OrganoLandView

Team Name

Pure Land Seekers

Team Members

Project Description

In response to the need of a local organic horticultural business, to be able to visually inspect collated data, relevant to land use decisions, we are creating a tool that enables relevant and available land data sets to be selected and prioritised so that colour coded overlays, in plan view, plus various other displays, can show a land buyer or owner what they need, to quickly decide whether a particular land parcel is suitable, how valuable and for what crops.

Data Story

After considering what Paul Hughes said Bostock would like, we initially settled on creating a web app that would upload all the appropriate data sets. A lengthy process began, of locating appropriate data sets and seeing what we could do with them. Along the way, we checked with Paul, who generally agreed all such information would be important. Then we ran into the obstacle of finding a valuable data set which was not in any familiar text format. None of us knew much about GIS or how to access data generated for it. After finding the GIS data set format information in Wikipedia and deciding it was a hopeless prospect to write our own reader we looked for a free reader and found QGIS. After downloading and installing, it soon became clear that it could do far more than what we downloaded it for. In fact, it could be customised to make our product but there was much to learn about how.

Before then, we accepted the opportunity to see what Bostock had and motivated their request for assistance, leading to on-site discussions with Group IT Manager Paul Hughes, as seen in our video.

Progressively, we were able to see downloaded data appear in QGIS although some of us struggled with computing hardware constraints, eventually limiting us to completing our product on one, recently bought laptop. Along the way, we became aware of the ability to include land imagery, property boundaries and road labels, along with all the point, line and area data about various potential hazards, affecting land use decisions.

We then learned about how our product could be migrated into a web app, which contains JavaScript for making SQL calls to library functions, that render QGIS equivalent displays, and will make calls to serverless SQLite imbedded code, that processes queries about particular locations.

Next, we looked into how this could then be used to create reasonably efficient mobile apps, that could provide the same functionality but add on augmented reality options. It raises process load limitations, in particular, the need to transform NZ coordinates, that our data sets use, into compatible global coordinates. Instead of being a data hungry web app, it would also make sense to code versions in the native smart phone languages, like Swift for iPhone, that have a copy of our internationalised data sets, for off-line use. At the same time, be able to update these on-line and add information that might better reside on a remote, regularly updated server, like aerial or satellite image data. Such apps could then talk to equipment that has IoT devices imbedded, to augment the reality of what can be seen through a backside camera, in addition to any desired QGIS like data display transparencies.