B. Sc. (Sixth Semester) Examination Rural Technology. (Application of Remote Sensing) AR- 7967

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1 B. Sc. (Sixth Semester) Examination 2013 Rural Technology (Application of Remote Sensing) AR Que. 1. Multiple choice question : (i) Which is not the example of continuous data : Answer : Rainfall (ii) Which is not a property of Geo spatial data : Answer : Scale (iii) Geometrical arragements that completely cover a surface is called : Answer : Tessellation (iv) Which statement is not correct : Answer : Polygon are three dimensional entity. (v) What is primary KEY : Answer : To uniquely identify the data (vi) Which type of scanner used in IRS satellite : Answer : Both (a) and (b) (Vii) Preprocessing technique of any images are : Answer : All of these (viii) In the raster data model we represent the data in : Answer : Grid structure (ix) In the vector data model, we represent the data in : Answer : All of these (x) In which DBMS model, we show the one to many relationship between data : Answer : Hierarchical data base model

2 2. Write short answer : Que (i) : Describe the active sensor. Ans. : Active sensors provide their own energy source for illumination. The sensor emits radiation which is directed toward the target to be investigated. The radiation reflected from that target is detected and measured by the sensor. Advantages for active sensors include the ability to obtain measurements anytime, regardless of the time of day or season. Active sensors can be used for examining wavelengths that are not sufficiently provided by the sun, such as microwaves, or to better control the way a target is illuminated. However, active systems require the generation of a fairly large amount of energy to adequately illuminate targets. Some examples of active sensors are a laser fluoro sensor and a synthetic aperture radar (SAR). Que (ii) : Discuss the feature of any one LANDSAT satellite. Ans. : First launched in 1972, the LANDSAT satellite series constitutes one of the longest continuous records in Earth observation. The objective of the LANDSAT program was always been to provide multi-spectral imagery of the Earth's land areas at moderate to high resolution, ( meter horizontal resolution) to support resource assessment, land-cover mapping, and to track inter-annual changes in the environment. Applications of LANDSAT data are quite diverse, comprising Earth Science, commercial applications, mining applications, government and military use. A few examples include mapping land-cover change (forest change, urbanization, etc), monitoring agricultural productivity, monitoring wetland health, mapping geologic resources, and targeting habitats for vectorborne disease eradication. Type of sensor used in LANDSAT satellite are Multi-spectral Scanner (LANDSAT MSS), Thematic MAPPER (LANDSAT TM), Enhanced Thematic MAPPER Plus (LANDSAT ETM+). LANDSAT imagery is relatively highresolution earth observation data that is acquired through sensors on one of the NASA LANDSAT satellites. The satellite sensors acquire high integrity images of the planet surface in a systematic fashion. Users can take this imagery and use it to determine the health and type of vegetation, amount of built surfaces, success of agriculture, or apply it for a myriad other uses like various geological derived applications as well as various mineral exploration activities. LANDSAT imagery is acquired in a very precise manner, to better emphasize particular land cover aspects. Some of the parameters of this precision involve a scene's radiometry, providing distinct characteristics to components of the image scene. These measures help determine what the images are good for, from a science perspective. For example, Bands 1, 2 and 3 are used together to approximate how the real world appears. Bands 4, 5 or 7 from ETM+ are used in combination with 1, 2 or 3 to demonstrate vegetation conditions. Que (iii) : Why data base management system is needed in GIS. Ans : Management of GIS data consists of storing a variety of data categorised under two types, entity (spatial data) and attribute ( aspatial ) data in a way that permits us to retrieve or display any contributions of these data after analysis. GIS database comprises spatial or entity or graphical database, nonspatial or attribue database and a linkage mechanism for their topology, to show the relationship between the spatial data and attribute data for further analysis. Non-spatial data can be stored in any conventional database, whereas spatial data, which is the dominant data in GIS, should have the database, which is capable of handling spatial data. Therefore conventional database has bees adapted to GIS for handling attribute data. The DBMS must allow the definition of data, their attribute, relationship, as well as providing security, an interface between the end users, their application. The other work of DBMS are (i) creating, modifying and deleting the database structure, (ii) adding, updating and deleting records (iii) the extraction of information from data and (iv) maintenance of integrity and application building. (iv) Que : How remote sening and GIS help in disaster management. Ans. Remote sensing or Earth Observation System (EOS) and GIS are among many tools available to disaster management.professionals today making the effective project planning which are more accurate now then ever before. Repetitive or multi-temporal coverage is justified on the basis of the need to study various dynamic phenomena whose changes can be identified over time. These include natural hazard events, changing land

3 usepatterns, and hydrologic and geologic characteristics of the region.from the inherent characteristics, namely, spatial continuity, uniform accuracy and precision, multi-temporal coverage and complete coverage regardless of site location, the remotely sensed data can be used very effectively, for: Quickly assessing severity and impact of damage due to flooding, earthquakes, oil spills and other disasters; Planning efficient escape routes from coastal areas during hurricane season; Charting quickest routes for ambulances to reach victims; Locating places for shelter for victims or refugees; Calculating population density in disaster-prone areas; Rapidly identifying hardest-hit disaster areas in order to provide early warning of potential disasters; Pre-disaster assessments to facilitate planning for timely evacuation and recovery operations during a crisis; Monitoring reconstruction or rehabilitation after a major disaster; and Developing, maintaining or updating accurate base maps. Que (v): Write in brief about the raster format of data structure. Ans. Raster data structure is incorporate the use of a grid-cell data structure where the geographic area is divided into cells, identified by row and column. This data structure is commonly called raster. While the term raster implies a regularly spaced grid other tessellated data structures do exist in grid based GIS systems. The size of cells in a tessellated data structure is selected on the basis of the data accuracy and the resolution needed by the user. There is no explicit coding of geographic coordinates required since that is implicit in the layout of the cells. A raster data structure is in fact a matrix where any coordinate can be quickly calculated if the origin point is known, and the size of the grid cells is known. Since grid-cells can be handled as two-dimensional arrays in computer encoding many analytical operations are easy to program. Several tessellated data structures exist, however only two are commonly used in GIS's. The most popular cell structure is the regularly spaced matrix or raster structure. This data structure involves a division of spatial data into regularly spaced cells. Each cell is of the same shape and size. Squares are most commonly utilized. Since geographic data is rarely distinguished by regularly spaced shapes, cells must be classified as to the most common attribute for the cell. Most raster based GIS software requires that the raster cell contain only a single discrete value. (vi) Que. Discuss the feature of CARTOSAT satellite. Ans. India lanuched two CARTOSAT satellite for mapping purpose. CARTOSAT 1 is the first Indian Remote Sensing Satellite capable of providing in-orbit stereo images. The images are used for Cartographic applications meeting the global requirements. Cameras of this satellite have a resolution of 2.5m (can distinguish a small car). The Cartosat 1 provides stereo pairs required for generating Digital Elevation Models, Ortho Image products, and Value added products for various applications of Geographical Information System (GIS). Some details of CARTOSAT - 1 are given below : 1. Lauunch date - 5 May Lauunch site - SHAR Centre Sriharikota, India 3. Lauunch Vehicle - PSLV-C6 4. Orbit km Polar Sun Synchronous 5. Payloads - PAN FORE, PAN - AFT 6. Orbit Period - 97 min 7. Number of Orbits Per day Revisit - 5 days 9. Mission life - 5 years

4 Section 3 : Write long answer : Que. (1) How vegetative index help in categorization of image vegetations. Ans : Vegetation has a unique spectral signature that enables it to be distinguished readily from other types of land cover in an optical/near-infrared image. The reflectance is low in both the blue and red regions of the spectrum, due to absorption by chlorophyll for photosynthesis. It has a peak at the green region. In the near infrared (NIR) region, the reflectance is much higher than that in the visible band due to the cellular structure in the leaves. Hence, vegetation can be identified by the high NIR but generally low visible reflectance. The shape of the reflectance spectrum can be used for identification of vegetation type. The reflectance spectra of dry grass and green grass is distinguished although they exhibit the generally characteristics of high NIR but low visible reflectance. Dry grass has higher reflectance in the visible region but lower reflectance in the NIR region. For the same vegetation type, the reflectance spectrum also depends on other factors such as the leaf moisture content and health of the plants. These properties enable vegetation condition to be monitored using remotely sensed images. The remote sensing data is used extensively for large area vegetation monitoring.. In many cases of vegetation remote sensing studies, vegetation index has been used as a primary source of information related to the biophysical characteristics of vegetation over large geographic area. Vegetation index, derived from remote sensing data, is used as a single measure of such canopy characteristics as biomass, productivity, leaf area index, photo-synthetically active radiation, or canopy closure. This technique of vegetation index was developed from the unique spectral characteristics of green vegetation in visible and near-infrared wavelengths Most satellite multispectral sensors supply image data obtained at those two spectral bands of red and near-infrared spectrums. Vegetation index is a simple form of mathematical transformation to combine the two bands data into a scale to enhance the characteristics of vegetation. There are three such indices, simple vegetation indices, rational vegetation indces and normalised differential vegetation indices. These indices are computed from the equations VI = Near IR - RED RVI = Red/Near IR NDVI = (Near IR- Red)/ (Near IR + Red Although there are several methods of calculating vegetation index using two spectral bands, the normalized difference vegetation index (NDVI) has been most widely used in many fields of applied remote sensing community. NDVI is calculated by dividing the difference of two spectral reflectance values by the sum of two spectral reflectance values. NDVI = (NIR R) / (NIR + R) The use of NDVI is being expanded beyond the monitoring of seasonal and inter-annual variation of vegetation condition and the mapping of vegetation cover. Recent development of data analysis, it is now being used to extract rather quantitative and sophisticated information related to the biophysical characteristics of vegetation. The biophysical variables that are currently achieved from the satellite data derived NDVI data include leaf area index (LAI), net primary production, and a fraction of photo-synthetically active radiation (FPAR). Que. (ii) Explain the different type imaging and non imaging sensor.

5 Ans : Imaging sensors are sensors that build up a digital image of the field of view. The spatial distribution of the signal strength will be recorded in the spatial distribution of the sensor's response. Non-imaging sensors return a signal based on the intensity of the whole field of view. The response of the sensor doesn't record how the input varies across the field of view. The different type of imaging and non-imaging sensor are : Que. (iii) What is the importance of relational database model in GIS. Ans : A Relational Database Management System (RDBMS) is a software system that provides access to a relational database. The software system is a collection of software applications that can be used to create, maintain, manage and use the database. A "relational database" is a database structured on the "relational" model. Data are stored and presented in a tabular format, organized in rows and columns with one record per row. Some feature of the Relational Database Management System (RDBMS) are : : Data Structure : The table format is simple and easy for database users to understand and use. RDBMSs provide data access using a natural structure and organization of the data. Database queries can search any column for matching entries. Multi-User Access :RDBMSs allow multiple database users to access a database simultaneously. Built-in locking and transactions management functionality allow users to access data as it is being changed, prevents collisions between two users updating the data, and keeps users from accessing partially updated records. Privileges : Authorization and privilege control features in an RDBMS allow the database administrator to restrict access to authorized users, and grant privileges to individual users based on the types of database tasks they need to perform. Authorization can be defined based on the remote client IP address in combination with user authorization, restricting access to specific external computer systems.

6 Network Access :RDBMSs provide access to the database through a server daemon, a specialized software program that listens for requests on a network, and allows database clients to connect to and use the database. Network access allows developers to build desktop tools and Web applications to interact with databases. Speed : The relational database model is not the fastest data structure. RDBMS advantages, such as simplicity, make the slower speed a fair trade-off. Optimizations built into an RDBMS, and the design of the databases, enhance performance, allowing RDBMSs to perform more than fast enough for most applications and data sets. Improvements in technology, increasing processor speeds and decreasing memory and storage costs allow systems administrators to build incredibly fast systems that can overcome any database performance shortcomings. Maintenance : This feature of RDBMSs, provide database administrators with tools to easily maintain, test, repair and back up the databases housed in the system. Many of the functions can be automated using built-in automation in the RDBMS, or automation tools available on the operating system. Language : RDBMSs support a generic language called "Structured Query Language" (SQL). The SQL syntax is simple, and the language uses standard English language keywords and phrasing, making it fairly intuitive and easy to learn. Many RD Que : (iv) Describe the function of data base management system. Ans : The few functions in the DBMS are: 1. Data Dictionary Management The place were DBMS stores definitions of the data elements and their relationships (metadata) is called data dictionary. The DBMS uses this function to look up the required data component structures and relationships. When programs access data in a database they are basically going through the DBMS. This function removes structural and data dependency and provides the user with data abstraction. The Data Dictionary is often hidden from the user and is used by Database Administrators and Programmers. 2. Data Storage Management This particular function is used for the storage of data and any related data entry forms or screen definitions, report definitions, data validation rules, procedural code, and structures that can handle video and picture formats. Users do not need to know how data is stored or manipulated. Also involved with this structure is a term called performance tuning that relates to a database s efficiency in relation to storage and access speed. 3. Data Transformation and Presentation This function exists to transform any data entered into required data structures. By using the data transformation and presentation function the DBMS can determine the difference between logical and physical data formats. 4. Security Management This is one of the most important functions in the DBMS. Security management sets rules that determine specific users that are allowed to access the database. Users are given a username and password or sometimes through biometric authentication (such as a fingerprint or retina scan) but these types of authentication tend to be more costly. This function also sets restraints on what specific data any user can see or manage. 5. Multiuser Access Control Data integrity and data consistency are the basis of this function. Multiuser access control is a very useful tool in a DBMS, it enables multiple users to access the database simultaneously without affecting the integrity of the database. 6. Backup and Recovery Management

7 Backup and recovery is used to when there is potential outside threats to a database. For example if there is a power outage, recovery management is how long it takes to recover the database after the outage. Backup management refers to the data safety and integrity; for example backing up all your mp3 files on a disk. 7. Data Integrity Management The DBMS enforces these rules to reduce things such as data redundancy, which is when data is stored in more than one place unnecessarily, and maximizing data consistency, making sure database is returning correct/same answer each time for same question asked. 8. Database Access Languages and Application Programming Interfaces A query language is a nonprocedural language. An example of this is SQL (structured query language). SQL is the most common query language supported by the majority of DBMS vendors. The use of this language makes it easy for user to specify what they want done without the headache of explaining how to specifically do it. 9. Database Communication Interfaces This refers to how a DBMS can accept different end user requests through different network environments. An example of this can be easily related to the internet. A DBMS can provide access to the database using the Internet through Web Browsers.