Knowledge for Development

Remote sensing and GIS

In the 1960s and 1970s, remote sensing was done from aircraft and mainly for military purposes using thermal infrared scanners (temperature) and radar systems (SLAR: side looking airborne radar). Recognising the potential for civil applications, primarily in agriculture (harvest estimates) and geology (possible presence of oil and gas), the first earth-orbiting satellites were equipped with technology for colour observations of the Earth. The potential of these space observations for meteorology was quickly identified, and the meteorological community launched a successful series of meteorological satellites of increasing complexity and capabilities, which has sustained until the very present.

Over the last decade, remote sensing has developed in various ways, strongly increasing its potential as a tool to support integrated agricultural management and sustainable rural development.First of all, geometric or spatial resolution has improved which implies that smaller details on the ground become visible, allowing for a better view of vegetation and its surrounding environment. Second, the improvement of the radiometric or spectral resolution combined with the integral use of information from different spectral channels allows a more accurate analysis and interpretation of the Remote Sensing data in terms of: type of crop, soil type, state of growth, and presence of disease. Moreover, this aspect facilitates the use of Remote Sensing data under less favourable atmospheric conditions. Thirdly, the number of operational Remote Sensing platforms is growing, which allows for almost continuous monitoring at a worldwide scale.Finally, the internet with its ever increasing capabilities has strongly facilitated the availability of Remote Sensing data and derived data and information products to users, even in remote places. 02/07/2013
Read more...
Produced by leading soil scientists from Europe and Africa, the Soil Atlas of Africa shows the changing nature of soil across the continent. It explains the origin and functions of soil, describes the different soil types that can be found in Africa and their relevance to both local and global issues. The atlas also discusses the principal threats to soil and the steps being taken to protect soil resources. It is a key resource for scientists, practitioners and policy and decision-makers. Informed decision making is currently limited by the scarcity of up to date data on the soil resources of Africa. The JRC, in collaboration with the FAO and African soil scientists, will launch a pan-African assessment on the state of soil resources at the forthcoming conference of the African Soil Science Society in Kenya (October 2013).  (EC Joint Research Centre, 01/05/2013) 02/07/2013
Read more...
Landsat represents the world's longest continuously acquired collection of space-based moderate-resolution land remote sensing data. Four decades of imagery provides a unique resource for those who work in agriculture, geology, forestry, regional planning, education, mapping, and global change research. On 30 May 2013, data from the Landsat 8 satellite (launched as the Landsat Data Continuity Mission – LDCM – on 11 February 2013) became available over the Internet free of charge. Data collected by the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS) onboard the spacecraft since 11 April 2013 are now available to download from EarthExplorerGloVis, and the LandsatLook Viewer. Learn what each of the 11 bands of Landsat 8 images are good for.  (USGS, 30/05/2013) 02/07/2013
Read more...
Satellite and aerial imagery play a significant role in modern day agricultural production and forest related activities. T he primary value of satellite and airborne imagery to agriculture and forestry is two-fold. Firstly, imagery provides valuable information that is useful for planning and managing the potential crop output, in a sustainable way. Imagery results in more sustainable food production. Secondly, imagery enables the gathering of knowledge about agriculture and forestry through local to regional to global scales. That knowledge enables a better understanding of overall production factors, but also contributes toward risk management decisions and supports predictive modelling of food supply and consumption. This article gives a thorough account of the applications of satellite imagery and GIS used in the agriculture and forestry sectors.(Vector1media, 13 May 2011) 01/07/2011
Read more...
By: Scheldeman, Xavier and van Zonneveld, Maarten. Bioversity International. 2010.This training manual is intended for scientists and students who work with biodiversity data and are interested in developing skills to effectively carry out spatial analysis based on (free) GIS applications with a focus on diversity and ecological analyses. These analyses offer a better understanding of spatial patterns of plant diversity and distribution, helping to improve conservation efforts. The training manual focuses on plants of interest for improving livelihoods (e.g. crops, trees and crop wild relatives) and/or those which are endangered.Spatial analyses of interspecific and intraspecific diversity are explained using different types of data: species presence morphological characterization data molecular data. Although this training focuses on plant diversity, many of the types of analyses described can also be applied for other organisms such as animals and fungi.http://www.bioversityinternational.org/training/training_materials/gis_manual.html 03/05/2011
Read more...
A set of new African continental maps was published in May 2013 by the Association of American Geographer (AAG) as a full-colour special supplement to the African Geographical Review. ‘A New Map of Standardized Terrestrial Ecosystems of Africa’ is the result of the efforts of a team of African and U.S. scientists, representing 37 experts from 18 countries who collaborated to produce the maps and ecosystems classification contained herein. To model the potential distribution of ecosystems, new continental datasets for several key physical environment datal ayers were developed at spatial and classification resolutions finer than existing similar data layers. A hierarchical vegetation classification was developed by African ecosystem scientists and vegetation geographers, who also provided sample locations of the newly classified vegetation units. The vegetation types and ecosystems were then mapped across the continent using a classification and regression tree inductive model, which predicted the potential distribution of vegetation types from a suite of biophysical environmental attributes including bioclimate region, biogeographic region, surficial lithology, landform, elevation and land cover.  (AAG, 01/05/2013) 02/07/2013
Read more...

E-mail Newsletter

 English  Français

» Download latest

Members