Monday, 30 November 2015

Remote sensing technology and community participation

In a previous post, I mentioned how communities can be empowered by providing them with relevant information to become active decision makers in water supply management.

One might think about which kind of information would be more relevant for them.
As regards this question, a recent article on FAO news section reports the decision of the Dutch government to enhance their cooperation with the UN agency by investing $7 million in remote sensing technology to monitor and improve water use for agriculture in Near East and Africa.

Photo: ©FAO
'Example of an interpreted satellite image: Blue showing areas with good water-to-yield ratios, yellow showing areas with poor-water-to-yield ratios'
Credits: http://www.fao.org/news/story/en/item/346377/icode/










Thus, this led me to think about the possible usefulness of giving communities access to data collected with this system. As a matter of fact, the purpose of the four-year program is to update a data portal of interpreted real-time remote sensing images -inclusive of data of inputs, such as rainfall and crop transpiration. Thus, experts can quickly identify the causes of low land productivity.

What seems interesting about this project is the possibility to share satellite images of the state of cropped areas to farmers, in order to show the success of good practices in scientific terms and stimulate the discussion about more productive techniques on the basis of the specific characteristics of land. The aim is that of improving water productivity in local agriculture. In this way, environmental sustainability, economic efficiency and community participation -three key elements of IWRM- would be improved. Still, I think that the most appropriate methods to give access to these data and discuss about them have to be explored.

Another aspect worth noting is that images in the database are already 'interpreted'. This can remedy the well-known 'lack of capacity and resources' of governments to 'analyze and work' with data resulting from remote sensing techniques (World Grain). But it does not seem clear how this interpretation will be conducted.

Finally, one might think about the possibility to link the spatial scales of analysis (continental level over the whole of Africa and Near East, country and river basin level and, irrigation scheme level) to decision-making levels. Thus, how it can be ensured that the voices of communities living in the river basin can access to the lower spatial scale data and they -and not only authorities at higher levels- are considered relevant actors in IRBM.

Sources:
http://www.fao.org/news/story/en/item/346377/icode/
http://www.un-spider.org/news-and-events/news/fao-develop-database-support-water-scarce-countries
http://www.world-grain.com/articles/news_home/World_Grain_News/2015/08/Database_to_help_water_scarce.aspx?ID=%7B7DB8D43E-0348-4B13-A0B1-E6F9DE5241F7%7D&cck=1

3 comments:

  1. Hi Greta! A very interesting blog post. :) I agree with you that the satellite data is very helpful in analysing how successful a particular area is in agriculture. At the same time, I feel that there needs to be other types of data to be simultaneously analysed such as falling rates of groundwater water table or changes in rainfall pattern across the year and over a decade. Perhaps we can also explore the data on soil erosion from remote sense technology..I guess these can help derive a more practical solution to areas where low productivity has already been a norm. :)

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  2. Hi Greta! a very interesting blog post! I agree the increase in remote sensing for agriculture is becoming highly useful. There is a new satellite which may interest you, it is known as the Soil Moisture Active Passive (SMAP) Satellite. Made by NASA and it is able to measure soil moisture, which will be highly influential for farmers, as they are able to predict droughts and floods and prepare accordingly. Additionally, SMAP will be beneficial for modelling hydrological change. I think satellites are becoming increasingly useful due to technological advancements, even though some caution may be needed. As satellites misrepresent data due to shadows and angles and noise caused by clouds (however this is highly variable depending on the type of satellite).

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  3. Thank you so much for your insightful comments, Satomi and Maria!
    Satomi, I have considered your suggestion to take into account soil erosion data in my new post, focusing on Farmer Field Schools.
    Maria, it seems that the satellite you mentioned can have really meaningful implications in water and land management; I will try to explore it, thanks for bringing it to my attention!

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