Download Soil Moisture Raster Data Directly in QGIS

Soil moisture plays an important role in agricultural monitoring, drought and flood prediction, forest fire prediction, water supply management, and other natural resource-related activities. Soil moisture observations can warn of imminent drought and flood conditions before other  standard indicators are triggered.  

As defined in AMS Glossary of Meteorology, soil moisture is "the total amount of  water vapor-containing water in  unsaturated soil." Soil moisture (sometimes called soil water) refers to surface water  in the pores of the soil, not rivers, lakes, or groundwater. Soil moisture levels are determined by a variety of factors other than weather conditions, such as soil type and associated vegetation. Second, soil moisture affects the various dynamics of soil and plants. Surface soil moisture is  water located 10 cm above the soil, and root zone soil moisture is  water  available to plants-generally considered to be located 200 cm above the soil floor. 

The amount of soil moisture can have very different effects depending on location, time of year, soil type and depth. For example, the same absolute value of soil moisture in the southeast may indicate a severe drought, but in the southwest it represents normal soil. To interpret soil moisture data, various other "metadata", especially soil properties, need to be evaluated and maintained. It also means that you may need multiple units of measurement to properly describe the condition, such as anomalies, daily ranking percentages, as well as "amount of water" (the amount of water present). Soil Moisture Monitoring Technology is experiencing rapid growth and innovation with the advent of new field and proximal sensors, new satellite and other remote sensing technologies, and improved modeling capabilities. This is  increasing the number of soil moisture data products under development.

Fortunately, recent technologies of Remote Sensing and GIS is enabling us to get the information about soil moisture from space. There are few earth observation sensors which operates in the orbit that has ability to record this data in timely manner. Some of them available to download for free, either in raw measurement format or processed ready-to-use format. One of the data provider in this kind of data is Japan Aerospace Exploration Agency (JAXA). They developed an API services that enabling us to get this data in a programmatical way. They also developed a plugin in QGIS ( a well known Free and Open Sourced GIS Software) which enabling us to get the data in a very easy and straightforward way. In this post, I attach a video tutorial about how to use the plugin to get the Soil Moisture data in multi-temporal and time series mindset. Check the video below. Any suggestions and input are absolutely appreciated. 

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