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lect 1-2.pdf

  1. Basic concept, components and applications of Remote Sensing Lec. 1-2 Dr. Sanjani S. Salunkhe, Assistant Professor, Dept. of Soil and Water Cons. Engg., Dr. D.Y.Patil CAET, Talsande
  2. • Remote sensing is the science and art of obtaining information about an object, area or phenomenon through an analysis of the data acquired by a device which is not in contact with the object, area or phenomenon under investigation. • Remote sensing data basically consists of wavelength intensity information acquired by collecting the electromagnetic radiation leaving the object at specific wavelength and measuring its intensity. WHAT IS REMOTE SENSING ?
  3. Fig. Sensor on-board satellite scans along line AB
  4. Components of Remote Sensing 1. Energy Source: i. Passive System: Sun, irradiance from earth’s materials. ii. Active System: Irradiance from artificially generated energy sources such as radar. 2. Platforms: These are vehicles to carry the sensor e.g. truck, aircraft, space shuttle, satellite, etc.
  5. 2. Sensors: Device to detect electro-magnetic radiation e.g. camera, scanner, etc. 3. Detectors: Handling signal data e.g. photographic, digital, etc. 4. Processing: Handling signal data e.g. photographic, digital etc. 5. Institutionalization: These are organizations for execution of all stages of remote sensing technology e.g. International and national organizations, research centres, universities, etc.
  6. Elements Involved in Remote Sensing: 1. Energy Source or Illumination (A) 2. Radiation and the Atmosphere (B) 3. Interaction with the Object (C) 4. Recording of Energy by the Sensor (D) 5. Transmission, Reception and Processing (E) 6. Interpretation and Analysis (F) 7. Application (G)
  7. • Types of sensing systems to record the information about any target: 1. Active sensing system and 2. passive sensing system Classification of Remote Sensing
  8. Advantages of remotely sensed data • Collection of data from both accessible and inaccessible areas on a repetitive bais • Quality, reliability and timeliness • Remote sensors collected data, it can be used and analysed multiple times for different applications. • Remote sensing technology like LiDAR collects point cloud data • Large area coverage
  9. • Remote sensing allows repetitive coverage which comes in handy when collecting data on dynamic themes such as water, agricultural fields and so on. • A single image captured through remote sensing can be analysed and interpreted for use in various applications and purposes. There is no limitation on the extent of information that can be gathered from a single remotely sensed image. • Remote sensing is un-obstructive especially if the sensor is passively recording the electromagnetic energy reflected from or emitted by the phenomena of interest (passive remote sensing does not disturb the object or the area of interest).
  10. • Remote sensing allows for map revision at a small to medium scale which makes it a bit cheaper and faster. • Colour composite can be obtained or produced from three separate band images which ensure the details of the area are far much more defined than when only a single band image or aerial photograph is being reproduced. • It is easier to locate floods or forest fire that has spread over a large region which makes it easier to plan a rescue mission easily and fast. • Remote sensing is a relatively cheap and constructive method reconstructing a base map in the absence of detailed land survey methods.
  11. Disadvantages of remotely sensed data • Remote sensing requires a special kind of training to analyse the images. • It is expensive to analyse repetitive photographs if there is need to analyse different aspects of the photography features. • The instruments used in remote sensing may sometimes be un-calibrated which may lead to un-calibrated remote sensing data. • Sometimes different phenomena being analysed may look the same during measurement which may lead to classification error.
  12. Uses of RS techniques in assessment and monitoring of land and water resources • Assessment of water availability in reservoirs for optimal management of water to meet irrigation demand. • Identifying, inventoryingand assessment ofirrigated crops. • Determination of irrigation water demands over space and time. • Estimation of crop yields. • Water logging and salinity problems in irrigatedlands.
  13. • Evapotranspiration studies. • Irrigation system performance evaluation. • Satellite remote sensing derived indicators such as chlorophyll, can monitor that algal bloom thus monitoring water quality in a spatio-temporal fashion. • Surface Water Quantity: One of the key argument is the lack of the ground data, which plays an important role in evaluating the status of water resource and taking useful measures to respond the threat of water scarcity. In this regard, earth observation can offers standardized and long-term observations to address such challenges.
  14. • The RS has capability of multi-temporal imaging and satellite imagery based indices (i.e., Normalized Difference Water Index (NDWI)), can efficiently identify, map and calculate the total surface area of the water bodies in different seasons (i.e., dry, wet) and by integrating satellite altimetry measurements which quantify and monitor the water storage change over time. • Ground water Quantity: For planning and management of water resource, need to know, globally how much fresh water available. Gravity Recovery and Climate Experiment (GRACE), continuously measuring the changes in earth’s mass hence gravity that are mainly due to water moving on and under the surface.
  15. WATER RESOURCES MANAGEMENT • Runoff and Hydrological Modelling: Remote Sensing techniques, they can be used in research areas like - determining watershed geometry, drainage network and other map-type information for distributed hydrologic models and for determining empirical flood peak, annual runoff or low flow equations and - providing input data like soil moisture or delineated land use classes, which are used for determining runoff co-efficient.
  16. • Remotely sensed data, particularly Landsat, Thematic Mapper (TM), SPOT), and Indian Remote Sensing Satellite (IRS) data has been used for calculation of drainage basin area and stream network density. • Hydrologic Engineering Center (HEC-1) model was used to demonstrate the efficacy of using Remote Sensing for re- computation of hydrologic variables. HEC-1 model was used in integrating detailed land use data from Landsat TM.
  17. • Flood Management: • Information acquired through Remote Sensing covers wide area, periodicity and spectral characteristics and is especially useful in comparing data before and after the flood. • The utility of satellite Remote Sensing has been demonstrated operationally for mapping flood inundated areas. • Partially cloud free data acquired, analysed and interpreted in near real time by IRS series satellites. • IRS-1C, IRS-1D, IRS-P6, Cartosat-1, Cartosat-2, Radarsat and Earth Resource Satellite (ERS) are used for flood inundation mapping, estimation of flood damage and infrastructure loss.
  18. • Watershed Management: • Space borne multi spectral data has been used to generate baseline information on various natural resources like soil, forest cover, surface water, groundwater and land use/land cover. • Subsequent integration of such information with slope and socio-economic data in a GIS has resulted in generation of location specific management plan for sustainable development of land and water resources within a watershed.
  19. • Drought Management: • Timely and reliable information about the onset of drought, its extent, intensity, duration and impact can limit drought related loss of life, minimize human suffering and reduce damage to the economy and environment. • Remote Sensing data from geostationary and polar orbiting weather satellites like Indian National Satellite (INSAT), National Oceanic and Atmospheric Administration (NOAA) and other global data are used as major inputs in rainfall predictions ranging from long-term seasonal predictions through medium range predictions to short-term predictions.
  20. • Irrigation Command Area Management: • Remote Sensing techniques can be immensely helpful in inventory of irrigated land, identification of crop types, crop extent, crop condition and estimation of crop yield, as demonstrated in various investigations in India and in other countries. • Periodic satellite monitoring of Irrigation Command Areas has helped in evaluating increase in irrigation utilization and improvement in agricultural productivity over a period of time.
  21. • Remote Sensing methods have been successfully applied in delineating saline and alkaline soils and detecting areas having ineffective water management practices leading to decrease in crop yield. • Remote Sensing techniques are now increasingly applied in land use planning and in identifying areas suitable for sustained irrigated cropping with the help of “irrigability maps” prepared from satellite data. • Vegetation Indices and demand-supply analysis is used in many Irrigation Command Areas in India to evaluate irrigation potential.
  22. Thank You
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