New online application supporting policy and program development in the Amazon

Originally posted by Glenn Hyman (CIAT):

We developed this beta version of a policy and program support system for ecosystem services management in the Amazon.  For more information on this application, see the news item on the CIAT webpage. The news article includes information on how to access the site and how to provide user feedback, something that we would very much appreciate. Capabilities of interactive map servers are finally realizing their potential.

The screen shot below shows the user defines an area for the application to calculate the opportunity costs of avoided deforestation.

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CGIAR-CSI Global PET/ Aridity Geospatial Datasets Available Online

Originally posted by Robert Zomer (ICIMOD):

Dear Colleagues…

We are happy to let you know that we have added more geospatial climate datasets to the CGIAR-CSI GeoPortal:

  1. CGIAR-CSI GLOBAL-PET and GLOBAL-ARIDITY GeoSpatial Database http://csi.cgiar.org/aridity The Global Potential Evapo-Transpiration (Global-PET) and Global Aridity Index (Global-Aridity) datasets provide high-resolution global raster climate data related to evapo-transpiration processes and rainfall deficit for potential vegetative growth. These datasets are based on modeling and analyses by Antonio Trabucco (currently at the Forest, Ecology and Management Research Group, K.U. Leuven), with the support of theInternational Water Management Institute (IWMI) and the International Centre for Integrated Mountain Development (ICIMOD), and are provided online by the CGIAR-CSI Consortium for Spatial Information with the support of the International Center for Tropical Agriculture (CIAT). The Global-PET and Global-Aridity datasets are provided for non-commercial use in standard ARC/INFO Grid format, at 30 arc seconds (~ 1km at equator), to support studies contributing to sustainable development, biodiversity and environmental conservation, poverty alleviation, and adaption to climate change globally, and in particular in developing countries.
  2. The CRU TS 2.1 Climate Database: Reformatted for GIS Spatial Analysis http://csi.cgiar.org/cru This database is now back on-line and available for download (was unavailable for awhile due to server crash)
  3. The CDM-AR Forest Definition On-Line Analysis Tool: http://csi.cgiar.org/cdm Now back on line, and functioning (was unavailable for awhile due to server crash) Many thanks to Antonio Trabucco, Sadir Mohammed, Andy Jarvis (and me, who spent my weekend on this!!!)

Best regards,
Robert (rzomer@icimod.org)

Google SMS in Uganda

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Today, Google Africa announced their launch of Google SMS in Uganda, which provides  a bundle of mobile services that allow users to access content on a range of topics, including traditional services such as sports scores and local news and also health and agriculture tips.

We are also launching Google Trader, a SMS-based “marketplace” application that helps buyers and sellers find each other, enabling greater access to markets and trade, especially for those who are most excluded today. With these services, we hope to help alleviate some of the information and access to markets barriers for the poor, especially those in rural areas. So, when farmers in Iganga want to sell their maize, they can list their crop on Google Trader and a miller in another trading center can find and contact them to buy their goods.

And, they also stated that (listen up, market price modeling team!):

We hope these services will help a variety of organizations already doing impressive work to reach a broader audience and those with the greatest need, in new and innovative ways, through the mobile phone. This is the first of many exciting, collaborative efforts we will be working on to support access to information in Uganda and more broadly, across Africa. So to everyone who participated in this effort, we say Webale Nyo!

Continue read at:
Official Google Africa Blog: Google SMS to serve needs of poor in Uganda

First lessons in Addis

Originally posted by Emily Schmidt (IFPRI):

The largest hazard here in Ethiopia (besides the normal cautions of don’t drink the tap water and steer clear of the raw meat dish) are door handles.  Most of the door handles are only slightly secure, and at any moment they may just come right out of the door as you are pulling it open.  Several times I have fallen backwards because I was trying to pull open a door with a little too much force and I took the door handle with me.  This experience is sort of like falling in the bathtub; you reach out for something to grab and the only object you find is a shower curtain (if you are lucky), which provides no stability whatsoever.  Same idea – as I feel gravity pull me backwards, I look for something to grab onto, but quickly realize that I am already holding the doorknob in my hand and there isn’t anything else to grab a hold of, so…away you go.  When you land, you feel ridiculous sitting in the middle of a hallway with a doorknob in your hand.  But, I am slowly learning to win this battle of doorknob wit, and I am becoming quite efficient at tugging lightly, and I try to stop and readjust if I sense any give in the doorknob.

PDF as a spatial data delivery format

As CJ briefly showcased at the CSI Nairobi meeting, ArcGIS can export layered maps into a nicely packaged PDF file that users can turn on and off different layers to overlay multiple spatial information.

Sure it’s not enough for us to do any analysis on it, but can be a really handy vehicle to deliver seriously layered spatial information to public. Since, hey, not everyone we interact with has to have a GIS software (or bandwidth-intensive web mapping apps), but everyone seems to have PDF reader.  Besides, you know, it’s so much better to send a one PDF with 10 maps than 10 map files (in whatever format). I also found a nice showcase place at http://acrobatusers.com/gallery/geospatial.

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I played this a little bit recently, and I soon realized the conversion process is, well, not a single-button process (why no one is surprised?).. I think (surely!) a lot of careful designing stage should be established to take a full advantage of this technique.

So, I wondered if anyone else has experience with it. Are you currently using it? Would you recommend it? Any good (or bad) experience? Would it be useful to collectively create some type of layout guideline or template to help facilitate data delivery process?

Quality and Accuracy of Disaster Data

Originally posted by Silvia Renn (WorldFish):

This is a comparative analysis of 3 global data sets.  Recognising the need for better quality data to support disaster preparedness and mitigation, the ProVention Consortium of the World Bank Disaster Management Facility, initiated a consolidated effort to evaluate the quality, accuracy and completeness of three global disaster data sets. These were NatCat maintained by Munich Reinsurance Company (Munich ); Sigma maintained by Swiss Reinsurance Company (Zürich) and EM-DAT maintained by the Centre for Research on the Epidemiology of Disasters (CRED, Université Catholique de Louvain, Brussels). http://www.emdat.be/Documents/Publications/WBFIN4.PDF

Personal Technology: Phoning in Data

There was an interesting article published in Nature last week about the use of mobile phones for research. It starts out quite basic but then gives some nice examples that could spark some new ideas. http://www.nature.com/news/2009/090419/full/458959a.html#B1

Personal technology: Phoning in data : Nature NewsPublished online 22 April 2009 | Nature 458, 959-961 (2009) | doi:10.1038/458959a News Feature Far from being just an accessory, mobile phones are starting to be used to collect data in an increasing number of disciplines. Roberta Kwok looks into their potential.

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via Nature

The data/methodology derived from the following health mapping project seems especially valuable:

Last June, Albert-László Barabási and his colleagues at Northeastern University in Boston, Massachusetts, published a study in Nature  that analysed the movements of 100,000 mobile-phone users (1). Eagle is now working with Barabási’s group and others to examine phone-operator data from a range of geographic areas, including records for millions of mobile-phone users in Europe and two East African countries. Eventually, Eagle hopes to detect common behavioural patterns, such as changes in movement or calling frequency, that occur during disease outbreaks, which could help alert public-health officials to the early stages of an epidemic.

It would be interesting to see if movement or calling frequency could be used to detect behavioural patterns before food shortages, harvests, etc.

(1) González, M. C., Hidalgo, C. A. & Barabási, A.-L. Nature 453, 779–782 (2008)

A Comparison of Globally Consistent Geospatial Databases

Originally posted by Silvia Renn (WorldFish):

An Inventory and Comparison of  Globally Consistent Geospatial Databases and Libraries
by Joseph F. Dooley Jr., published by FAO in 2005,

 

…is a great compendium of commercial and public domain geodata. Part II is especially interesting as it lists, compares and assesses available geodata.

http://www.fao.org/docrep/008/a0118e/a0118e00.HTM

“The inventory is divided into two parts: with Part One of the inventory presenting overview, terminology and summary sections of globally consistent data libraries; while Part Two contains a categorization of the data sources identified broken into topical subsections based on the individual core data layers specified by UNGIWG and FAO. The report also includes a matrix rating the suitability of the various data sources identified to each of the core data layers specified by UGIWIG and FAO, and introduces Virtual Base Maps as a potential cost-effective means for: providing spatial referencing to remote field offices, enhancing Internet map serving capabilities, and facilitating mapping via GPS handheld devices.”

WhereCamp on BBC Digital Planet – Podcast

Originally posted by Silvia Renn (WorldFish):

I was reading www.edparsons.com blog (Ed Parsons is a geospatial technologist at Google) and came across his post related to the Wherecamp (and data license issues).

http://www.edparsons.com/2009/04/digital-planet-and-geodata/

He heard about it on the podcast of the BBC Radio World Service programme, Digital Planet. Checkout the podcast (at around 13:30) and you may hear some familiar voices:

http://www.bbc.co.uk/worldservice/science/2009/04/090420_digitalplanet_140409.shtml

Population Data Overview

Originally posted by Silvia Renn (WorldFish):

Most of us need to use population data in our GIS work. Mapping Global and Rural Populations (1) is great report that explains the origins, contents and differences of the major population data available. The report describes data (not only population) from the following sources:

  1. United Nations Population Division
  2. U.S. Census Bureau’s International Program Center
  3. World Gazetteer
  4. City Population
  5. Digital Chart of the World (DCW)Environmental Systems Research Institute, Inc. (ESRI)
  6. National Geospatial-Intelligence Agency Vector Smart Map level0
  7. National Geospatial-Intelligence Agency Vector Smart Map level1
  8. National Geospatial-Intelligence Agency GEONet Names Server (GNS)
  9. Database of Nighttime Lights of the World (NOAA)
  10. Global Land Cover Characteristics (GLCC) dataset
  11. Global Land Cover 2000 database (GLC2000)
  12. MOderate Resolution Imaging Spectroradiometer (MODIS)
  13. Gridded Population of the World version 3 (GPW v3) dataset; (CIESIN)
  14. EuroGeographics Seamless Administrative Boundaries of Europe
  15. LandScan Global Population Database, 2002, (ORNL)
  16. United Nations Environment Programme (UNEP) Global Resource Information Database
  17. Global map of urban areas Boston University’s Department of Geography
  18. World Water Development Report II (UNESCO) Indicators for World Water Assessment Programme
  19. Poverty Mapping Project
  20. International Boundaries datase UN Geographic Information Working Group (DPKO/UNCS)

(1) M. Salvatore, F. Pozzi, E. Ataman, B. Huddleston and M. Bloise – Mapping Global Urban and Rural Population Distributions – Environment and Natural Resources Series, No. 24 – FAO, Rome, 2005

MapWindow GIS

Originally posted by Silvia Renn (WorldFish):

If you are  looking for an “easy to use” and mostly stable open source software, I can recommend MapWindow GIS. It has all basic GIS functions and great plugins (such as a Google Earth screen shot app).

I have been using this software regularly and the nice thing is that (in comparison to many other OS packages out there) the functions actually work without crashing. It is also quite intuitive to use – QGIS is probably easier but not stable when it comes to working with larger raster files.

I also like the selection of functions MapWindow GIS has and at times I prefer using this software to the commercial one.  Here is a list which will give you a good overview of what the software can do. The plugins are also worth a look!

OpenCellID

Always wondered how to get the position data out of GSM without GPS in Africa. Glad to know there is a dedicated crowd-sourcing project underway! OpenCellID project aims to “..create a complete database of CellID worlwide, with their locations.” Quite a lot of African cells have been already mapped. 😀

Check out their effort at http://www.opencellid.org.