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Groundwater – Porosity and Permeability

Groundwater refers to the water that resides beneath the Earth's surface in the pores and crevices of rock, sediment, and soil. Two key properties that influence the movement and storage of groundwater are porosity and permeability: 1. Porosity:    - Definition: Porosity refers to the volume percentage of void spaces (pores or openings) in a geological material, such as soil or rock.    - Role: Porosity determines how much water a subsurface material can hold. It is a measure of the material's capacity to store water.    - Factors: Porosity is influenced by the size and arrangement of particles within the material. Highly porous materials have more void spaces, while less porous materials have fewer.    - Units: Porosity is expressed as a percentage, with 0% indicating complete solidity (no pore spaces) and 100% indicating complete void space. 2. Permeability:    - Definition: Permeability refers to the ability of a geological material to transmit fluids, such as water. It meas...

Surface water pollution and Environmental

Surface water pollution refers to the contamination of water bodies such as rivers, lakes, and oceans by various pollutants. These pollutants can come from both natural sources and human activities. Environmental impacts of surface water pollution are significant and include: 1. Ecosystem Damage: Pollutants like industrial chemicals, agricultural runoff, and sewage can harm aquatic ecosystems. They can disrupt the balance of aquatic life, leading to fish kills and the decline of biodiversity. 2. Water Quality: Contaminated surface water can affect the quality of drinking water sources. When pollutants enter rivers and lakes, they can make water unsafe for human consumption, leading to health risks. 3. Human Health: Surface water pollution can impact human health when polluted water is used for drinking, recreation, or irrigation. Contaminants like bacteria, heavy metals, and toxic chemicals can cause various diseases and health problems. 4. Economic Costs: Cleanup and mitigation of sur...

Contrast manipulation

Contrast stretching is a common image enhancement technique in remote sensing used to improve the visual quality and interpretability of satellite or aerial imagery. It involves expanding the range of pixel values in an image, typically by remapping the original values to a new range. This process enhances the visual contrast between different features in the image. 1. Linear Contrast Stretching:    Linear contrast stretching is the simplest form of contrast stretching. It involves applying a linear transformation to the pixel values in the image. The transformation stretches the original range of pixel values to a new range. This is typically done using the following formula for each pixel in the image:        NewPixelValue = (OriginalPixelValue - MinOriginalValue)  (NewMaxValue - NewMinValue) / (MaxOriginalValue - MinOriginalValue) + NewMinValue    - `OriginalPixelValue` is the value of the pixel in the original image.    - `MinOriginalValue` and `MaxOriginalValue` are the minimum an...

8 bit and 16 bit image

In remote sensing, "eight-bit" and "sixteen-bit" refer to the number of bits used to represent the pixel values in an image. This affects the image's color or grayscale depth, which, in turn, influences the level of detail and precision in the image. - Eight-Bit Image: An eight-bit image uses 8 bits per pixel to represent color or grayscale information. This means each pixel can have 2^8 (256) different possible values. In a grayscale eight-bit image, you have 256 shades of gray, ranging from black to white. In a color eight-bit image, you can represent a limited palette of 256 colors. Eight-bit images are suitable for basic visual interpretation but may lack fine detail and subtle color variations. - Sixteen-Bit Image: A sixteen-bit image uses 16 bits per pixel, providing a significantly wider range of possible values, which is 2^16 (65,536). In remote sensing, sixteen-bit images are often used when high precision is required, especially in applications like la...

Radiometric Resolution

Radiometric resolution in remote sensing refers to the ability of a remote sensing system, such as a satellite or aerial sensor, to capture and represent different levels of brightness or energy in the electromagnetic spectrum. It's an important aspect of the sensor's capability to distinguish variations in the intensity of radiation reflected or emitted by the Earth's surface. Here are some key points about radiometric resolution: 1. Quantifying Brightness: Radiometric resolution is essentially a measure of how finely the sensor can quantize or measure the amount of energy in each pixel of an image. It is usually expressed in terms of the number of bits used to represent pixel values. 2. Bit Depth: The number of bits determines the range of values that can be represented. For example, an 8-bit sensor can represent 2^8 (256) different brightness levels, while a 16-bit sensor can represent 2^16 (65,536) levels. Higher radiometric resolution, as in a 16-bit sensor, can captur...

Wetland and significance

Wetlands are ecologically valuable areas characterized by the presence of water, whether seasonally or permanently. They play a crucial role in the environment and offer numerous significant benefits: 1. Biodiversity: Wetlands are among the most biologically diverse ecosystems on Earth. They provide a habitat for a wide variety of plants, animals, and microorganisms. Many species, including migratory birds, amphibians, and insects, rely on wetlands for breeding, feeding, and shelter. 2. Flood Control: Wetlands act as natural sponges, absorbing and storing excess water during heavy rains or floods. This helps reduce the risk of downstream flooding and prevents damage to communities and infrastructure. 3. Water Quality Improvement: Wetlands filter and purify water by trapping and breaking down pollutants, excess nutrients, and sediments. They improve water quality before it flows into rivers, lakes, or oceans. 4. Climate Regulation: Wetlands store and release water gradually, helping to ...

Watershed. Catchment. Basin

A watershed, also known as a river basin or drainage basin, is a fundamental concept in geohydrology and hydrology. It refers to a specific geographic area or region of land where all the surface water, including rainfall, snowmelt, and runoff, drains into a common outlet, such as a river, lake, or ocean. Here's an explanation of each term: 1. Watershed: A watershed is essentially a natural hydrological unit defined by the topography of the land. It represents the entire area from which all precipitation and surface water flow eventually gathers at a single point. This point is typically where the main river or stream within the watershed exits into a larger body of water, such as an ocean. Watersheds come in various sizes, from small ones that encompass a few square miles to enormous ones that cover entire continents. 2. River/Drainage Basin: A river basin or drainage basin is another way to describe a watershed. It's the land area that collects and channels water into a river...

Digital Number and Reflectance Value

Digital number (DN) and reflectance value are two important concepts in remote sensing, particularly when dealing with satellite or aerial imagery. Here's an explanation and differentiation of these terms: 1. Digital Number (DN):    - Digital number, often abbreviated as DN, is a raw, unprocessed value assigned to each pixel in a digital image. It represents the brightness or radiance of the pixel as recorded by the sensor.    - DN values are typically expressed in a numerical range, often from 0 to 255 for 8-bit images, or 0 to 65535 for 16-bit images, depending on the bit depth of the sensor.    - These values are directly related to the amount of light or electromagnetic radiation received by the sensor, but they are not yet converted into physical units like reflectance. 2. Reflectance Value:    - Reflectance is a measure of how much electromagnetic radiation (usually in the visible or infrared spectrum) is reflected by a surface. It is often expressed as a percentage or a deci...

Digital image processing

Digital image processing in remote sensing involves the manipulation of satellite or aerial images to extract useful information about the Earth's surface. Here are the basic steps involved: 1. Image Acquisition: Remote sensing devices, such as satellites and aerial cameras, capture images of the Earth's surface. These images are usually in digital format and consist of pixels, each representing a small portion of the Earth's surface. 2. Preprocessing: This step involves the initial cleaning and enhancement of the raw image data. It includes tasks like radiometric calibration to correct for sensor-related distortions and atmospheric correction to account for the effects of the Earth's atmosphere on the image. 3. Image Enhancement: Enhancement techniques like contrast adjustment, histogram equalization, and filtering are used to improve the visual quality of the image and make important features more discernible. 4. Image Registration: Multiple images from different sour...

Radiometric correction

Radiometric correction in remote sensing is a crucial process that aims to remove or reduce variations in the recorded radiance values of an image, ensuring that the data accurately represents the reflectance properties of the Earth's surface. This correction is essential for extracting meaningful information from remotely sensed imagery. 1. Source of Radiometric Error:    Radiometric errors in remote sensing can originate from various sources, including:    a. Atmospheric Effects: The Earth's atmosphere can scatter and absorb incoming sunlight and reflected light from the surface. These atmospheric effects can introduce errors in radiance values, particularly in the blue and ultraviolet spectral regions.    b. Sensor Characteristics: Different sensors have varying spectral and radiometric characteristics, leading to inconsistencies in radiance measurements.    c. Satellite Orbits: Variations in the satellite's position, speed, and angle relative to the Earth's surface ...

Geometric Correction

Geometric Correction: - Geometric correction is a critical process in remote sensing and digital image processing. It involves adjusting and aligning an image so that it accurately represents the Earth's surface in terms of scale, orientation, and spatial accuracy. This correction compensates for various geometric distortions and errors introduced during image acquisition and sensor characteristics, ensuring that the image can be used for precise geospatial analysis and mapping. Source of Geometric Error: - Geometric errors in remote sensing arise from various sources, including inaccuracies in sensor characteristics, platform movement, Earth's curvature, terrain relief, atmospheric conditions, and other factors. These errors can lead to distortions, misalignments, and inaccuracies in the positioning and representation of objects within an image. Types of Geometric Error: - Geometric errors can manifest in different ways, including:   1. Scale Error: Inaccurate representation o...

Types of image

1. Visible Image:    - A visible image is captured in the range of the electromagnetic spectrum that is visible to the human eye, typically spanning wavelengths from about 400 to 700 nanometers (nm). These images resemble what the human eye sees and are often used for visual inspection and interpretation. 2. Infrared Image:    - Infrared imagery captures radiation in the infrared portion of the electromagnetic spectrum, beyond what is visible to the human eye. It is useful for applications such as night vision, heat detection, and identifying temperature variations. 3. Multispectral Image:    - Multispectral imagery is captured in multiple distinct bands or channels across the electromagnetic spectrum. Each band provides information about a specific range of wavelengths, allowing for the analysis of different characteristics of the scene, such as vegetation health or land use. 4. Hyperspectral Image:    - Hyperspectral imagery captures data in numerous narrow and contiguous bands acros...

Geology and Tectonic. Indian Shield

1. Ch (Chattisgarh Basin): Chattisgarh Basin is a geological region in central India known for its sedimentary rock formations. It's important for its mineral resources, including coal and iron ore. 2. CIS (Central Indian Shear Zone): CIS is a tectonic boundary in central India where the Indian Plate interacts with the Eurasian Plate. It's characterized by significant faulting and seismic activity. 3. GR (Godavari Rift): The Godavari Rift is a geological feature associated with the rifting and splitting of the Indian Plate. It's located in the Godavari River basin in southeastern India. 4. M (Madras Block): The Madras Block is a stable continental block in southern India. It's part of the Indian Plate and is not associated with active tectonic processes. 5. Mk (Malanjkhand): Malanjkhand is known for its copper deposits and is one of the largest copper mines in India. 6. MR (Mahanadi Rift): The Mahanadi Rift is a geological feature related to the rifting of the Indian Pl...

Terminology. Remote Sensing

Absorptance : The ratio of the radiant energy absorbed by a substance to the energy it receives. Band : The specific wavelength interval in the electromagnetic spectrum. Digital image : An array of digital numbers (DN) arranged in rows and columns, having the property of an intensity value and their locations. Digital Number : An intensity value of a pixel in a digital image. Digital Image Processing : The numerical manipulation of DN values for the purpose of extracting information about the phenomena of the surface they represent. Electromagnetic Radiation (EMR) : The Energy propagated through a space or a medium at a speed of light. Electromagnetic Spectrum : The continuum of EMR that ranges from short wave high frequency cosmic radiations to long wavelength low frequency radio waves. False Colour Composite (FCC) : An artificially generated colour image in which blue, green and red colours are assigned to the wavelength regions to which they do not belong in nature. For example, in ...