the energy source and the wavelength region used. 🛰️ 1. Active Remote Sensing 📘 Concept: In active remote sensing , the sensor sends out its own energy (like a signal or pulse) to the Earth's surface. The sensor then records the reflected or backscattered energy that comes back from the surface. ⚙️ Key Terminology: Transmitter: sends energy (like a radar pulse or laser beam). Receiver: detects the energy that bounces back. Backscatter: energy that is reflected back to the sensor. 📊 Examples of Active Sensors: RADAR (Radio Detection and Ranging): Uses microwave signals to detect surface roughness, soil moisture, or ocean waves. LiDAR (Light Detection and Ranging): Uses laser light (near-infrared) to measure elevation, vegetation...

geostationary and sun-synchronous

Orbital characteristics of Remote sensing satellite geostationary and sun-synchronous Orbits in Remote Sensing Orbit = the path a satellite follows around the Earth. The orbit determines what part of Earth the satellite can see , how often it revisits , and what applications it is good for . Remote sensing satellites mainly use two standard orbits : Geostationary Orbit (GEO) Sun-Synchronous Orbit (SSO) Geostationary Satellites (GEO) Characteristics Altitude : ~35,786 km above the equator. Period : 24 hours → same as Earth's rotation. Orbit type : Circular, directly above the equator . Appears "stationary" over one fixed point on Earth. Concepts & Terminologies Geosynchronous = orbit period matches Earth's rotation (24h). Geostationary = special type of geosynchronous orbit directly above equator → looks fixed. Continuous coverage : Can monitor the same area all the time. Applications Weather...

India remote sensing

1. Foundational Phase (Early 1970s – Early 1980s) Objective: To explore the potential of space-based observation for national development. 1972: The Space Applications Programme (SAP) was initiated by the Indian Space Research Organisation (ISRO), focusing on applying space technology for societal benefits. 1975: The Department of Space (DoS) was established, providing an institutional base for space applications, including remote sensing. 1977: India began aerial and balloon-borne experiments to study Earth resources and assess how remote sensing data could aid in agriculture, forestry, and hydrology. 1978 (June 7): Bhaskara-I launched by the Soviet Union — India's first experimental Earth Observation satellite . Payloads: TV cameras (for land and ocean surface observation) and a Microwave Radiometer. Significance: Proved that satellite-based Earth observation was feasible for India's needs. 1981 (November 20): Bhaskara-II launche...

Linear Arrays Along-Track Scanners or Pushbroom Scanners

Multispectral Imaging Using Linear Arrays (Along-Track Scanners or Pushbroom Scanners) Multispectral Imaging: As previously defined, this involves capturing images using multiple sensors that are sensitive to different wavelengths of electromagnetic radiation. Linear Array of Detectors (A): This refers to a row of discrete detectors arranged in a straight line. Each detector is responsible for measuring the radiation within a specific wavelength band. Focal Plane (B): This is the plane where the image is formed by the lens system. It is the location where the detectors are placed to capture the focused image. Formed by Lens Systems (C): The lens system is responsible for collecting and focusing the incoming radiation onto the focal plane. It acts like a camera lens, creating a sharp image of the scene. Ground Resolution Cell (D): As previously defined, this is the smallest area on the ground that can be resolved by a remote sensing sensor. In the case of linear array scanne...

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