Applications of soil spectroscopy on Land Health Surveillance

Hands-on Soil Infrared Spectroscopy Training Course

Getting the best out of light11 – 14 November 2013

Applications of soil spectroscopy on Land Health Surveillance

Ermias BetemariamErick Towett

Context (i)• Soil comes to the global agenda:

– Sustainable intensification took soil as a x-cutting

– Global Environmental Benefits - land degradation and soils are among the priority global benefits (GEF/UNCCD)

• SOC as useful indicator of soil health

• Importance of soil carbon in global carbon cycle and climate mitigation

• carbon trading purposes requires high levels of measurement precision

• Increasing demand for soil data at fine spatial resolution

2Ermias Betemariam, Erick Towett | Hands-on soil infrared spectroscopy training course | Nairobi | May 2014 |

Context There is a lack of coherent and rigorous sampling and assessment

frameworks that enable comparison of data (i.e. meta-studies) across a wide range of environmental conditions and scales

Soil monitoring is expensive to maintain Soil degradation and loss is a challenge High spatial variability in soil properties- large data sets reduce uncertainty

Context (iI)

High spatial variability of SOC can rise sevenfold when scaling up from point sample to landscape scales, resulting in high uncertainties in calculations of SOC stocks. This hinders the ability to accurately measure changes in stocks at scales relevant to emissions trading schemes (Hobley and Willgoose, 2010)

Soil spectroscopy key for Land Health Surveillance

Ermias Betemariam, Erick Towett | Hands-on soil infrared spectroscopy training course | Nairobi | May 2014 | 3

Land Health (SD4)Land Health - the capacity of land to sustain delivery of essential ecosystem services

Land health surveillance aims to provide statisticallyvalid estimates of land health problems, quantify keyrisk factors associated with land degradation, andtarget cost-effective interventions to reduce or reversethese risks.


Land Health Projects

No. Name of project

1Africa Soil Information Service (AfSIS)/Africa Soils (SSA)

2Strengthening capacity for diagnosis and management of soil micronutrient deficiencies (SSA)

3Soil monitoring protocol for the World Bank Living Standards Measurement Study (Ethiopia & ..)

4Carbon sequestration options in pastoral & agro-pastoral systems in Africa (Burkina Faso & Ethiopia)5Land health surveillance for high value biocarbon development (Kenya, Burkina Faso & Sierra

Leone)6Land health surveillance system for smallholder cocoa in Ivory Coast

7Trees for food security in Eastern Africa (Rwanda, Ethiopia, Burundi & Uganda)

8Land health surveillance for mitigation of climate change in agriculture (Kenya & Tanzania)

9Land health surveillance system in support of Malawi food security project (Malawi)

10Land health surveillance system for targeting agroforestry based interventions for sustainable land productivity in the western highlands of Cameroon

11A Protocol for Measurement and Monitoring Soil Carbon Stocks in Agricultural Landscapes

Land Health Projects (i)


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Land Health Projects (ii)

Ermias Betemariam, Erick Towett | Hands-on soil infrared spectroscopy training course | Nairobi | May 2014 |

Land Health out-scaling projects (iii)

Tibetan Plateau/ Mekong

Parklands Malawi

National surveillance systemsRegional Information Systems

Project baselines

Rangelands E/W AfricaSLM Cameroon MICCA E. Africa

Global-Continental Monitoring Systems

Evergreen Ag / Horn of Africa

CRP5 pan-tropical basins AfSIS

EthioSIS- Ethiopia

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Cocoa - CDI


AfSIS ✓60 primary sentinel sites

➡ 9,600 sampling plots➡ 19,200 “standard” soil samples➡ ~ 38,000 soil spectra

AfSIS: Soil functional properties (1)

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EthioSIS 97 Sentinel sites


AfSIS: Soil functional propertiesSpectral diagnostics tools can be used to produce soil maps

Prediction map for soil organic carbon for sub-Saharan Africa. (Source: Africa Soil Information Service)


AfSIS: Soil functional propertiesFrom polygon-based to probabilistic mapping

+

Probability of observingcultivation

Current lime requirement ? ~ min [prob(pH < 5.5), prob(cult)]

Probability topsoil pH < 5.5 ... very acid soils

Grid-based probabilistic maps increases the reliability of the map and its power to be combined with other data sources (remote sensing & terrain data)

(Walsh, 2013)

=

Taxonomic soil classification systems provide little information on soil functionality in particular the productivity function (Mueller et al 2010)

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Living Standards Measurement Study-LSMS-IMS (3)Improve measurements of agricultural productivity through methodological validation and research

Mobile phones for quick soil screening- being tested

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Low cost MIR soil testing for smallholder farmers


Carbon sequestration in pastoral & agro-pastoral systems (4)

Effects of range management on soil organic carbon stocks in savanna ecosystems of Burkina Faso & Ethiopia

Fire (controlled burning -19 years) – Burkina Faso

Grazing (Exclosures 12- 36 years) – Ethiopia

Fire influence:• Carbon allocation - SOC gain• Decrease input - SOC loss

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ResultsNo Sig difference in SOC between burned and unburned plots

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ResultsNo Sig difference in SOC between burned and unburned plots

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ResultsNo sig. difference in SOC between closed and open plots for all age categories

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Challenges in cocoa productionBiocarbon development in East and West Africa (5)• Develop effective and cost efficient carbon monitoring, reporting and

verification systems that can enable smallholders to access carbon markets• Soil spectroscopy will be key component

Estimating biocarbon using LiDAR data- Taita, Kenya(a) indigenous forest, (b) mixed stand of local and exotic species (Eucalyptus sp.) and (c) cropland with scattered trees

Janne et al., 2013

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Smallholder cocoa in Ivory Coast-V4C (6)

Disease + pest?

Soil fertility?

Major challenges

LDSF and soil spectroscopy to identify constraints & target interventions in cocoa production

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Trees for food security –ACIAR

Rwanda

Ethiopia

Characterize land health constraints and assessing Agroforestry intervention outcomes

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Mitigating Climate Change in Agriculture-MICCA (8)

East African Dairy Development (EADD- Kenya)

Conservation agriculture (CARE- Tanzania)

Characterize (baseline) and assess impacts of climate smart agriculture practices

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Measurement and Monitoring Soil Carbon Stock (11)Can we measure soil carbon cost effectively?

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Land Health Surveillance

Consistent field protocol

Soil spectroscopyCoupling with remote sensingPrevalence, Risk factors, Digital

mapping

Sentinel sites Randomized sampling schemes

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Measurement and Monitoring Soil Carbon Stock (11)

Why measure carbon?

1

What will the protocol deliver?

2

3How much will it

cost?

4 Sampling

5 Field work

6 Lab work

7 Data analysis

8 Presenting results

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Sample size determination

Sample allocation Moisture content

Soil Carbon stock Error

Measurement and Monitoring Soil Carbon Stock (11)

Web and excel based tool

…. and reporting

DATA INFORMATION KNOWLEDGE WISDOM

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A management that leads to a DECREASE in bulk density will UNDER ESTIMATES SOC stocks & vice versa

C conc.(%) Depth(cm)Bulk density (g/cm) SOC stock (Mg/ha) Error

1.5 150 1.2 270 1.5 150 1 225 -16.67%

Monitoring SOC stocks

(Ellert and Bettany, 1995)

Bulk density as confounding variable in comparing SOC stocks

Think mass not depth

Why cumulative soil mass?

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10 50 100 150 200 2500

2000

4000

6000 NIR spectroscopyThermal oxidationSample preparationSoil sampling

Number of samples

Co

st (

US

D)

Personnel Others0

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15NIR spectroscopy Thermal oxidationSample preparation Soil sampling

Co

st p

er

sam

ple

(U

SD

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Cost –error analysis

0 500 1000 15000

2000

4000

6000

8000 Thermal oxidationNIR spectroscopy

Number of samples

Cost

(USD

)

Comparisons of costs of measuring SOC using a commercial lab and NIR

CostIR is cheaper (~ 56%) than dry combustion method for large number of samples

ThroughputCombustion ~ 30-60 samples/dayNIR ~ 350 samples/dayMIR ~ 1000/day


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0 200 400 600 800 10000.00

2.00

4.00

6.00

8.00

10.00

Number of samples

Hal

f 95%

con

fiden

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terv

al (t

C h

a-1)

0 5000 10000 15000 200000.00

2.00

4.00

6.00

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10.00

Cost of carbon measurement (USD)

Hal

f 95%

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Cost –error analysisCosts of measurement often exceed the benefits – soil spectroscopy address this challenge

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Activity Sources of uncertainty

Sampling Sampling design (random, stratified random)

Sample size

SOC measurement

Natural variability (spatial)

Sample preparation (e.g. contamination, subsampling)

Lab method used (instrument resolution)

Human error

Field data collection (e.g. soil mass, volume)

SOC prediction using IR

Imported uncertainties (from reference data)

Model (assumption) Instrument and human errors

Mapping SOC

Covariates used

Image pre -processing (geometric and radiometric corrections)

Scale/resolution (e.g. farm vs landscape)

Model (assumption, strength)

Sources of uncertainty

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Common causes of measurement uncertainty• the instruments used, • the item being measured,• the environment, • the operator, • other sources

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CASE 1 High precision (repeatable) High accuracy Random error (less biased)

CASE 2 High precision (repeatable) Low accuracy Systematic error (biased)

CASE 3 Low precision (not repeatable) High accuracy Random error (less biased)

CASE 4 Low precision (not repeatable) Low accuracy Systematic error (biased)

Accuracy versus precision


Things to be careful!

Proper labelingAvoid contamination

Lets do it right

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Data archiving/publishingDatasaving – dataverse: http://thedata.harvard.edu/dvn/

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http://thedata.harvard.edu/dvn/

• More research on cost-effective measurement tools• Web services are needed that allow optimised soil information to be

automatically exchanged via the internet• Proximal soil sensing

• Reduce uncertainties in measurements- error propagates• Develop national capacities, networking and partnership • Baselines are established for important soil properties across Africa• Soil spectroscopy filling the data gaps- at National, Regional & Global

levels• Enable decision makers have clear understanding of soil status and trends• Spectroscopy is proved good- adoption and application

• Cross sentinel/regional sites analysis

Finally…

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Thank you

Applications of soil spectroscopy on Land Health Surveillance

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