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aggradational stacking pattern

dominantly aggradational stacking pattern with subordinate progradational intervals. 
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Change Detection

Change detection is the process of finding differences on the Earth's surface over time by comparing satellite images of the same area taken on different dates . After supervised classification , two classified maps (e.g., Year-1 and Year-2) are compared to identify land use / land cover changes .  Goal To detect where , what , and how much change has occurred To monitor urban growth, deforestation, floods, agriculture, etc.  Basic Concept Forest → Forest = No change Forest → Urban = Change detected Key Terminologies Multi-temporal images : Images of the same area at different times Post-classification comparison : Comparing two classified maps Change matrix : Table showing class-to-class change Change / No-change : Whether land cover remains same or different Main Methods Post-classification comparison – Most common and easy Image differencing – Subtract pixel values Image ratioing – Divide pixel values Deep learning methods – Advanced AI-based detection Examples Agricult...

Accuracy Assessment

Accuracy assessment is the process of checking how correct your classified satellite image is . 👉 After supervised classification, the satellite image is divided into classes like: Water Forest Agriculture Built-up land Barren land But classification is done using computer algorithms, so some areas may be wrongly classified . 👉 Accuracy assessment helps to answer this question: ✔ "How much of my classified map is correct compared to real ground conditions?"  Goal The main goal is to: Measure reliability of classified maps Identify classification errors Improve classification results Provide scientific validity to research 👉 Without accuracy assessment, a classified map is not considered scientifically reliable . Reference Data (Ground Truth Data) Reference data is real-world information used to check classification accuracy. It can be collected from: ✔ Field survey using GPS ✔ High-resolution satellite images (Google Earth etc.) ✔ Existing maps or survey reports 🧭 Exampl...

Geographic DBMS

A Relational Database Model stores data in the form of tables . Each table contains: Rows → Individual records Columns → Attributes or fields Tables can be connected using common fields called keys . Terminologies 1. Table A collection of related data arranged in rows and columns. Example: ID Name Population 1 Palakkad 130000 2 Thrissur 315000 2. Row (Record) Represents one feature or entry. 👉 Example "Palakkad" is one record. 3. Column (Field / Attribute) Represents one property of data. 👉 Example Population is a field. 4. Primary Key A unique field used to identify each record. 👉 Example ID column. 5. Foreign Key A field used to connect two tables.  Example in GIS (QGIS / ArcGIS) Suppose you have: Table 1: District Boundary Layer District_ID District_Name 1 Palakkad 2 Malappuram Table 2: Rainfall Data District_ID Rainfall 1 2200 mm 2 2800 mm 👉 Both tables share District_ID Using this field, GIS joins rainfall data to district maps. Where Used in GIS Attribute tables of...

Data File Management in GIS

In Geographic Information Systems (GIS) , a lot of spatial and attribute data are stored in files. Managing these files properly helps in fast searching, updating, and analyzing geographic data . 1️⃣ Simple List File (Unordered File) ✅ Concept A Simple List File is the most basic way of storing data. Records are stored one after another without any order . 👉 There is no sorting or indexing . ✅ Example in GIS Suppose you are storing details of villages in a district. Village ID Village Name Population 103 Kottayi 5400 101 Chittur 12500 107 Nallepilly 8200 Here, the data is stored randomly. IDs are not arranged in order. ✅ How Searching Works If you want to find Village ID 107 : GIS must check each record one by one This takes more time if data is large. ✅ Advantages ✔ Easy to create ✔ Suitable for small datasets ❌ Disadvantages ✖ Slow searching ✖ Difficult to manage large spatial databases 2️⃣ Ordered Sequential File ✅ Concept In an Ordered Sequential File , records are stored in a so...

Disaster Risk Reduction

Disaster Risk Reduction 

Weighted Overlay in GIS: A Spatial Decision-Making Technique

Weighted Overlay is a widely used spatial decision-making technique in Geographic Information Systems (GIS). It functions as an analytical method that balances multiple spatial factors by assigning relative importance to each variable. Essentially, it integrates scientific reasoning with logical evaluation to determine the suitability of locations for specific purposes. In simple terms, Weighted Overlay is a method that combines several spatial raster layers. Each layer represents a different factor influencing the decision-making process. Before integration, the values of each raster layer are standardized to a common evaluation scale, typically ranging from 1 to 5 or 1 to 9. Subsequently, each layer is assigned a weight based on its relative importance. The final suitability value for each cell is calculated by summing the weighted contributions of all layers. The conceptual formula can be expressed as: Final Suitability Value = (Layer 1 × Weight 1) + (Layer 2 × Weight 2) + ... + (La...

River braided

Conceptual diagram of a braided river and its stratigraphic deposits. Zones of thread confluence and thread splitting, shown by blue arrows, facilitate the formation, accretion, and deformation of bank-attached and mid-channel bars. Within a larger channel-belt sand body, bar deposits can be stratigraphically preserved as packages characterized by sigmoidal bar clinothems that accrete in the direction of bar growth and downlap (e.g., blue arrows in cross-stream stratigraphic view) onto older deposits

Folding and Faulting

Folding and Faulting

Anticipatory action

💡Anticipatory action is the smart way to provide humanitarian assistance for forecastable events, ahead of the shock. 🚀 When a pre-agreed forecast threshold is crossed, a set of pre-agreed and pre-financed humanitarian interventions is triggered. Acting before the event protects lives, livelihoods, and dignity. 🤝 Anticipatory action is interwoven with other humanitarian approaches and with climate and development efforts. It builds on early warnings, early action, climate adaptation, and disaster preparedness.