Our Recent Research Efforts A-Xing Zhu and James E. Burt Department of Geography, University of...

Our Recent Research EffortsOur Recent Research Efforts

A-Xing Zhu and James E. BurtA-Xing Zhu and James E. Burt

Department of Geography, University of Wisconsin-Madison, Department of Geography, University of Wisconsin-Madison, Madison, Wisconsin, USAMadison, Wisconsin, USA

OutlineOutline

1. Neighborhood Size 1. Neighborhood Size EffectsEffects

2. Purposive Sampling2. Purposive Sampling

Impact of Neighborhood Size Impact of Neighborhood Size on Terrain Derivatives and on Terrain Derivatives and

Digital Soil MappingDigital Soil Mapping

A-Xing Zhu, James E. Burt, Michael A-Xing Zhu, James E. Burt, Michael Smith, Rongxun Wang, Jing GaoSmith, Rongxun Wang, Jing Gao

Department of Geography, University of Wisconsin-Madison, Department of Geography, University of Wisconsin-Madison, Madison, Wisconsin, USAMadison, Wisconsin, USA

Digital Soil Mapping Using GIS/RS

f ( E )

Digital Soil Maps Soil-Environment Relationships

Cl, Pm, Og, Tp …

Prediction through overlay(Inference)

G.I.S./R.S. TechniquesG.I.S./R.S. Techniques

Artificial Intelligence/Machine Learning TechniquesArtificial Intelligence/Machine Learning Techniques

Digital Terrain Analysis

The values of these derivatives are The values of these derivatives are computed over a neighborhood which computed over a neighborhood which seems to be impacted by:seems to be impacted by: DEM resolutions (Chang and Tsai, 1991; DEM resolutions (Chang and Tsai, 1991;

Thompson et al., 2001; Wilson et al., 2000)Thompson et al., 2001; Wilson et al., 2000) Neighborhood size (NS) over which they are Neighborhood size (NS) over which they are

computed (Wood, 1996)computed (Wood, 1996)

90ft. Resolution,180ft. NS





The objective of this research is to The objective of this research is to investigate the effect of DEM resolution investigate the effect of DEM resolution and NS on digital soil mappingand NS on digital soil mapping

We seek the answers to the following We seek the answers to the following three questions:three questions: Q1: How does the difference between field Q1: How does the difference between field

measured and computed slope gradient measured and computed slope gradient change with respect to DEM resolution and change with respect to DEM resolution and NS?NS?

Q2: What is the sensitivity of terrain derivatives Q2: What is the sensitivity of terrain derivatives to NS and resolution?to NS and resolution?

Q3: What is the impact of NS on digital soil Q3: What is the impact of NS on digital soil mapping? What impacts does resolution of mapping? What impacts does resolution of DEM on the quality of digital soil map? DEM on the quality of digital soil map?

Dane County, Wisconsin, USADane County, Wisconsin, USA

Two Study SitesTwo Study Sites

81 field slope measurements

43 field soil series observations(over a 75 hectare subsection with 4 different soil series)

First create a least squares regression polynomial First create a least squares regression polynomial surface over a user-specified neighborhood areas using surface over a user-specified neighborhood areas using (Wood, 1996; Shary et al., 2002; Schmidt et al., 2003):(Wood, 1996; Shary et al., 2002; Schmidt et al., 2003):

z = z = rrxx22 + + ttyy22 + + ssxy + xy + ppx + x + qqy + y + uu

Compute terrain derivatives (slope gradient, Compute terrain derivatives (slope gradient, slope aspect, profile and contour curvature) by slope aspect, profile and contour curvature) by analyzing the polynomial (Florinsky, 1998).analyzing the polynomial (Florinsky, 1998).

Gridded Surface Fitted Polynomial Surface

Method for computing terrain derivatives

Software to do this: 3dMapper

Original Elevation data sources:Original Elevation data sources: a 10ft. DEM from a 2000 air photographya 10ft. DEM from a 2000 air photography a 30ft. DEM from a 1995 air photographya 30ft. DEM from a 1995 air photography

Coarsening the 10ft. DEM to 15ft., 20ft., 25ft., Coarsening the 10ft. DEM to 15ft., 20ft., 25ft., 30ft., 35ft. 40ft., 45ft., 50ft EMs using the 30ft., 35ft. 40ft., 45ft., 50ft EMs using the nearest neighbor approach in ESRI Arc/INFO.nearest neighbor approach in ESRI Arc/INFO.

Coarsening the 30ft. DEM to 35ft. 40ft., 45ft., Coarsening the 30ft. DEM to 35ft. 40ft., 45ft., 50ft. DEMs using the nearest neighbor approach 50ft. DEMs using the nearest neighbor approach in ESRI Arc/INFO.in ESRI Arc/INFO.

Values of terrain derivatives were computed for Values of terrain derivatives were computed for each DEM resolution over each neighborhood each DEM resolution over each neighborhood size, up to 300ft. with 5 ft incrementsize, up to 300ft. with 5 ft increment

Experiment Design

Q 1: Q 1: Difference in slope gradient by NS and resolutionDifference in slope gradient by NS and resolution

0

1

2

3

4

5

6

10 25 40 55 70 85 100115130145160175190205220235250265280295

Neighborhood Size(feet)

RM

SE

(slo

pe

per

cen

tag

e)

10ft_DEM

15ft_10ft

20ft_10ft

25ft_10ft

30ft_10ft

35ft_10ft

40ft_10ft

45ft_10ft

50ft_10ft

30ft_DEM

35ft_30ft

40ft_30ft

45ft_30ft

50ft_30ft

Observations:Observations: 1. The difference is 1. The difference is smallest not at thesmallest not at the finest neighborhoodfinest neighborhood size, but rather atsize, but rather at some larger size,some larger size, about 100 feet in thisabout 100 feet in this casecase

2. Resolution does not 2. Resolution does not seem to play a roleseem to play a role

Q 2: Sensitivity to NS (with resolution at 10 ft)

Q 2: Relative change across NS (with resolution at 10 ft)

Q 2: Sensitivity to DEM resolution (with NS around 150 ft)

What does all of these say?What does all of these say?

Soil scientists do use a specific neighborhood sizeSoil scientists do use a specific neighborhood size to measure slope gradient for soil investigationto measure slope gradient for soil investigation What they use is often different from what isWhat they use is often different from what is computed using a 3x3 kernel.computed using a 3x3 kernel. NS has much stronger impact on terrain derivativesNS has much stronger impact on terrain derivatives at smaller neighborhood sizeat smaller neighborhood size

The question is “so what?”The question is “so what?” Does this matter for digital soil mapping? Does this matter for digital soil mapping?

Fuzzy Inference Engine

Soil Series Map

The SoLIM (The SoLIM (SoSoil-il-LLandscape andscape IInference nference MModel) approach (Zhu et al. 2001) is used to odel) approach (Zhu et al. 2001) is used to derive soil series maps:derive soil series maps:

Knowledge AcquisitionSoilSeries: Ambrant Instance: 1 Pmaterial: Granite_geology.rel Elevation: Ambrant_north-facing-at-4000-4500-ft_Elevation.rel Aspect: Ambrant_north-facing-at-4000-4500-ft_Aspect.rel Gradient: Ambrant_15-60%_Gradient.rel Canopy: Ambrant_medium-tree-density_Tree_Density.rel Curvature: Ambrant_convex-to-straight_Curvature.rel Instance: 2 Pmaterial: Granite_geology.rel Elevation: Ambrant_south-facing-at-4000-6000-ft_Elevation.rel Aspect: Ambrant_south-facing-at-4000-6000-ft_Aspect.rel Gradient: Ambrant_15-60%_Gradient.rel Canopy: Ambrant_medium-tree-density_Tree_Density.rel Curvature: Ambrant_convex-to-straight_Curvature.rel

(Knowledgebase)

GIS/RS Techniques

(Environment Database)

Experiment Design for impact on soil mapping

Experiment Design for impact on soil mappingDigital Soil Mapping Experiment:Digital Soil Mapping Experiment:

Fuzzy Inference Engine

SoilSeries: Ambrant Instance: 1 Pmaterial: Granite_geology.rel Elevation: Ambrant_north-facing-at-4000-4500-ft_Elevation.rel Aspect: Ambrant_north-facing-at-4000-4500-ft_Aspect.rel Gradient: Ambrant_15-60%_Gradient.rel Canopy: Ambrant_medium-tree-density_Tree_Density.rel Curvature: Ambrant_convex-to-straight_Curvature.rel Instance: 2 Pmaterial: Granite_geology.rel Elevation: Ambrant_south-facing-at-4000-6000-ft_Elevation.rel Aspect: Ambrant_south-facing-at-4000-6000-ft_Aspect.rel Gradient: Ambrant_15-60%_Gradient.rel Canopy: Ambrant_medium-tree-density_Tree_Density.rel Curvature: Ambrant_convex-to-straight_Curvature.rel

KnowledgebaseEnvironment Database

Non-Terrain:Terrain derivatives:

Versions of Soil Series Maps

…

Constant Constant Varying by NS and resolution

Experiment Design for impact on soil mappingEvaluation of Soil Map Quality:Evaluation of Soil Map Quality:

Sampling Strategy: Sampling Strategy: Transect samplingTransect sampling

Quality Measure:Quality Measure: Percent correctly mapped Percent correctly mapped

Thompson Farm Site

Q3:Q3: Impact on digital soil mapping - NSImpact on digital soil mapping - NS

0

10

20

30

40

50

60

70

80

10 20 40 50 70 80 100

110

130

140

160

170

Neighborhood Size

(%)

Acc

ura

cy

10 ft.

15 ft.

30 ft.

DEM Resolution

Observations:Observations: 1. Highest accuracy is neither at the smallest NS, nor at the1. Highest accuracy is neither at the smallest NS, nor at the largest NS, somewhere in the middle, about 100-110 feetlargest NS, somewhere in the middle, about 100-110 feet similar to that of similar to that of slope neighborhood sizeslope neighborhood size in this case in this case 2. The difference in accuracy is quite large, about double in2. The difference in accuracy is quite large, about double in this casethis case

0

10

20

30

40

50

60

70

80

10 20 40 50 70 80 100

110

130

140

160

170

Neighborhood Size(%

) A

ccu

racy

10 ft.

15 ft.

30 ft.

Resolution

0

1

2

3

4

5

6

10 25 40 55 70 85 100115130145160175190205220235250265280295

Neighborhood Size(feet)

RM

SE

(slo

pe

per

cen

tag

e)

10ft_DEM15ft_10ft20ft_10ft25ft_10ft30ft_10ft35ft_10ft40ft_10ft45ft_10ft50ft_10ft30ft_DEM35ft_30ft40ft_30ft45ft_30ft50ft_30ft

Observations:Observations: 1. DEM resolution does not seem to play much a role when 1. DEM resolution does not seem to play much a role when a variable neighborhood approach is taken, as long as thea variable neighborhood approach is taken, as long as the resolution is within the optimal NS.resolution is within the optimal NS. 2. Larger NS mutes the role of resolution even further.2. Larger NS mutes the role of resolution even further.

Q3:Q3: Impact on digital soil mapping - Role of DEM resolutionImpact on digital soil mapping - Role of DEM resolution

Summary of Findings

1. NS used by soil scientists are often different from that computed form the 3x3 kernel in ArcGIS

2. Impact of NS on terrain derivatives are much stronger at smaller NS. It is more important to choose a proper NS when NS is small.

3. The impact of this difference in neighborhood size on digital soil mapping can be amplified through the computed terrain derivatives, causing significant difference in the quality of the so-derived soil maps

4. DEM resolution does not have much an impact when neighborhood size is accounted for

Implications

1.At least for digital soil mapping, choosing an appropriate neighborhood size is more important than increasing the resolution of DEM.

2. Cost-effectiveness of acquiring high resolution DEM for digital soil mapping needs re-examination.

3. Common sense: scale or spatial extent or neighborhood size should be tied to the scale of the process under concern, not the resolution of the data at hand.

Future Studies

1.What is the spatial extent (neighborhood size) soil scientists use when conducting soil investigation? Does it change over different landscape? How does it change among field soil scientists?

2.What is the utility of high resolution DEM (particularly Lidar) for digital soil mapping?

Purposive Sampling for Digital Soil Mapping

A-Xing Zhu1, Baolin Li2, Edward English1 Lin Yang2, Chengzhi Qin2, James E. Burt1, Chenghu Zhou2

1 Department of Geography

University of Wisconsin-Madison, USA

2 State Key Lab of Resources and Environmental Information System

Institute of Geographical Sciences and Natural Resources Research

Chinese Academy of Sciences, China

Predictive Soil Mapping: The Basis and Key Issue:

S <= f ( E )

Relationships between Soil and Its Environment(Soil – Landscape Model)

Environmental Conditions

G.I.S./R.S.

Local Experts

Knowledge Acquisition

Artificial Neural Network

Large Point Set

Case-Based Reasoning

Typical Pedon Set

Spatial Data Mining

Existing Soil Maps

Predictive Soil Mapping:

The Problem:

Extensive fieldwork

For areas where there are

no soil experts and no available soil maps andno field observations

how to obtain the needed soil-landscape model?

The challenge is that field observation is typically very costly, time consuming, and often ineffective

Our objective is to develop a method to improve the efficiency of field sampling so that predictive soil is not only possible but also efficient for unmapped areas

Predictive Soil Mapping:

How we do it? - Purposive Sampling

Assumptions:

The unique status of soil types is created under unique combinations of environmental conditions.

The spatial locations of typical soil types can be approximated by the locations of unique combination of environmental conditions.

soil typesCombination of

environmental conditions

GIS/RS

Fuzzy Classification - FCM

Purposive SamplingMethod:

soil typesCombination of

environmental conditions

Environmental Conditions

Sample the Center of the Combination

Fuzzy Membership Map for Each Combination

Interpretation

Soil-Landscape Model

S <= f ( E )

Soil Spatial Distribution

SoilSeries: Ambrant Instance: 1 Pmaterial: Granite_geology.rel Elevation: Ambrant_north-facing-at-4000-4500-ft_Elevation.rel Aspect: Ambrant_north-facing-at-4000-4500-ft_Aspect.rel Gradient: Ambrant_15-60%_Gradient.rel Canopy: Ambrant_medium-tree-density_Tree_Density.rel Curvature: Ambrant_convex-to-straight_Curvature.rel Instance: 2 Pmaterial: Granite_geology.rel Elevation: Ambrant_south-facing-at-4000-6000-ft_Elevation.rel Aspect: Ambrant_south-facing-at-4000-6000-ft_Aspect.rel Gradient: Ambrant_15-60%_Gradient.rel Canopy: Ambrant_medium-tree-density_Tree_Density.rel Curvature: Ambrant_convex-to-straight_Curvature.rel

Soil-Landscape Model

Environmental database

Purposive SamplingFor Predictive Mapping:

Inference (prediction)

Study area: A glaciated plain in Wisconsin Soil scientist: John Campbell

3500 m

ete

rs

3200 meters

Case Studies – The U.S. Case

Memberships of Environmental Combinations

Class 9

Class 1

Class 7

Class 5

Class 4


The catenary sequence of soils in the area

Glacial Till

Kidder

Virgil

Sable Mayville

Loess Cap

St. Charles

McHenry


Spatial distribution of soils over the area


LegendKidder

McHenry

St.Charles

Sable

Mayville

Virgil

3,5

00

mete

rs3,200 meters

LegendKidder

McHenry

Sable

Virgil

3,5

00

mete

rs3,200 meters

Validation of Results

Area Accuracy

Overall 76%

Drumlins 95%

Inter-Drumlins 63%

A total of 50 field points*

* Points used to develop the soil-landscape model were not used for validation


Area: 60km2.Elevation: 276 ~ 363mAverage slope: 2 °.Landuse: corn and wheat farming.Parent material: silt loam loess.

The study area is located in a small watershed in North-Eastern China

Case Studies – The Chinese Case

The catenary sequence of soil types


Class 3 Class

4

Class13

Class 10

Class 6

Class 2 ，5

Class 11

Class 7

Class 8

Class 12

Class 1 Class

9

Mollic Bori-Udic Cambosols Typic Hapli-Udic

Isohumosols -1

Lithic Udi-Orthic Primosols

Typic Hapli-Udic Isohumosols -2

Typic Bori-Udic Cambosols

Fibric Histic-typic Haplic-Stagnic Gleyosols

Pachic Stagni-Udic Isohumosols

YANGLIN

This map is better than the above one, but you should translate it into English.

Soil type mapSoil type map

Legend

N

Subgroup soil map of study

area

Mollic Bori-Udic Cambosols

Typic Hapli-Udic Isohumosols

Typic Bori-Udic Cambosols

Lithic Udi-Orthic Primosols

Pachic Stagni-Udic Isohumosols

Fibric Histic-Typic Haplic Stagnic Gleyosols


a. Random sampling b. regular sampling

c. transecting sampling

Validation points: 64

Evaluation of soil map


Overall accuracy: 72%Along the transect : 80%

The approach does seem to allow us to improve the efficiency of developing soil-landscape model of reasonable quality.

The approach seemed to work better in areas with strong relief

Summaries

However, the limitations of fuzzy classification techniques is the key challenge facing this approach

Thank You!Thank You!

Our Recent Research Efforts A-Xing Zhu and James E. Burt Department of Geography, University of...

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