Kriging in GIS and variogram

Kriging is an advanced spatial interpolation technique used in GIS (Geographic Information System) that estimates values for unknown locations based on the values observed at nearby known locations. It is a geostatistical method that takes into account not only the distances between points but also the spatial correlation or variability in the data.

Unlike simpler interpolation methods like IDW, which assume a constant variation across the study area, kriging incorporates the spatial autocorrelation of the data to produce more accurate and precise estimates. Kriging considers the spatial arrangement and patterns of the data points to generate a surface that honors the underlying spatial structure.

The key principle behind kriging is the variogram, which quantifies the spatial correlation between pairs of points at different distances. The variogram measures how the values of nearby points vary from each other as a function of distance. It provides information about the spatial dependence or variability in the dataset.

The kriging process involves three main steps:

1. Variogram modeling: The first step in kriging is to construct a variogram, which is a plot of the semivariance (a measure of dissimilarity or variability) against distance or lag between pairs of points. The variogram helps to understand the spatial structure of the data and determine the range, sill, and nugget effect. Based on the variogram, a mathematical model is fitted to describe the spatial correlation.

2. Interpolation: Once the variogram is modeled, kriging calculates the weights or coefficients for the known points based on their spatial relationship to the target location. The weights are determined through a process known as kriging equations, which consider the variogram and covariance between points. These equations generate the optimal weights that minimize the prediction error.

- Ordinary Kriging (OK): Assumes a constant mean value across the study area.

- Simple Kriging (SK): Accounts for an unknown mean value, estimating it from the data.

- Universal Kriging (UK): Incorporates additional spatially correlated variables (covariates) in addition to the location coordinates.

3. Prediction: The final step is the estimation of values at the unknown locations using the calculated weights. Kriging provides not only the predicted values but also the estimation error or uncertainty associated with each prediction. This information can be valuable in decision-making processes.

Kriging is particularly useful when dealing with spatial datasets that exhibit spatial autocorrelation, anisotropy (directional dependence), or irregularly spaced points. It provides a more sophisticated approach to spatial interpolation by considering the inherent spatial relationships in the data.

GIS software typically provides various kriging algorithms and tools that allow users to model the variogram, perform the interpolation, and generate kriging predictions and associated error maps.

Comments

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...

Solar Radiation and Remote Sensing

Satellite Remote Sensing Satellite remote sensing is the science of acquiring information about Earth's surface and atmosphere without physical contact , using sensors mounted on satellites. These sensors detect and record electromagnetic radiation (EMR) that is either emitted or reflected from the Earth's surface. Solar Radiation & Earth's Energy Balance Solar Radiation is the primary source of energy for Earth's climate system. It originates from the Sun and travels through space as electromagnetic waves . Incoming Shortwave Solar Radiation (insolation) consists mostly of ultraviolet, visible, and near-infrared wavelengths . When it reaches Earth, it can be: Absorbed by the atmosphere, clouds, or surface Reflected back to space Scattered by atmospheric particles Outgoing Longwave Radiation is the infrared energy emitted by Earth back into space after absorbing solar energy. This process helps maintain Earth's thermal bala...

Morpho-Tectonic Framework of India

The MorphoTectonic Framework of India refers to the combined study of the country's landforms (morphology) and its geological tectonic features. This framework provides insights into how geological forces have shaped India's topography over millions of years. Here's a breakdown of this concept: 1. Morphology: This aspect focuses on the physical features and landforms of India. It includes the study of mountains, plateaus, plains, valleys, rivers, and other surface features. For example, the Himalayas, Western Ghats, IndoGangetic Plains, and Deccan Plateau are prominent morphological features of India. 2. Tectonics: Tectonics deals with the movement and deformation of the Earth's lithosphere (the outermost rigid layer of the Earth). In the case of India, it primarily involves the interactions of the Indian Plate with neighboring tectonic plates. India is situated at the convergence of several major tectonic boundaries: Collision with the Eurasian Plate: The most sign...

Neighbourhood Operations

Neighbourhood Operations in GIS? In GIS and raster data , neighbourhood operations look at a group of nearby pixels (not just one) to understand or change a pixel's value. Think of it like checking what's around a house before deciding what color to paint it! Why "Neighbourhood"? Each pixel has " neighbours " (just like how your house has nearby houses). Neighbourhood operations check these nearby pixels and do some calculation to get a new value. 1. Aggregations (Summarizing Nearby Values) Aggregation means combining values of several pixels into one. We do this to: Find the average of surrounding pixels Find the minimum or maximum value Smooth the map (make it less rough) 🧒🏻 Example: Imagine checking the test scores of 9 students sitting around you and finding the average score . That's aggregation! 2. Filtering Techniques Filtering is used to improve or highlight features in a raster image, just like f...

India – Geographic Location – Spatial Significance

India's geographic location holds immense spatial significance due to its position on the world map. Here's an explanation of India's geographic location and its spatial significance: Geographic Location: India is a vast South Asian country located on the Indian subcontinent. Its geographic coordinates are approximately between 8°4'N and 37°6'N latitude and 68°7'E and 97°25'E longitude. It is surrounded by several important bodies of water: - To the west, it has a coastline along the Arabian Sea. - To the east, it is bordered by the Bay of Bengal. - To the south, it faces the Indian Ocean. - To the north, India shares its land borders with Pakistan, China, Nepal, Bhutan, Bangladesh, and Myanmar. Spatial Significance: 1. Strategic Location: India's location places it at the crossroads of South Asia and the Indian Ocean region. This strategic position has made it historically important for trade, diplomacy, and geopolitics. 2. Trade and Commerce: India...

Vineesh V, Geography

Search This Blog