Blog List

Thursday, 24 November 2016

Empowering fall webworm surveillance with mobile phone-based community monitoring: a case study in northern China

Published Date
Volume 27, Issue 6pp 1407–1414

Original Paper
DOI: 10.1007/s11676-016-0230-5

Cite this article as: 
Wang, C., Qiao, Y., Wu, H. et al. J. For. Res. (2016) 27: 1407. doi:10.1007/s11676-016-0230-5


Recent advances in information and communication technologies, such as mobile Internet and smartphones, have created new paradigms for participatory environment monitoring. The ubiquitous mobile phones with capabilities such as a global positioning system, camera, and network access, offer opportunities to establish distributed monitoring networks that can perform a wide range of measurements for a landscape. This study examined the potential of mobile phone-based community monitoring of fall webworm (Hyphantria cuneaDrury). We built a prototype of a participatory fall webworm monitoring system based on mobile devices that streamlined data collection, transmission, and visualization. We also assessed the accuracy and reliability of the data collected by the local community. The system performance was evaluated at the Ziya commune of Tianjin municipality in northern China, where fall webworm infestation has occurred. The local community provided data with accuracy comparable to expert measurements (Willmott’s index of agreement >0.85). Measurements by the local community effectively complemented remote sensing images in both temporal and spatial resolution.


  1. Danielsen F, Skutsch M, Burgess ND, Jensen PM, Andrianandrasana H, Karky B, Lewis R, Lovett JC, Massao J, Ngaga Y (2011) At the heart of REDD+: a role for local people in monitoring forests? Conserv Lett 4(2):158–167CrossRefGoogle Scholar
  2. Evans K, Guariguata MR (2008) Participatory monitoring in tropical forest management: a review of tools, concepts and lessons learned. Center for International Forestry Research (CIFOR), Bogor, Indonesia
  3. Ferster CJ, Coops NC (2013) A review of earth observation using mobile personal communication devices. Comput Geosci 51:339–349CrossRefGoogle Scholar
  4. Itô Y, Miyashita K (1968) Biology ofHyphantria cunea Drury (Lepidoptera: Arctiidae) in Japan. V. Preliminary life tables and mortality data in urban areas. Res Popul Ecol 10(2):177–209CrossRefGoogle Scholar
  5. Kanhere S (2013) Participatory sensing: crowdsourcing data from mobile smartphones in urban spaces. In: Hota C, Srimani P (eds) Distributed computing and internet technology, vol 7753. Springer, Berlin, pp 19–26CrossRefGoogle Scholar
  6. Kelly NM, Tuxen K (2003) WebGIS for monitoring “Sudden Oak Death” in coastal California. Comput Environ Urban Syst 27(5):527–547CrossRefGoogle Scholar
  7. Kennedy R, Mcleman R, Sawada M, Smigielski J (2014) Use of smartphone technology for small-scale silviculture: a test of low-cost technology in Eastern Ontario. Small-scale For 13(1):101–115CrossRefGoogle Scholar
  8. Larrazabal A, Mccall MK, Mwampamba TH, Skutsch M (2012) The role of community carbon monitoring for REDD+: a review of experiences. Curr Opin Environ Sustain 4(6):707–716CrossRefGoogle Scholar
  9. Li SM, Saborowski J, Nieschulze J, Li ZY, Lu YC, Chen EX (2007) Web service based spatial forest information system using an open source software approach. J For Res 18(2):85–90CrossRefGoogle Scholar
  10. Sader SA, Ross K, Reed FC (2002) Pingree forest partnership: monitoring easements at the landscape level. J For 100(3):20–25Google Scholar
  11. Stuart-Hill G, Diggle R, Munali B, Tagg J, Ward D (2005) The event book system: a community-based natural resource monitoring system from Namibia. Biodivers Conserv 14(11):2611–2631CrossRefGoogle Scholar
  12. Su MW, Fang YL, Tao WQ, Yan GZ, Ma W, Zhang ZN (2008) Identification and field evaluation of the sex pheromone of an invasive pest, the fall webworm Hyphantria cunea in China. Chin Sci Bull 53(4):555–560CrossRefGoogle Scholar
  13. Whitelaw G, Vaughan H, Craig B, Atkinson D (2003) Establishing the Canadian community monitoring network. Environ Monit Assess 88(1–3):409–418CrossRefPubMedGoogle Scholar
  14. Willmott CJ (1981) On the validation of models. Phys Geogr 2(2):184–194Google Scholar
  15. Yang ZQ, Wei JR, Wang XY (2006) Mass rearing and augmentative releases of the native parasitoid Chouioia cunea for biological control of the introduced fall webworm Hyphantria cunea in China. Biocontrol 51(4):401–418CrossRefGoogle Scholar

For further details log on website :

No comments:

Post a Comment

The Future of Smart City Technology, From an MIT Professor

Carlo Ratti’s The City of Tomorrow examines how tech will shift and reshape the urban landscape Author By  Patrick Sisson Screenshot...