THE USE OF REMOTE SENSING AND EDDY COVARIANCE TECHNOLOGIES TO CHARACTERIZE CROPLAND, DROUGHT AND LAND MANAGEMENTS AND THEIR IMPACTS ON ECOSYSTEM DYNAMICS
dc.contributor.advisor | Xiao, Xiangming | |
dc.contributor.author | Zhou, Yuting | |
dc.contributor.committeeMember | Basara, Jeffrey | |
dc.contributor.committeeMember | Luo, Yiqi | |
dc.contributor.committeeMember | Steiner, Jean | |
dc.contributor.committeeMember | McCarthy, Heather | |
dc.date.accessioned | 2017-05-12T15:48:46Z | |
dc.date.available | 2017-05-12T15:48:46Z | |
dc.date.issued | 2017-05-12 | |
dc.date.manuscript | 2017-04-07 | |
dc.description.abstract | With the increasing population, human needs more food, fresh water, and other ecosystem services, which burdens the agricultural and natural ecosystems. Under the background of climate change, meeting these human needs becomes more challenging because of increasing temperature, climate extremes, etc. and their interaction with human activities. Thus, it is important to understand the impacts of climate change and human activities on ecosystem dynamics. The land-use and land-cover change, one of the most important human activities, greatly affects the function and dynamics of ecosystems. Drought is one of the most costly natural disasters and imposes wide-ranging impacts on the economy, environment, and society. This dissertation aimed to strengthen the usage of remote sensing and eddy covariance techniques in paddy rice mapping, agricultural drought monitoring, land management effects assessment, and evaluating the impacts of drought on cattle production. Chapter 2 identified the different flooding/transplanting periods of paddy rice and natural wetlands. The natural wetlands foods earlier and have a shorter duration than paddy rice in the Panjin Plain, a temperate region in China. Using this asynchronous flooding stages, this chapter extracted the paddy rice planting area from the rice-wetland coexistent area using MODIS and Landsat 8 imagery. The comparison and validation tests indicated high accuracy of our paddy rice map. Chapter 3 quantified the agricultural drought of tallgrass prairie in the SGP using a remotely sensed water-related vegetation index derived from MODIS. The results are comparable to other widely used drought products. The spatial pattern of drought duration was highly correlated with the decreasing precipitation gradient from east to west. LSWI-based drought depictions are sensitive to both precipitation anomalies from the historical mean and abnormal seasonal precipitation distributions. A comparison with other widely used drought products is made. Chapter 4 examined the impacts of burning, baling, and grazing on canopy and carbon fluxes in a pasture through integrating PhenoCam images, satellite remote sensing, and eddy covariance data. Landsat images were used to assess the baling area and the trajectory of vegetation recovery. MODIS vegetation indices (VIs) were used in the Vegetation Photosynthesis Model (VPM) to estimate gross primary production (GPPVPM) at a MODIS pixel for the flux tower (baled) site. Multiple datasets allowed studying intra-annual variations caused by various management practices. The larger increase of GPP after large rain in baled grassland (photosynthetically more active vegetation) compensated the reduction in GPP caused by baling. This result indicated that the interaction of management practices with climate is important when studying their impacts on GPP. Chapter 5 evaluated the impacts of drought on cattle production in the SGP during 2000-2015 use meteorological, remote sensing, and statistical data. The results showed that the consecutive years of drought and high temperatures in 2011 and 2012 dramatically decreased the cattle production in OK and TX. The decrease extent in KS was smaller probably because of the greater accessibility to the groundwater resource. 2011 was a whole year drought in the SGP which decreased the hay production and thus cattle production, while 2012 was a summer drought year in the Corn Belt which increased the corn price and thus cattle production. The Random Forest method performed well and shows the potential in predicting the dynamics of cattle production. | en_US |
dc.identifier.uri | http://hdl.handle.net/11244/50829 | |
dc.language | en_US | en_US |
dc.subject | Remote sensing | en_US |
dc.subject | Eddy covariance | en_US |
dc.subject | Land use and land cover change | en_US |
dc.subject | drought | en_US |
dc.thesis.degree | Ph.D. | en_US |
dc.title | THE USE OF REMOTE SENSING AND EDDY COVARIANCE TECHNOLOGIES TO CHARACTERIZE CROPLAND, DROUGHT AND LAND MANAGEMENTS AND THEIR IMPACTS ON ECOSYSTEM DYNAMICS | en_US |
ou.group | College of Arts and Sciences::Department of Microbiology and Plant Biology | en_US |
shareok.nativefileaccess | restricted | en_US |