Land Surface Remote Sensing and Hydrology

Scientists at AER are improving methods to monitor and predict regional and global change through a variety of approaches, sensors and data sets.

By improving methods to monitor changes in land surface cover, open water, and vegetated wetlands, AER scientists are contributing to local and global understanding of the drivers and impacts of climate variations on terrestrial ecosystems.  These studies also improve the accuracy of measuring and predicting water vapor, precipitation, cloud properties, surface radiation budget, soil moisture and surface air temperature.

AER’s approaches for measuring and modeling land surface evaporation apply state-of-the-art retrieval capabilities to microwave and infrared satellite data. The studies will improve the scientific community’s understanding of how moisture and energy cycles in the soil, vegetation, and atmosphere vary across land surfaces globally.

Land surface remote sensing projects include:

  • Land surface microwave emissivity 
  • Microwave emission depth
  • Land surface temperature

Flood mapping and prediction

AER scientists are improving the accuracy of mapping techniques to assess regional flood likelihood and estimate inundation extent in real time. The approaches combine microwave sensors that “see through clouds” with topography, land cover, historic inundation and stream routing data. The improvements will provide the capability to produce high resolution inundation maps globally that can be used for local risk assessment or up-scaled for national or international initiatives.

  • For methane emission studies, AER is investigating use of the NASA Soil Moisture Active Passive (SMAP) satellite for deriving seasonal inundation maps. 
  • AER is adapting current flood mapping models to map terrestrial hydrology. Initiatives include down-scaling flood data from lower-resolution microwave sensors (e.g., 10-50 km resolution) to make higher resolution flood maps (e.g., 100 m scale). 

Soil moisture and temperature

AER scientists use land surface models to simulate how soil moisture, surface temperature, and other surface conditions respond to weather conditions.  Applications include modeling of soil strength for military, commercial, and agricultural trafficability estimates and simulation of infrared and microwave sensor scenes for testing sensor and retrieval algorithm performance.

AER scientists have developed an innovative mapping method that leverages lower-resolution microwave data that can "see through clouds" to provide high-resolution inundation maps in real time as flood waters expand.  This example shows flood extent mapped daily at the Mississippi-Missouri confluence during the 1993 Midwest Flood. Gauge height data (right) is used to validate the flood map (left) projected daily from low-resolution microwave data.