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How to use MODIS remote sensing data in Python?
MODIS is a satellite remote sensing instrument that collects data daily across the globe at 250-500 m resolution. Learn how to import, clean up and plot MODIS data in Python Import and stack MODIS imagery in Python. Scale MODIS surface reflectance values to the appropriate range using Python.
What is the scale factor of MODIS data?
Looking at the table for the MOD09GA product, you can see that the MODIS data have a scale factor of 0.0001. This means you should multiply each layer by that value to get the actual reflectance values of the data.
What is MODIS and what does MODIS do?
Moderate Resolution Imaging Spectrometer (MODIS) is a satellite-based instrument that continuously collects data over the Earth’s surface. Currently, MODIS has the finest temporal resolution of the publicly available remote sensing data, spanning the entire globe every 24 hrs.
How many bands of data does MODIS have?
Currently, MODIS has the finest temporal resolution of the publicly available remote sensing data, spanning the entire globe every 24 hrs. MODIS collects data across 36 spectral bands; however, in this class, you will only work with the first 7 bands.
Where can remote sensing data be collected from?
Remote sensing data can be collected from the ground, the air (using airplanes or helicopters) or from space. You can imagine that data that are collected from space are often of a lower spatial resolution than data collected from an airplane.
How is multispectral imagery used in remote sensing?
This week you will work with multispectral imagery or multispectral remote sensing data. Multispectral remote sensing is a passive remote sensing type. This means that the sensor is measuring light energy from an existing source – in this case the sun.
How to describe multi-band remote sensing data?
Define multispectral (or multi-band) remote sensing data. Describe at least 3 differences between NAIP imagery, Landsat 8 and MODIS in terms of how the data are collected, how frequently they are collected and the spatial and spectral resolution. Describe the spatial and temporal tradeoffs between data collected from a satellite vs an airplane.