Vineesh V, Geography

1. Indus River Dispute:    - Issue: Disputes between India and Pakistan over the sharing of the Indus River waters.    - Reason: Historical conflicts and the Indus Water Treaty's limitations have led to disagreements on water distribution. 2. Ganges-Brahmaputra River Basin:    - Issue: Water-sharing disputes between India and Bangladesh.    - Reason: Varied monsoon patterns and increasing demand for water resources contribute to conflicts over the Ganges and Brahmaputra rivers. 3. Teesta River Dispute:    - Issue: Contentious water-sharing agreement between India and Bangladesh.    - Reason: Divergent interests and the absence of a comprehensive water-sharing treaty lead to disagreements, impacting both countries. 4. Yamuna River Pollution:    - Issue: High pollution levels in the Yamuna River affecting both India and downstream Pakistan.    - Reason: Urbanization, industrial discharge, and inadequate waste management contribute to water pollution. 5. Bhagirathi-Hooghly River Syste

1. Cauvery River Dispute:    - Reason: Allocation of Cauvery River water for agricultural irrigation, particularly between Karnataka and Tamil Nadu.    - Origin: Western Ghats in Karnataka. Flows through Karnataka, Tamil Nadu, Kerala, and Puducherry. 2. Krishna River Dispute:    - Reason: Disagreements over the sharing of Krishna River water for irrigation, power generation, and other uses among Maharashtra, Karnataka, and Andhra Pradesh.    - Origin: Mahabaleshwar in Maharashtra. Flows through Maharashtra, Karnataka, Telangana, and Andhra Pradesh. 3. Godavari River Dispute:    - Reason: Contention over the utilization and distribution of Godavari River water for various purposes, including agriculture and industry.    - Origin: Trimbak in Maharashtra. Flows through Maharashtra, Chhattisgarh, Telangana, and Andhra Pradesh. 4. Yamuna River Dispute:    - Reason: Allocation of Yamuna River water for drinking, irrigation, and other needs, with conflicts arising between Haryana, Delhi, and

The Normalized Difference Vegetation Index (NDVI) is a numerical indicator that uses the red and near-infrared spectral bands. NDVI is highly associated with vegetation content. High NDVI values correspond to areas that reflect more in the near-infrared spectrum. Higher reflectance in the near-infrared correspond to denser and healthier vegetation. Formula NDVI = (NIR – Red) / (NIR + Red) NDVI (Landsat 8) = (B5 – B4) / (B5 + B4) Green Normalized Difference Vegetation Index (GNDVI): Green Normalized Difference Vegetation Index (GNDVI) is modified version of NDVI to be more sensitive to the variation of chlorophyll content in the crop. " The highest correlation values with leaf N content and DM were obtained with the GNDVI index in all data acquisition periods and both experimental phases. … GNDVI was more sensible than NDVI to identify different concentration rates of chlorophyll, which is highly correlated at nitrogen, in two species of plants." (Gitelson et al. 1996) Formula

Short-Wave Infrared (7, 6 4) The short-wave infrared band combination uses SWIR-2 (7), SWIR-1 (6), and red (4). This composite displays vegetation in shades of green. While darker shades of green indicate denser vegetation, sparse vegetation has lighter shades. Urban areas are blue and soils have various shades of brown. Agriculture (6, 5, 2) This band combination uses SWIR-1 (6), near-infrared (5), and blue (2). It's commonly used for crop monitoring because of the use of short-wave and near-infrared. Healthy vegetation appears dark green. But bare earth has a magenta hue. Geology (7, 6, 2) The geology band combination uses SWIR-2 (7), SWIR-1 (6), and blue (2). This band combination is particularly useful for identifying geological formations, lithology features, and faults. Bathymetric (4, 3, 1) The bathymetric band combination (4,3,1) uses the red (4), green (3), and coastal bands to peak into water. The coastal band is useful in coastal, bathymetric, and aerosol studies because

  1. Aquifers:    - Definition: Aquifers are rocks and soils that possess both porosity and permeability.    - Porosity: Refers to the presence of open spaces (pores) within the material.    - Permeability: Indicates the ability of the material to transmit fluids (water, in this context) through those pores. 2. Aquicludes:    - Definition: Aquicludes are rocks and soils that have porosity but lack permeability.    - Porosity: They contain open spaces, but...    - Permeability: ...are not conducive to the easy movement of fluids due to the lack of interconnected pathways. 3. Aquitards:    - Definition: Aquitards have porosity, but their permeability is limited.    - Porosity: They have open spaces...    - Limited Permeability: ...yet the movement of fluids is slower or restricted compared to aquifers due to lower permeability. 4. Aquifuge:    - Definition: Aquifuge rocks and soils have neither porosity nor permeability.    - No Porosity: They lack open spaces for water to be stored...  

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 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 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

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 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