M. TAPELA , R. TSHEKO, N.J. BATISANI Botswana College of Agriculture

1. M. TAPELA, R. TSHEKO, N.J. BATISANI Botswana College of Agriculture Training Course for the SADC THEMA – 28 Feb-11 Mar, 2011 Agriculture Service Remote Sensing Concepts

2. Agenda SADC THEMA Services PRESENTATION FORMAT • Introduction • Overview of Agricultural Applications • Remote Sensing Basics

3. 1. Introduction: What can you see ? Land based observation Satellite Imagery Aerial Photography

4. 2) Overview of Agricultural Applications Remote Sensing Applications and Products: • About 70% of the Earth’s land surface is covered with vegetation • Remote sensing is used for agriculture, forests, rangelands, wetlands and urban vegetation assessment • There are generally three (3) areas in which remote sensing products are used in agriculture, namely: • crop type classification, • crop condition assessment, • crop yield estimation (prediction)

5. 2) Overview of Agricultural Monitoring Crop type classification and crop area estimation: • Based on the premise that a crop can be identified based on its spectral signature • Requires knowledge of the developmental stages of each crop in the area to be investigated • A crop calendar is used to list expected developmental status and appearance of each crop in an area throughout the growing season • Crop area (crop masks) is estimated/measured from land use maps derived from high spatial resolution imagery

6. 2) Overview of Agricultural Monitoring Crop condition assessment: • Information on crop condition can be obtained from satellite imagery to assess; • Crop disease • Insect/Pest damage • Crop stress • Disaster damage (flood, drought, hail storms, fire) • Depending on the observed problems, remedial measures could be put in place such as replanting, herbicides/fertilizer treatment, and drainage

7. 2) Overview of Agricultural Monitoring Crop yield estimation: • Achieved by determining the area of each crop type and estimating the yield per unit area of each crop • Crop yield depends on several factors such as soil moisture, soil fertility, air and soil temperature • Yield can also be affected by disease, insects’ infestation, physical damage • Field inspection of sample sites are used to; • validate the satellite observations • develop correlations between spectral signatures and crop yield

8. 2) Overview of Agricultural Monitoring Crop yield prediction : • Historical data on crop yield from individual fields as well as satellite information can be used for crop yield prediction • Meteorological satellites provide both climatic and meteorological data that is required for yield prediction • Satellite information can be used to determine how in a certain year yield deviates from the normal trend • Monitoring biomass over time can provide important information about the likelihood of good or poor harvest as well as the stability of the natural ecosystem

9. 2) Overview of Agricultural Monitoring Product Comments CNDVI Crop Specific NDVI WRSI Water Requirements Satisfaction Index WRSI-Anom WRSI Anomaly map SOS Start of Season (Onset of Rains) SOS-Anom SOS Anomaly map Phenology Estimates of phenology based on planting and crop cycle length SWI Soil Water Index Estimates Agricultural Remote Sensing Products

10. 3) Remote Sensing Basics Definition of Remote Sensing : • Remote sensing may be defined as the art, science, and use of technology to observe an object, area or phenomena and obtain information about it whilst not in contact with it. • The term embraces a number of observation or sensor techniques ranging from; • photography, • multispectral, • thermal • hyperspectral sensing • Satellite-based observation methods have gained wide application compared to aerial photography

11. 3) Remote Sensing Basics Definition of remote sensing :

12. 3) Remote Sensing Basics Definition of remote sensing :

13. The Electromagnetic spectrum: • The basis for remote sensing is the measurement of varying energy levels (Electro-Magnetic, or EM) of a single entity • Though photons travel at constant speed of light, they however travel at varying frequencies and wavelengths • The photon wave is dual in nature • The distribution of all photon energies over a range of observed frequencies is described as the Electromagnetic spectrum, EM 3) Remote Sensing Basics

14. The Electromagnetic spectrum: • The visible region is composed of representative colours ranging from; • Violet: 0.4 - 0.446 μm; • Blue: 0.446 - 0.500 μm; • Green: 0.500 - 0.578 μm; • Yellow: 0.578 - 0.592 μm; • Orange: 0.592 - 0.620 μm; • Red: 0.620 - 0.7 μm;. 3) Remote Sensing Basics

15. The Electromagnetic spectrum : • To rely only on the visible part of the EM to make a distinction between objects observed on earth greatly limit our earth observation capabilities especially during instances of poor visibility such as cloud cover, night time and dust storms. • The ability to detect outside the visible range allows us to make observations even when vision is limited • Different sensors are designed such that they are able to detect a specific range in the spectrum 3) Remote Sensing Basics

16. Sensors: Remote sensors may be situated on the ground, on an aircraft or balloon (or some other platform within the Earth's atmosphere), or on a spacecraft or satellite outside of the Earth's atmosphere. Ground-based sensors are often used to record detailed information about the surface which is compared with information collected from aircraft or satellite sensors Sensors onboard platforms far away from their targets, typically view a larger area, but cannot provide great detail 3) Remote Sensing Basics

17. 3) Remote Sensing Basics Sensors :

18. Sensors: • The category of new high resolution satellite sensors include four satellites: • Ikonos, operated by SpaceImaging • QuickBird, operated by DigitalGlobe • EROS, operated by ImageSat • Spot 5, operated by SpotImage 3) Remote Sensing Basics

19. Sensors: • IKONOS 3) Remote Sensing Basics

20. Sensors: • QUICKBIRD 3) Remote Sensing Basics

21. EROS (Earth Resources Observation Satellite) • Launched on December 2000 • Panchromatic with 1.8 m spatial resolution 3) Remote Sensing Basics

22. Land Observation Satellites/Sensors: • SPOT (Système Pour l'Observation de la Terre) is a series of Earth observation imaging satellites designed and launched by CNES (Centre National d'Études Spatiales) of France, with support from Sweden and Belgium. • It is capable of sensing either in a high spatial resolution single-channel panchromatic (PLA) mode, or a coarser spatial resolution three-channel multispectral (MLA) mode 3) Remote Sensing Basics

23. Land Observation Satellites/Sensors: • Chronological Launch History of the SPOT Satellites 3) Remote Sensing Basics

24. Spectral and Spatial Resolution of the Landsat and SPOT 3) Remote Sensing Basics

25. IRS-P6 (launched October 2003) • Indian Remote Sensing 3) Remote Sensing Basics

26. Landsat 3) Remote Sensing Basics

27. ASTER (launched, December 1999) 3) Remote Sensing Basics

28. MESRIS 3) Remote Sensing Basics

29. ESA Earth Observation Programme 3) Remote Sensing Basics

30. Spatial Resolution: • The spatial resolution of the sensor and refers to the size of the smallest possible feature that can be detected • Images where only large features are visible are said to have coarse or low resolution. In fine or high resolution images, small objects can be detected. • For a homogeneous feature to be detected, its size generally has to be equal to or larger than the resolution cell. 3) Remote Sensing Basics

31. Spectral Resolution: • Spectral resolution describes the ability of a sensor to define fine wavelength intervals • The finer the spectral resolution, the narrower the wavelength range for a particular channel or band • Advanced multi-spectral sensors called hyperspectral sensors, detect hundreds of very narrow spectral bands throughout the visible, near-infrared, and mid-infrared portions of the electromagnetic spectrum 3) Remote Sensing Basics

32. Temporal Resolution: • Temporal Resolution refers to the length of time it takes for a satellite to complete one entire orbit cycle. • The revisit period of a satellite sensor is usually several days • Some satellite systems are able to point their sensors to image the same area between different satellite passes • Spectral characteristics of features may change over time and these changes can be detected by collecting and comparing multi-temporalimagery 3) Remote Sensing Basics

33. Radiometric Resolution: • Radiometric Resolution describes its ability to discriminate very slight differences in energy. • The finer the radiometric resolution of a sensor, the more sensitive it is to detecting small differences in reflected or emitted energy. • corresponds to the number of bits used for coding numbers in binary format. 3) Remote Sensing Basics

34. Weather Satellites/Sensors: • Meteorological satellites to monitor weather conditions around the globe • . • These satellites use sensors which have fairly coarse spatial resolution (when compared to systems for observing land) and provide large areal coverage\ • Temporal resolutions are generally quite high, providing frequent observations which allows for near-continuous monitoring of global weather conditions 3) Remote Sensing Basics

35. Weather Satellites/Sensors : • The GOES (Geostationary Operational Environmental Satellite) System. 3) Remote Sensing Basics

36. Weather Satellites/Sensors : • The GOES (Geostationary Operational Environmental Satellite) System. GOES East and West Coverage 3) Remote Sensing Basics

37. Weather Satellites/Sensors : • NOAA AVHRR (Advanced Very High Resolution Radiometer) 3) Remote Sensing Basics

38. 3) Remote Sensing Basics Radiation - Earth Surface Interactions :

39. 3) Remote Sensing Basics Radiation - Target Interactions : • There are three (3) forms of interaction that can take place when energy strikes, or is incident (I) upon the surface. These are: • absorption (A); • transmission(T); • reflection (R).

40. 3) Remote Sensing Basics Radiation - Leave Interactions : • Chlorophyll strongly absorbs radiation in the red and blue wavelengths but reflects green wavelengths • In autumn, there is less chlorophyll in the leaves, so there is less absorption and proportionately more reflection of the red wavelengths, making the leaves appear red or yellow (yellow is combination of red and green wavelengths)

41. 3) Remote Sensing Basics Radiation - Leave Interactions :

42. 3) Remote Sensing Basics Radiation - Water Interactions : • Water typically looks blue or blue-green due to stronger reflectance at these shorter wavelengths, and darker if viewed at red or near infrared wavelengths. • Suspended sediment present in the upper layers of the water body, then this will allow better reflectivity and a brighter appearance of the water.

43. 3) Remote Sensing Basics Spectral Signatures: Reflectance of vegetation and water at different wavelengths can be used to identify and separate different materials or objects using multi-spectral data

44. 3) Remote Sensing Basics Spectral Signatures: A combination of wavelengths (more than one) may be used to make the distinction in what we call multi-spectral remote sensing

45. 3) Remote Sensing Basics Spectral Signatures: • Spectral Reflectance may also be used to distinguish between different vegetation types (Crop Masks)

46. ReferencesBrown E. M.(2008) Famine Early Warning Systems and Remote Sensing Data. Springer-Verlag Berlin HeidelbergCanada Centre for Remote Sensing. 2010. Fundamentals of Remote SensingLillesand, T.M. and Kiefer, R.W. (1994) Remote Sensing and Image Interpretation. John Wiley and Sons Inc., New YorkRemote Sensing Tutorial. http://rst.gsfc.nasa.gov

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