Innovative tools for agriculture, S-Map

1. Innovative Tools for Agriculture
using S-map Online
as a case study
James Barringer
Landcare Research
Lincoln, New Zealand
Also acknowledging S-map Online colleagues at LCR (David Medyckyj-Scott, Tim Heuer, Andrew
Cowie, Sam Carrick, Allan Hewitt, Linda Lilburne), colleagues at SPC, and all of the Pedologists
and organizations that have collected Pacific Soils Data.

2. Outline
1. outline the objectives of sharing soils data and
related knowledge
2. What is S-map Online
3. What are the results of making these data and
knowledge available.
4. How might this innovation benefit PICTs

3. 1. Objectives of sharing data
and knowledge

4. Policy Context
NZ Government Open Policy Data:
Open - Available - Authoritative - Well Managed - Reasonably
Priced (expected to be free) - Reusable.
Landcare Research’s Core purpose:
drive innovation in the management of terrestrial biodiversity
and land resources.
Guiding Principle:
High quality science data should underpin research, policy
formation and business decisions around land use decisions.

5. In the
beginning
there was a
paper map
and a soil
report that
you could
buy.

6. Then digital soil maps
SOIL NAME CODE AER'N BS% CEC R'DP CM N PH P K SAL'Y MIN SLOPE MAX SLOPE TEXT A TEXT B TEXT INF DEPTH A DEPTH B DEPTH INF AWC A AWC B DRWC A DRWC B DRWC INF
SOILS OF THE COASTAL MARSHES
LABASA 1 4 76 45 60 0.22 4.5 8 1.85 0.8 0 0 3 3 4 15 45 40 13 13 10 10 22
TIRI 2 4 98 56 65 0.17 5.1 35 1.94 0.9 0 0 4 4 0 32 33 0 16 14 16 14 0
SOSO 3 4 32 51 45 0.64 4.1 15 0.37 1 0 0 3 2 0 10 35 0 13 12 10 8 0
DREKETI 4 4 23 57 60 1.04 4.5 15 0.37 1.2 0 0 3 2 0 15 45 0 13 12 10 8 0
DOGO 5 2 [100] 112 0 0.11 7.1 35 10.50 2.1 0 0 3 3 0 0 0 0 0 0 0 0 0
SOILS OF THE BEACH STRANDS DUNES AND ESTUARIES
NUKU 6 6 99 42 150 0.25 8.2 8 0.18 0.2 0 2 5 5 5 10 20 120 9 9 8 8 30
YASAWA 7 6 100 40 160 0.25 8.0 8 0.10 0.2 0 2 5 5 5 10 50 100 8 8 28 28 30
TACILEVU 8 4 100 41 80 0.37 8.2 8 0.06 0 0 2 4 4 0 15 65 0 10 10 22 22 0
VUNIBAU 9 4 42 14 150 0.07 5.8 8 0.08 0 0 3 4 5 5 15 35 100 10 9 22 24 30
WAIKALOU 10 6 40 15 100 0.10 6.0 8 0.15 0.2 0 6 4 5 5 30 35 35 10 8 21 28 28
VOLIVOLI 11 4 40 10 150 0.11 6.6 8 0.16 0 0 7 5 5 5 15 60 75 8 8 28 28 28
VUNAVUTU 12 4 86 35 125 0.19 6.5 8 0.78 0 0 1 2 3 2 30 45 50 13 15 10 11 11
DEUBA 13 4 75 25 60 0.22 5.5 8 0.10 0.8 0 1 4 5 5 20 40 0 9 9 22 24 0
DAWASAMU 14 6 30 10 150 0.20 7.3 3 0.00 0.2 0 2 4 5 5 8 22 120 10 8 22 28 30
VUNILAGI 15 4 90 50 70 0.20 7.0 8 0.70 0.8 0 2 2 2 0 30 40 0 13 13 9 9 0
RANA 16 4 94 47 30 0.48 7.3 8 0.53 0.2 0 3 4 0 0 30 0 0 17 0 21 0 0
QARIBUTA 17 4 33 49 30 1.47 4.5 8 1.08 0 0 0 8 0 0 30 0 0 18 0 20 0 0
NAKELO 18 6 78 11 100 0.02 6.3 8 0.05 0 0 0 3 3 4 15 60 25 13 13 13 13 24
TOGURU 19 4 78 18 40 0.14 5.6 8 0.31 0.8 0 0 4 4 0 23 17 0 16 16 22 22 0
NASELESELE 20 6 free lime 19 120 0.20 7.4 8 0.22 0 0 1 5 5 5 25 30 25 6 5 24 24 30
SOILS OF THE MAJOR FLOODPLAINS
MUAINASE 21 6 74 29 75 0.20 6.0 8 0.19 0 0 0 3 3 4 22 53 30 15 13 11 13 22
REWA 22 6 76 27 100 0.23 5.6 8 0.13 0 0 0 4 3 4 28 78 25 13 14 12 14 12
LAWAI 23 6 92 32 140 0.23 6.5 8 2.50 0 0 3 4 4 4 49 60 41 16 10 22 18 18
TAMANUA 24 4 85 30 65 0.24 5.7 8 0.09 0 0 3 3 3 0 38 27 0 13 13 15 15 0
NADURU 25 6 47 21 110 0.11 5.5 8 0.07 0 0 3 3 3 3 30 20 60 13 13 11 11 12
WAINIBUKA 26 6 80 43 110 0.20 5.6 8 0.87 0 0 3 2 2 2 20 30 60 13 13 9 9 9
SIGATOKA 27 6 84 32 120 0.20 5.7 8 1.20 0 0 1 3 3 3 75 25 20 14 14 12 12 12
YAQARA 28 6 60 27 120 0.30 5.8 8 0.41 0 0 3 3 3 3 20 40 60 13 13 12 13 12
WAINIVESI 29 5 67 33 140 0.07 5.8 8 0.68 0 0 3 3 3 2 25 50 65 13 13 12 13 15
NAVUA 30 5 67 30 90 0.30 5.7 8 0.16 0 0 3 4 3 0 33 57 0 14 14 14 14 0
TOKOTOKO 31 4 62 29 80 0.20 5.4 8 0.81 0 0 0 3 2 0 35 45 0 14 12 13 9 0
NAUSORI 32 4 49 24 70 0.20 5.1 8 0.20 0 0 0 3 2 0 28 42 0 14 13 13 12 0
MELIMELI 33 2 10 92 50 1.96 4.5 8 0.97 0 0 0 4 8 0 13 37 0 14 20 10 20 0
and soil attributes

7. How we used to share digital data…
In 2009, Landcare Research supplied less
than 50 copies of LRIS data to users
2000’s
1970’s
1980’s
1960’s

8. 2. What is S-map Online

9. • Consistent soil map coverage – replace previous
patchwork of individual surveys
• Rationalised soil naming convention
• Key soil attributes for all soils
• Additional derived information for all soils
• Centralised curation and quality assurance
• Ease of integration of soil with other data sets/ models
• Application from paddock to national scales
• Web accessible
S-map – NZ’s new soils information

10. S-map Online (= Web Accessible)
Soils information that is:
easily found/discovered
readily accessible
easy to “use”
rich in information
foster communities of cooperation
readily understood/everyday language(s)
easy to maintain
updatable (dynamic)

11. S-map factsheet

12. S-map print map

13. 3. Results of making data and
knowledge available.

14. User Statistics (S-map)
S-map Online (4 ½ years)
• Launched 29/8/2011
• 140,000 visits from 77,000 visitors
• 320,000 pages viewed
• 3.9 million screen maps
• Nearly 200,000 point queries
• 9,000 maps printed
• 135,000 soil fact sheets generated
• http://smap.landcareresearch.co.nz

15. S-map Online Trends
0
1000
2000
3000
4000
5000
6000
7000
8000
Visits/Visitors
Visitors
Visits
Visitors
Factsheets
Linear (Visits)
Linear (Visitors)

16. 3. How might this innovation
benefit PICTs?

17. Context for
Pacific Development Challenges
• Small countries (population, land area, arable land)
• Remote (large internal and external distances to markets)
• Small-holder farming (subsistence, product quality)
• Land Tenure (customary tenure, absentee landowners)
• Alternative income sources (remittances, etc.)
• Urban drift and emigration

18. Why might a soil portal be valuable in
the Pacific Region ?
• Very Limited or irregular funding
• Limited soils expertise – network/collaborate
• High turn-over of experienced staff
• Need to protect “institutional knowledge”
• As a repository for soils data
• Small areas – “no economy of scale”
• Remote areas – hard to access
• Subsistence agriculture

19. State of Pacific Soils Knowledge
• Existing soil survey reports and maps are often
hard to obtain.
• Reports written for a more scientific audience
rather than land users.
• Loss of knowledge through promotion or
retirement of soil scientists.
 Limited ability to turn scientific data into
knowledge useful to a range of users.
 Resulting in poorer land use decision-
making at many levels.
 Impacts environment, biodiversity,

20. Country Scale Area
(km2)
Area
(%)
Surveyor Date Dig
Cook Islands 10,000 225 85% NZ DSIR Soil 1972-78 
Tonga 10,000 672 60% NZ DSIR Soil 1980s 
Fiji 50,000 18070 92% DSIR/LCR 1980s 
Kiribati 10,000 770 1% USP 1985 
FSM 10,000 693 80% USDA 1980-85 ?
French Pol. 40,000 2994 49% ORSTOM 1975-85 ?
New Caledonia 300,000 18850 88% ORSTOM 1953 ?
Samoa 50,000 2842 100% DSIR Land 1989 
American Samoa 126,720 206 97% USDA 1984 ?
Palau 10,000 516 ? USDA 1983 ?
Tokelau - 10 - USDA 1988 ?
Niue 50,000 263 100% DSIR Soil 1985 
Mariana Islands 50,000 477 ? USDA 1988 ?
Guam 190,080 541 100% USDA 1988 ?
Marshall Islands ? 174 ? USDA 1989 ?
PNG 100,000 64630 100% AUS. PNGRIS 1985 – 95 
Solomon Islands 150,000 26556 100% UK MOD/LRD ?
Tuvalu - 23 - - - -
Vanuatu 50,000 12105 100% AUS. VANRIS 1993 
Wallis & Futuna 40,000 176 100% ORSTOM 1986 ?

21. Who is it for ?
Soil scientists: soil taxonomic unit descriptions and other
key data.
Agricultural extension officers: easy transfer of knowledge
between scientist and farmers.
Farmers: advice on land use options and hazards (erosion,
flooding, etc.).
Environmental scientists: supporting data for research and
modelling.
Planners/Policy Makers: information and knowledge to
support policy and decision-making.
Other users/needs can be recognised and catered for as
required.

22. Current Status of Pacific Soil Portal
• Endorsed by Heads of Agriculture and
Forestry Services (HOAFS) in Fiji – 2006
• Included in SPC strategic plan 2006-2008
• Global Financial Crisis = no funding
• Global Soil Partnership/Pacific Soil
Partnership (PSP) - support since 2010
• CSIRO/LCR/SPC and “member countries”
• PSP currently applying for ACIAR funding ?

23. Soils Data in PNG
• Embedded in PNGRIS only?
• National coverage but coarse scale
• Is it all digitized/available/accessible?
• How helpful at farm-scale?
BUT
• May be useful in identifying priority areas
• Secure/protect and build on knowledge base

24. THANK YOU