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.

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
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The excessive use of irrigation water has resulted in serious environmental concerns in many dry-land countries, where rising demand has deteriorated groundwater resources, depleted aquifers, and accelerated saltwater intrusion. Scientists in Spain are working on new technologies to classify and monitor irrigated crops with a goal of promoting sustainable agricultural practices. The field studies the researchers designed were to evaluate the potential of multispectral reflectance and seven vegetation indices in the visible and near-infrared spectral range for discriminating and classifying bare soil and several horticultural irrigated crops. The research is the first step of a broader project with the overall goal of using satellite imagery with high spatial and multispectral resolutions for mapping irrigated crops. (American Society for Horticultural Science via Physorg, 1/4/2011) 30/08/2011
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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
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by Norbert Henninger, Florence Landsberg, with the Ministry of Agriculture, Animal Industry and Fisheries, Uganda, Uganda Bureau of Statistics, Food and Agriculture Organization of the United Nations, and the International Livestock Research Institute, October, 2010This report commissioned by the World Resource Institute, USA, uses mapping data to examine the spatial relationships between poverty, livestock production systems, the location of livestock services, in order to ensure that government investments in the livestock sector benefit smallholders and high-poverty locations. The process of compiling the data, producing the maps, and analyzing the map overlays has shown that: Analysts working with the Uganda Bureau of Statistics, the Ministry of Agriculture, Animal Industry and Fisheries, and other collaborators can combine poverty maps with maps of livestock systems and distributions, milk surplus and deficit areas, and areas of high disease risk to highlight relationships that might not otherwise be obvious. From these map overlays, analysts can create new indicators and maps juxtaposing levels of poverty and the type and levels of livestock production. Analysts can use these indicators and maps to select geographic areas with specific poverty and livestock profiles for pro-poor targeting. Decision-makers can use these new indicators and maps to make more informed and transparent choices when prioritizing investments in the livestock sector and to communicate these priorities to the public. Maps showing milk surplus and deficit areas can highlight geographic differences in market opportunities for poor dairy farmers. This information can help policymakers, dairy researchers, and development agencies to better target knowledge dissemination, market infrastructure investments, and service delivery to dairy farmers.(Source: World Resources Institute, Feb. 2011) 18/03/2011
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NOAA-funded researchers hope a new climate information system they developed will help West African farmers help themselves. Rainwatch is a prototype geographic information system (GIS) that monitors monsoon rainfall and tracks season rainfall attributes. This information is crucial because sub-Saharan Africa depends more strongly and directly on rainfall than any other region on Earth, yet the area has the fewest rainfall monitoring stations and significant delays that occur between data collection and its availability for users. Rainwatch automates and streamlines key aspects of rainfall data management, processing and visualization. A major appeal is its simplicity – all interactive interfaces, symbols and names used are unpretentious and self explanatory. In addition, the system can be used by Africans without any outside assistance such as satellite information. In a successful 2009 demonstration involving seven rain gauge stations in Niger, Rainwatch was shown to directly address the area's need for better rainfall data acquisition, management, representation and rapid dissemination. The programme continued in 2010, when it dramatically showed the return of abundant rainfall. It is expected to expand beyond Niger. Because Rainwatch is simple to operate and more streamlined in design and scope than existing systems, the researchers hope the programme will be adopted and used more widely throughout West Africa where other more complicated rainfall data dissemination systems have had limited success. (NOAA, 12/5/2011) 07/06/2011
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Remote sensing - an overview

by Paul Geerders
Remote imaging sensors use electromagnetic radiation, emanating from the earths' surface, either directly (thermal radiation: temperature) or reflected by it. There are two main types; active and passive. In the latter case the source is sunlight (visible light scanners) or an artificial source carried by the sensing platform (radar, lidar). Remote Sensing uses radiation with wavelengths roughly between 400 nm (ultraviolet) and 4 cm (radio waves). 02/01/2005
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