In many developing countries, some natural areas are faced with gaps in appropriate map coverage mainly on land use and land cover (LULC) changes. This situation makes it difficult to plan and implement natural environmental protection and natural resource management programs. Remote sensing and geographic information systems (GIS) are excellent tools for mapping LULC changes. This study investigated LULC changes in ‘Somone’ coastal lagoon in Senegal using multisource remote sensed data. Data sets included aerial photographs recorded in March 1954, and February 1978, as well as satellite images recorded in February 2003 and April 2016. All images were geometrically corrected and segmented. Photos and/or images interpretations were made with the aid of computer and post-classification change detection technique was applied to classify multisource data and to map changes. Stratified sampling was used to assess all classification results. The accuracies of image classifications averaged 65% (1954), 62% (1978), 79% (2003) and 88% (2016). The post-classification analysis resulted in the largest overall accuracy of 66, 72.7, 72.4 and 80.6% for the 1954–1978, 1978-2003 and 2003–2016 image pairs, respectively. Results indicated an increase in Settlements, from 0.29% in 1954 to 9.21% in 2016, the expansion of the Sabkha, from 5.29% in 1954 to 18.48% in 2016. The mangrove forest has experimented a reduction between 1954 and 1978 (from 4.07% to 0.56%) and a regeneration (linked to the protection and preservation policies within the protected area) from the year 2003 to 2016 (from 1.44% to 2.65%). However, the forest areas were greatly reduced (from 51.06% in 1954 to 10.86% in 2016) and replaced by Settlements (urbanization) as well as Croplands.
| Published in | American Journal of Remote Sensing (Volume 7, Issue 2) |
| DOI | 10.11648/j.ajrs.20190702.12 |
| Page(s) | 35-49 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2019. Published by Science Publishing Group |
Multi-source Data, Remote Sensing, LULC Changes, Visual Interpretation Assisted by Computer, Somone Coastal Lagoon, Senegal
| [1] | Green, K., Kempka, D. & Lackey, L. Using remote sensing to detect and monitor land cover and land-Use change. 1994. Photogrammetric Engineering & Remote Sensing. 60 (3) 331-337. |
| [2] | Tappan, G. G., Hadj, A., Wood, E. C., and Lietzow, R. W. Use of Argon, Corona, and Landsat imagery to assess 30 years of land resource changes in west-central Senegal. 2000, Photogrammetric Engineering and Remote Sensing, 66, 727–736. |
| [3] | Rogan, J. & Chen, D. M. Remote sensing technology for mapping and monitoring land-cover and land-use change. 2004, Progress in Planning. 6, 1301–325. |
| [4] | Shalaby, A. & Tateishi, R. Remote sensing and GIS for mapping and monitoring land cover and land-use changes in the Northwestern coastal zone of Egypt. 2007, Applied Geography 27, 28–41. doi: 10.1016/j.apgeog.2006.09.004. |
| [5] | Droj, G. GIS and remote sensing in environmental management. 2012, Journal of environmental protection and ecology. 2 (10), 1-7. |
| [6] | Song, D-X., Huang, C., Sexton, J. O., Channan, S., Feng, M. & Townshend, J. R. Use of Landsat and Corona data for mapping forest cover change from the mid-1960s to 2000s: Case studies from the Eastern United States and Central Brazil. 2014, International Journal of Remote Sensing. XXXXXXX, http://dx.doi.org/10.1016/j.isprsjprs.2014.09.005. |
| [7] | Nations Unies, (2017). Rapport sur l’Atelier ONU/République islamique d’Iran sur l’exploitation des techniques spatiales pour la surveillance des tempêtes de poussière et des sécheresses dans la région du Moyen-Orient. Téhéran, 5-9 novembre 2016. A/AC.105/1132. p. 13. |
| [8] | Foody, G. M. Status of land cover classification accuracy assessment. 2003. Remote Sensing of Environment 80, 185-201. http://www2.geog.ucl.ac.uk/~mdisney/teaching/teachingNEW/GEOGG141/papers/foody.pdf. |
| [9] | Anderson, J. R. Land use and land cover changes. A framework for monitoring. 1977, Journal of research by Geological Survey. 5, 143-153. |
| [10] | Ingram, K., Knapp, E. and Robinson, J. W. Procedure for change detection using Landsat digital data. 1981, International Journal of Remote Sensing. 2, 277-291. |
| [11] | Singh, A. Change detection in the tropical forest environment of northern India using Landsat. 1986, In: Eden, M., Parry, J. (Eds.), Remote Sensing and Land Management. pp. 237–253. |
| [12] | Singh, A. Digital change detection techniques using remotely sensed data. 1989 International Journal of Remote Sensing 10, 989–1003. http://dx.doi.org/10.1080/01431168908903939. |
| [13] | Lu, D. S., Mausel, P., Batistella, M., Moran, E. Land-cover binary change detection methods for use in the moist tropical region of the Amazon: a comparative study. 2005, International Journal of Remote Sensing 26, 101–114. |
| [14] | Ban Y, Yousif O. Multitemporal spaceborne SAR data for urban change detection in China. 2012, IEEE J Sel Top Appl Earth Obs Rem Sen 5 (4): 1087–1094. |
| [15] | Du P, Liu S, Gamba P, Tan K, Xia J Fusion of difference images for change detection over urban areas. 2012, IEEE J Sel Top Appl Earth Obs Remote Sens 5: 1076–1086. doi: 10.1109/JSTARS.2012.2200879. |
| [16] | Lu, D. S., Mausel, P., Brondı´zio, E. S., Moran, E. Change detection techniques. 2004, International Journal of Remote Sensing 25, 2365–2407. http://dx.doi.org/10.1080/0143116031000139863. |
| [17] | Petit, C. C., and Lambin, E. F. Integration of multi-source remote sensing data for land cover change detection. 2001, International Journal of Geographical Information Science, 15, 785–803. |
| [18] | Turner, B. L., Meyer, W. B., & Skole, D. L. Global land-use/land-cover change: towards an integrated study. 1994, Ambio. Stockholm, 23 (1), 91-95. |
| [19] | Bussi, G., Dadson, S. J., Prudhomme, C., & Whitehead, P. G. Modelling the future impacts of climate and land-use change on suspended sediment transport in the River Thames (UK). 2016, Journal of hydrology, 542, 357-372. |
| [20] | Almutairi, A. and Warner, T. A. Change Detection Accuracy and Image Properties A Study Using Simulated Data. 2010, Remote Sensing. 2. 1508-1529. |
| [21] | Ban, Y. and Yousif, O. Change Detection Techniques: A Review. In Ban, Y. (ed.) Multitemporal Remote Sensing. 2016, Remote Sensing and Digital Image Processing 20, DOI 10.1007/978-3-319-47037-5_2. |
| [22] | Dwivedi, R. S. Kumar, A. B. & Tewari, K. N. The utility of multi-sensor data for mapping eroded lands. 1997, International Journal of Remote Sensing. 18 (11), 2303-2318. http://dx.doi.org/10.1080/014311697217620. |
| [23] | Arastoo, B. and Ghazaryan, S. Landcover Changes Detection in Semnan province by Remote Sensing Techniques. 2013, International Journal of Agronomy and Plant Production. Vol., 4 (7), 1637-1644. |
| [24] | Lee, T., Richards, J. A., and Swain, P. Probabilistic and evidential approaches for multisource data analysis. 1987, IEEE Transaction on Geoscience and Remote Sensing, GE-25 (3), 283–293. |
| [25] | Benediktsson, J. A., Swain, P. H., and Ersoy, O. K. Neural network approaches versus statistical methods in classification of multisource remote sensing data. 1990, IEEE Transactions on Geoscience and Remote Sensing, 28 (4), 540–552. http://dx.doi.org/10.1109/TGRS.1990.572944. |
| [26] | Sorberg, A. H. S., Jain, A. K. & Taxt, T. Multisource classification of remotely sensed data: fusion of Landsat TM and SAR images. 1994, IEEE Transactions on Geoscience and Remote Sensing. 32 (4), 768–778. http://dx.doi.org/10.1109/36.298006. |
| [27] | Mouat, D. A., and Lancaster, J. Use of remote sensing and GIS to identify vegetation change in the upper San Pedro river watershed, Arizona. 1996, Geocarto International, 11, 55–67. |
| [28] | Benediktsson, J. A. and Kanellopoulos, I. Classification of multisource and hyperspectral data based on decision fusion. 1999, IEEE Transactions on Geoscience and Remote Sensing, 37 (3), 1367–1377. |
| [29] | Salami, A. T., Ekanade, O., and Oyinloye, R. O. Detection of forest reserve incursion in south-western Nigeria from a combination of multi-date aerial photographs and high-resolution satellite imagery. 1999, International Journal of Remote Sensing, 20, 1487–1497. |
| [30] | Bruzzone, L. and Prieto, D. F. Unsupervised change detection in multisource and multisensor remote sensing images. In: Proceedings. 2000, IEEE 2000 international geoscience and remote sensing symposium. Presented at the IGARSS 2000, vol 6, pp 2441–2443. doi: 10.1109/IGARSS.2000.859602. |
| [31] | Tappan, G. G., Hadj, A., Wood, E. C., & Lietzow, R. W. (2000). Use of Argon, Corona, and Landsat imagery to assess 30 years of land resource changes in west-central Senegal. Photogrammetric engineering and remote sensing, 66 (6), 727-736. |
| [32] | Reid, R. S., Kruska, R. L., Muthui, N., Taye, A., Wotton, S., Wilson, C. J., and Mulatu, W., Land-use and land-cover dynamics in response to change in climatic, biological and socio-political forces: the case of southwestern Ethiopia. 2000, Landscape Ecology, 15, 339–355. |
| [33] | Weng, Q. Land use change analysis in the Zhujiang Delta of China using satellite remote sensing, GIS and stochastic modelling. 2002, Journal of Environmental Management, 64, 273–284. |
| [34] | Amarsaikhan, D. and Douglas, T. Data fusion and multisource image classification. 2004, International Journal of Remote Sensing, 25 (17), 3529–3539. |
| [35] | Stein, A. Use of single- and multi-source image fusion for statistical decision-making. 2005, International Journal of Applied Earth Observation and Geoinformation, 6 (3–4), 229–239. |
| [36] | Ganasri, B. P. & Aedla, Raju & Dwarakish, GS. Different Approaches for Land Use Land Cover Change Detection: A Review. Research and Reviews: 2013, Journal of Engineering and Technology. 2. 44-48. |
| [37] | Frihy, O. E. Dewidar, K. M. Nasr, S. M. & El Raey M. M. Change detection of the northeastern Nile Delta of Egypt: Shoreline changes, Spit evolution, margin changes of Manzala lagoon and its islands. 1998, International Journal of Remote Sensing. 19 (10), 1901-1912. http://dx.doi.org/10.1080/014311698215054. |
| [38] | Cesar, A., Robles, B. and Arturo R-L. Land Use mapping and change detection in the coastal zone of northwest Mexico using remote sensing techniques. 2002, Journal of Coastal Research, 18 (31,514-522. West Palm Beach IFlorida), ISSN 0749-0208. |
| [39] | Calvo, S., G. Ciraolo & G. L. Loggia. Monitoring Posidonia oceanica meadows in a Mediterranean coastal lagoon (Stagnone, Italy) by means of neural network and ISODATA classification methods. 2003, International Journal of Remote Sensing 24: 2703–2716. |
| [40] | Ahmed, M. H., Leithy, B. M., Thompson, J. R., Ramdani, M., Ayache, F. and Hassan. Application of remote sensing to site characterisation and environmental change analysis of North African coastal lagoons. 2009, Hydrobiologia. 622 (1), 147–171. Dio: 10.1007/s10750-008-9682-8. |
| [41] | Allen, R. A. Estimating Coastal Lagoon Tidal Flooding and Repletion with Multidate ASTER Thermal Imagery. 2012, Remote Sensing. 4, 3110-3126. http://dx.doi.org/10.3390/rs4103110. |
| [42] | CSE, 2015. Rapport sur l’ etat de l’ environnement du Senegal. P 96. |
| [43] | FAO. Land cover classification system. Classification concepts and user manual. 2005, Software version 2. P. 189. ISBN: 92-5-105327-8. |
| [44] | Clinton, W. J. Release of Imagery Acquired by Space-Based National Intelligence Reconnaissance Systems, Executive Order No. 12951, 22 February 1995, Washington, D. C. |
| [45] | Bouziani, M., Goita, K. & Dong-Chen, H. Rule-based classification of a Very High-Resolution Image in an urban environment using multispectral segmentation guided by cartographic data. 2010, IEEE Transaction on Geoscience and Remote Sensing. 48 (8), 3198-3211. http://dx.doi.org/10.1109/TGRS.2010.2044508. |
| [46] | Benga, E. Geomorphological study of the mangrove of the Somone estuary. Report "Study of mangroves and estuaries of Senegal Saloum and Somone. 1984, UNESCO-EPEEC, 55-70. |
| [47] | Sakho, I., Mesnage, V., Deloffre, J., Lafite, R., Niang, I., Faye, G. The influence of natural and anthropogenic factors on mangrove dynamics over 60 years: The Somone Estuary, Senegal. 2011, Estuarine, Coastal and Shelf Science. 94, 93-101. https://doi.org/10.1016/j.ecss.2011.05.032. |
| [48] | Haack, B., Mahabir, R., & Kerkering, J. (2015). Remote sensing-derived national land cover land use maps: a comparison for Malawi. Geocarto International, 30 (3), 270-292. |
| [49] | Franklin SE, Wulder MA. Remote sensing methods in medium spatial resolution satellite data land cover classification of large areas. 2002, Prog Phys Geogr. 26: 173–205. |
| [50] | Berberoglu S, Akin A. Assessing different remote sensing techniques to detect land use/cover changes in the eastern mediterranean. 2009, Int J Appl Earth Obs Geoinf. 11: 46–53. |
| [51] | M. A. Toure, M. L. Ndiaye, V. B. Traore, G. Faye, B. Cisse, A. Ndiaye, C. T. Wade, P.(2016). Using of Landsat Images for Land Use Changes Detection in the Ecosystem: A Case Study of the Senegal River Delta. International Journal of Environment Agriculture and Biotechnology (ISSN: 2456-1878). 1 (2), pp. 200-209. |
| [52] | Lillesand, T. M.; Kiefer, R. W. Remote Sensing and Image Interpretation. 1994, 3 rd. (Ed.), John Wiley and Sons, New York, 750. |
| [53] | Sivakumar, R. Image Interpretation of Remote Sensing data. 2010, Geospatial World. https://www.geospatialworld.net/article/image-interpretation-of-remote-sensing-data/. |
| [54] | Puig, C. J., Hyman, G. and Bolaños, S. Digital Classification vs. Visual Interpretation: a case study in humid tropical forests of the Peruvian Amazon. 2002, http://gisweb.ciat.cgiar.org/sig/download/ghyman/Puig2002DigitalVsVisual.pdf. |
| [55] | Karsenty, A. Questioning rent for development swaps: new marketbased instruments for biodiversity acquisition and the land-use issue in tropical countries. 2007, International Forestry Review, 9 (1), 503-513. |
| [56] | Yoon G. W., Cho S. I., Jeong S., Park J. H., Object oriented classification using Landsat images. 2010, p. 1-3. |
| [57] | Congalton, R. G., and Green, K. Assessing the Accuracy of Remotely Sensed Data: Principles and Practices. 1999. Lewis Publishers, Boca Raton, Florida, 137 p. |
| [58] | Richards, J. A. Remote Sensing Digital Image Analysis, 5th ed.; 2006, Springer: Heidelberg, Germany. |
| [59] | Duman, K., Eryildirim, A., & Cetin, A. E.). Target detection and classification in sar images using region covariance and co-difference. In Algorithms for Synthetic Aperture Radar Imagery XVI (Vol. 7337, p. 73370P). 2009, April International Society for Optics and Photonics. |
| [60] | Jensen, K. R. Phylogenetic systematics and classification of the Sacoglossa (Mollusca, Gastropoda, Opisthobranchia).1996, Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, 351 (1335), 91-122. |
| [61] | Gumma, M. K., Thenkabail, P. S., Teluguntla, P., Rao, M. N., Mohammed, I. A., & Whitbread, A. M. Mapping rice-fallow cropland areas for short-season grain legumes intensification in South Asia using MODIS 250 m time-series data. 2016, International Journal of Digital Earth, 9 (10), 981-1003. |
| [62] | Congalton, R. G. A review of assessing the accuracy of classifications of remotely sensed data. Remote Sens. Environ. 1991, 37, 35–46. http://dx.doi.org/10.1016/0034-4257(91)90048-B. |
| [63] | Girard M. C. & Girard C. M. 1999. Traitement des données de télédétection. DUNOD Ed. Paris, pages 326 à 334. |
| [64] | Justine M. Caractérisation de la dynamique d'occupation du sol de la ville de Kissangani (R. D. Congo) et sa périphérie entre 2002 et 2010, Master en Bioingénieur en gestion des forêts et des espaces naturels. 2012, Université de Liège, 99 pages. |
| [65] | Chen, G., G. J. Hay, L. M. T. Carvalho, and M. A. Wulder. “Object-Based Change Detection.” 2012, International Journal of Remote Sensing 33 (14): 4434–4457. doi: 10.1080/01431161.2011.648285. |
| [66] | Hussain, M., D. Chen, A. Cheng, H. Wei, and D. Stanley. “Change Detection from Remotely Sensed Images: From Pixel-Based to Object-Based Approaches.” 2013, ISPRS Journal of Photogrammetry and Remote Sensing80: 91–106. doi: 10.1016/j.isprsjprs.2013.03.006. |
| [67] | Lunetta, R. S., D. M. Johnson, J. G. Lyon, and J. Crotwell. “Impacts of Imagery Temporal Frequency on Land-Cover Change Detection Monitoring.” 2004, Remote Sensing of Environment89 (4): 444–454. doi: 10.1016/j.rse.2003.10.022. |
| [68] | Yan, G., Mas, J. F., Maathuis, B. H. P., Xiangmin, Z., & Van Dijk, P. M. Comparison of pixel–based and object–oriented image classification approaches—a case study in a coal fire area, Wuda, Inner Mongolia, China. 2006, International Journal of Remote Sensing, 27 (18), 4039-4055. |
| [69] | Fichera, C. R., Modica, G., & Pollino, M. Land Cover classification and change-detection analysis using multi-temporal remote sensed imagery and landscape metrics. 2012, European Journal of Remote Sensing, 45 (1), 1-18. |
| [70] | Perez, M. J.; Kobayashi, H.; Matsumura, I. Analysis of land use change in Comayagua County, Honduras, based on remote sensing and field survey data. J. 2005, JASS, 21, 199–208. |
| [71] | Batar, A. K., Watanabe, T. and Kumar, A. Assessment of Land-Use/Land-Cover Change and Forest Fragmentation in the Garhwal Himalayan Region of India. 2017, Environments 2017, 4, 34; doi: 10.3390/environments4020034. |
| [72] | Congalton, R., and MacLeod, R., 1994, Change detection accuracy assessment on the NOAA Chesapeake Bay Pilot Study. Proceedings of the 1st International Symposium on the Spatial Accuracy of Natural Resource Data Bases, W illiamsburg, V irginia (Bethesda, Maryland: American Society for Photogrammetry and Remote Sensing), pp. 78–87. |
| [73] | Macleod, R. D. and Congalton, R. G. Quantitative Comparison of change-detection Algorithms for monitoring Eelgrass from Remotely Sensed Data. 1998, Photogrammetric Engineering ad Remote Sensing, 64, 207-2016. |
| [74] | Brown, M. S., Goldin, J. G., McNitt-Gray, M. F., Greaser, L. E., Sapra, A., Li, K. T.... & Aberle, D. R. (2000). Knowledge-based segmentation of thoracic computed tomography images for assessment of split lung function. Medical physics, 27 (3), 592-598. |
| [75] | Landis J. T. and Koch G. G. The Measurement of observer agreement for categorical data. 1977, Biometrics, 33, 159-174. |
| [76] | Xing, J. and Sieber, R. E. A land use/land cover change geospatial cyberinfrastructure to integrate big data and temporal topology. 2015, International Journal of Geographical Information Science, DOI: 10.1080/13658816.2015.1104534. |
| [77] | Sakho, I. Evolution et fonctionnement hydro-sedimentaire de la lagune de la Somone, Petite Cote, Senegal., (Sciences de l’environnement. 2011, Universite de Rouen; Universite Cheikh Anta Diop de Dakar), 254. |
| [78] | Cabinet EDE (Environment, Waste, Water), 2016. Etude d´impacts Environnemental et social du dragage de la lagune de Somone. p. 225. |
| [79] | Ruiz-luna, Arturo, John Turner, and Fernando Alonso-p. “Land Cover Changes and impact of Shrimp Aquaculture on the Landscape in the Ceuta Coastal Lagoon System, Sinaloa, Mexico”. 2003, 46: 583–600. https://doi.org/10.1016/S0964-5691(03)00036-X. |
| [80] | Kadeba, A, B M I Nacoulma, A Ouedraogo, Y Bachmann, and A Thiombiano. “Land Cover Change and Plants Diversity in the Sahel: A Case Study from Northern Burkina Faso” 2015, 58 (1): 109–23. https://doi.org/10.15287/afr.2015.350. |
| [81] | Gaglio, Mattias, Vassilis G Aschonitis, Elena Gissi, Giuseppe Castaldelli, and Elisa A Fano.. “Land Use Change Effects on Ecosystem Services of River Deltas and Coastal Wetlands: Case Study in Volano – Mesola – Goro in Po River Delta (Italy).” 2016, Wetlands Ecology and Management, 20. https://doi.org/10.1007/s11273-016-9503-1. |
| [82] | Campbell, J. B., & Wynne, R. H. Introduction to remote sensing. 2011, Guilford Press. |
| [83] | Ellis, E. C., Klein Goldewijk, K., Siebert, S., Lightman, D., & Ramankutty. Anthropogenic transformation of the biomes, 1700 to 2000. 2010, Global ecology and biogeography, 19 (5), 589-606. |
| [84] | Kennish M J and Hans W. P. Coastal Lagoons critical habitat for environmenetal change. 2010, Marine Science series Taylor and Francis group. p. 555. |
| [85] | Stolt, M., Bradley, M., Turenne, J., Payne, M., Scherer, E., Cicchetti, G.... & Oakley, B. (2011). Mapping shallow coastal ecosystems: a case study of a Rhode Island lagoon. 2011, Journal of Coastal Research, 27 (6A), 1-15. |
| [86] | Mahapatro, D., Panigrahy, R. C. and Panda, S. Coastal Lagoon: Present Status and Future Challenges 2 Classifications of Coastal Lagoons. 2013, International Journal of Marine Science, 3 (23), 178–186. https://doi.org/10.5376/ijms.2013.03.0023. |
| [87] | Duck, R. W and da Silva, J. F. Coastal lagoons and their evolution: A hydromorphological perspective. 2012, Estuarine, Coastal and Shelf Science, 110, 2–14. https://doi.org/10.1016/j.ecss.2012.03.007. |
| [88] | Garrido, J., Pérez-bilbao, A and Benetti, C. J. Biodiversity and Conservation of Coastal Lagoons Ecosystems Biodiversity. 2011, Oscar Grillo and Gianfranco Venora, IntechOpen. P30, DOI: 10.5772/24934. Available from: https://www.intechopen.com/books/ecosystems-biodiversity/biodiversity-and-conservation-of-coastal-lagoons. |
| [89] | Viaroli, P., Lasserre, P., & Campostrini, P. (Eds.). (2007). Lagoons and coastal wetlands in the global change context: impacts and management issues: selected papers of the International Conference" Coast Wet Change", Venice, 26-28 April 2004. Springer. |
| [90] | Barry, N. Y., Traore, V. B., Ndiaye, M. L., Isimemen, O., Celestin, H. and Sambou, B. (2017) Assessment of Climate Trends and Land Cover/Use Dynamics within the Somone River Basin, Senegal. American Journal of Climate Change, 6, 513-538. https://doi.org/10.4236/ajcc.2017.63026 Paulya, D., and Yiiez-arancibiab, A. Fisheries in Coastal Lagoons.1994, 377–399. |
| [91] | Avelar, S., & Tokarczyk, P. (2014). Analysis of land use and land cover change in a coastal area of Rio de Janeiro using high-resolution remotely sensed data. Journal of Applied Remote Sensing, 8 (1), 083631. |
APA Style
Ndéye Yacine Barry, Mamadou Lamine Ndiaye, Celestin Hauhouot, Bienvenu Sambou. (2019). Using Remote Sensing Technics for Land Use Land Cover Changes Analyses from 1950s to 2000s in Somone Tropical Coastal Lagoon, Senegal. American Journal of Remote Sensing, 7(2), 35-49. https://doi.org/10.11648/j.ajrs.20190702.12
ACS Style
Ndéye Yacine Barry; Mamadou Lamine Ndiaye; Celestin Hauhouot; Bienvenu Sambou. Using Remote Sensing Technics for Land Use Land Cover Changes Analyses from 1950s to 2000s in Somone Tropical Coastal Lagoon, Senegal. Am. J. Remote Sens. 2019, 7(2), 35-49. doi: 10.11648/j.ajrs.20190702.12
AMA Style
Ndéye Yacine Barry, Mamadou Lamine Ndiaye, Celestin Hauhouot, Bienvenu Sambou. Using Remote Sensing Technics for Land Use Land Cover Changes Analyses from 1950s to 2000s in Somone Tropical Coastal Lagoon, Senegal. Am J Remote Sens. 2019;7(2):35-49. doi: 10.11648/j.ajrs.20190702.12
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Download@article{10.11648/j.ajrs.20190702.12,
author = {Ndéye Yacine Barry and Mamadou Lamine Ndiaye and Celestin Hauhouot and Bienvenu Sambou},
title = {Using Remote Sensing Technics for Land Use Land Cover Changes Analyses from 1950s to 2000s in Somone Tropical Coastal Lagoon, Senegal},
journal = {American Journal of Remote Sensing},
volume = {7},
number = {2},
pages = {35-49},
doi = {10.11648/j.ajrs.20190702.12},
url = {https://doi.org/10.11648/j.ajrs.20190702.12},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajrs.20190702.12},
abstract = {In many developing countries, some natural areas are faced with gaps in appropriate map coverage mainly on land use and land cover (LULC) changes. This situation makes it difficult to plan and implement natural environmental protection and natural resource management programs. Remote sensing and geographic information systems (GIS) are excellent tools for mapping LULC changes. This study investigated LULC changes in ‘Somone’ coastal lagoon in Senegal using multisource remote sensed data. Data sets included aerial photographs recorded in March 1954, and February 1978, as well as satellite images recorded in February 2003 and April 2016. All images were geometrically corrected and segmented. Photos and/or images interpretations were made with the aid of computer and post-classification change detection technique was applied to classify multisource data and to map changes. Stratified sampling was used to assess all classification results. The accuracies of image classifications averaged 65% (1954), 62% (1978), 79% (2003) and 88% (2016). The post-classification analysis resulted in the largest overall accuracy of 66, 72.7, 72.4 and 80.6% for the 1954–1978, 1978-2003 and 2003–2016 image pairs, respectively. Results indicated an increase in Settlements, from 0.29% in 1954 to 9.21% in 2016, the expansion of the Sabkha, from 5.29% in 1954 to 18.48% in 2016. The mangrove forest has experimented a reduction between 1954 and 1978 (from 4.07% to 0.56%) and a regeneration (linked to the protection and preservation policies within the protected area) from the year 2003 to 2016 (from 1.44% to 2.65%). However, the forest areas were greatly reduced (from 51.06% in 1954 to 10.86% in 2016) and replaced by Settlements (urbanization) as well as Croplands.},
year = {2019}
}
TY - JOUR T1 - Using Remote Sensing Technics for Land Use Land Cover Changes Analyses from 1950s to 2000s in Somone Tropical Coastal Lagoon, Senegal AU - Ndéye Yacine Barry AU - Mamadou Lamine Ndiaye AU - Celestin Hauhouot AU - Bienvenu Sambou Y1 - 2019/10/14 PY - 2019 N1 - https://doi.org/10.11648/j.ajrs.20190702.12 DO - 10.11648/j.ajrs.20190702.12 T2 - American Journal of Remote Sensing JF - American Journal of Remote Sensing JO - American Journal of Remote Sensing SP - 35 EP - 49 PB - Science Publishing Group SN - 2328-580X UR - https://doi.org/10.11648/j.ajrs.20190702.12 AB - In many developing countries, some natural areas are faced with gaps in appropriate map coverage mainly on land use and land cover (LULC) changes. This situation makes it difficult to plan and implement natural environmental protection and natural resource management programs. Remote sensing and geographic information systems (GIS) are excellent tools for mapping LULC changes. This study investigated LULC changes in ‘Somone’ coastal lagoon in Senegal using multisource remote sensed data. Data sets included aerial photographs recorded in March 1954, and February 1978, as well as satellite images recorded in February 2003 and April 2016. All images were geometrically corrected and segmented. Photos and/or images interpretations were made with the aid of computer and post-classification change detection technique was applied to classify multisource data and to map changes. Stratified sampling was used to assess all classification results. The accuracies of image classifications averaged 65% (1954), 62% (1978), 79% (2003) and 88% (2016). The post-classification analysis resulted in the largest overall accuracy of 66, 72.7, 72.4 and 80.6% for the 1954–1978, 1978-2003 and 2003–2016 image pairs, respectively. Results indicated an increase in Settlements, from 0.29% in 1954 to 9.21% in 2016, the expansion of the Sabkha, from 5.29% in 1954 to 18.48% in 2016. The mangrove forest has experimented a reduction between 1954 and 1978 (from 4.07% to 0.56%) and a regeneration (linked to the protection and preservation policies within the protected area) from the year 2003 to 2016 (from 1.44% to 2.65%). However, the forest areas were greatly reduced (from 51.06% in 1954 to 10.86% in 2016) and replaced by Settlements (urbanization) as well as Croplands. VL - 7 IS - 2 ER -
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