Skip to main content

Evolution of Indian Platform

The Indian Platform, also known as the Indian Shield or the Peninsular Shield, is a stable geological region that forms the core of the Indian subcontinent. It has a complex geological history that spans billions of years. Here's an overview of the evolution of the Indian Platform:


1. Archean Eon (4 billion to 2.5 billion years ago):

    The earliest geological history of the Indian Platform dates back to the Archean Eon, during which some of the oldest rocks on Earth were formed.

    The Dharwar Craton, located in the southern part of the Indian Platform, is one of the prime examples of Archeanage geological formations in India.


2. Proterozoic Eon (2.5 billion to 541 million years ago):

    During the Proterozoic Eon, the Indian Platform witnessed significant geological events.

    Sedimentary basins formed, leading to the accumulation of thick sequences of sedimentary rocks.

    The Vindhyan Supergroup, a prominent sedimentary rock formation, was deposited during this time.


3. Rodinia Supercontinent (1.3 billion to 750 million years ago):

    India was part of the supercontinent Rodinia during this period.

    It was situated near the southern margin of Rodinia.


4. Breakup of Rodinia and Formation of Gondwana (750 million to 540 million years ago):

    Rodinia began to break apart during the Neoproterozoic.

    India separated from the supercontinent and was positioned closer to Antarctica, forming part of the Gondwana supercontinent.


5. Cambrian to Devonian Periods (541 million to 358 million years ago):

    During this time, India experienced marine sedimentation and the deposition of sedimentary rocks in shallow seas.


6. Carboniferous to Permian Periods (358 million to 252 million years ago):

    India was located near the equator and experienced extensive coalforming swamps and glacial deposits.


7. Mesozoic Era (252 million to 66 million years ago):

    India remained part of Gondwana during the early Mesozoic, but it began drifting northward.

    This northward movement eventually led to its separation from Gondwana and initiated the formation of the Indian subcontinent.


8. Cenozoic Era (66 million years ago to present):

    The most significant phase in the evolution of the Indian Platform occurred during the Cenozoic.

    India continued to move northward and eventually collided with the Eurasian Plate around 50 million years ago.

    This collision resulted in the uplift of the Himalayan mountain range and the Tibetan Plateau, significantly impacting the Indian Platform's geology and topography.


The collision with the Eurasian Plate is a defining event in the evolution of the Indian Platform, shaping its current geological features and creating some of the world's most prominent mountain ranges, including the Himalayas. This collision also continues to influence seismic activity in the region. Overall, the geological evolution of the Indian Platform reflects its role in the assembly of the Indian subcontinent and its dynamic geological history.





Comments

Popular posts from this blog

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...

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...

History of GIS

The history of Geographic Information Systems (GIS) is rooted in early efforts to understand spatial relationships and patterns, long before the advent of digital computers. While modern GIS emerged in the mid-20th century with advances in computing, its conceptual foundations lie in cartography, spatial analysis, and thematic mapping. Early Roots of Spatial Analysis (Pre-1960s) One of the earliest documented applications of spatial analysis dates back to  1832 , when  Charles Picquet , a French geographer and cartographer, produced a cholera mortality map of Paris. In his report  Rapport sur la marche et les effets du cholĂ©ra dans Paris et le dĂ©partement de la Seine , Picquet used graduated color shading to represent cholera deaths per 1,000 inhabitants across 48 districts. This work is widely regarded as an early example of choropleth mapping and thematic cartography applied to epidemiology. A landmark moment in the history of spatial analysis occurred in  1854 , when  John Snow  inv...

Supervised Classification

In the context of Remote Sensing (RS) and Digital Image Processing (DIP) , supervised classification is the process where an analyst defines "training sites" (Areas of Interest or ROIs) representing known land cover classes (e.g., Water, Forest, Urban). The computer then uses these training samples to teach an algorithm how to classify the rest of the image pixels. The algorithms used to classify these pixels are generally divided into two broad categories: Parametric and Nonparametric decision rules. Parametric Decision Rules These algorithms assume that the pixel values in the training data follow a specific statistical distribution—almost always the Gaussian (Normal) distribution (the "Bell Curve"). Key Concept: They model the data using statistical parameters: the Mean vector ( $\mu$ ) and the Covariance matrix ( $\Sigma$ ) . Analogy: Imagine trying to fit a smooth hill over your data points. If a new point lands high up on the hill, it belongs to that cl...

Pre During and Post Disaster

Disaster management is a structured approach aimed at reducing risks, responding effectively, and ensuring a swift recovery from disasters. It consists of three main phases: Pre-Disaster (Mitigation & Preparedness), During Disaster (Response), and Post-Disaster (Recovery). These phases involve various strategies, policies, and actions to protect lives, property, and the environment. Below is a breakdown of each phase with key concepts, terminologies, and examples. 1. Pre-Disaster Phase (Mitigation and Preparedness) Mitigation: This phase focuses on reducing the severity of a disaster by minimizing risks and vulnerabilities. It involves structural and non-structural measures. Hazard Identification: Recognizing potential natural and human-made hazards (e.g., earthquakes, floods, industrial accidents). Risk Assessment: Evaluating the probability and consequences of disasters using GIS, remote sensing, and historical data. Vulnerability Analysis: Identifying areas and p...