aerial photography; land use; mosaic; low-cost; high resolution; Burkina Faso
Abstract :
[en] In recent decades, the Kou watershed in south-western Burkina Faso has suffered from poor water management. Despite the abundance of water, most water users regularly face water shortages because of the increase in the amount of land under irrigation. To help them achieve a more equitable allocation of irrigated land, local stakeholders need an easily managed low-cost tool for monitoring and mapping these irrigated zones. The aim of this study was to develop a fast and low-cost procedure for mosaicing and georeferencing amateur small-scale aerial photographs for land-use surveys. Sets of tens (2009) and hundreds (2007) of low-altitude aerial photographs, with a resolution of 0.4 m and 0.8 m, respectively, were used to create a detailed land-cover map of typical African small-scale irrigated agriculture. A commercially available stitching tool and GIS allowed georeferenced ‘mono-images’ to be constructed; both mosaics were warped on a high-resolution SPOT image with a horizontal root mean square error (RMSE) of about 11 m. The RMSE between the two image datasets was 2 m. This approach is less sensitive to atmospheric conditions that are non-predictable in programming satellite imagery.
Research Center/Unit :
Université de Liège, Département Sciences et Gestion de l’Environnement, Arlon, Belgium
Disciplines :
Environmental sciences & ecology
Author, co-author :
Wellens, Joost ; Université de Liège - ULiège > DER Sc. et gest. de l'environnement (Arlon Campus Environ.) > DER Sc. et gest. de l'environnement (Arlon Campus Environ.)
Tychon, Bernard ; Université de Liège - ULiège > DER Sc. et gest. de l'environnement (Arlon Campus Environ.) > Agrométéorologie (relation agriculture-environ. physique)
Language :
English
Title :
An easy and low-cost method for preprocessing and matching small-scale amateur aerial photography for assessing agricultural land use in Burkina Faso
Publication date :
August 2013
Journal title :
International Journal of Applied Earth Observation and Geoinformation
ISSN :
1569-8432
eISSN :
1872-826X
Publisher :
Elsevier Science, Amsterdam, Netherlands
Volume :
23
Pages :
273-278
Peer reviewed :
Peer Reviewed verified by ORBi
Funders :
APEFE - Association pour la Promotion de l'Éducation et de la Formation à l'Étranger WBI - Wallonie-Bruxelles International
Baker, W.L., Honaker, J.J., Weisberg, P.J., 1995. Using aerial photography and GIS to map Forrest-Tundra ecotone in Rocky Mountain National Park, Colorado, for global change research. Photogrammetric Engineering and Remote Sensing 61, 313-320.
Carmel, Y., Flather, C., Dean, D., 2006. A methodology for translating positional error into measures of attribute error, and combining the two error sources. In: Proceedings of the 7th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, Lisbon, Portugal, pp. 3-17.
Carreiras, J.M.B., Pereira, J.M.C., Pereira, J.S., 2006. Estimation of tree canopy cover in evergreen oak woodlands using remote sensing. Forest Ecology and Management 223, 45-53.
CartoTalk, 2012. Aerial Image Stitching along with GIS, www.cartotalk.com (accessed 03.09.12).
Cleve, C., Kelly, M., Kearns, F.R., Moritz, M., 2008. Classification of the wildland-urban interface: a comparison of pixel-and object-based classifications using high resolution aerial photography. Computers, Environments and Urban Systems 32, 317-326.
ERDAS, 2002. IMAGINE OrthoBASE User's Guide. ERDAS INC., Atlanta, USA, p. 484. FAO, 2002. World Agriculture: Towards 2015/2030. FAO, Rome, Italy, p. 106.
FAO, 2002. World Agriculture: Towards 2015/2030. FAO, Rome, Italy, 106
FAO, 2011. Global Map of Irrigation Areas, www.fao.org (accessed 28.10.11).
Foody, G.M., 2000. Estimation sub-pixel land cover classification accuracy assessment. Remote Sensing of Environment 26, 469-478.
Jaffrain, G., Boussim, J., Diallo, A., Sidibe, N., Yago, D., Pare, F., 2005. Guide Technique de la Nomenclature de la Base de Données d'Occupation des Terres (BDOT), Burkina Faso. In: Technical Report, Institut Géographique du Burkina (IGB), Ouagadougou, Burkina Faso, p. 40.
Kadmon, R., Harari-Kremer, R., 1999. Studying long-term vegetation dynamics using digital processing of historical aerial photographs. Remote Sensing of Environment 68, 164-176.
Kardoulas, N.G., Bird, A.C., Lawan, A.I., 1996. Geometric correction of SPOT and Landsat imagery: a comparison of map-and GPS-derived control points. Photogrammetric Engineering and Remote Sensing 62 (10), 1173-1177.
Kressler, F.P., Bauer, T.B., Franzen, M., 2005. Object-oriented classification of orthophotos to support update of spatial databases. In: Geoscience and Remote Sensing Symposium, 2005, IGARSS '05. Proceedings. 2005 IEEE International, vol. 1, pp. 1-4.
Land Info, 2012. High-resolution Satellite Imagery, http://www.landinfo.com (accessed 03.05.12).
Lillesand, T.M., Kiefer, R.W., Chipman, J.W., 2004. Remote Sensing and Image Interpretation. Wiley, NY, USA, p763.
Lunetta, R.S., Elvidge, C.D., 1998. Remote Sensing Change Detection: Environmental Monitoring Methods and Applications. Ann Arbor Press, Chelsea, MI, p. 318.
Morgan, J.L., Gergel, S.E., Coops, N.C., 2010. Aerial photography: a rapidly evolving tool for ecological management. BioScience 60 (1), 47-59.
New House Internet Services B.V., 2010. http://www.ptgui.org (accessed 28.10.11).
Oberthür, T., Cock, J., Andersson, M.S., Naranjo, R.N., Casta~neda, D., Blair, M., 2007. Acquisition of low altitude digital imagery for local monitoring and management of genetic resources. Computers and Electronics in Agriculture 58, 60-77.
Pe~na-Barragán, J.M., Jurado-Expósito, M., López-Granados, F., Atenciano, S., Sánchezde la Order, M., García-Ferrer, A., García-Torres, L., 2004. Assessing land-use in olive groves from aerial photographs. Agriculture, Ecosystems and Environment 103, 117-122.
PRLog, 2009. Volume Digitization of Maps and Aerial Photographs, www.prlog.org (accessed 03.09.12).
Raal, P.A., Burns, M.E.R., 1996. Mapping and conservation importance rating of South African coastal vegetation as an aid to development planning. Landscape and Urban Planning 34, 389-400.
Rabatel, G., Delenne, C., Deshayes, M., 2008. A non-supervised approach using Gabor filters for vine-plot detection in aerial images. Computers and Electronics in Agriculture 62, 159-168.
Rembold, F., Carnicelli, S., Nori, M., Ferrai, G.A., 2000. Use of aerial photographs, Landsat TM imagery and multidisciplinary field survey for land-cover change analysis in the lakes region (Ethiopia). International Journal of Applied Earth Observation and Geoinformation 2 (3-4), 181-189.
Rocchini, D., Di Rita, R., 2005. Relief effects on aerial photos geometric correction. Applied Geography 25, 159-160.
Stow, D., Hamada, Y., Coulter, L., Anguelova, Z., 2008. Monitoring shrubland habitat changes through object-based change identification with airborne multispectral imagery. Remote Sensing of Environment 112, 1051-1061.
Townshend, J.R.G., Justice, C.O., Gurney, C., McManus, J., 1992. The impact of misregistration on change detection. IEEE Transactions on Geoscience and Remote Sensing 30, 1054-1060.
Urama, 2005. Land-use intensification and environmental degradation: empirical evidence form irrigated and rain-fed farms in south eastern Nigeria. Journal of Environmental Management 75 (3), 199-217.
Wang, H., Ellis, E.C., 2005. Image misregistration error in change measurements. Photogrammetric Engineering and Remote Sensing 71, 1037-1044.
Warner, W.S., Graham, R.W., Read, R.E., 1996. Small Format Aerial Photography. Whittles Publishing, UK, p. 348.
Wellens, J., 2011. Renforcement structurel de la capacité de gestion des ressources en eau pour l'agriculture dans le bassin du Kou, www.ge-eau.org (accessed 28.10.11).
Wentz, E.A., Stefanov, W.L., Gries, C., Hope, D., 2006. Land use cover mapping from diverse data sources for an arid urban environments. Computers, Environment and Urban Systems 30, 320-346.
Zharikov, Y., Skilleter, G.A., Loneragan, N.R., Taranto, T., Cameron, B.E., 2005. Mapping and characterizing subtropical estuarine landscapes using aerial photography and GIS for potential application in wildlife conservation and management. Biological Conservation 125, 87-100.
