Data management plan for the grant, "DISES: Integrating environmental justice into urban forest assessment and valuation tools: blueprint for the future."

Data management plan for the grant, "Multi-Source Irrigation Status and Type Mapping." This grant will quantify the long-term irrigation status and system type changes in the Mississippi Alluvial Valley for an advanced understanding of irrigation-induced water resource changes by integrating multi-source earth observation data, machine learning techniques, artificial intelligence and cloud computing.

Data management plan for the project "Detecting Irrigation System Types for Agricultural Lands Across the Nation."

Data management plan for the grant, "Patterns and Drivers of Intra-Urban Heat and Pollution Island Interactions." Research on the urban heat island (UHI) and urban pollution island (UPI) effects at the neighborhood scale by integrating sensor networks, earth observations, and geospatial analysis. The spatial patterns and intra-annual variability of UHI-UPI interactions and model the urban form drivers controlling UHI-UPI interaction variability will also be examined. These data will be analyzed to determine when and where urban heat islands and urban pollution islands occur, and the risks that their interaction poses to urban residents. These results will support informed decision-making for urban heat and air pollution mitigation.

Data management plan for the grant, "Collaborative Research: MRA: Particulates in canopy flowpaths: A missing mass flux at the macrosystem scale?" This research will investigate a vital, but currently uncharacterized, macrosystem biogeochemical function within forest canopies at the very start of the terrestrial hydrologic cycle: particulate concentration, flux, and composition in rainwaters draining from forest canopies. We will address three major objectives: (1) Estimate the net rainfall (TF+ SF) water and particulate mass flux across forest types; (2) Characterize the particulate composition (C:N:P, including C components, like total C, organic C, black C, and microplastic C) of TF and SF; and (3) Identify major drivers of macrosystem variability in net rainfall particulate flux and composition.