This data set contains the boundaries of Missouri's 114 counties plus the boundary of the city of St. Louis.

This child data release provides the information needed to download from the USGS EarthExplorer portal digital orthophotos acquired during a tracer experiment performed on the Missouri River near Columbia, Missouri, on May 5, 2021. One of the primary goals of this tracer experiment was to assess the feasibility of inferring concentrations of a visible dye (Rhodamine WT) from various types of remotely sensed data in a large, highly turbid natural river channel. Previous research on remote sensing of tracer dye concentrations has focused on clear-flowing streams, but the Missouri River is much more turbid. As a result, the effect of the dye on the reflectance of the water could be obscured by the effects of suspended sediment on reflectance. This experiment thus provided an initial test of the potential to map dye concentrations from remotely sensed data in more turbid rivers like the Missouri. The experiment involved introducing a pulse of Rhodamine WT dye into the channel at an upstream transect and then observing the dispersion of the dye along the river using various in situ and remote sensing instruments. A flight contractor, Surdex Corporation, was enlisted to acquire digital orthophotography of the Missouri River area near Columbia MO, spanning the approximately 7 mile reach of the channel from river miles 176-183, during the experiment. Eight lines were flown starting around 9 am and flown 10 to 20 minutes apart, ending at 11:25 am central standard time. The images were captured with a Leica ADS100 Digital Mapping Camera. All survey ground control was also acquired and processed by Surdex, imagery was controlled using Airborne GPS/IMU technology on board the aircraft at the time of acquisition and processed against a stationary GPS base station. Four band digital imagery was processed and triangulated and then the imagery was fully orthorectfied and moaicked for 10cm digital orthophotography delivered as 4-band tiles. The resulting data set consists of orthophotos with a 10 cm pixel size. Surdex Corporation used the raw imagery to produce high resolution 10 cm 4-band (red, green, blue, and near-infrared) orthophotos for each of eight passes over the project area of interest. Tiled deliverable products were created from a custom tiling scheme consisting of 19 tiles for each of the eight flight lines and consist of 4 band tiff files with corresponding .tfw world files. The data set delivered by the flight contractor was transferred to the USGS Earth Resources Observation and Science (EROS) Center for archiving and distribution via the EarthExplorer web portal at https://earthexplorer.usgs.gov. EROS also produced metadata describing the orthophotos in the file EROSmetadata.csv. The orthophotos can can be obtained by visiting the EarthExplorer web site at https://earthexplorer.usgs.gov/and using the Entity ID field in the EROSmetadata.csv file. On the EarthExplorer home page, go to the second tab of the panel on the left, labeled Data Sets, select Aerial Imagery/High Resolution Orthoimagery, and click on Additional Criteria at the bottom. On the Additional Criteria tab, click the plus symbol next to Entity ID, enter the Entity ID value from the EROSmetadata.csv file for the tile of interest, and click on Results at the bottom. The tile should then appear in the results tab with several options represented by icons to show the footprint, overlay a browse image, or show the metadata and browse in a separate window. To download the data, click on the fifth icon from the left, which features a green download arrow pointing toward a disk drive, and click Download on the resulting pop-up to begin downloading a zip file. This zip archive contains a number of files in two subfolders. For example, for line 1, tile 10: 1) 4023644_line1_10.zip\MO\2021\202106_missouri_river_dye_columbia_mo_10cm_utm15_cnir\index001 contains shapefiles of tile layouts and exposure times for each flight line and tile and the metadata and ortho accuracy reports from the flight contractor. The folder 2) 4023644_line1_10.zip\MO\2021\202106_missouri_river_dye_columbia_mo_10cm_utm15_cnir\vol001 has the actual image as a tif (like line1_10.tif) and corresponding .tfw world file (like line1_10.tfw). These files can be opened and viewed in GIS or image processing software.

This data release includes hyperspectral image transects acquired from an Uncrewed Aircraft System (UAS) during a tracer experiment performed on the Missouri River near Lexington, Missouri, on May 11, 2024. One of the primary goals of this study was to assess the feasibility of inferring concentrations of a visible dye (Rhodamine WT) in a large, highly turbid natural river channel using data from a Uncrewed Aircraft Systems (UAS)-based hyperspectral imaging system. Previous research on remote sensing of tracer dye concentrations demonstrated the ability to obtain moderately precise concentration estimates from standard red-green-blue (RGB) video and orthophotos and this experiment allowed us to evaluate the hypothesis that more detailed spectral information could enable concentrations to be inferred with greater accuracy and precision. The broader objective motivating tracer studies along the Missouri River is to gain insight regarding the dispersion processes that influence the movement and survival of endangered sturgeon larvae. This data release provides access to several data sets obtained to support this experiment: 1. Image header files, quicklook previews, trajectory information, and other supporting files associated with hyperspectral data cubes acquired from a UAS for each of four separate flights conducted during the dye release. 2. Hyperspectral data cubes acquired from a UAS for each of four separate flights conducted during the dye release, processed to obtain calibrated reflectance values, and ultimately used to produce hyperspectral image transects. Please refer to the metadata file for further detail about each data set. Overall, these data were used to assess the potential for estimating tracer dye concentrations in turbid rivers from UAS-based hyperspectral image data.

The EnviroAtlas St. Louis, Missouri Meter-Scale Urban Land Cover (MULC) dataset comprises 4188 km2 around the city of St. Louis and surrounding land in parts of eleven counties within Illinois and Missouri. These MULC data and maps were derived from several sources from multiple years: LiDAR (2008-2012); 1-m pixel, four-band (red, green, blue, and near-infrared) leaf-on aerial photography acquired from the United States Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP, 2012, 2014-2016); leaf-off 6-inch pixel four-band imagery (2015) as well as ancillary vector data (e.g., roads, building footprints.). Eight land cover classes were mapped: Water, Impervious Surfaces, Soil/Barren, Tree/Forested, Grass/Herbaceous Non Woody Vegetation, Agriculture, and Wetlands (Woody and Emergent). Wetlands were delineated using the best available existing wetlands data, which was a National Wetlands Inventory (NWI) layer. An analysis of 745 completely random and 226 stratified random photo-interpreted land cover reference points yielded a simple overall user's accuracy (MAX) of 81% and an overall fuzzy user's accuracy (RIGHT) of 90% (see confusion matrices below). This dataset was produced in three phases by the University of Missouri and the East-West Gateway Council of Governments for the Missouri Resource Assessment Partnership (MoRAP) and the US EPA to support research and online mapping activities related to the EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets ).

This data release includes MATLAB source code associated with a manuscript titled "Hyperspectral Image Transects during Transient Events in Rivers (HITTER): Framework development and application to a tracer experiment on the Missouri River, USA" that was developed to support a tracer experiment performed on the Missouri River near Lexington, Missouri, on May 11, 2024. One of the primary goals of this study was to assess the feasibility of inferring concentrations of a visible dye (Rhodamine WT) in a large, highly turbid natural river channel using data from a Uncrewed Aircraft Systems (UAS)-based hyperspectral imaging system. Previous research on remote sensing of tracer dye concentrations demonstrated the ability to obtain moderately precise concentration estimates from standard red-green-blue (RGB) video and orthophotos and this experiment allowed us to evaluate the hypothesis that more detailed spectral information could enable concentrations to be inferred with greater accuracy and precision. The broader objective motivating tracer studies along the Missouri River is to gain insight regarding the dispersion processes that influence the movement and survival of endangered sturgeon larvae. A total of eight .m files are provided below to illustrate how the HITTER approach is implemented within the context of this particular case study on the Missouri River, and seven of the .m files are general functions that could be applied to other, similar data sets with appropriate modifications of input parameters and file paths. More specifically, the following .m files are included: 1. ProcessingLogNanoDye.m: a script intended to be run in sequence, with the various sections of the script corresponding to different steps in the HITTER framework by calling the remaining functions in this list. 2. nanoTrajectory.m: import trajectory information recorded during a UAS flight along with the frame index used to link trajectories to specific scan lines from the hyperspectral imaging system; 3. getHoverCubes.m: interactively select hyperspectral data cubes for further processing; 4. projectLine.m: project individual pixels along hyperspectral scan lines into real-world spatial coordinates based on the trajectory information; 5. linkLine2cube.m: link data cubes to projected scan line spatial coordinates and resample the hyperspectral data to a reduced set of output times; 6. sonde4nano.m: link hyperspectral image transects to field measurements of dye concentration; 7. genObraLin.m: perform Optimal Band Ratio Analysis (OBRA) to establish an empirical relationship between dye concentration and spectral reflectance, using source code originally developed for estimating water depth following the approach summarized by Legleiter and Harrison (2019) and included in the Optimal River Bathymetry Toolkit (Legleiter, 2020; Legleiter, 2021); and 8. cube2dyeMap.m: create a map of estimated dye concentrations from a processed hyperspectral data cube using an OBRA relationship derived using genObraLin.m, with a custom colormap from the crameri.m file that can be obtained via the link provided below. The .m files are thoroughly documented, with numerous comments to facilitate understanding of the code, but the user will need to update input parameters and file paths before attempting to use this code to apply the HITTER framework to a different data set. The code was developed in MATLAB R2024a (Version 24.1) with the Image Processing and Mapping Toolboxes (https://www.mathworks.com/products/matlab.html). Please note that the code is made available without warranty or support, as described in the distribution liability section of the metadata associated with this data release.

This datatset was developed by the Missouri Department of Natural Resources. This geo-dataset assigns 18 primary geologic units to the 2014 Missouri Natural Glades shapefile. It also represents the next iteration of the 2014 version increasing the previous number of glade polygons by 9,200 and the total acreage by over 23,500. Within the last four years, improved imagery and the expansion of mapping in several new counties resulted in these additions. The revised mapping and addition of more accurate geology shapefiles permitted the assignments of specific geologic units to the glade polygons. The American Bird Conservancy provided access to ArcMap to complete this project. The geo-dataset is designed to represent concise locations for the statewide distribution of Missouriâs principal glade-producing rock formations for dolomite, limestone, sandstone, igneous, shale and chert bedrock. The authors interpreted various imagery, geologic and topographic maps then conducted field surveys to validate mapping interpretations in various glade-producing landscapes. All of the glades can be readily cross-referenced to their respective natural community based on the delineation of the rock type incorporated into the geologic unit name. For example: Roubidoux, Lamotte, Channel, and St. Peters are all sandstone glade natural communities.

This child data release includes hyperspectral and RGB images acquired from an Unmanned Aircraft System (UAS) during an experiment performed at the USGS Columbia Environmental Research Center, near Columbia, Missouri, on April 2, 2019. The purpose of the experiment was to assess the feasibility of inferring concentrations of a visible dye (Rhodamine WT) tracer from various types of remotely sensed data in water with varying levels of turbidity. Whereas previous research on remote sensing of tracer dye concentrations has focused on clear-flowing streams, the Missouri River is much more turbid and the reflectance signal associated with the sediment-laden water could obscure that related to the presence and amount of dye. This experiment thus provided an initial test of the potential to map dye concentrations from remotely sensed data in more turbid rivers like the Missouri, where tracer studies involving the release of a visible dye can provide insight regarding the dispersal of endangered sturgeon larvae. The experiment involved manipulating the turbidity and Rhodamine WT dye concentration in two water tanks, acquring hyperspectral and RGB images, and attempting to infer dye concentrations from the images for varying levels of turbidity. Hyperspectral imagery (HSI) was collected with a Headwall Nano-Hyperspec (Headwall Photonics, Bolton, MA), a pushbroom sensor that measures reflectance from 400 - 1000 nm in the VNIR (visual and near-infrared). Sensor calibration was performed by collecting a dark reference with the lens cap on, and a white reference with a 25.4 cm x 25.4 cm Labsphere Spectralon? (Labsphere, INC, North Sutton, NH) calibrated diffuse reference target that reflects 99% of light in accordance with the National Institute of Standards and Technology. The sensor was mounted to a DJI Ronin-MX gimbal (DJI, Shenzhen, China) affixed to a DJI M600 Pro unmanned aerial vehicle (UAV) and flown 30 m above the tanks, yielding a ground sampling distance of 2 cm. The gimbal provides stability for the payload which aids in post-processing of the HSI. The UAV repeated a flight plan over the two tanks to create image data cubes. The resulting HSI was radiometrically corrected in the Headwall HyperspecIII SpectralView software package to convert raw digital numbers to radiance. The same software was used to orthorectify the images, which applies latitude and longitude GPS information to the cubes using data from an Xsens MTi-G-710 inertial measurement unit (IMU; Xsens, Enschede, The Netherlands). The white reference was included in each scene and used to make atmospheric corrections in ENVI (Harris Geospatial Solutions, Inc., Broomfield, CO) to convert radiance to relative reflectance. Timestamps from HSI were then compared to time stamps from the field spectra in a related data release to select only the data cubes that were nearest in time to when the field spectra were recorded. The RGB images were acquired using the built-in 12 megapixel camera on a DJI Mavic Pro UAV with an on-board GPS that collected position data during the flights. Images were acquired on a two-second interval while the UAV hovered in the same position. The original RGB images were used directly without further pre-processing. Time stamps for the images were used to link them to turbidity and concentration measurements made in situ in each tank during the experiment. The image data are compiled in a set of zip files, two for the hyperspectral images and one for the RGB images, and a text file listing the time stamps and file names for both types of images. The hyperspectral and RGB images selected for analysis were based on the time interval during which field spectra were recorded. The RGB image closest in time to each of the hyperspectral images used was selected from the list of available RGB images.

This data release includes digital orthophotos acquired during a tracer experiment performed on the Missouri River near Lexington, Missouri, on May 11, 2024. The orthophotos were acquired from a fixed-wing crewed aircraft and are provided as background images. One of the primary goals of this study was to assess the feasibility of inferring concentrations of a visible dye (Rhodamine WT) in a large, highly turbid natural river channel using data from a Uncrewed Aircraft Systems (UAS)-based hyperspectral imaging system. Previous research on remote sensing of tracer dye concentrations demonstrated the ability to obtain moderately precise concentration estimates from standard red-green-blue (RGB) video and orthophotos and this experiment allowed us to evaluate the hypothesis that more detailed spectral information could enable concentrations to be inferred with greater accuracy and precision. The broader objective motivating tracer studies along the Missouri River is to gain insight regarding the dispersion processes that influence the movement and survival of endangered sturgeon larvae. This data release provides access to two digital orthophotos acquired from a fixed-wing crewed aircraft to support this experiment: 1. A reach-scale mosaic that shows the dye pulse shortly after injection into the river and provides context for the study and the various data sets acquired during the experiment. 2. A higher-resolution orthophoto focused on the area where hyperspectral image transects were obtained, provided to serve as a background reference image for the other data sets. Please refer to the metadata file for further detail about each data set. Overall, these data were used to assess the potential for estimating tracer dye concentrations in turbid rivers from UAS-based hyperspectral image data.