GeoAnalytics Tools Applied to Large Geospatial Datasets

Depth to Water, Saturated Thickness, and Other Geospatial Datasets Used in the Design and Installation of a Groundwater Monitoring-Well Network in the High Plains Aquifer, Colorado

Data Series ◽

10.3133/ds472 ◽

2009 ◽

Author(s):

Jennifer L. Flynn ◽

L. Rick Arnold ◽

Suzanne S. Paschke

Keyword(s):

Groundwater Monitoring ◽

High Plains ◽

High Plains Aquifer ◽

Monitoring Well ◽

Geospatial Datasets ◽

Water Saturated ◽

Saturated Thickness ◽

Groundwater Monitoring Well

Download Full-text

An effective assessment protocol for continuous geospatial datasets of forest characteristics using USFS Forest Inventory and Analysis (FIA) data

Remote Sensing of Environment ◽

10.1016/j.rse.2010.05.010 ◽

2010 ◽

Vol 114 (10) ◽

pp. 2337-2352 ◽

Cited By ~ 55

Author(s):

Rachel Riemann ◽

Barry Tyler Wilson ◽

Andrew Lister ◽

Sarah Parks

Keyword(s):

Forest Inventory ◽

Forest Inventory And Analysis ◽

Assessment Protocol ◽

Geospatial Datasets ◽

Effective Assessment

Download Full-text

Geospatial Open Data Usage and Metadata Quality

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi10010030 ◽

2021 ◽

Vol 10 (1) ◽

pp. 30

Author(s):

Alfonso Quarati ◽

Monica De Martino ◽

Sergio Rosim

Keyword(s):

Spatial Information ◽

Open Data ◽

Poor Quality ◽

Data Usage ◽

Open Government Data ◽

Metadata Quality ◽

Geospatial Datasets ◽

Government Data ◽

Determining Factor

The Open Government Data portals (OGD), thanks to the presence of thousands of geo-referenced datasets, containing spatial information are of extreme interest for any analysis or process relating to the territory. For this to happen, users must be enabled to access these datasets and reuse them. An element often considered as hindering the full dissemination of OGD data is the quality of their metadata. Starting from an experimental investigation conducted on over 160,000 geospatial datasets belonging to six national and international OGD portals, this work has as its first objective to provide an overview of the usage of these portals measured in terms of datasets views and downloads. Furthermore, to assess the possible influence of the quality of the metadata on the use of geospatial datasets, an assessment of the metadata for each dataset was carried out, and the correlation between these two variables was measured. The results obtained showed a significant underutilization of geospatial datasets and a generally poor quality of their metadata. In addition, a weak correlation was found between the use and quality of the metadata, not such as to assert with certainty that the latter is a determining factor of the former.

Download Full-text

Modeling Streamflow and Sediment Loads with a Photogrammetrically Derived UAS Digital Terrain Model: Empirical Evaluation from a Fluvial Aggregate Excavation Operation

Drones ◽

10.3390/drones5010020 ◽

2021 ◽

Vol 5 (1) ◽

pp. 20

Author(s):

Joseph P. Hupy ◽

Cyril O. Wilson

Keyword(s):

Soil Erosion ◽

Point Cloud ◽

Empirical Evaluation ◽

Digital Terrain Model ◽

Surface Flow ◽

Sediment Loading ◽

Terrain Model ◽

Digital Terrain ◽

Statistical Measures ◽

Geospatial Datasets

Soil erosion monitoring is a pivotal exercise at macro through micro landscape levels, which directly informs environmental management at diverse spatial and temporal scales. The monitoring of soil erosion can be an arduous task when completed through ground-based surveys and there are uncertainties associated with the use of large-scale medium resolution image-based digital elevation models for estimating erosion rates. LiDAR derived elevation models have proven effective in modeling erosion, but such data proves costly to obtain, process, and analyze. The proliferation of images and other geospatial datasets generated by unmanned aerial systems (UAS) is increasingly able to reveal additional nuances that traditional geospatial datasets were not able to obtain due to the former’s higher spatial resolution. This study evaluated the efficacy of a UAS derived digital terrain model (DTM) to estimate surface flow and sediment loading in a fluvial aggregate excavation operation in Waukesha County, Wisconsin. A nested scale distributed hydrologic flow and sediment loading model was constructed for the UAS point cloud derived DTM. To evaluate the effectiveness of flow and sediment loading generated by the UAS point cloud derived DTM, a LiDAR derived DTM was used for comparison in consonance with several statistical measures of model efficiency. Results demonstrate that the UAS derived DTM can be used in modeling flow and sediment erosion estimation across space in the absence of a LiDAR-based derived DTM.

Download Full-text