Assignment: MODIS Land Surface Temperature

The objective of this lab is to delve deeper into climate variables with Google Earth Engine. By the end of this lab you will be able to explore long-term trends in temperature data for specific regions of interest.

Monitoring land surface temperature (LST) with MODIS imagery

Calling MODIS LST datasets

The MOD11A2 V6 product provides an average 8-day land surface temperature (LST) in a 1200 x 1200 kilometer grid. Each pixel value in MOD11A2 is a simple average of all the corresponding MOD11A1 LST pixels collected within that 8 day period. The 8 day compositing period was chosen because twice that period is the exact ground track repeat period of the Terra and Aqua platforms. In this product, along with both the day- and night-time surface temperature bands and their quality indicator (QC) layers, are also MODIS bands 31 and 32 and eight observation layers. The product is available from 05/03/2000 to present.

• • Let's start by defining a region of interest (roi).

  • For this lab we will first work over Oklahoma City, Oklahoma. Please note that you are welcome to use any other city, as long as you explain which city you have used. Use the geometry tool to draw a polygon and define your region of interest (roi). Remember to rename the 'geometry' to 'roi'.

  • Next we will use some code to extract the bands we need from the MOD11A2 product. We are interested in the bands that contain the estimated temperature data.

// Import image collection
var modis = ee.ImageCollection('MODIS/006/MOD11A2');

• Specify the dates of interest.

// A start date is defined and the end date is determined by advancing 1 year from the start date.
var start = ee.Date('2015-01-01');
var dateRange = ee.DateRange(start, start.advance(1, 'year'));

// Filter the LST collection to include only images from time frame and select day time temperature band

var modLSTday = modis.filterDate(dateRange).select('LST_Day_1km');