MY_PORTFOLIO

Land Surface Temperature (LST) is an important parameter used in various scientific and environmental studies to understand surface energy fluxes, monitor urban heat islands, assess vegetation stress, and study climate change impacts. Landsat 8, a satellite operated by NASA and the USGS, captures multispectral imagery that can be used to derive Land Surface Temperature.  Here's a brief overview of how LST is estimated using Landsat 8 data: 1. Thermal Infrared Band: Landsat 8 carries the Thermal Infrared Sensor (TIRS), which captures data in two thermal bands:  Band 10 (10.60-11.19 µm) and Band 11 (11.50-12.51 µm). These bands are sensitive to emitted thermal radiation from the Earth's surface. 2. Radiance and Brightness Temperature Conversion: Radiance values recorded by Landsat 8 TIRS are converted to brightness temperatures using calibration coefficients and formulas provided by the sensor's specifications. This step accounts for sensor-specific characteristics and atmos...

The Topographic Wetness Index (TWI) and Normalized Difference Water Index (NDWI) are both used in geospatial analysis but serve different purposes and are calculated using distinct methodologies.  Here are the key differences between TWI and NDWI: 1. Purpose:           TWI: It quantifies the propensity of a landscape to accumulate water based on terrain characteristics derived from                                    digital elevation models (DEMs). TWI assesses the potential wetness of an area.         NDWI: Primarily used for water body detection, NDWI identifies the presence or absence of water in satellite or aerial                          imagery by leveraging differences in the reflectance of near-infrared and green or shortwave infrared band...

The Topographic Wetness Index (TWI) is a terrain-based algorithm used in hydrology and environmental modeling to quantify the degree of wetness or soil moisture content in a landscape. It calculates the propensity of an area to accumulate water based on terrain characteristics derived from digital elevation models (DEMs).  Here's a brief explanation of the TWI: Calculation Method: TWI is derived from the ratio of local upslope contributing area to the tangent of the slope angle. The formula for TWI often involves the following steps: Slope Calculation: Calculating the slope or gradient of the terrain using elevation data. Steeper slopes generally have lower TWI values. Flow Accumulation: Determining the upslope contributing area, which represents the accumulated flow or water that moves downslope towards a specific location. TWI Formula: The TWI calculation involves dividing the natural logarithm (ln) of the upslope contributing area by the slope. The resulting value represents...

The Normalized Difference Water Index (NDWI) is a spectral index used in remote sensing and geographic information systems (GIS) to identify and analyze the presence of water in satellite or aerial imagery. NDWI is particularly valuable for various applications, including environmental monitoring, land cover classification, and water resource management.  Here's a brief overview of NDWI: NDWI can be calculated using Sentinel-2 data by utilizing the bands available in its multispectral sensors. Specifically, NDWI is typically computed using the following bands:   NIR (Near-Infrared): Sentinel-2 band 8 (approximately 842-872 nm) Green : Sentinel-2 band 3 (approximately 534-564 nm) Key Characteristics: Water Detection: NDWI is effective in identifying the presence of water because water absorbs and scatters light differently than other surfaces. As a result, NDWI values tend to be higher in areas with water bodies. Scale Independence: NDWI can be applied at different spatial re...