The hands-on session contains six exercises which are organized in three thematic blocks:

Transcription

1 Hands-on Exercises EO2HEAVEN Training Workshop, South Africa, November 2011 The hands-on session contains six exercises which are organized in three thematic blocks: 1. Cholera in Africa, 2. Air pollution in Durban, South Africa, 3. Air pollution in Saxony, Germany. The first two blocks are mainly targeted for this workshop, whereas the third block deals with a more computationally complex task and can be regarded as optional. Please address the tutors for any questions and do not hesitate to ask for help at any time. We appreciate any comments on usability, requests for functionality or general remarks and comments (negative or positive). Please address the tutors directly or send an to Johannes Brauner (johannes.brauner@tu-dresden.de). We are looking forward to your feedback and are eager to improve our developments to better match the users expectations. Requirements on your computer Firefox (> 5.0.1), JavaScript enabled, Outgoing firewall allows access to ports 80 and Block 1 Case Study 3 Cholera in Africa The block deals with cholera. The first two exercises deal with a simple client (targeted at decision makers). The third one presents a more complex client (e.g. for scientists who are familiar with Geoinformation Systems (GIS)). The aim of this Case Study is to investigate the role of environmental factors and conditions in the dynamics of cholera outbreaks and the responsible pathogen (toxigenic Vibrio cholerae) in southern Africa. This is of interest to researchers but also, importantly, to decision makers at different levels of government and non-governmental organisations who are involved with designing, selecting and implementing appropriate and effective intervention strategies and options. Intervention strategies and options are re-active as well as pro-active. This necessitates different requirements from a research as well as decision making perspective. The software tools and components developed and planned to be developed as part of EO2HEAVEN will or are addressing the following: To support an iterative and integrated research approach that allows for the integration of datasets from different sensors, example satellite data; ground based measurements; field data and laboratory results (Figure 1). 1

2 To enable the researchers in different fields, for example health, remote sensing, water ecosystems and microbiologists to find, access, extract, visualise, analyse, and model the data and publish (make available) research results and findings. To enable decision makers involved with planning, developing and implementing intervention strategies to: o Visually track the progress of an outbreak over time and space o Optimise intervention strategies by being able to view the changes in environmental factors and conditions that have been shown/known to precede cholera outbreaks as well as modulate the intensity of an outbreak after it has started. To view the environmental based results and findings within in a social context, i.e. to be available to get some indication of the potential vulnerability of an area/region where the pathogen (Vibrio cholerae) is known/has been shown to be endemic (i.e. occur in the water bodies in between outbreaks; OR areas that report regular outbreaks) in the event when environmental conditions are becoming favourable increasing the potential for an outbreak to occur OR the potential intensity of an outbreak after it has already started and different intervention options need to be considered. Controlled studies to investigate the influence of a specific factor(s) on the pathogen cell level; analysis of field samples collected for chemico-physical & biological properties Laboratory Studies: In vitro Historical preemergence system state Environmental change Outbreaks Model Exploration: In Silico Field Studies: In vivo Data analysis and mining for temporal and spatial patterns and correlation, hypotheses generation or testing, prediction or simulation modelling, parameter estimation, sensitivity analyses Adapted from Plowright et al., 2008 Figure 1. Iterative and integrated research approach followed for the Cholera Case Study. Exercise 1 CS3 Cholera African level time2maps Client The time2maps client is targeted to users who are not familiar with GIS and is thus optimized in regard to improved usability and simplicity. Only the most important functionality is available. The exercise starts with general instructions (which can be used as reference to solve the exercises). The datasets shown are provided by the WHO. General instructions (as reference): URL of the client: (Please click on the link or copy and paste it into your browser) You can select different layers (cholera cases and respective statistics, rainfall and anomalies) in the top right corner of the map (click on the + symbol), 2

3 You can fade out the layer list by clicking on the - symbol in the top right corner so it does not interfere with the map visualization any more, If a time-enabled layer (layers that contain time dependent information) is selected in the layer list, a time slider and a play button are shown: o Use the time slider to select a fixed date (the selected layer from the selected time is shown, e.g. rainfall anomalies in 1998), o Use the play button to play a sequence, starting with the date selected by the time slider and showing the e.g. changes the rainfall from 1979 until 2010, Click on a country to see more detailed (statistical) information on the right hand side: o Use the See detailed statistics buttons to show the data in tables: Use the See statistics on Chart button to generate a chart containing a combined time series visualization of one health data parameter (e.g. cholera) and one environmental parameter (e.g. rainfall anomalies), Print or download the chart by clicking on the two buttons in the top right corner of the shown chart. o Click on the x Button in the top right corner to close all pop-up windows to show the map again. Use the download.csv link in the top right corner of the client to download all available data in a simple CSV (comma separated value) format to use it in your own statistics program or GIS, If you want to use the data sets in a desktop GIS use the following Web Mapping Service (WMS) URLs and copy and paste them into your GIS: o Health data: o EO data: 1) Visualize and familiarize yourself with the evolution of total cholera cases / inhabitants in Africa through the last 30 years. a. Click on the + right next to Select Data set to show the list of available layers. b. Select the layer total cases per per year (1970 to 2009) and afterwards click on the - symbol to fade out the list of layers to gain a better view on the map. c. You see a time slider and play button below the map which indicates that the layer contains time dependent data on a yearly basis. d. Run the animation by clicking on the play button left to the time slider. 2) Identify a year where total cases / for Uganda is between 100 and 499 by just locking at the legend on the right hand side and pause the animation. a. Run the animation again and stop it (by clicking on the play button again) when the animation has reached Alternatively, you move the time slider to 1998 without starting the animation. 3) You now want to take a closer look at the situation in Uganda in 1998 to see how many cases were reported in that year. a. Click on Uganda in the map (the country is now highlighted) and see the answer to your question on the right below the legend cases were reported for Uganda in ) What is the fatality rate in Uganda for 1998? a. Same statistics Solution: ) What is the population density in Uganda for 1998? 3

4 a. Same statistics Solution: ) Is the total number of cholera cases in Uganda in 1998 somehow special in comparison to the other countries? a. Take a look at the statistics again and focus on the number of cases. b. It is shown that the number of cholera cases is the maximum of the reported 30 years. 7) You wonder if the number of cholera cases is related to rainfall anomalies in Uganda for the past 30 years. To analyse the relation of the two parameters you can display them simultaneously in a chart and use this chart e.g. in a paper you are currently writing. a. Select Uganda by clicking in the map. b. Click on the button See details/statistics to display a table with all available data from 1970 to c. To show the chart, select the two parameters Cases per persons and Rainfall index and click on the button See statistics on Chart. d. A new window with the chart is displayed. Take a look and try to answer your question. e. To reuse the chart for your paper download the image by clicking on the download button in the top right corner of the chart and save it to your computer. f. Return to the map view by closing both windows by clicking on the x button in the top right corner. 8) You now want to compare the situation in Uganda to the one in Mozambique to see if the situation was better or worse there in a. Click on Mozambique in the map and take a look at the Cases / and Fatality rate and compare them to the numbers for Uganda. b. You see that the number of cases per persons is lower in Uganda but the fatality rate is one percent higher than in Mozambique. 9) In the end you are interested in what country reports highest under five years of age mortality in contribution of diarrhoeal diseases (including cholera) in a. Select the dataset (it is the third last in the layer list). You see that the Play button and time slider are not shown any more. b. By taking a look in the legend (the darkest colour is shown only once) you can identify Ethiopia. By clicking on Ethiopia in the map, statistics are shown and indicate a mortality rate of 27 %. Exercise 2 CS3 Cholera Uganda level (Kasese district) time2maps This exercise is an extension of Exercise 1, showing a more detailed situation of cholera case distribution over space and time in Uganda (Kasese district close to Lake Edward and Lake George) from General instructions (as reference): URL of the client: (Please click on the link or copy and paste it into your browser), Alternatively, you can select Uganda on the map visualization in the time2maps client from the previous exercise and then click on the button See detailed view in the lower right corner of the client, You can select the layers in the top right corner of the map (click on the + symbol), the selected layers are shown simultaneously (layers can be deselected accordingly), 4

5 You can fade out the layer list by clicking on the - symbol in the top right corner so it does not interfere with the map visualization any more, If a time-enabled layer (layers that contain time dependent information) is selected a time slider and a play button are shown (temporal extent an resolution of the data set are shown above the time slider), Use the time slider to select and fix a date, Use the play button to play a sequence, starting with the date selected by the time slider, Click on a cholera case (depicted by the symbol) to see more detailed information about this case on the right hand side, Use the download.csv link in the top right corner of the client to download all available data in a simple CSV (comma separated value) format, If you want to use the data sets in a desktop GIS use the following Web Mapping Service URLs and copy and paste them into your GIS: o Health / EO data: 1) Enable and disable the layers by ticking the boxes and prepare a view to your liking (the Cholera layer should be enabled in any case). In contrast to Exercise 1, multiple layers can be shown at once. 2) You are interested in the distribution of cholera in the Kasese district from 2008 to You remember that in the beginning of 2009 a cholera wave was reported. a. Move the time slider to Week 7 in 2009 (when moving the time slider the currently selected week is shown right above the time slider) and click the play button. Watch the animation until it ends. You can see the distribution and cholera cases hot spots during the time. 3) Now, you want to see whether there is a connection between rainfall anomalies and the number of cholera cases. a. Select the Rainfall index Uganda as Base Layer. b. Make sure at least Cholera is selected as Overlay. c. Again, move the time slider to Week 7 in 2009 and click the play button. Watch the animation until it ends. You can now see the distribution of cholera cases, cholera cases hot spots and rainfall anomalies over time. d. Do you see a distinct connection between dry periods (rainfall index < 0) and the occurrence of cholera? 4) You are interested in the village of Katholhu. How many total cholera cases can you find in Katholhu in week 22/2009 and how many cases were female? a. Move the time slider to week 22/2009. b. Click on the village of Katholhu (Hint: It is the southernmost Cholera case for this particular week). c. You see that four cases were reported for that week (three female and one male). Three of four cases were still in their mid-twenties. 5) You want to download the data and send them to another scientist to check it in more detail. a. Click on the download.csv link in the top right corner. 6) Try to answer the following questions: 5

6 a. What s the temporal extent of the data set of the Cholera layer (exact start and end date)? Solution: b. What s its temporal resolution? Solution: Weeks. Exercise 3 CS3 Cholera Ugandian level (Kasese district) ATOS Advanced Client This exercise deals with the same area of interest as Exercise 2 but uses another tool an advanced client to take a look at the same data sets. The client provides much more functionality than the time2maps client and is therefore targeted to people who are familiar with GIS. Please use the following information to start the advanced client: URL of the client: User name: saworkshop Password: saworkshop Choose Web Client Case study chosen: Workshop Exercise. 1) Zoom to Uganda (use the navigation and zoom buttons in the top bar under the map). 2) Search in the catalogue the available data sets for Uganda, and select: Uganda administrative areas, Uganda lakes, Uganda Rivers, STRM90 topography a. Click on search data set. b. Focus on Uganda. c. The result list is shown. d. Select the layers by ticking the checkboxes. 3) Hide the administrative areas by unchecking it in the layer list in the left. 4) Move the layers to change their order (by clicking on the layer, holding the left mouse button and dragging it): a. Uganda administrative areas b. Uganda - rivers c. Uganda -lakes d. STRM90 e. OpenStreetMap 5) Display the administrative areas again, but decrease the opacity. a. Use the right mouse button to click on the layer (a context menu will show up). b. Navigate the mouse pointer over Set Opacity to show the opacity slider. c. Move the slider to the left to decrease the opacity. 6) You now want to display the cholera data. a. Use the catalogue to find the Uganda cholera cases layer per year ( WHO Cholera: cases per year (time) ) and take a look at the metadata. i. Click on Search data set. ii. Enter the keyword WHO in the search form. iii. Find the dataset. iv. Add the layer to the map. 6

7 v. Click on the >> button to see the metadata. b. What s the temporal extent of the data set? (Find details in the shown metadata) c. What s its temporal resolution of the data set? (Find details in the shown metadata) 7) Zoom to the max extent of the layer. a. Use the right mouse button on the layer to open up the context menu again. b. Click on Zoom to full extent. 8) Change the order of the layers to have the three administrative/lakes/rivers layers in the top of the Cholera layer. 9) Zoom to the max extent of the Uganda administrative layer. 10) What is the current year displayed, and for this year, how many cases per persons were reported? a. Select the imported cholera layer in the layer selector. b. Select the I (it is a capital i) button. c. Click on Uganda. d. Solution: 2009, 3.38 cases per persons. 11) You now want to compare it with the situation in a. Right click on the cholera layer and left click on Time range. b. Move the slider in the bottom of the pop up window to the left until 1998 is shown. c. Alternatively, you can click on Current time and select the date directly. 12) Finally you want to see the datasets about children mortality. You can import them from an external Web Service. a. Click on Import external layer. b. Copy this URL: c. Select WFS. d. Click on Load and select children_mortality. e. The data set will be shown in the client. Block 2 Case Study 2 Air pollution in Durban The focus of CS2 (Air Pollution in Durban) is to be able to produce a map showing the risk of respiratory diseases based on the level of different pollutants. In the Advanced Client we want to be able to provide specific users with data for more detailed analysis. For the purpose of this exercise we will be using in-situ data that was measured at certain stations to perform 2 simple analyses. The first analysis we will do is to look at specific pollutant data at a specific site on a specific day. Next we will look at a time series to show the change in pollutant levels over time, and then we will look at comparing data at 2 different stations over a specific time. Exercise 4 - CS2 Air pollution in Durban ATOS advanced client / 52N SOS Client Please use the following information to start the advanced client: URL of the client: User name: saworkshop Password: saworkshop 7

8 Choose Web Client Case study chosen: Workshop Exercise. To begin with we need to focus only on our area of interest, in this case Durban: 1) Zoom to Durban We now want to select a specific pollutant, SO 2 : 2) Import in-situ values (NO x parameter) for Durban, from external interoperable sensor observation service. a. Import external layer. b. Copy the URL: c. Select NOX. d. Click on Load. e. Select NOX. Next we want to see the information from a specific station on a specific day: 3) What is the value of NO x for Ferndale (north most station) on the 1rst of March 2011? a. Select NOX (SOS) in the layer manager. b. Select the tool I. c. Click on the north most station. d. Solution: 5.2. Now that the initial analysis is done, we want to see how the levels of this pollutant changes over time: 4) Consult the NO x values: a. Click in the time series button (depicted by a chart in the value column). b. What are the first and the last value that were measured? Solution (see legend): , 0:00 (12.8 ppb) and , 23:00 (5.2 ppb) c. Change the time range to to (use sliders in the overview time series) d. Consult data (mouse over the time series chart) e. Obtain the maximum value f. Solution: :00 /32.7 ppb g. Consult data (mouse over the time series chart) h. Obtain the minimum value i. Solution: :00 / 1.1 ppb The data from this station can then be compared to that at another station to see if there are major differences in changing pollutant levels at different stations: 5) Compare with another time series: a. Click on Add new Timeseries b. Click on Tab Theme 8

9 c. Chose the following SOS in the drop down box on the top of the menu: d. Select the theme SO2 e. Select the station f. Click on the green button to load the time series. g. You can now see the different measurements at the two stations. Exercise 5 CS2 Air pollution in Durban ATOS Light Client In the Light Client we want to provide specific end users with simple maps to highlight risk in specific areas, and is not intended for detailed scientific analysis. For the purpose of this exercise we will be using historical in-situ sensed data that was obtained from the South African Air Quality Information System (SAAQIS) sensor net to create a risk map in both real time and with forecasted values. The second exercise is to create a map that displays monthly data for a specific parameter and then allows one to see the evolution of the parameter over time. This is similar to the Advanced Client exercise (Exercise 4) except that the results are displayed in maps as opposed to in graphs (time series) and the raw data. To begin with we need to open the Client: URL of the client: User name: saworkshop Password: saworkshop Choose: Light Web Client Now we want to create a risk map over a certain time frame and see its evolution over time: Consult risk map in a time range: o Click over previous till find : 01/07/2010 o See the evolution in the time of the risk map. o Click on play. o Click over +1, +2 and +3 to see the forecasted values. In order to see specific parameters, in this case PM 10, over a monthly time scale: Consult the environmental parameters: o Click on the PM10 Button. o Change the Slider to see the evolution in the time. o Select the Location: Southern Works to see the chart for the PM10. o Change the Values for Monthly. o Change the time range. o Click over play to see the evolution of the parameter in the time. Block 3 Case Study 1 Air pollution in Saxony 9

10 Block 3 contains one optional exercise. The scenario in Saxony is similar to the one in Durban. Exercise 6 CS1 Saxony ATOS Advanced Client To show that even more complex calculations can be carried out in the advanced EO2HEAVEN client, we want to show you how to calculate an NDVI (Normalized Differentiated Vegetation Index) to check how healthy the vegetation is in the urban centre around Dresden (the capital of German Federal State Saxony). Please use the following information to start the advanced client: URL of the client: User name: saworkshop Password: saworkshop Choose Web Client Case study chosen: Saxony Case Study Please note: You need to be patient. The calculation and download of the larger data sets (satellite images) take some time. An initial view of Dresden is provided, overlaid with a few satellite scenes. First, you need to find Dresden in the map (Hint: It should already be centred). 1) Zoom to Dresden (use the buttons in the top bar under the map) You can see a larger wooden area (shown in darker red) to the North East of Dresden (the Dresdner Heide ). To check the health of the area you need to use functionality of a Web Processing Service provided by Spot Image in France. 2) Click on Execute Process. a. Select the layer: IMG_S J2 in the Layer Manager (left Panel). b. Right Click over the layer. c. Select Execute Process -> Compute NDVI. d. Select the layer to process. e. Click on Execute and be patient (a larger amount of data needs to be transported over the net). 3) Download the result and the original data: a. Select the new layer resulted of the process execution. b. Right click on it. c. Select the layer: Source Image WPSIMGID d. Select the layer: IMG_S J2. e. Click on Download and save it to your computer. 10