Geographical Techniques MCQ Quiz in मल्याळम - Objective Question with Answer for Geographical Techniques - സൗജന്യ PDF ഡൗൺലോഡ് ചെയ്യുക

Lorenz curve is a mathematical curve that shows a visual extent of departure for any given distribution.

Lorenz curve:

• In economics, the Lorenz curve is a graphical representation of the distribution of income or of wealth.
• It was developed by Max O. Lorenz in 1905 for representing inequality of wealth distribution.
• The percentage of households is plotted on the x-axis, the percentage of income on the y-axis.
• The values are cumulative in nature.
• It can also be used to show the distribution of assets. In such use, many economists consider it to be a measure of social inequality.
• It is also useful in business modeling: e.g., in consumer finance, to measure the actual percentage y% of delinquencies attributable to the x% of people with worst risk scores.

Gini Coefficient:

• The Gini coefficient is a single number aimed at measuring the degree of inequality in a distribution.
• It was developed by the Italian statistician and sociologist Corrado Gini and published in his 1912 paper Variability and Mutability
• It is most often used in economics to measure how far a country's wealth or income distribution deviates from a totally equal distribution.
• G = A/(A + B)
• It is also equal to 2A and to 1 − 2B due to the fact that A + B = 0.5
• Since the axes scale from 0 to 1

Characteristics of a histogram:

• A histogram is a chart that plots the distribution of a numeric variable’s values as a series of bars.
• Each bar typically covers a range of numeric values called a bin or class.
• A bar’s height indicates the frequency of data points with a value within the corresponding bin.
• The histogram generally shows a frequency distribution.
• In order to use a histogram, we simply require a variable that takes continuous numeric values.
• Histograms are good for showing general distributional features of dataset variables. 

• A histogram is used to summarize discrete or continuous data.

Parts of a Histogram

1. The title: The title describes the information included in the histogram.
2. X-axis: The X-axis are intervals that show the scale of values under which the measurements fall.
3. Y-axis: The Y-axis shows the number of times that the values occurred within the intervals set by the X-axis.
4. The bars: The height of the bar shows the number of times that the values occurred within the interval, while the width of the bar shows the interval that is covered. For a histogram with equal bins, the width should be the same across all bars.

A graphical presentation of a histogram,

Therefore, it is clear that Histogram is associated with Continuous frequency distribution.

The correct answer is Colours.Important Points

•  Chorochromatic maps use colors to represent geographical data. These maps often use different colors to indicate different categories of data.
• For example, a chorochromatic map might use one color to represent mountainous areas, another color to represent plains, and yet another to represent bodies of water.

Therefore, the correct answer from your options is "1) Colours"
Additional Information

Lines:

• In cartography, lines are typically used to represent features that are linear in nature, such as roads, rivers, or boundaries. Isoline maps, which include contour maps, use lines to connect points of equal value.
• For example, on a contour map, each line represents a specific elevation above sea level.

Points:

• Point symbols are used to represent specific locations or discrete data points on a map.
• These can include things like cities, individual landmarks, or data sampling locations.

Pictures:

• Pictorial symbols or pictograms, which can be considered as a type of picture, are often used on maps to represent particular features or points of interest.
• For example, a small icon of an airplane might be used to represent the location of an airport, or a tree symbol might be used to represent a national park. This type of representation is common on tourist and thematic maps.

Answer

Option 3) (B), (C) and (E) only

Maps are the representation of various parts of Earth showing the details on a particular scale. Maps can be classified on the basis of scale into four types.

Key Points

Cadastral Maps:

Cadastral Maps are drawn on a very large scale, varying from 16 inches to a mile, to 32 inches to a mile. Most of the cadastral map has a scale between 1: 500 and 1: 2,500. They show all possible details of an area. These are drawn especially to demarcate the boundaries of fields, buildings to register the ownership.

Topographical Map:

Topographical Maps are drawn on a large scale which is smaIIer than that of Cadastral maps. They show principal topographic forms like relief, drainage, towns, village, forests, etc. The scale varies from 1:25000 to 1:50000.

Wall Maps:

Wall Maps are also known as classrooms, as they are used for class room study. Their scale is smaller than that of the topographicaI maps but larger than the Globe. The scale for wall maps ranges from 1:100000 to 1:500000.

Globe: 

Globe is drawn on a very small scale giving general information about the physical, climatic, and economic characteristics of different regions. They have a scale of 1:1000000 or smaller .

Additional Information

Maps on the basis of purpose can be classified into different types. These are Political Maps, Historical Maps, Economic Maps, Weather and Climatic Maps, Relief Maps, Geological Maps, etc. Hence the correct sequence of maps from larger to smaller scale is Cadastral, Topographic, Wall, and Globe.

Correct Answer: ​1: 10,000

Map Scale:

• A representative fraction (RF) is the ratio of a distance on the map to a distance on the ground.
• Representative Fraction ( R. F. ) shows the relationship between the map distance and the corresponding ground distance in units of length.
• R. F. is generally shown infractions because it shows how much the real world is reduced to fit on the map.
• For example, a fraction of 1: 24,000 shows that one unit of length on the map represents 24,000 of the same units on the ground i.e. one mm, one cm, or one inch. on the map representing 24,000 mm, 24,000 cm, and 24,000 inches, respectively of the ground.

Key Points

•  According to their scale, all options classified as, 1: 10,000 = Cadastral map, 1: 125,000 = Topographical map, 1 : 1,000,000 = Wall map, 1 : 3,000,000 = Atlas map.
• In Cadastral Map Shows the area on a large scale. 
• A 'large' scale map is one in which a given part of the Earth is represented by a large area on the map.
• Large scale maps generally show more detail than small scale maps because at a large scale there is more space on the map in which to show features.
• Large scale maps are typically used to show site plans, local areas, neighborhoods, towns, etc. 1:2,500 is an example of a large scale.
• A large-scale map showing the boundaries of subdivisions of land, usually with the directions and lengths thereof and the areas of individual tracts, compiled for the purpose of describing and recording ownership.
• Large-scale diagrams or map shows more precise dimensions and features.
• Cadastral maps commonly range from scales of 1:500 to 1:10,000.​

Additional Information

• The scale of a map is the ratio of a distance on the map to the corresponding distance on the ground. This simple concept is complicated by the curvature of the Earth's surface, which forces scale to vary across a map. The scale on a map shows the size of the area represented by the map. For example, a scale of 1:10,000 on a map means that 1 mm on the map is the same as 10,000 mm in reality. 10,000 mm is the same as 10 m. Different maps have different scales, such as 1:50,000 or 1:25,000.

Correlation coefficient:

• The correlation coefficient is a statistical measure of the strength of the relationship between the relative movements of two variables.
• The values range between -1.0 and 1.0. A calculated number is greater than 1.0 or less than -1.0 means that there was an error in the correlation measurement.
• A correlation of -1.0 shows a perfect negative correlation, while a correlation of 1.0 shows a perfect positive correlation.
• A correlation of 0.0 shows no linear relationship between the movements of the two variables.
• The coefficient of correlation is the square root of the coefficient of determination.
• The zero value of the correlation coefficient cannot estimate the value of a dependent variable.
• A value of exactly 1.0 means there is a perfect positive relationship between the two variables.
• For a positive increase in one variable, there is also a positive increase in the second variable.
• A value of -1.0 means there is a perfect negative relationship between the two variables.
• Pearson's correlation coefficient,

	=	correlation coefficient
	=	values of the x-variable in a sample
	=	mean of the values of the x-variable
	=	values of the y-variable in a sample
	=	mean of the values of the y-variable

Therefore, c and d are true.

The correct answer is: C, B, A, D

Key Points

• Normal Distribution Basics:
  • It is symmetric about the mean, with the highest frequency occurring at the mean score.
  • The frequency decreases as we move away from the mean in either direction.
  • The total area under the normal curve equals 1, representing total probability or total frequency.
• Interpretation of Intervals Relative to the Mean (40):
  • C (30 to X̅): This interval ranges from 30 up to the mean 40, covering a 10-unit range just below the mean. Since it is close to the mean, it contains relatively high frequency.
  • B (X̅ to 55): This interval goes from 40 to 55, covering 15 units just above the mean. It contains slightly less frequency compared to C, as it moves further from the mean.
  • A (30 to 50): This interval spans from 30 to 50, covering 20 units around the mean, including parts below and above it. It includes frequencies from both sides of the mean, thus has a moderate total frequency.
  • D (10 to X̅): This is the largest interval extending farthest below the mean (10 to 40), covering 30 units. However, since it stretches further away from the mean, the average frequency per unit is lower, and the overall frequency is less concentrated.
• Frequency Ordering Logic:
  • The highest frequencies are near the mean; intervals closer to the mean have higher frequency densities.
  • Intervals extending farther from the mean have lower frequency densities due to the shape of the normal curve.
  • Therefore, among the given intervals, the one closest and smallest around the mean (30 to 40) has the highest frequency, and the widest interval extending farthest (10 to 40) has the lowest.

Additional Information

• In a normal distribution, approximately 68% of data lies within one standard deviation from the mean. Although the standard deviation is not given, the frequency concept still follows the proximity principle: scores nearer the mean have higher occurrence.
• Interval C (30 to 40) is closest to the mean on the lower side and therefore will contain the highest frequency among the intervals listed.
• Interval B (40 to 55) moves away from the mean but still within a moderate range, so frequency is somewhat less than C but more than the larger intervals.
• Interval A (30 to 50) includes parts of both sides of the mean but is broader and thus has a moderate frequency, less than intervals closer to the mean.
• Interval D (10 to 40), despite being large, extends farthest from the mean, where frequencies tail off, resulting in the lowest frequency of all intervals.
• Thus, ordering frequencies in ascending order as C, B, A, D aligns with the characteristics of the normal distribution curve.

the correct answer is Digital Globe

The agency associated with IKONOS remote sensing data is DigitalGlobe.

Important Points 

•  DigitalGlobe is a U.S.-based company. It was founded in 1992 as EarthWatch Inc. (previously known as EarthWatch Inc.) and later rebranded as DigitalGlobe.
• The company has headquarters in Westminster, Colorado, United States, and provides satellite imagery and geospace data services to customers around the world.
• IKONOS was the first commercial high-resolution remote sensing satellite launched in 1999
• The satellite was capable of capturing images with a resolution of one meter and provided high-quality satellite imagery for various applications such as urban planning, environmental monitoring, and mapping.
• Much of Google Earth and Google Maps' high-resolution imagery is provided by DigitalGlobe, as is imagery used in TerraServer.
• The IKONOS satellite
  •  is a high-resolution satellite operated by MAXAR Technologies Inc.
  • Its capabilities include capturing a 3.2m multispectral,
  •  Near-Infrared (NIR) 0.80-meter panchromatic resolution at the nadir.
  • Its applications include both urban and rural mapping of natural resources and natural disasters, tax mapping, agriculture and forestry analysis, mining, engineering, construction, and change detection.

Additional Information 

There are many remote sensing agencies and satellite companies operating around the world. Some of the notable ones include:

• Airbus Defence and Space - Provider of Earth Observation and Geo-Intelligence solutions with a fleet of satellites including Pleiades, TerraSAR-X, and TanDEM-X.

• Maxar Technologies - One of the largest providers of Earth Intelligence and geospatial information with a fleet of satellites including WorldView, RADARSAT, and Globalstar.

• CNSA (China National Space Administration) - The Chinese government agency responsible for the national space program and operates the China remote sensing satellite system with satellites such as Ziyuan, Gaofen, and Yaogan.

• ISRO (Indian Space Research Organization) - The Indian government agency responsible for the country's space program and operates a fleet of remote sensing satellites including Resourcesat, Cartosat, and . Oceansat

• ROSCOSMOS (Russian Federal Space Agency) - The Russian government agency responsible for the country's space program and operating remote sensing satellites such as Kanopus and Resure

The correct answer is -Statement I is true but Statement II is false.
Important Points 

• Statement I: Digital Elevation Model (DEM) is a raster format.
  • This statement is true.
  • Digital Elevation Model (DEM) is a type of data model that represents the surface of the Earth's terrain as a grid of elevation values.
  • It is stored in a raster data format, which is a grid of cells that represent a continuous surface.
• Statement II: All pixels are of different shapes and sizes in DEM.
  • This statement is false.
  • In a Digital Elevation Model (DEM),
  • the pixels (also known as cells) are all of the same size and shape.
  • Each cell represents a particular elevation value and they are arranged in a grid format to form a continuous surface representation of the terrain.

Key Points Digital Elevation Model (DEM)

•  A digital elevation model is a bare-earth raster grid referenced to a vertical datum.
• When you filter out non-ground points such as bridges and roads, you get a smooth digital elevation model.
• The built (power lines, buildings, and towers) and natural (trees and other types of vegetation) aren’t included in a DEM.
• it is a digital cartographic dataset that represents a continuous topographic elevation surface through a series of cells.
• Each cell represents the elevation (Z) of a feature at its location (X and Y).
• When you void vegetation and man-made features from elevation data, you generate a DEM.
• A bare-earth elevation model is particularly useful in hydrology, soils, and land use planning
• Some of the remote sensing methods for obtaining DEM surfaces are:
  • SATELLITE INTERFEROMETRY
  • PHOTOGRAMMETRY
  • LiDAR

Additional Information 

When it comes to elevation, we have three different ways to model elevation. For example, it includes:

• DEM – Digital Elevation Models
• DSM – Digital Surface Models
• DTM – Digital Terrain Models and even
• TIN – Triangular Irregular Networks

 Digital Surface Model (DSM)​

• A DSM captures the natural and built features on the Earth’s surface.
• A DSM is useful in 3D modeling for telecommunications, urban planning, and aviation.
• Urban planners use DSM to check how a proposed building would affect the viewshed of residents and businesses.

 Digital Terrain Models

• A DTM is a vector data set composed of regularly spaced points and natural features such as ridges and brake lines.
• A DTM augments a DEM by including linear features of the bare-earth terrain.
• This means that a DTM is simply an elevation surface representing the bare earth referenced to a common vertical datum.

Triangular Irregular Network (TIN)

• is a type of digital terrain model that represents the topographic surface of the Earth as a set of non-overlapping triangles.
• In a TIN, the vertices of the triangles represent sample points of the terrain, such as the elevations of peaks, valleys, and ridges, while the edges of the triangles connect these points to form a network of triangles.
• The elevation values within each triangle are calculated using linear interpolation based on the elevations of its three vertices.

Correct Answer: D

Key Points

• A negatively skewed distribution is the distribution composed of mostly large observations and a few relatively small observations. For example, a test score on a very easy test of some general education courses will probably follow a negatively skewed distribution. A negatively skewed (also known as left-skewed) distribution is a type of distribution in which more values are concentrated on the right side (tail) of the distribution graph while the left tail of the distribution graph is longer.
• Most of the students will do very well, but a few students may never come to class and will score very poorly, so test scores will be composed of many high scores and a few relatively very low scores.
• In this case, Median should be used instead of mean since it is not influenced by a few relatively very low scores.
• in a negatively skewed distribution mean is less than the median since the mean is influenced by a few relatively very low scores.

Important Points

•  In a Positively skewed distribution, the mean is greater than the median as the data is more towards the lower side and the mean average of all the values, whereas the median is the middle value of the data

Additional Information

• A positively skewed distribution is the distribution that is composed of mostly small observations and a few relatively or extremely large observations. For example, test scores on a very difficult exam probably follow a positively skewed distribution.
• Because most students probably will Score quite low and only a few students probably will score high. To this date, I still remember my biochemistry mid-term at the University of Calcutta. we have over 120 students with 115 scores of 20- 50 out of a hundred, only less than 5 score 70 to 80. for this skewed distribution, the median is the one to use since it is not influenced by a few relative ne very high scores.