Terminology. Remote Sensing

Absorptance : The ratio of the radiant energy absorbed by a substance to the energy

it receives.

Band : The specific wavelength interval in the electromagnetic spectrum.

Digital image : An array of digital numbers (DN) arranged in rows and columns,

having the property of an intensity value and their locations.

Digital Number : An intensity value of a pixel in a digital image.

Digital Image Processing : The numerical manipulation of DN values for the purpose

of extracting information about the phenomena of the surface they represent.

Electromagnetic Radiation (EMR) : The Energy propagated through a space or a

medium at a speed of light.

Electromagnetic Spectrum : The continuum of EMR that ranges from short wave

high frequency cosmic radiations to long wavelength low frequency radio waves.

False Colour Composite (FCC) : An artificially generated colour image in which

blue, green and red colours are assigned to the wavelength regions to which they do

not belong in nature. For example, in standard a False Colour Composite blue is

assigned to green radiations (0.5 to 0.6 µm), green is assigned to red radiations (0.6

to 0.7 µm and red is assigned to Near Infrared radiation (0.7 to 0.8 µm).

Gray scale : A medium to calibrate the variations in the brightness of an image that

ranges from black to white with intermediate grey values.

Image : The permanent record of a scene comprising of natural and man-made

features and activities, produced by photographic and non–photographic means.

Scene : The ground area covered by an image or a photograph.

Sensor : Any imaging or non–imaging device that receives EMR and converts it into

a signal that can be recorded and displayed as photographic or digital image.

Reflectance : The ratio of the radiant energy reflected by a substance to the energy

it receives.

Spectral Band : The range of the wavelengths in the continuous spectrum such as

the green band ranges from 0.5 to .6 µ and the range of NIR band 0.7 to 1.1 µ.

Comments

GIS data continuous discrete ordinal interval ratio

In Geographic Information Systems (GIS) , data is categorized based on its nature (discrete or continuous) and its measurement scale (nominal, ordinal, interval, or ratio). These distinctions influence how the data is collected, analyzed, and visualized. Let's break down these categories with concepts, terminologies, and examples: 1. Discrete Data Discrete data is obtained by counting distinct items or entities. Values are finite and cannot be infinitely subdivided. Characteristics : Represent distinct objects or occurrences. Commonly represented as vector data (points, lines, polygons). Values within a range are whole numbers or categories. Examples : Number of People : Counting individuals on a train or in a hospital. Building Types : Categorizing buildings as residential, commercial, or industrial. Tree Count : Number of trees in a specific area. 2. Continuous Data Continuous data is obtained by measuring phenomena that can take any value within a range...

History of GIS

The history of Geographic Information Systems (GIS) is rooted in early efforts to understand spatial relationships and patterns, long before the advent of digital computers. While modern GIS emerged in the mid-20th century with advances in computing, its conceptual foundations lie in cartography, spatial analysis, and thematic mapping. Early Roots of Spatial Analysis (Pre-1960s) One of the earliest documented applications of spatial analysis dates back to 1832 , when Charles Picquet , a French geographer and cartographer, produced a cholera mortality map of Paris. In his report Rapport sur la marche et les effets du choléra dans Paris et le département de la Seine , Picquet used graduated color shading to represent cholera deaths per 1,000 inhabitants across 48 districts. This work is widely regarded as an early example of choropleth mapping and thematic cartography applied to epidemiology. A landmark moment in the history of spatial analysis occurred in 1854 , when John Snow inv...

Disaster Management

1. Disaster Risk Analysis → Disaster Risk Reduction → Disaster Management Cycle Disaster Risk Analysis is the first step in managing disasters. It involves assessing potential hazards, identifying vulnerable populations, and estimating possible impacts. Once risks are identified, Disaster Risk Reduction (DRR) strategies come into play. DRR aims to reduce risk and enhance resilience through planning, infrastructure development, and policy enforcement. The Disaster Management Cycle then ensures a structured approach by dividing actions into pre-disaster, during-disaster, and post-disaster phases . Example Connection: Imagine a coastal city prone to cyclones: Risk Analysis identifies low-lying areas and weak infrastructure. Risk Reduction includes building seawalls, enforcing strict building codes, and training residents for emergency situations. The Disaster Management Cycle ensures ongoing preparedness, immediate response during a cyclone, and long-term recovery afterw...

How to find drugs against the Corona. Covid 19

FOR SCIENTISTS (and others interested): How to find drugs against the coronavirus: First clues on how we can beat COVID-19. This shows the many ways we can interfere with its replication cycle by repurposing existing drugs - summarized in today's Science journal. LINK TO ARTICLE: https://science.sciencemag.org/content/367/6485/1412 .... Vineesh V Assistant Professor of Geography, Directorate of Education, Government of Kerala. https://g.page/vineeshvc

Geographic phenomena fields objects boundaries.

In geography, geographic phenomena refer to features or processes that can be observed and studied on Earth's surface. These phenomena can be classified into three main categories: fields , objects , and boundaries . Each category has distinct characteristics, representations, and applications in Geographic Information Systems (GIS). 1. Fields A field represents continuous, spatially varying data where a value is present at every location within the study area. It describes conditions that exist across a geographic area. Characteristics : Continuity : Fields have no discrete boundaries; the data is continuous. Gradual Variability : The values of a field change gradually across space. Representation : Typically modeled using raster data in GIS, where a grid structure assigns a value (e.g., temperature or elevation) to each cell. Examples : Temperature Map : Shows temperature variation across a region. Rainfall Distribution : Displays rainfall levels over a large g...

Vineesh V, Geography

Search This Blog