We are currently working with several Maori iwi in New Zealand to improve their GIS capabilities and integrate spatial knowledge in their decision-making processes. The main aim of this work is enabling the iwi to create and manage their own GIS projects and use the results to enhance their day to day operations and long-term planning. In this pilot study on land use improvement with GIS and RS we created a spatial model to find the best land uses for a given land block and then integrated the results with profit forecasts in order to provide the landowners with a better understanding of the land capability. We used high resolution data captured with drones as well as freely available spatial datasets that we processed, reclassified, weighted and combined using ESRI ArcGIS software. The result is a series of land unit polygons, each representing a unique combination of possible land uses and relative forecast profit. This combined spatial and economic information provides a comprehensive understanding of the potential of a block of land. The modelling process is simple, flexible, clear to understand and easy to replicate, but more importantly it can be effectively used to make informed land management decisions.

1. 1
Improving
a collaborative pilot study with local indigenous organisations
Elisa Puccioni
Senior GIS Analyst at Kenex

2. Hamilton 14-16 May
IT ALL STARTED HERE…

3. Why should I use GIS?
Can it help understand
my land better?
How will it add value to my
organisation?

5. Basic GIS skills
+
Basic GIS tools
THE CHALLENGE:
How to keep it simple?

6. Forestry
AgriculturePasture
Manuka
Honey

7. $800 NZD/ha per year
(harvest in 25 years)
$600 NZD/ha
(rolling hills agriculture)
1 hive per ha – average
NZD/kg applied
$2,000 NZD/ha (flats)
$100k NZD/ha (blueberry)
Parameters analysed
Terrain parameters
Current land cover
Land use capability
Erosion areas
Water availability
Water quality
Soil characteristics
Parameters missing

8. FIRST STEP, FLYING A DRONE… THEN, CREATING THE GIS

9. 1
FIRST STEP, FLYING A DRONE… THEN, CREATING THE GIS
1 2 3 4 5

10. 1
FIRST STEP, FLYING A DRONE… THEN, CREATING THE GIS
2 3 4 52

11. 1
FIRST STEP, FLYING A DRONE… THEN, CREATING THE GIS
2 3 4 53

12. 1
FIRST STEP, FLYING A DRONE… THEN, CREATING THE GIS
2 3 4 54

13. 1
FIRST STEP, FLYING A DRONE… THEN, CREATING THE GIS
2 3 4 55

14. 1
FIRST STEP, FLYING A DRONE… THEN, CREATING THE GIS
2 3 4 5
+
LandCare LUC classes, river line,
riparian margins, high risk erosion areas

15. 1 2 3 4 5
+
LandCare LUC classes, river line,
riparian margins, high risk erosion areas
HIGH RES DATA
LOW RES DATA

16. PUTTING ALL TOGETHER: Spatial Models
Parameters ResultsBinary Maps
6 parametersFlat Land
7 parametersBlueberry
5 parameters
Rolling
Hills
2 parametersForestry
3 parametersHoney
Reclass
&
Weight
Areas with all the
parameters
presents
Total ha calculated
for each area
Profit/ha calculated
and applied
Fuzzy
Overlay
AND

17. Final Land Capability Map
$12.4K
$7.3K
15.5 ha
9.1 ha
$5.4K
4.5 ha
$3.6K $9K
0.3 ha
$250 $600 $30K
$10k1.6 ha

18. The modelling process is simple and
flexible, easy to teach.
With it we can model for different
land uses.
We used only ArcGIS tools (and
DroneDeploy)
Landowners were happy of the
increased knowledge of their land.
WHAT WE LEARNED:
Data at block resolution is hard to
find, limiting the model accuracy.
We love drones, but they are
expensive and time consuming.
We still need extensions and apps
to complete the model ($$)
Image interpretation can be
complicated with basic GIS skills
PROS CONS

19. 1
2
3
BUILD YOUR GIS PLATFORM
CREATE DB & FIND MISSING DATA
4
5
LEARN THE TOOLS AND PRACTICE
SHARE ONLINE!
CREATE NEW PROJECTS & DIY!

20. Questions
&
Feedback
Thank
you!
Moka Apiti