Computer Sciences Commons^™

Citizen Science Sensor Development - Smap | Soil Moisture Active Passive, Hagop Hovhannesian

STAR Program Research Presentations

“Detailed monitoring of soil moisture provides a view of how our whole Earth system works.”

The Soil Moisture Active Passive (SMAP) satellite mission was launched in January 2015; its main purpose is to acquire global measurements of soil moisture. SMAP partnered with the GLOBE program (Global Learning and Observations to Benefit the Environment), which is an international program where students collect environmental variables in a scientifically methodical way. SMAP readings and maps have various uses in various fields, which include monitoring drought, predicting floods, assisting in crop productivity, and linking water, energy and carbon cycles. The goal of this project …

The Mexican Water Forest: Benefits Of Using Remote Sensing Techniques To Assess Changes In Land Use And Land Cover, Maria F. Lopez Ornelas

Master's Projects and Capstones

In the past 30 years, anthropogenic activities like urbanization, agriculture, road fragmentation and deforestation have resulted in changes in the land use and land cover (LULC) in the Mexican Water Forest. Due to the important ecosystem services, and the natural resources this forest provides, in Mexico, it has become increasingly necessary to use new technologies and tools to support the planning, implementation and integration of forest management and conservation plans, as well as ecological and socioeconomic analysis of this ecosystem. Remote Sensing techniques and Geographic Information Systems (GIS) have been a true technological and methodological revolution in the acquisition, management …

Exploring Data Mining Techniques For Tree Species Classification Using Co-Registered Lidar And Hyperspectral Data, Julia K. Marrs

Theses and Dissertations

NASA Goddard’s LiDAR, Hyperspectral, and Thermal imager provides co-registered remote sensing data on experimental forests. Data mining methods were used to achieve a final tree species classification accuracy of 68% using a combined LiDAR and hyperspectral dataset, and show promise for addressing deforestation and carbon sequestration on a species-specific level.

Bottom-Up Ggm Algorithm For Constructing Multilayered Hierarchical Gene Regulatory Networks That Govern Biological Pathways Or Processes, Sapna Kupari, Wenping Deng, Chathura J. Gunasekara, Vincent Chiang, Huann-Sheng Chen, Hairong Wei, Et. Al.

Michigan Tech Publications

Background: Multilayered hierarchical gene regulatory networks (ML-hGRNs) are very important for understanding genetics regulation of biological pathways. However, there are currently no computational algorithms available for directly building ML-hGRNs that regulate biological pathways.

Results: A bottom-up graphic Gaussian model (GGM) algorithm was developed for constructing ML-hGRN operating above a biological pathway using small- to medium-sized microarray or RNA-seq data sets. The algorithm first placed genes of a pathway at the bottom layer and began to construct an ML-hGRN by evaluating all combined triple genes: two pathway genes and one regulatory gene. The algorithm retained all triple genes where a regulatory …

Synthesis Of Satellite Microwave Observations For Monitoring Global Land-Atmosphere Co2 Exchange, Lucas Alan Jones

Graduate Student Theses, Dissertations, & Professional Papers

This dissertation describes the estimation, error quantification, and incorporation of land surface information from microwave satellite remote sensing for modeling global ecosystem land-atmosphere net CO₂ exchange. Retrieval algorithms were developed for estimating soil moisture, surface water, surface temperature, and vegetation phenology from microwave imagery timeseries. Soil moisture retrievals were merged with model-based soil moisture estimates and incorporated into a light-use efficiency model for vegetation productivity coupled to a soil decomposition model. Results, including state and uncertainty estimates, were evaluated with a global eddy covariance flux tower network and other independent global model- and remote-sensing based products.