This web map was developed to assist the community of Leoti, Kansas, with nearby playa and playa catchment identification. As potential hotspots for aquifer recharge, playas near city water supply wells can be targeted for preservation or restoration in an effort to improve local groundwater recharge.More information:https://playasworkforkansas.com/tomorrows-water/https://www.gmd1.org/documents/PLJV-Playas.pdfhttps://pljv.org/grant-helps-kansas-communities-address-water-supply/https://pljv.org/two-kansas-projects-support-local-water-sustainability/The primary web map source is accessed from the Kansas Applied Remote Sensing Rest Services:https://services.kars.geoplatform.ku.edu/arcgis/rest/servicesLast edited 06/22/2023

Companies in the Surveying and Mapping Services industry have struggled with volatile downstream demand over the past few years. Demand for surveying services fluctuates in response to construction activity, as surveyors are a necessity for construction projects. Although demand for surveying services has risen in areas like heavy and civil engineering construction, as well as exploration, these gains haven’t been enough to counterbalance a drop in demand from residential building construction. Slow growth in the number of surveyors has constrained the market’s size, as more experienced surveyors are retiring while fewer young people are interested in pursuing surveying as a career. Overall, revenue is expected to have contracted at an annualised 3.9% over the five years through 2024-25 to $4.0 billion, including an anticipated plummet of 7.1% in 2024-25. Technological advancements in surveying and mapping services have influenced the industry’s performance. Cost-effective drone surveying technology with fast processing speeds has allowed some companies to provide value-added products that appeal to time-sensitive clients. However, some downstream clients with large capital resources have bypassed third-party surveying service providers, even though they can offer specialised services, and developed in-house surveying capabilities for cost efficiency, limiting surveyors’ pricing ability. Some large-scale surveyors have capitalised on a flurry of high-profile projects to build stronger reputations and expand their market share. Over the coming years, a recovery in key downstream sectors, including residential housing construction, as interest rates ease will improve the industry’s performance. As softening interest rates improve downstream conditions, surveyors working in construction markets will be in a better position to capitalise on improved downstream conditions. Investment in apartment and townhouse construction will also rally, driven by government efforts to solve housing supply shortages over the coming years. Industry revenue is projected to climb at an annualised 2.2% over the five years through 2029-30 to $4.1 billion.

Indiana's Statewide Lidar data is produced at 1.5-meter average post spacing for all 92 Indiana Counties covering more than 36,420 square miles. New Lidar data was captured except where previously captured Lidar data exists, or the participating County bought-up to a higher resolution of 1.0-meter average post spacing Lidar data. Existing Lidar data exists for: Porter, Steuben, Noble, De Kalb, Allen, Madison, Delaware, Hendricks, Marion, Hancock, Morgan, Johnson, Shelby, Monroe, and portions of Vermillion, Parke, Vigo, Clay, Sullivan, Knox, Gibson, and Posey. These existing Lidar datasets were seamlessly integrated into this new statewide dataset. From this seamless Lidar product a statewide 5-foot post spacing hydro-flattened DEM product was created and is also available. See the FGDC Metadata provided for more details.

This statewide project is divided into three geographic areas captured over a 3-year period (2011-2013):
Area 1 (2011) Indiana central counties: St. Joseph, Elkhart, Starke, Marshall, Kosciusko, Pulaski, Fulton, Cass, Miami, Wabash, Carroll, Howard, Clinton, Tipton, Boone, Hendricks, Marion, Morgan, Johnson, Monroe, Brown, Bartholomew, Lawrence, Jackson, Orange, Washington, Crawford, and Harrison.

Area 2 (2012) Indiana eastern counties: LaGrange, Steuben, Noble, DeKalb, Whitley, Allen, Huntington, Wells, Adams, Grant, Blackford, Jay, Hamilton, Madison, Delaware, Randolph, Hancock, Henry, Wayne, Shelby, Rush, Fayette, Union, Decatur, Franklin, Jennings, Ripley, Dearborn, Ohio, Scott, Jefferson, Switzerland, Clark, and Floyd.

Area 3 (2013) Indiana western counties: Lake, Porter, LaPorte, Newton, Jasper, Benton, White, Warren, Tippecanoe, Fountain, Montgomery, Vermillion, Parke, Putnam, Vigo, Clay, Owen, Sullivan, Greene, Knox, Daviess, Martin, Gibson, Pike, Dubois, Posey, Vanderburgh, Warrick, Spencer, and Perry.

Funders of OpenTopography Hosting of the Indiana Statewide Lidar and DEM data: USDA NRCS, Indiana, ISPLS Foundation, Indiana Geographic Information Office, Indiana Office of Technology, Indiana Geological Survey, Surdex Corporation, Vectren Energy Delivery, Indiana, Woolpert, Inc., and Individual IGIC Member Donations from Jim Stout, Jeff McCann, Cele Morris, Becky McKinley, Phil Worrall, and Andy Nicholson.

To explore a web map of topographic differencing for the entire state of Indiana click here

This part of DS 781 presents data for the geologic and geomorphic map of the Offshore of Point Reyes map area, California. The vector data file is included in "Geology_OffshorePointReyes.zip," which is accessible from http://pubs.usgs.gov/ds/781/OffshorePointReyes/data_catalog_OffshorePointReyes.html. Marine geology and geomorphology was mapped in the Offshore of Point Reyes map area from approximate Mean High Water (MHW) to the 3-nautical-mile limit of Californiaâ  s State Waters. MHW is defined at an elevation of 1.46 m above the North American Vertical Datum of 1988 (NAVD 88) (Weber and others, 2005). Offshore geologic units were delineated on the basis of integrated analyses of adjacent onshore geology with multibeam bathymetry and backscatter imagery, seafloor-sediment and rock samples (Reid and others, 2006), digital camera and video imagery, and high-resolution seismic-reflection profiles. The onshore bedrock mapping was compiled from Galloway (1977), Clark and Brabb (1997), and Wagner and Gutierrez (2010). Quaternary mapping was compiled from Witter and others (2006) and Wagner and Gutierrez (2010), with unit contacts modified based on analysis of 2012 LiDAR imagery; and additional Quaternary mapping by M.W. Manson. The morphology and the geology of the Offshore of Point Reyes map area result from the interplay between tectonics, sea-level rise, local sedimentary processes, and oceanography. The Point Reyes Fault Zone runs through the map area and is an offshore curvilinear reverse Fault Zone (Hoskins and Griffiths, 1971; McCulloch, 1987; Heck and others, 1990; Stozek, 2012) that likely connects with the western San Gregorio fault further to the south (Ryan and others, 2008), making it part of the San Andreas Fault System. The Point Reyes Fault Zone is characterized by a 5 to 11 km-wide zone that is associated with two main fault structures, the Point Reyes Fault and the Western Point Reyes Fault (fig. 1). Tectonic influences impacting shelf morphology and geology are related to local faulting, folding, uplift, and subsidence. Granitic basement rocks are offset about 1.4 km on the Point Reyes thrust fault offshore of the Point Reyes headland (McCulloch, 1987), and this uplift combined with west-side-up offset of the San Andreas Fault (Grove and Niemi, 2005) resulted in uplift of the Point Reyes Peninsula, including the adjacent Bodega and Tomales shelf. The Western Point Reyes Fault is defined by a broad anticlinal structure visible in both industry and high-resolution seismic datasets and exhibits that same sense of vergence as the Point Reyes Fault. The deformation associated with north-side-up motion across the Point Reyes Fault Zone has resulted in a distinct bathymetric gradient across the Point Reyes Fault, with a shallow bedrock platform to the north and east, and a deeper bedrock platform to the south. Late Pleistocene uplift of marine terraces on the southern Point Reyes Peninsula suggests active deformation west of the San Andreas Fault (Grove and others, 2010) on offshore structures. The Point Reyes Fault and related structures may be responsible for this recent uplift of the Point Reyes Peninsula, however, the distribution and age control of Pleistocene strata in the Offshore of Point Reyes map area is not well constrained and therefore it is difficult to directly link the uplift onshore with the offshore Point Reyes Fault structures. Pervasive stratal thinning within inferred uppermost Pliocene and Pleistocene (post-Purisima) units above the Western Point Reyes Fault anticline suggests Quaternary active shortening above a curvilinear northeast to north-dipping Point Reyes Fault zone. Lack of clear deformation within the uppermost Pleistocene and Holocene unit suggests activity along the Point Reyes Fault zone has diminished or slowed since 21,000 years ago. In this map area the cumulative (post-Miocene) slip-rate on the Point Reyes Fault Zone is poorly constrained, but is estimated to be 0.3 mm/yr based on vertical offset of granitic basement rocks (McCulloch, 1987; Wills and others, 2008). With the exception of the bathymetric gradient across the Point Reyes Fault, the offshore part of this map area is largely characterized by a relatively flat (<0.8à °) bedrock platform. The continental shelf is quite wide in this area, with the shelfbreak located west of the Farallon high , about 35 km offshore. Sea level has risen about 125 to 130 m over about the last 21,000 years (for example, Lambeck and Chappell, 2001; Peltier and Fairbanks, 2005), leading to broadening of the continental shelf, progressive eastward migration of the shoreline and wave-cut platform, and associated transgressive erosion and deposition (for example, Catuneanu, 2006). Land-derived sediment was carried into this dynamic setting, and then subjected to full Pacific Ocean wave energy and strong currents before deposition or offshore transport. Much of the inner shelf bedrock platform is composed of Tertiary marine sedimentary rocks, which are underlain by Salinian granitic and metamorphic basement rocks, including the Late Cretaceous porphyritic granite (unit Kgg), which outcrops on the seafloor south of the Point Reyes headland. Unit Kgg appears complexly fractured, similar to onshore exposures, with a distinct massive, bulbous texture in multibeam imagery. The Tertiary strata overlying the granite form the core of the Point Reyes syncline (Weaver, 1949) and include the early Eocene Point Reyes Conglomerate (unit Tpr), mid- to late Miocene Monterey Formation (unit Tm), late Miocene Santa Margarita Formation (unit Tsm), late Miocene Santa Cruz Mudstone (unit Tsc), and late Miocene to early Pliocene Purisima Formation (unit Tp). The Point Reyes Conglomerate is exposed on the seafloor adjacent to onshore outcrops on the Point Reyes headland and has a distinct massive texture with some bedding planes visible, but the strata are highly fractured. Based on stratigraphic correlations from seismic reflection data and onshore wells, combined with multibeam imagery, we infer rocks of the early Eocene Point Reyes Conglomerate extend at least 6 km northwest from onshore exposures at Point Reyes headland. The absence of unit Tsc in onshore wells (Clark and Brabb, 1997) suggests these rocks are unlikely to occur within the Tertiary section of this map area, north of the Point Reyes Fault. In this map area, unit Tu represents seafloor outcrops of a middle Miocene to upper Pliocene sequence overlying unit Tpr, that may include units Tm, Tsm, and Tp. Seafloor exposures of unit Tu are characterized by distinct rhythmic bedding where beds are dipping and by a mottled texture where those beds become flat-lying. Modern nearshore sediments are mostly sand (unit Qms and Qsw) and a mix of sand, gravel, and cobbles (units Qmsc and Qmsd). The more coarse-grained sands and gravels (units Qmsc and Qmsd) are primarily recognized on the basis of bathymetry and high backscatter. The emergent bedrock platform north and west of the Point Reyes headland is heavily scoured, resulting in large areas of unit Qmsc and associated Qmsd. Both Qmsc and Qmsd typically have abrupt landward contacts with bedrock and form irregular to lenticular exposures that are commonly elongate in the shore-normal direction. Contacts between units Qmsc and Qms are typically gradational. Unit Qmsd forms erosional lags in scoured depressions that are bounded by relatively sharp and less commonly diffuse contacts with unit Qms horizontal sand sheets. These depressions are typically a few tens of centimeters deep and range in size from a few 10's of meters to more than 1 km2. There is an area of high-backscatter, and rough seafloor southeast of the Point Reyes headland that is notable in that it includes several small, irregular "lumps", with as much as 1 m of positive relief above the seafloor (unit Qsr). Unit Qsr occurs in water depths between 50 and 60 meters, with individual lumps randomly distributed to west-trending. This area on seismic-reflection data shows this lumpy material rests on several meters of latest Pleistocene to Holocene sediment and is thus not bedrock outcrop. Rather, it seems likely that this lumpy material is marine debris, possibly derived from one (or more) of the more than 60 shipwrecks offshore of the Point Reyes Peninsula between 1849 and 1940 (National Park Service, 2012). It is also conceivable that this lumpy terrane consists of biological "hardgrounds". Video transect data crossing unit Qsr near the Point Reyes headland was of insufficient quality to distinguish between these above alternatives. A transition to more fine-grained marine sediments (unit Qmsf) occurs around 50â  60 m depth within most of the map area, however, directly south and east of Drakes Estero, backscatter and seafloor sediment samples (Chin and others, 1997) suggest fine-grained sediments extend into water depths as shallow as 30 m. Unit Qmsf is commonly extensively bioturbated and consists primarily of mud and muddy sand. These fine-grained sediments are inferred to have been derived from the Drakes Estero estuary or from the San Francisco Bay to the south, via predominantly northwest flow at the seafloor (Noble and Gelfenbaum, 1990). References Cited Catuneanu, O., 2006, Principles of Sequence Stratigraphy: Amsterdam, Elsevier, 375 p. Chin, J.L., Karl, H.A., and Maher, N.M., 1997, Shallow subsurface geology of the continental shelf, Gulf of the Farallones, California, and its relationship to surficial seafloor characteristics: Marine Geology, v. 137, p. 251-269. Clark, J.C., and Brabb, E.E., 1997, Geology of the Point Reyes National Seashore and vicinity: U.S. Geological Survey Open-File Report 97-456, scale 1:48,000. Galloway, A.J., 1977, Geology of the Point Reyes Peninsula Marin County, California: California Geological Survey Bulletin 202, scale 1:24,000. Grove, K. and Niemi, T., 2005, Late Quaternary deformation and slip rates in the northern San

A real-world multi-vehicle multi-modal V2V and V2X dataset Recently published datasets have been increasingly comprehensive with respect to their variety of simultaneously used sensors, traffic scenarios, environmental conditions, and provided annotations. However, these datasets typically only consider data collected by one independent vehicle. Hence, there is currently a lack of comprehensive, real-world, multi-vehicle datasets fostering research on cooperative applications such as object detection, urban navigation, or multi-agent SLAM. In this paper, we aim to fill this gap by introducing the novel LUCOOP dataset, which provides time-synchronized multi-modal data collected by three interacting measurement vehicles. The driving scenario corresponds to a follow-up setup of multiple rounds in an inner city triangular trajectory. Each vehicle was equipped with a broad sensor suite including at least one LiDAR sensor, one GNSS antenna, and up to three IMUs. Additionally, Ultra-Wide-Band (UWB) sensors were mounted on each vehicle, as well as statically placed along the trajectory enabling both V2V and V2X range measurements. Furthermore, a part of the trajectory was monitored by a total station resulting in a highly accurate reference trajectory. The LUCOOP dataset also includes a precise, dense 3D map point cloud, acquired simultaneously by a mobile mapping system, as well as an LOD2 city model of the measurement area. We provide sensor measurements in a multi-vehicle setup for a trajectory of more than 4 km and a time interval of more than 26 minutes, respectively. Overall, our dataset includes more than 54,000 LiDAR frames, approximately 700,000 IMU measurements, and more than 2.5 hours of 10 Hz GNSS raw measurements along with 1 Hz data from a reference station. Furthermore, we provide more than 6,000 total station measurements over a trajectory of more than 1 km and 1,874 V2V and 267 V2X UWB measurements. Additionally, we offer 3D bounding box annotations for evaluating object detection approaches, as well as highly accurate ground truth poses for each vehicle throughout the measurement campaign. Data access Important: Before downloading and using the data, please check the Updates.zip in the "Data and Resources" section at the bottom of this web site. There, you find updated files and annotations as well as update notes. The dataset is available here. Additional information are provided and constantly updated in our README. The corresponding paper is available here. Cite this as: J. Axmann et al., "LUCOOP: Leibniz University Cooperative Perception and Urban Navigation Dataset," 2023 IEEE Intelligent Vehicles Symposium (IV), Anchorage, AK, USA, 2023, pp. 1-8, doi: 10.1109/IV55152.2023.10186693.