Category Archives: Data sources

Online data sources: Harvest choice

One example of of spatial data on the web every week… this week Harvest choice

Harvest Choice

Description: Harvest Choice is a collaboration between various partners that aim to build decision support databases, analytical tools, and knowledge delivery mechanisms to promote evidence-based decisions regarding agricultural investment and intervention options. It does this by providing information on a list of crop and livestock commodities. Continue reading

Online data sources: the Atlas of African Agriculture Research & Development

Data source of the week

There is a wealth of information on e.g., land use, climate and species available online. But you need to know where to look. My plan is to highlight one example every week (let’s see if I can keep up with that). You’ll find more examples on data.ecodiv.org.

Atlas of African Agriculture Research & Development

Description: The e-atlas is a repository of data useful for agriculture research and development in Africa. It provides online, open-access to spatial data and tools that is generated and maintained by a community of research scientists, development analysts, and practitioners working in and for Africa. The e-Atlas highlights the ubiquitous nature of smallholder agriculture in Africa and provides data needed to describe the many factors shaping the location, nature, and performance of agricultural enterprises and the strong interdependencies among farming, natural resource stocks and flows, rural infrastructure, and the well-being of the poor. Continue reading

What if Google decides to discontinue Google Scholar?

Since Google discontinued Google reader I have always been wondering; what if they decide to stop with Google Scholar? If you are lucky enough to have access to an university library, you should be fine. But there are also a number of freely available alternatives. Just checking my bookmarks gave me gave me the list below. None of these tools have been able to convince me to abandon Google Scholar (to be completely fair, I haven’t tried them all out extensively), but at least if Google decides to kill of Scholar, I have somewhere else to go: Continue reading

New: Quantum map, a simplified QGIS version

An announcement on the QGIS mailing list about NIWA Quantum map made me curious. How is this going to differ from QGIS? As it turns out, NIWA Quantum map is basically QGIS with a simplified interface, i.e., it has some GIS functionality hidden or removed to be less confusing for users not familiar with GIS. They used the customization options to disable the editing functions, so users can enable that if required. I wonder though why they did not do the same with the analytical functions, rather then removing it all together.

It furthermore has a custom plugin added to provide easy access to a number of data layers for New Zealand. As these are WMS or WFS data sources, you can of course open them in QGIS too, or any WMS or WFS compatible software for that matter.

Poverty maps on HarvestChoice

Data on poverty levels, important for amongst others development study, yet very difficult to get. Sure, you can get global statistics from e.g., the FAO, Worldbank, here or here. But these give you highly aggregated data (mostly by country), not the sub-national level data often needed.

Luckily for those that need sub-national level data, HarvestChoice published in 2010 global sub-national poverty maps. The maps give the distribution of various poverty indices at sub-national level. More recently, Continue reading

Update of GADM datasets

It is always good to keep an eye on your data sources if you don’t want to miss out on new versions. Like the Global Administrative Areas database (GADM), which published version 2 of their data set earlier this year (I thought about revisiting their site after reading this post). A fairly relevant update with updated boundaries for e.g., Sudan.¬† and with level two administrative boundaries now available for most countries.

The files are available as shapefile, ESRI personal or file geodatase, Google earth .kmz file or R spatial polygon dataframe. If only they would make it available in spatialite format.. (I know, it is easy enough to import shapefiles into a Spatialite database, I am just being lazy).