Remote Sensing and Data Characteristics

Remote Sensing

  • Discovery shuttle surveyed 70% of surface of earth

  • Optimized management of natural resources

    • Remote (>2m from target)

    • Proximal (<2m from target)

  • Reflectance - Radiation

    • Interaction with atmosphere and target

    • Part of the energy used to collect the remote sensing will be reflected

      • Energy that is reflected will be different than what is emitted

    • Many remote systems are passive, they get energy from the sun (electromagnetic energy)

    • Interaction with target

      • Absorption

      • Transmission

      • Reflection

      • You know how much energy is being sent out so whatever doesn't get reflected is split between the other

  • Satellite sensor system

    • Put in your own energy

  • Hyperspectral Non-Imaging Systems

    • Biophysical Measurements

      • Vegetation fraction

      • Leaf area

      • Pigment type and density

      • Leaf-water content

    • Using

      • Data collection platform

      • Digital phot

      • Hyperspectral. Profile

      • Measuring Chlorophyll

  • Energy/target Interaction

    • Seeing the changes in chlorophyll/what color is reflected

    • Can evaluate areas affect by their color presentation in GIS with remote sensing

  • Importance of remote Sensing data

    • Synoptic view: satellite images are big-picture views of large areas of the surface

    • Repetitive coverage: Repeated images of the same regions, taken at regular intervals over period

    • Multispectral data: Satellite sensors are designed to operate in many different portions of the electromagnetic spectrum

  • Resolution of remote sensing systems **** exam

    • Spatial resolution - area per Pixel

      • Lets us know the area, changing scale 

      • How sharp is the image

      • Many products stop at 1m

    • Spectral resolution - energy range

      • Which type of energy you are looking for

      • Should have more than one part of energy range that characterizes energy range

      • You have an image in each color (R,G,B) viewing all these at the same time get you spectral resolution

      • Phone is a multispectral imagery system on your phones camera

      • Three basic questions

        • What region of spectrum is critical

        • How many band are necessary

        • How wide is every band

      • For healthy vegetation we need to go outside of visible range (near-infrared)

      • Broad Band Vegetation Indices

        • NDVI

          • Higher is health vegetation

        • Near infrared was lots of reflectance

          • Red has less

          • The bigger difference between these two is what makes a healthy plant

          • This is also influenced by sun presence

      • Specific Band Vegetation Indices

    • Radiometric Resolution - sensitivity

      • Within each energy range

      • Two different satellites given red green blue energy range, but they will have different output

    • Temporal Resolution - Revisit Time

      • You need the technology now (ie with fire)

    • Resolution parameters must satisfy project objectives

      • You can have the best technology but it takes unreasonable amount of computers

      • What can be done with the budget, best bang for your buck

  • True color image

    • Common one is with wide band detector (400-500nm blue, 500-600nm green, 600-700nm red)

    • Now remote sensing switch H(ue)S(aturation)C(olor)

  • False color Image

    • Shift the color up the nm (500-600blue, 600-700mn green, 700-900nm red

      • Image is shown in red with healthy vegetation

  • Image Application

    • NDVI = NIR-R / NIR+R

  • Radiometric Resolution

    • Instrument sensitivities enable the assignment of a wider range of gray scale values per each pixel

    • Amount of memory on the computer that each number occupy

    • 8 bit system (0-255) you have 256 shades of grey

      • Want higher system resolution because there is sometimes a 1% difference in color of dead and healthy plant

  • Temporal Resolution

    • How often can you get that image, very important criteria for NRM

    • Satellites rotate so there is a cyclic nature of the photography

    • Quality of the image is determined if 85% of the image is cloud free

    • Panchromatic (grey scale) has best resolution

      • Lay color on top of the image, but for truly detailed analysis you need to know the resolution of the color sensor to understand

  • Data selection Criteria

  • Platforms for aerial photography

    • Ballons, light aircraft, military, drone        

    • Height from the ground, bigger pictures, losing resolution but takes less time

  • Image geo-referencing

    • Regardless of how you get the image need to transform the image, between aerial photo and reference image

    • To get the georeferenced image

  • Ortho Imagery Requirements

    • Exterior orientation

      • Camera orientation

    • Camera model

      • Accounts for lens distortion

    • DEM

      • Relief displacement, compensating for elevation

  • Conditions for aerial photography

    • No smoke or haze, no clouds or cloud shadows, solar angle 30 degrees above horizon, less than 5 degree of tilt

  • Multispectral imagery

    • Automated analysis of satellite imagery fo 30 years

  • Thermal imagery

    • Used for detecting stress in field crops