African Association of
Remote Sensing of the Environment
 
 

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  • 08 Oct 2012 12:30 PM | Administrator (Administrator)

    Authors:

    RAKOTONDRAOMPIANA, Solofo(1),(2) ; FARAMALALA, Miadana(3) ; RAKOTONIAINA, Solofoarisoa(1),(4) ; RAZANAKA, Samuel(5)

    1. Institut & Observatoire de Géophysique d’Antananarivo (IOGA), laboratoire de géophysique de l’environnement et télédétection. Université d’Antananarivo (Madagascar)
    2. Ecole Supérieure Polytechnique d’Antananarivo, département de géologie. Université d’Antananarivo (Madagascar)
    3. Faculté des Sciences, département de biologie et écologie végétales. Université d’Antananarivo (Madagascar)
    4. Faculté des sciences, département de physique. Université d’Antananarivo (Madagascar)
    5. Centre National de Recherche sur l’Environnement (CNRE). Madagascar

    Abstract:

    Comité National Télédétection (CNT) is a network of spatial images end-users in Madagascar. Objectives are capacity building, to share information and to encourage emergence of new projects using remote sensing data. CNT was operational since 2009 and this is our first return of experiences.

    CNT is an initiative of searchers from University of Antananarivo and it gathers about forty institutions including public administration, universities, private companies and NGOs.

    It allows us to transmit to member scientific information about satellites and remote sensing data, to get information from members about their situation so we could use this information for capacity building and negotiation with foreign partners.

    CNT has now its own website where we put all information to member and share image data to all users.

    But we also meet some problems concerning mainly the legal status of CNT.


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    This post was written by Solofo Rakotondraompiana, Miadana Farmalala, Solofoarisoa Rakotoniaina, Samuel Razanaka. Contact Solofo Rakotondraompiana srakotondraompiana@gmail.com for more information.

  • 08 Oct 2012 12:20 PM | Anonymous
    In Morocco, establishing an Integrated Water Resource Management System is fundamental for sustainable development. With regards to its mission CRTS is carrying numerous actions through the country to demonstrate the role of the rapidly evolving earth observation programs for collecting and disseminating water related information in cost effective and sustainable ways. In this paper, parts of the results from these actions will be presented from different applications in different water contexts.

    The first case study aims at developing, in the Souss-Massa hydraulic basin, an integrated approach including the exploitation of the satellite data, the pre-existing data and the Geographical Information Systems (GIS) as sources of information and tools of analysis within the water management process. This region has continuous aquifers that are facing a severe depletion because of intensive irrigated activities. The use of multi-sensors and multi-temporal satellite images (optics and radar) enables to highlight new practices on the current situation of the land use, particularly in the irrigated areas during the last decades. The land use changes analysis shows the surface expression of the groundwater over-exploitation by generating an intensive dynamic, with regards to different aspects of land use changes, in particular in terms of irrigated zones extension. These changes are of two forms, closely related to the reduction (disappearance) or the extension (appearance) of irrigated agricultural activities. In the first case, they are essentially related to the urbanization pressure, soil degradation, and groundwater overexploitation. In the second case, considered as more dominant, these changes take form of appearance of new irrigated farms where groundwater is still more available. Although the general trend at the basin scale shows a continuous increase in irrigated surfaces, locally these irrigated zones are disappearing. The extension seems to be more generalized for the whole plain region and not simply limited to the upstream as it was expected.

    The second case study concerns Ighrem region which is facing a critical situation with regards to potable water resources sustainability. This region has a discontinuous aquifer systems and week surface water contributions because of its arid climate. This area belongs to the Anti-Atlas Mountains considered as part of the Panafrican chain with complex and intensive deformations and a large lithological variability; witch makes more difficult the characterization of its hydrogeologic context. The approach was based on the integration of multi-sensors earth observation data, the existing data and the field truth in order to contribute to the groundwater prospecting process. This allows us to produce details information from lineament and lithological mapping in order to better characterize the aquifer system. In particular, radar imagery had been used for mapping zones with high recharge potential. On the other hand, the integration of these information in a quantitative approach known as Weight of Envidence Modelling for combining evidence in support of an hypothesis. This method has been used based on key hydrogeologic predictors for groundwater prospecting: geology, geomorphology, hydrology and recharge potential. This enabled us to identify and locate the zones presenting high aquifer potentials. These zones are supposed to guide geophysical prospecting to better refine the location of productive drilling in the future.

    The third case study concerns the Sebou hydraulic basin which is receiving more than 1/3 of Moroccan surface water potentialities per year. The aim of the study is to demonstrate the use of earth observation data to better characterize the key hydrologic parameters for water balance evaluation. Actual evapotranspiration (AET) and rainfall are the elements in water balance estimation that give sound information on water availability. At this stage of the work rainfall products were taken from ground meteorological stations and the AET was estimated from remote sensing and GLDAS global meteorological data using the Surface Energy Balance System (SEBS) model. On the other hand, to better refine the calculated daily average of the evaporative fraction a detailed land use map from very high resolution imagery were used for surface parameters. Furthermore, climatological water balance estimation was done over rainfed and irrigated croplands for a specific period in 2010 and 2011.

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    This post was written by A. Er-Raji and D. El Hadani (Royal centre for Remote Sensing, Morocco). Contact A. Er-Raji at er-raji@crts.gov.ma for more information.
  • 08 Oct 2012 12:05 PM | Anonymous

    There are several cases of poor transport services in Uganda that are caused by the bad state of roads. Road maintenance proved ad hoc until recently when the need for preventive maintenance was recognised and plans of making it a priority put in place.

    Since roads are geographically located, the use of Geographical Information Technologies (GITs) in collecting, managing and analysing road condition is paramount. And yet, these technologies are under-utilized for road maintenance. This paper derives from research aimed at accentuating the use of GITs for Road Infrastructure Maintenance (RIM) in Uganda.

    The research addressed three objectives namely to:

    1. Access the gaps and limitations in GIT use and access for RIM,
    2. Develop a methodological framework for enhancing the use of GITs in RIM
    3. Develop a Geographical Information Systems for Transportation (GIS-T) data model for RIM in Uganda.

    In line with the 3rd objective, the paper specifically presents an object data model for RIM. This was accomplished through identification of road maintenance data requirements, review of: organisational reports, workshop proceedings, organisational terms of reference for various projects and existing data models & standards in transportation. An understanding and consideration of the Information Quality Levels (IQL) was paramount. This resulted into a conceptual and logical data model for RIM based on concepts of dynamic segmentation (Dynseg) and linear referencing. The conceptual model depicted using entity relationship diagrams identifies with 3 entities - the road’s network and the point & line events that exist on it. Besides logically documenting the various classes from the conceptual data model, the ESRI provided template for logical data modelling was used. The model separately emphasizes objects having spatial reference, objects without spatial reference and the relationships between them.


    The study concludes that a common definition and understanding of the country’s transportation network is essential to adoption of the proposed model. The choice of GIS software with the full set of dynseg tools is fundamental for implementation of the physical model. This idea of modelling data is a contribution to standardisation of geographic datasets for the sector.


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    This post was written by Lydia Mazzi Kayondo - Ndandiko. Contact her at lndandiko@gmail.com for more information.

  • 08 Oct 2012 9:00 AM | Administrator (Administrator)

    ABSTRACT

    The study is focused on surveying and monitoring tree cover in the argan tree sparse forest of south-west Morocco. Remote sensing data are one IKONOS image from 2003 and one GeoEye image from 2011 (obtained throughGoogle Earth); the latter image has been registered with the 10m resolution IKONOS image used as reference. An object-oriented classification approach has been used to identify tree crowns on both images. However the multi-temporal comparison of results of the two classifications appears not reliable. An alternative solution is proposed through the interactive analysis of the scattergram of 2 channels, one from IKONOS (panchromatic) and one of GeoEye image (sum of 3 bands). In the studied area, tree cover is very low (about 8%) and there are no drastic changes in tree density from 2003 to 2011, except in restricted disturbed areas.

    KEYWORDS: Morocco, argan tree, fractional vegetation cover, tree density, IKONOS, Google Earth, multitemporal analysis

    RÉSUMÉ

    L’étude porte sur la cartographie du couvert arboré de la forêt claire d’arganiers du sud-ouest du Maroc. Les données utilisées sont une image IKONOS de 2003 et une image GeoEye de 2011, extraite de Google Earth ; cette dernière est corrigée géométriquement pour être superposable à l’image IKONOS (résolution spatiale 10m). L’approche de classification orientée objet permet de cartographier de façon assez satisfaisante les couronnes des arbres sur les deux images. Cependant la comparaison des résultats des deux classifications laisse apparaître des artefacts et ne peut servir à une analyse diachronique fiable. La solution alternative proposée repose sur l’analyse interactive de l’histogramme bi-varié de deux canaux provenant respectivement de l’image de 2003 et de celle de 2011. Pour la zone étudiée, le couvert arboré a un faible recouvrement (8% en moyenne) et apparaît stable de 2003 à 2011, avec localement une légère diminution de densité des arbres.

    MOTS-CLéS: Maroc, arganier, couvert arboré, densité d’arbres, IKONOS, Google Earth, analyse diachronique


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    This post was written by Bernard Lacaze (CNRS). Contact him at lacaze.bernard@gmail.com for more information.

  • 08 Oct 2012 8:30 AM | Administrator (Administrator)
    This paper presents a new method of texture modeling using geostatistic theory. From variographics abacus and variogram proprieties, we used fractal and exponential models to characterize Brodatz textures. In this approach, we modeled a texture by a vector called « feature vector » whose components are the parameters characterizing the experimental variogram, notably the « Slope », the « Range », the « Landing » and the « Fractal Dimension ». To estimate these parameters, we use exponential and fractal models. The parameters estimated by this approach help to promote an adequate method of quantitative analysis variogram of textural images. The new method proposed here help also to solve the problem of preferential direction selection often asked by Haralick method of co-occurrence matrix. A comparative study of the proposed method of fractal dimension evaluation and the one proposed in a literature shows that the results obtained are identical with a hundredth of precision on the Brodatz texture images. To demonstrate the applicability of our approach we use to classify a SAR image of ERS-1 from the Atlantic coast of Cameroon. Our approach is one of the great family of supervised classification. It is based on the methods of structural classification. The particularity of this approach lies in the fact that each pixel is fully characterized by its feature vector.

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    This post was written by Fotsing Janvier (University of Buea). Contact him at jfotsing@gmail.com for more information.

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