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2022-07-04T01:03:08Z

Teaching & AcademicsScienceRemote Sensing

Remote Sensing - fundamentals and applications

Learn the fundamentals and applications of remote sensing
Rating: 0.0 out of 50.0 (0 ratings)
4 students
Created by AulaGEO Academy, Mirza Waleed
Last updated 3/2022
English
English [Auto], Spanish

What you'll learn

  • Remote Sensing Background
  • Types of Remote Sensing
  • Applications of Remote Sensing data
  • Multispectral Satellite data Microwave (Radar) Satellite data Hyperspectral, Satellite data Applications in Land Cover Applications in Agriculture
  • Applications in Forestry, Applications in Geology, Applications in Hydrology, Applications in Sea-ice, Applications in Oceans and Coastal

Requirements

  • no recqurements

Description

Remote sensing is the process of detecting and monitoring the physical characteristics of an area by measuring its reflected and emitted radiation at a distance (typically from satellite or aircraft). Special cameras collect remotely sensed images, which help researchers "sense" things about the Earth. Some examples are:

  • Cameras on satellites and airplanes take images of large areas on the Earth's surface, allowing us to see much more than we can see when standing on the ground.

  • Sonar systems on ships can be used to create images of the ocean floor without needing to travel to the bottom of the ocean.

  • Cameras on satellites can be used to make images of temperature changes in the oceans.

Some specific uses of remotely sensed images of the Earth include:

  • Large forest fires can be mapped from space, allowing rangers to see a much larger area than from the ground.

  • Tracking clouds to help predict the weather or watching erupting volcanoes, and help watching for dust storms.

  • Tracking the growth of a city and changes in farmland or forests over several years or decades.

  • Discovery and mapping of the rugged topography of the ocean floor (e.g., huge mountain ranges, deep canyons, and the “magnetic striping” on the ocean floor).



Section-1: Introduction

  1. Course Introduction

Section-2: Remote Sensing Background

  1. Remote Sensing

  2. Principle of Remote Sensing

  3. Important concepts for Principle of Remote Sensing

  4. History of Remote sensing

Section-3: Types of Remote Sensing

  1. Sensor based types of Remote Sensing

  2. Resolution based types and characteristics of Remote Sensing

  3. Purpose based types of Remote Sensing

Section-4: Applications of Remote Sensing data

  1. Multispectral Satellite data

  2. Microwave (Radar) Satellite da ta

  3. Hyperspectral Satellite data

  4. Applications in Land Cover

  5. Applications in Agriculture

  6. Applications in Forestry

  7. Applications in Geology

  8. Applications in Hydrology

  9. Applications in Sea-ice

  10. Applications in Oceans and Coastal

Who this course is for:

  • geographers
  • geology proffesionals
  • GIS users
  • land science proffesionals
  • earth science students
  • social studies teachers

Instructors

AulaGEO Academy
Specialists in GIS - BIM - LAND and Smart process training
AulaGEO Academy
  • 3.9 Instructor Rating
  • 1,821 Reviews
  • 19,262 Students
  • 120 Courses

We choose the best courses and make them available to new audiences.

Our training offer covers the entire spectrum of data intelligence:

Art - Capture - Modeling - Design - Construction - Operation. Using technological development and process improvement as a transverse thread.

The creators of courses with which we have decided to work have been carefully selected, to offer a complementary set of knowledge. We firmly believe that today people do not seek courses to fill their walls with diplomas; but to make their abilities more productive.

Mirza Waleed
Geospatial Researcher
Mirza Waleed
  • 4.2 Instructor Rating
  • 37 Reviews
  • 1,320 Students
  • 3 Courses

Waleed is a Ph.D. student in Geography at HKBU, Hong Kong. He has been working in the Remote Sensing domain for the last four years focusing on Google Earth Engine, Geospatial Data Science, and Machine/Deep Learning. His research interests include but are not limited to 1) Hazard Risk-Resilience studies, 2) Monitoring rapid urbanization/urban sprawl patterns, 3) Forecasting future land use and land surface temperature patterns, 4) Applications of Google Earth Engine in ecology, Paleoclimatology, and Microclimate (UHI).

His research activities primarily revolve around the use of GEE, RS workflow automation through GEE, Python, ArcGIS Pro, QGIS, TerrSet, PowerBi, and Python-based Geospatial Modules.

He’s focusing on regional/national/global scale studies involving GEE and is also available for working and collaboration opportunities in the aforementioned domains.

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