GIS + Practice
Abstract
‘Unmasking’ masked address data: A medoid geocoding solution
In recent years, there has been a consistent push for more open data initiatives, particularly for datasets collected by public agencies or groups that receive public funding. However, there is a tension between the release of open data and the preservation of individual and household privacy, whose balance shifts due to increased data availability, the sophistication of analysis techniques, and the computational power available to users. As a result, data masking is a standard tool used to preserve privacy, in which the data publishers obfuscate some identifying features in the dataset while attempting to maintain as much accuracy and precision as possible. For spatial datasets, the geocoding of administratively-masked data has been a consistent problem. Here, we present a medoid-based technique that geocodes masked data while minimizing the spatial uncertainty associated with the masking approach. Unfortunately, many commercial geocoding software packages can either not geocode administratively-masked data at all or may provide false positives by assigning points to city or street centroids. We demonstrate the results of our medoid-based geocoding approach by comparing it to commercial geocoding software. The results suggest that a medoid geocoding approach is mechanically simple to deploy and maximizes the spatial precision of the resulting geocodes.
Proximal Sensing
Topographic Correction of Proximally Sensed, High Resolution VisNIR Soil Spectra for Horizon-Scale Chemomapping
Soil properties are highly spatially heterogeneous both vertically and laterally in the subsurface making soil behavior particularly difficult to characterize and predict. Intact, horizon-scale soil monoliths can be collected to maintain soil heterogeneity and allow spatial analysis of soil properties using laboratory-based proximal sensing methods such as VisNIR hyperspectral imaging spectroscopy (HSI). HSI measures reflectance intensity spectra at 1.2 nm spectral resolution in the visible and near-infrared (400-1000 nm) with a pixel size of approximately 0.25 mm by 0.25 mm. However, surface roughness caused by the natural size, shape, and arrangement of soil aggregates and pores poses a challenge to mapping soil properties using HSI because non-flat surface topography influences the measured spectral signature. HSI methods currently handle the influence of surface roughness by artificially leveling the surface of intact monoliths. However, this approach could potentially disrupt the arrangement of the soil properties of interest. We aim to correct soil spectral signatures collected from non-flat surfaces for the influence of the angle between the hyperspectral camera and the surface being scanned (slope) and the direction the surface is facing in relation to the light sources (aspect) using a custom 3D printed sample array. This sample array presents homogenized soil samples with known composition at 91 prescribed orientations under the hyperspectral scanner. A novel algorithm was applied to discern the relationship between surface geometry and the observed reflectance spectra at each orientation. This new method allows predictions of soil properties to be made from pixels presented at any orientation in relation to the hyperspectral camera and light source. This advancement allows investigation of the spatial distribution of multiple soil properties on samples that have been prepared for soil structure and macropore network characterization and hence display a naturally rough surface (e.g., intact soil monoliths).
ArcGIS Indoors
Utilize a subset of campus buildings, our multi-disciplinary team performed the following tasks:
1. Instantiated and managed an ArcGIS Enterprise Indoors portal
2. Georeferenced CAD floor plan data to pre-determined specs
3. Attempted integration between Tririga (space system of record) and GIS, utilizing FME software
4. Attempted integration with parking space and building occupancy data
5. Where automation failed, manual efforts were employed to enhance data
6. Created ArcGIS Pro web scenes and uploaded to ArcGIS Enterprise
7. Developed presentation graphics from Indoors Viewer