Millenials and Fillennials (Ethical Challenge and Responses).pptx
Brennan - Soil Survey Applications of LiDAR Data
1. Soil Survey Applications of LIDAR Improving the topographic Base Joe Brennan Northern Great Plains Region USDA-NRCS Soil Survey Staff
2.
3.
4.
5.
6.
7.
8. Improving topographic Base 2009 2010 LIDAR Available - Blue IFSAR Available - Green LIDAR & IFSAR Coverage in the Eastern Dakotas (USDA-SCA, SCD, TSP)
9. SRTM 30m Digital Elevation Model USGS NED 30m Digital Elevation Model USGS NED 10m Digital Elevation Model IFSAR 5m DTM Slope in Hilly AND Rolling Terrain
10. NED 30m Digital Elevation Model NED 10m Digital Elevation Model 1m Terrain Model Bare-Earth LIDAR Nearly Level and Level Terrain
11. Why Now?: Improved Terrain Base Materials – LIDAR/IFSAR 1-5m DTM Existing Terrain Base Materials – USGS 10m DEMs LIDAR Landsape Position Identification - Prairie Pothole Region - Northeastern South Dakota Soil Survey ApplicationS OF LIDAR Terrain Depressions Terrain Depressions
20. High Resolution DEMs – Building Consistent Mapping Techniques Soil Survey ApplicationS OF LIDAR
21. Why Now?: LIDAR Hydric Landscape Analysis - Northeastern South Dakota Wet Year Ortho Imagery (Fall 1997) Spectral Ortho Rectified Radar Image (IFSAR) or Intensity Image (LIDAR) Composite Hydric Rating Highest Probability Model for Potential Wetlands Define Inputs Guide Field Work Soil Survey ApplicationS OF LIDAR Soil Survey Hydric Rating Soils 5m DTM from LIDAR or IFSAR Terrain
22. LIDAR – Soil Landscape Covariates – Till Plain – Northeastern North Dakota Slope Gradient Slope Shape Wetness Depression Distance Local Relief Relative Position Soil Survey ApplicationS OF LIDAR Existing Knowledge & Documentation
23. LIDAR – Soil Series Inference – Till Plain – Northeastern North Dakota Series 1 Series 2 Soil Survey ApplicationS OF LIDAR
24. LIDAR – Applications of Inference Models – Till Plain – Northeastern North Dakota Inherent Soil Productivity Soil Survey ApplicationS OF LIDAR Organic Carbon Management Zones
25. LIDAR Soil Series Inference - Glacial Lake Agassiz - North Dakota Soil Survey ApplicationS OF LIDAR
26.
Editor's Notes
Joe Brennan Soil Data Quality Specialist for GIS in North Dakota and the Northern Great Plains MLRA Region. Topographic rendering of North Dakota demonstrates that North Dakota is most certainly not flat State with variable landscapes needs a multidimensional strategy to model the topography
Soil Landscape Modeling has been seen as the future of Soil Survey for the last ten years with SOLIM (Soil Land Inference Model) and susbequent projects. Field Soil Scientist have tacit knowledge of Soil Landscape relationships to the point that many can predict to a high level of accuracy where a soil series will occur within a mapunit that may contain 5-10 series. The only thing preventing us from making strides in this effort is the limited availability of datasets that accurately represent the landscape. Therefore we have been a part of multiple efforts in the last several years to improve the topographic base, which our State Conservationist has strongly supported. Not only for soil survey, but for other applications that will come to light as we further explore this data.
To demonstrate the importance of this data I went through an exercise in cross-sectioning the same landscape using all digital terrain data we have available to us. SRTM is interferometric radar data that creates a surface model not a terrain model.
Then the National Elevation Dataset 30m resolution creates a smooth terrain model, but coarser in resolution
And 10m resolution. These are both good products, but they are limited by spatial resolution and the intervals in the existing hypsography.
IFSAR is also a surface model, but is post-processed into a digital terrain model that is a fairly accurate representation of the surface in the right conditions
LIDAR is of course the gold standard having seemingly limitless applications
In the Eastern Dakotas and NW MN the data is becoming readiliy available. We have pursued IFSAR in areas of moderate relief recognizing that a statewide LIDAR collection is unlikely with the lower land-use intensity outside of the Red-River Basin. While LIDAR and IFSAR are very different products we are using them interchangably for soil survey. IFSAR data is a desirable product in canopy free conditions and luckly for us in North Dakota that is 99% of the state.
Slope in lower relief areas are better represented by remotely sensed terrain models LIDAR & IFSAR
Microrelief is best represented by LIDAR where cms of elevation change can make all the difference in soil formation
While the difference between these two oblique views are very subtle, when you get right down to it in modeling for such things a depressional landscapes these products make all the difference.
In older soil surveys less soils were used and often times certain unique features were glossed over, that may be seen as critical. Glaciolacustrine soils identified in soil survey, where we would expect them to also be mapped on ice-walled lake plains
The coarser beach ridges on Lake Agassiz are often times not ridges at all, but may only be a foot or so difference in elevation and sometimes not recognizable in photography
Ice drag markings in the Red River Valley need to be further investigated to see if there is a unique morphological environment
Patterns of surface drainage are very evident in LIDAR data. We see a lot of soils formerly mapped as depressional with surface drainage.
The complexity of a channel in alluvium is significant to soil formation and potential landuse and is most certainly not evident in leaf on imagery
Slope length is significant in conservation planning, it is not populated in many soil surveys, but maybe we can take a second look
We can better quantify which slopes are contained within delineations, to build consistent slope groups and consistent methods of interpreting slopes
Soils & Hydrology can both be infered in a great level of detail, to some degree through accurate depiction of the landscape.
![[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Improving topographic Base](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)