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 Geographic Information System (CGIS):

- Roger Tomlinson develops the world's first operational GIS in Ottawa, Canada.

- CGIS used for Canada Land Inventory, incorporating data on soils, agriculture, wildlife, etc.

6. 1964 - Laboratory for Computer Graphics and Spatial Analysis:

- Howard T. Fisher establishes the Laboratory for Computer Graphics and Spatial Analysis at Harvard.

- Develops influential software code and systems distributed worldwide.

7. Late 1970s to Early 1980s - Commercialization of GIS:

- Public domain GIS systems MOSS and GRASS GIS in development.

- Commercial vendors (M&S Computing, ESRI, Intergraph, Bentley Systems, CARIS, ERDAS) emerge with features from CGIS.

8. 1986 - Desktop GIS Emerges:

- Mapping Display and Analysis System (MIDAS), the first desktop GIS, is released.

- Renamed MapInfo for Windows in 1990, marking the shift from research to business.

9. Late 20th Century - Consolidation and Standardization:

- Rapid growth in GIS systems consolidates on a few platforms by the end of the century.

- Users begin exploring GIS data over the Internet, requiring format and transfer standards.

10. 21st Century - Integration with IT and Internet Infrastructure:

- Integration of GIS with IT and Internet technologies like relational databases, cloud computing, SAAS, and mobile computing becomes a major trend.

- Growing number of free, open-source GIS packages customized for specific tasks.

Comments

Platforms in Remote Sensing

In remote sensing, a platform is the physical structure or vehicle that carries a sensor (camera, scanner, radar, etc.) to observe and collect information about the Earth's surface. Platforms are classified mainly by their altitude and mobility : Ground-Based Platforms Definition : Sensors mounted on the Earth's surface or very close to it. Examples : Tripods, towers, ground vehicles, handheld instruments. Applications : Calibration and validation of satellite data Detailed local studies (e.g., soil properties, vegetation health, air quality) Strength : High spatial detail but limited coverage. Airborne Platforms Definition : Sensors carried by aircraft, balloons, or drones (UAVs). Altitude : A few hundred meters to ~20 km. Examples : Airplanes with multispectral scanners UAVs with high-resolution cameras or LiDAR High-altitude balloons (stratospheric platforms) Applications : Local-to-regional mapping ...

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...

Resolution of Sensors in Remote Sensing

Spatial Resolution 🗺️ Definition : The smallest size of an object on the ground that a sensor can detect. Measured as : The size of a pixel on the ground (in meters). Example : Landsat → 30 m (each pixel = 30 × 30 m on Earth). WorldView-3 → 0.31 m (very detailed, you can see cars). Fact : Higher spatial resolution = finer details, but smaller coverage. Spectral Resolution 🌈 Definition : The ability of a sensor to capture information in different parts (bands) of the electromagnetic spectrum . Measured as : The number and width of spectral bands. Types : Panchromatic (1 broad band, e.g., black & white image). Multispectral (several broad bands, e.g., Landsat with 7–13 bands). Hyperspectral (hundreds of very narrow bands, e.g., AVIRIS). Fact : Higher spectral resolution = better identification of materials (e.g., minerals, vegetation types). Radiometric Resolution 📊 Definition : The ability of a sensor to ...

Optical Sensors in Remote Sensing

1. What Are Optical Sensors? Optical sensors are remote sensing instruments that detect solar radiation reflected or emitted from the Earth's surface in specific portions of the electromagnetic spectrum (EMS) . They mainly work in: Visible region (0.4–0.7 µm) Near-Infrared – NIR (0.7–1.3 µm) Shortwave Infrared – SWIR (1.3–3.0 µm) Thermal Infrared – TIR (8–14 µm) — emitted energy, not reflected Optical sensors capture spectral signatures of surface features. Each object reflects/absorbs energy differently, creating a unique spectral response pattern . a) Electromagnetic Spectrum (EMS) The continuous range of wavelengths. Optical sensing uses solar reflective bands and sometimes thermal bands . b) Spectral Signature The unique pattern of reflectance or absorbance of an object across wavelengths. Example: Vegetation reflects strongly in NIR Water absorbs strongly in NIR and SWIR (appears dark) c) Radiance and Reflectance Radi...

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...

Vineesh V, Geography

Search This Blog