How to collect spatial information from databases (for free!)
There is so much open data available… But where can we find it? What is out there? What can we do with it? And if you were able to find it, how would you use it?
In this workbook, I’d like to take you on a journey. We will look into a few online and open available (yes; for free) databases from which you can uncover the possibilities that space information offers you.
As IMARA mostly is looking into land restoration projects, I’d like to take you first on a tour through some databases that give you a first view from above. This is a different perspective than the perspective you normally have when walking in the field. I use these datasets before I even have a talk with someone about the area: I might not be from the area, but that doesn’t mean that I am completely clueless about what the area looks like from above.
During this explanation, we will take a look at Ethiopia. If you are from Ethiopia yourself, you probably know the area very well from the ground. But how do you explain this, while talking to someone who is not from Ethiopia or not from the specific region of your interest?
Geodata can support you with this. In addition to this, is a very strong advantage of geodata that it supports in a very objective way and you are able to go back in time!
You have collected information in the field and you have looked into the stakeholders in your field. You did this to be able to construct a proper dialogue between stakeholders to tackle your issue of interest.
1. Going back in time
As soon as you know which issue you will focus on, and you know exactly where it is located, you can start to take a look back in time. But why would we want to go back in time?
Going back in time, gives you an idea of what has been going on in the area before, and how this might influence the future. For example, imagine you are talking to someone in the field, and the person tells you that he owned a perfect piece of land a few years back, but now this land is taken over by a large commercial project. Chances are, that this person might never be able to get his land back. Another example can be that someone owns a plot of land, which is now ‘taken away’ by the river (due to the natural meandering of the river). By taking a look back in time, you can see where the river was firstly located, and you might be even able to predict where it will ‘meander’ to. These are dynamics you can see from above, which might help you in supporting a strong dialogue.
How can we do this?
You can go into the field and ask everyone around what has been going on in the area. The advantage of this is that you have the opportunity to talk to stakeholders directly. The disadvantage is that you do not get a complete overview.
Therefore, we will use Google Earth Timelapse to take a view from above, while going back in time. In the following video I’ve walked through the Google Earth Timelapse application and I’ll show you how you can create a time-lapse of an area in less than a minute.
What can we do with the information?
As soon as you have created a time-lapse of your area of interest, you will be able to use this information. But what can you do with such information? This time-lapse can be shown to all stakeholders or project partners to start a conversation.
Below you see an example of the development of irrigation in Saudi Arabia (1984–2018). The development of the area over time, as seen from above, can give you an idea of the magnitude of such an irrigation development. By combining this information with other datasets, you will be able to give an idea of the water use / water productivity of the area. Based on this information, policies can be adjusted in order to provide a sustainable future for the area.
Bringing the time-lapse possibilities closer to you; in the time-lapse below, you see the development of Addis Ababa [Ethiopia] (1984–2018). Land use change, in this case urbanisation, can lead to changes in the landscape and the landscape dynamic. The pressure on agriculture increases, due to an increase in people living and eating in the city. This, in combination with the land being used as urban area, gives you an idea of the need for agriculture to be performed further away from the city. This leads to more transportation of the food, and a potential increase in food prices. Obviously, not all information is available from space and can be derived from time-lapses. A time-lapse can help you in knowing where to find areas where you would like to interview stakeholders.
Timelapse — teams in Ethiopia
2. Over space & over time
Yesterday we went back in time to see the time-lapse of the area and we linked this to stakeholders. Geodata can also support you in seeing things over space and over time. This means you can go back into time, but you can also get a view of your whole area (or your whole catchment) and see the dynamics of the area.
By collecting data over space and over time, you can prepare even better for a dialogue. If you know which dynamics have been taking place where, you know which stakeholders to ask which questions. Where are your efforts most needed?
How can we do this?
Today we will take a look at satellite images. There is more to it than the eye can see; that is the strength with satellite information. Our eyes, the sensors of our bodies, can only see a relative small part of the electromagnetic spectrum. Other sensors can see much more; think about temperature for example. Our eyes are not the sensors that can see changes in temperature, but these sensors can be carried by for example drones or satellites.
We can use the Sentinel Playground in order to ‘play’ with the satellite data and information.
What can we do with this information?
Take a look at the following pre-set combination of bands in the Sentinel Playground:
- Natural color — this dataset gives you an optical image. This means that the image is similar to the way that our eyes would look at the earth. We can see this image as a photo from the earth from space.
- Color Infrared (vegetation) — this dataset has a very prominent red colour. This dataset shows you the measured Near-InfraRed. This is a ‘colour’ we cannot see, but which can be measured. Vegetation is very visible using Infrared. This means that as soon as the area is more red, there is more vegetation and when you see less red; there is less vegetation.
- False color (urban); this combination of bands shows you most clearly where cities / urban areas are located.
- Agriculture — this combination of bands is most suitable for analysing which crops are cultivated on which plot of land. Different crops / different plants will give different colours on the image.
- Moisture index — this combination of bands shows the moisture in your area. It shows changes in available water (which can also be stored in plants themselves). The more blue the image, the higher the moisture availability. The redder the image, the lower the moisture availability. (same location as natural color image > do you see how much more information is visible with other combinations of bands?)
Each dataset can be seen as a layer of a cake. The more ‘layers’ you use, the more you will be able to show what is happening where and why in the real world. By for example combining vegetation with the moisture index and knowing what happened over time, you know even better who to talk to and which questions you can ask.
The real world cannot be displayed by only one dataset. You need multiple datasets to create a ‘whole’ and complete view of the real world. But keep in mind; this view from above, will never be completely complete… You need ground truth, you need to know what people are doing where and why. That can explain certain phenomenon which you can see in your data.
You can use geodata to your advantage by evaluating where you need to find specific stakeholders that are dealing with specific issues as you identified.
Teams in Ethiopia — use of Sentinel Playground
Below you can find a document with changes in season (february — september) and changes in years (2016–2020):
3. Thematic Information
There are thematic datasets available for free that can help you support your dialogue even more. We will take a look at some globally available datasets: Global Forest Watch (GFW), WaPOR (by FAO) and SoilGrids (ESRI).
Global Forest Watch (GFW)
This Global Forest Watch is an initiative from the World Resource Institute and is an online platform, which shares data and tools for monitoring forests.
In the video below, you get a tour through the Global Forest Watch, where I show you how to collect valuable information to support your case. You will be able to visualise data in a map, but you can also collect data from dashboards regarding your specific area of interest.
You can find the GFW here:
WaPOR — Water productivity
The Water Productivity Open Access Portal (WaPOR) is a geoportal developed by the Food and Agricultural Organization (FAO). The main aim of the portal is to use earth observation data to monitor water productivity in Africa and the Near East.
In the video below is explained what data is available and how you can use the information to your advantage. Keep in mind that this information can help to support the assumptions you created based on the timelapse and the satellite data from the Sentinel Playground. By overlaying more datasets, you will be able to ask more concrete questions to all stakeholders in your area to find out what the most pressing issues are, where they are most pressing and when.
You can find the WaPOR database here:
SoilGrids — global gridded soil information
SoilGrids is a system for digital soil mapping based on global compilation of soil profile data and environmental layers by ESRI. SoilGrids uses over 230 000 soil profile observations from the field and satellite information to predict and fit all details of the soil on a global scale.
In the following video, you can find an example of how to work with the dataset, but I highly encourage you to take a look at the database yourself to see what information is available. Data globally available within the database are: organic carbon, bulk density, Cation Exchange Capacity (CEC), pH, soil texture) at seven depths in the soil.
You can find the SoilGrids database here:
