Skip to main content

Application of Remote Sensing. Vegetation Mapping

Mapping and monitoring of vegetation cover and changes: Remote sensing can be used to map and monitor vegetation cover, including forests, grasslands, and croplands, and to detect changes in vegetation over time.


Identification of different types of vegetation: Remote sensing can be used to classify different types of vegetation, such as deciduous, coniferous, and mixed forests, and to differentiate between different types of crops.


Measurement of vegetation productivity and health: Remote sensing can be used to measure the productivity and health of vegetation, by generating vegetation indices such as NDVI (Normalized Difference Vegetation Index) and LAI (Leaf Area Index)


Assessment of water resources and watersheds: Remote sensing can be used to assess the health and distribution of vegetation in relation to water resources and watersheds, which can help in managing irrigation systems, water supply and flood control.


Forest inventory and management: Remote sensing can be used to estimate forest biomass, volume, and species composition, which can help in managing forest resources and planning for sustainable forest management


Detection of invasive species: Remote sensing can be used to detect and map invasive plant species, which can help in managing and controlling the spread of these species in natural ecosystems.


Identification of potential restoration sites: Remote sensing can be used to identify areas where vegetation restoration is needed and to assess the success of restoration efforts.


Identification of land use and land cover changes: Remote sensing can be used to identify and map land use and land cover changes, including urbanization, deforestation, and agriculture expansion, which can help in managing and conserving natural resources.





Comments

Popular posts from this blog

Regional Geography, Systematic Geography, Idiographic, Nomothetic, Inductive and Deductive Approaches

T wo major ways of studying Geography : the Regional Approach and the Systematic Approach . It also explains the related ideas of idiographic vs. nomothetic and inductive vs. deductive reasoning , especially in the context of the Hartshorne–Schaefer debate . 1. Regional Geography: “All About One” Regional Geography studies one particular region in detail . A region is an area that has some degree of homogeneity (sameness) within its boundary but is also unique or different from other regions . For example, if we study Palakkad District , we may study: Relief and drainage Climate Soil Vegetation Agriculture Population Occupation Economy Culture Political characteristics The purpose is to understand the complete geographical personality of Palakkad and the relationships among its different features. Key concepts Region: A geographical area with identifiable characteristics and boundaries. Homogeneity: Si...

Kuhn’s Paradigms

The given content explains Thomas S. Kuhn’s model of scientific development , its application to geography, and criticisms by Karl Popper, Paul Feyerabend, Michel Foucault , and others. 1. Basic Idea Kuhn argued that science does not develop continuously in a straight line . Instead, scientific development occurs through: Preparadigm → Paradigm → Normal Science → Crisis → Scientific Revolution → New Paradigm A new paradigm may replace an older one, producing a major change in the way scientists understand and study a subject. Concepts and Terminologies Concept / Term Simple Meaning Paradigm A commonly accepted framework/model that guides scientific research Exemplar A successful concrete problem-solution used as a model for future research Disciplinary Matrix Shared beliefs, values, concepts, methods and techniques of a scientific community Preparadig...

Multispectral and Hyperspectral Imaging Systems

The main idea is how a remote-sensing sensor collects information about an area . A sensor does not simply take an ordinary photograph. It measures the electromagnetic energy reflected or emitted by objects in different wavelength bands . Depending on how many bands are measured and how the sensor collects them, different imaging systems are used. 1. Multispectral vs. Hyperspectral Multispectral imaging (MSI) records information in a limited number of relatively broad, separate spectral bands , such as blue, green, red, near-infrared and shortwave infrared. Hyperspectral imaging (HSI) records information in many narrow and usually contiguous spectral bands . Therefore, it provides a much more detailed spectral signature of each pixel. The resulting dataset is commonly called a hyperspectral data cube (hypercube) because it contains: X-axis → spatial information Y-axis → spatial information Z-axis → wavelength/spectral information Thus, hype...

Discrete Detectors and Scanning mirrors Across the track scanner Whisk broom scanner.

Multispectral Imaging Using Discrete Detectors and Scanning Mirrors (Across-Track Scanner or Whisk Broom Scanner) Multispectral Imaging:  This technique involves capturing images of the Earth's surface using multiple sensors that are sensitive to different wavelengths of electromagnetic radiation.  This allows for the identification of various features and materials based on their spectral signatures. Discrete Detectors:  These are individual sensors that are arranged in a linear or array configuration.  Each detector is responsible for measuring the radiation within a specific wavelength band. Scanning Mirrors:  These are optical components that are used to deflect the incoming radiation onto the discrete detectors.  By moving the mirrors,  the sensor can scan across the scene,  capturing data from different points. Across-Track Scanner or Whisk Broom Scanner:  This refers to the scanning mechanism where the mirror moves perpendicular to the direction of flight.  This allows for t...

Satalite

Landsat → Land resources SPOT → High-resolution mapping IRS → Indian natural-resource mapping ASTER → Geology + thermal + DEM QuickBird → Very high spatial resolution MODIS → Daily global monitoring GOES → Weather monitoring AVHRR → Weather + vegetation + ocean AVIRIS → Hyperspectral imaging Highest spectral resolution: AVIRIS (224 narrow bands) Highest spatial resolution in this list: QuickBird (~0.61 m PAN) Highest temporal frequency: GOES (minutes) Best broad global monitoring: MODIS Indian sensors: IRS-LISS III and LISS IV Hyperspectral: AVIRIS Thermal + multispectral + DEM: ASTER abbreviations MSS – Multispectral Scanner System TM – Thematic Mapper ETM+ – Enhanced Thematic Mapper Plus GOES – Geostationary Operational Environmental Satellite AVHRR – Advanced Very High Resolution Radiometer HRV – High Resolution Visible HRVIR – High Resolution Visible and Infrared HRG – High Resolution Geometric ...