Spatial Data Management of Bio Regional Assessments Phase 1 for Coal Seam Gas Challenges and Opportunities

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1 Spatial Data Management of Bio Regional Assessments Phase 1 for Coal Seam Gas Challenges and Opportunities By Dr Zaffar Sadiq Mohamed-Ghouse Principal Consultant, Spatial & IT, GHD zaffar.sadiq@ghd.com 1

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3 Project Background Project Activities Stocktake and geo-referencing of water assets Collation of relevant associated data and metadata Assessment of current water assets condition Assessment of water assets vulnerabilities to coal and coal seam gas mining Identification of knowledge and information gaps

4 Challenges 4 months project duration 12 weeks for GIS Data screening - 50 layers were identified useful for the project from different agencies - 50 GB size Varying data structure and data quality Computation - Multiple database joins (Spatial & Non Spatial) Limitation tight time frame for quality check procedures Agreement from key stakeholders within the consultation time frame Stakeholders domain knowledge in NRM with limited Spatial experience

5 Water Assets Information Tool (WAIT) An Microsoft Access database developed by Office of Water Science Can be linked to water assets feature classes (using File Identifier) and to each features (using Asset ID) Describing water asset (31 input fields) and its vulnerability (8 input fields) Some fields can contains multiple inputs (up to 7000 characters).

6 Water Assets Information Tool Data Model

7 Water Asset and Vulnerability data production process WAIT Data Model Data Collection Data Automation Process Spatial Collaborative Online Tool Data Screening and Preprocessing Asset s Values Sensitivity Analysis SCOT Web tool Asset Identification Rule Based Decision End User Consultation WAIT Populated Data Base Domain Knowledge

8 Data Screening Semi automated screening process to assist domain specialist (hydrologist, ecologist, socio-economist etc.) to asses spatial data suitable to describe water assets. ArcToolbox interface for generating data summary Python scripts to generate following summary from the spatial data: Work on geodatabase, raster, and shapefile Basic spatial information such as format and extent. Summary of the unique attribute values from each field. A sample of generated data summary

9 Data Processing Asset Identification and Value Identification Domain knowledge used to: Identifying water feature as an asset based on its spatial location and attribute information. For example, floodplain vegetation along river stream. Reassigning water feature into WAIT data model Identifying values from the selected dataset A sample of generated data summary and transform it into meaningful information

10 Data Processing Asset Identification and Value Identification Python script for: Performing geoprocessing (i.e. Water Asset Values Information Overlay) between water asset and dataset containing value Overlay Summary Statistics Asset s Values WAIT information Generating summary statistic of the values of each asset Combining values information into environmental, hydrological, economic, and A sample of generated data summary socio-cultural values as per WAIT data model.

11 Data Processing Sensitivity Analysis Domain knowledge used to: Generating rule matrix based spatial proximity of water assets to certain activity, water asset characteristics and its values Assigning sensitivity value based on WAIT data model. Python script: Transferring each rule in the matrix into a series of query statements Assigning sensitivity value on feature matched the query statements A sample of generated data summary

12 Metadata Generation and Map Development Metadata Generation ANZMet Lite used to generate ANZLIC metadata profile version 1.1. File Identifier is used to define spatial layer for water asset Map Development Map template for reporting purposes. XML file generated from ANZMET Lite

13 Water Asset and Vulnerability data production process WAIT Data Model Data Collection Data Automation Process Spatial Collaborative Online Tool Data Screening and Preprocessing Asset s Values Sensitivity Analysis SCOT Web tool Asset Identification Rule Based Decision End User Consultation WAIT Populated Data Base Domain Knowledge

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21 Need for rapid data management solution for client problems Ability to harmonise heterogeneous data from varied organisation (Government, Industry and academia) in a quick time frame Ability to engineer dash board for the scientist to interact with data harmonised Need to produce simple visualisation models to communicate complex issues for the general public to engage and socialise concepts and policy for community consultation Centralised to Federated approach on storing and retrieve information Web based interactive tools with simple language for citizens to interact (Participatory Approach)

22 Opportunities New developments in data analysis - applicability for water sector context Opportunities (from a user perspective) Analysing and communicating temporal variability Analysing and communicating dynamic processes Improving user interaction with data Policy and regulation review Risk approaches

23 Summary Smart ways to organise unstructured data in a relational database Built on open source/technology platform Ability to analyse data on spatially and web enabled platform The user needs a web browser to interact with data Dynamic ways (on the fly) to generate information Intuitive reporting functionality

24 Thank You Questions? zaffar.sadiq@ghd.com Think Spatial! 24