Abstract
This paper is aimed at introducing a new approach to estimate the density of Brown Plant Hoppers (BPHs) at provincial scale. The model is based on the topology of a light-traps network (to gather the information about the BPHs) of a province. The BPHs density is determined based on Unit Disk Graph technique where each light-trap becomes a vertex and the edges reflect the relations on the mutual transfer of BPHs between light-traps. The model uses the historical light-traps data as the input to estimate the density of unknown location via an influence function. The experimental results of the model are performed in a typical province of the Mekong Delta region, namely Dong Thap province of Vietnam.
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References
Köhl, M., Magnussen, S., Marchett, M.: Sampling Methods, Remote Sensing and GIS Multiresource Forest Inventory, pp. 80–120. Springer, Heidelberg (2006) ISBN: 3-540-32571-9
Treuil, J.-P., Drogoul, A., Zucker, J.-D.: Modélisation et Simulation à base d’Agents. Dunod Editions, 1–13 (2008) ISBN: 978-2-10-050216-5
Kozak, M., Wieczorlowski, R.: ΠPS sampling versus stratified sampling - Comparison of effeciency in agricultural surveys. Statistics in transaction 7(1), 5–12 (2005)
Trumper, E.V., Garat, O.: Population density sampling and dispersion pattern of Delphacodes kuscheli Fennah (Homoptera: Delphacidae) in oat crops: Asociación Argentina de EcologÃa. Ecologia Austral 11, 123–130 (2001)
Bellido, J. M., Bellido, J. M., Pérez, N.: A new optimal allocation sampling design to improve estimates and precision levels of discards from two different Fishery Units of Spanish trawlers in northeast Atlantic waters (ICES subareas VIIc,j,k): Instituto Español de OceanografÃa, BoletÃn. Instituto Español de OceanografÃa, Vol. 23, pp. 73-83.(2007); ISSN: 0074-0195
Talvitie, M., Leino, O., Holopainen, M.: Inventory of Sparse Forest Populations Using Adaptive Cluster Sampling. The Finnish Society of Forest Science, The Finnish Forest Research Institute, Silva Fennica, Vol. 40 (1), pp. 101-108, (2006) ISSN: 0037-5330
Spalding, A.: Light trap transects – a field method for ascertaining the habitat preferences of night-flying Lepidoptera, using Mythimna turca (Linnaeus 1761) (Lepidoptera: Noctuidae) as an example. Journal of Insect Conservation 8, 185–190 (2004)
Schmera, D.: Assessing stream dwelling caddisfly assemblages (Insecta: Trichoptera) collected by light traps in Hungary. Biodiversity and Conservation 12, 1175–1191 (2003)
Kato, M., et al.: Various population fluctuation patterns of light-attracted beetles in a tropical lowland dipterocarp forest in Sarawak. In: The Society of Population Ecology, vol. 42, pp. 97–104. Springer, Tokyo (2000)
Hastings, A.: The spatial spread of invasions: new developments in theory and evidence. In: Ecology Letters, vol. 8, pp. 91–101. Blackwell Publishing Ltd./CNRS (2005); doi: 10.1111/j.1461-0248.2004.00687.x
Brännström, Å., Sumpter, D.J.T.: Coupled map lattice approximations for spatially explicit individual-based models of ecology. Bulletin of Mathematical Biology 67, 663–682 (2005); DOI:10.1016/j.bulm.2004.09.006
Otuka, A., et al. (eds.): A migration analysis of the rice planthopper Nilaparvata lugens from the Philippines to East Asia with three-dimensional computer simulations.The Society of Population Ecology (2005); doi:10.1007/s10144-005-0216-1
Otuka, A.: Migration of rice planthoppers and simulation techniques. In: Heong, K.L., Hardy, B. (eds.) Planthoppers: new threats to the sustainability of intensive rice production systems in Asia, pp. 343–356. International Rice Research Institute, Los Baños (2009)
Phan, H.C., Huynh, X.H., Drogoul, A.: An agent-based aproach to the simulation of Brown Plant Hopper (BPH) invasion in the Mekong Delta. In: 2010 IEEE-RIVF International Conference on Computing and Communication Technologies, Hanoi, Vietnam (2010); doi:10.1109/RIVF.2010.5633134
Brent, N.C., Charles, J.C., David, S.J.: Unit Disk Graph. Discrete Mathematics 86, 165–177 (1990)
Thai, M.T., et al.: On approximation algorithms of k-connected m-dominating sets in disk graphs. Theoretical Computer Science 385, 49–59 (2007)
Wu, W., et al.: Minimum connected dominating sets and maximal independent sets in unit disk graphs. Theoretical Computer Science 352, 1–7 (2006)
Marathe, M.V., Breu, H., Hunt, H.B.: Simple Heuristics for Unit Disk Graphs. Networks 25(2), 59–68 (1995); doi:10.1002/net.3230250205
Nguyen, N.D., et al.: Inferring equation-based models from individual-based models. In: PRIMA 2010 Conference, pp. 183–190 (2010)
Muhammad, J.S., Matt, D.: Effect of Neighborhood on In-Network Processing in Sensor Networks. In: Cova, T.J., Miller, H.J., Beard, K., Frank, A.U., Goodchild, M.F. (eds.) GIScience 2008. LNCS, vol. 5266, pp. 133–150. Springer, Heidelberg (2008)
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Truong, V.X., Huynh, H.X., Le, M.N., Drogoul, A. (2011). Estimating the Density of Brown Plant Hoppers from a Light-Traps Network Based on Unit Disk Graph. In: Zhong, N., Callaghan, V., Ghorbani, A.A., Hu, B. (eds) Active Media Technology. AMT 2011. Lecture Notes in Computer Science, vol 6890. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23620-4_30
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DOI: https://doi.org/10.1007/978-3-642-23620-4_30
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