GE as effective tool for Water Resource Decision Support
May 31, 2016 20:29:14 GMT
frankmcvey (Angel) and washi like this
Post by rainy on May 31, 2016 20:29:14 GMT
Dear fellow Google Earthers
I'm providing an abstract of a paper to be presented at a South African Conference in September 2016. It is followed by some screenshots of the data referred to in the article. Unfortunately the KMZ's are too large to upload but I'm publishing some (rather large) images as examples.
Using Google™ Earth Pro as an effective visualisation tool for Water Resource Decision Support
B. Haasbroek1, M. Musariri2, G. Maree3
1 Hydrosol Consulting, Pretoria, South Africa
2 Chief Directorate: Water Information Management, DWS, Pretoria, South Africa
3 AECOM SA Pty (Ltd), Centurion, South Africa
Abstract
Google™ Earth (GE) has been providing detailed satellite imagery, supporting coverages and geographical analysis tools to millions of users across the world for several years. The application is free (including the Pro version currently) and the information and tools are of high quality. In a recent scientific review of the South African National Water Resources Monitoring network, GE was used to provide hydrological, environmental and anthropogenic spatial datasets to water resource and aquatic ecosystem specialists. The specialists use these datasets to identify theoretical monitoring sites independently of current monitoring activities. GE was then used in 9 National workshops as an effective visual decision support tool where the governmental department, specialists and other stakeholders could review each monitoring site. Important sites that need improvement, redundant sites and new monitoring sites could interactively be identified and reasons provided from the mass of data made available through coverages converted to KMLs. This paper will describe the datasets and decisions made as well as provide lesson learnt in generating and using large datasets in GE.
Keywords: Google Earth, spatial analysis, water resources monitoring network design
1. Overview of the entire Water Management Area (WMA) and the Secondary Catchment and Rivers in the WMA
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2.Ecological Data
Including per river stretch Ecological Importance and Sensitivity, Ecological Water Requirements Sites.
3. Anthropogenic Data
Including land cover (red - mining and industry, orange - informal/rural settlements, green - cultivated lands and pivots, dark brown - urban areas, purple - plantations), water treatment and waste water treatment plants, domestic supply dams, power stations etc.
4. Hydrological data
Including Unit Natural Runoff (mm/a) - shaded areas where navy is 1000 mm/a; and total natural runoff (million m3 per annum) - circle sizes
5. Theoretical Monitoring sites (based on preceding data)
Red - Hydrological, Green - Environmental and Yellow - Anthropogenic Sites
6. Current Surface Water Monitoring Sites
Purple stars - surface quantity, Blue Stars - reservoirs monitoring. White stars around smaller stars - Water Quality monitoring.
7. Assessing each individual station
All information per station available by clicking on the marker.
8. Assessing gaps, redundancies and other constraints.
I'm providing an abstract of a paper to be presented at a South African Conference in September 2016. It is followed by some screenshots of the data referred to in the article. Unfortunately the KMZ's are too large to upload but I'm publishing some (rather large) images as examples.
Using Google™ Earth Pro as an effective visualisation tool for Water Resource Decision Support
B. Haasbroek1, M. Musariri2, G. Maree3
1 Hydrosol Consulting, Pretoria, South Africa
2 Chief Directorate: Water Information Management, DWS, Pretoria, South Africa
3 AECOM SA Pty (Ltd), Centurion, South Africa
Abstract
Google™ Earth (GE) has been providing detailed satellite imagery, supporting coverages and geographical analysis tools to millions of users across the world for several years. The application is free (including the Pro version currently) and the information and tools are of high quality. In a recent scientific review of the South African National Water Resources Monitoring network, GE was used to provide hydrological, environmental and anthropogenic spatial datasets to water resource and aquatic ecosystem specialists. The specialists use these datasets to identify theoretical monitoring sites independently of current monitoring activities. GE was then used in 9 National workshops as an effective visual decision support tool where the governmental department, specialists and other stakeholders could review each monitoring site. Important sites that need improvement, redundant sites and new monitoring sites could interactively be identified and reasons provided from the mass of data made available through coverages converted to KMLs. This paper will describe the datasets and decisions made as well as provide lesson learnt in generating and using large datasets in GE.
Keywords: Google Earth, spatial analysis, water resources monitoring network design
1. Overview of the entire Water Management Area (WMA) and the Secondary Catchment and Rivers in the WMA
2.Ecological Data
Including per river stretch Ecological Importance and Sensitivity, Ecological Water Requirements Sites.
3. Anthropogenic Data
Including land cover (red - mining and industry, orange - informal/rural settlements, green - cultivated lands and pivots, dark brown - urban areas, purple - plantations), water treatment and waste water treatment plants, domestic supply dams, power stations etc.
4. Hydrological data
Including Unit Natural Runoff (mm/a) - shaded areas where navy is 1000 mm/a; and total natural runoff (million m3 per annum) - circle sizes
5. Theoretical Monitoring sites (based on preceding data)
Red - Hydrological, Green - Environmental and Yellow - Anthropogenic Sites
6. Current Surface Water Monitoring Sites
Purple stars - surface quantity, Blue Stars - reservoirs monitoring. White stars around smaller stars - Water Quality monitoring.
7. Assessing each individual station
All information per station available by clicking on the marker.
8. Assessing gaps, redundancies and other constraints.
