Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-8, 1295-1300, 2014
https://doi.org/10.5194/isprsarchives-XL-8-1295-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
28 Nov 2014
Monitoring the performance of community forestry to achieve REDD+ goals through geospatial methods
H. Gilani1, S. Krishna Gautam2, M. S. R. Murthy1, U. A. Koju1, K. Uddin1, and B. Karky1 1International Centre for Integrated Mountain Development, Kathmandu, Nepal
2Department of Forest Research and Survey, Nepal
Keywords: MRV, REDD+, community forests, linear regress model and biomass change Abstract. Measurement, reporting and verification (MRV) is included in the Cancun, Mexico, in 2010 under climate change agreements, as one of the most critical elements necessary for the successful implementation of any reducing of emissions from deforestation and forest degradation and the role of conservation, sustainable management of forests and enhancement of forest carbon stocks in developing countries (REDD+) mechanism. Community forestry is recognised as a successful model for conserving forests, raising awareness among local people and decentralising the forest governance practices. In the world, Nepal is considered as a leader in community-based forest management. This study conducted in 16 community forests (2384.76 ha) of Kayar Khola watershed (8002 ha) of Chitwan district, Nepal.

In this paper, satellite images IKONOS-2 (2002) and GeoEye-1 (2009 & 2012) were used which have 1 m and 0.5 m ground spatial distance (GSD) respectively. Geographic information system (GIS) participatory approach was embraced for the boundaries delineation of community forests. Geographic object-based image analysis (GEOBIA) classification technique was performed and overall accuracy 94 % with 92.91 % producer’s and 96.2 % user's accuracies. Through change matrix method, 25.49 ha and 1.08 ha area deforested while 179.84 ha and 33.24 ha reforested in two time periods 2002–2009 and 2009–2012 respectively. Overall within 16 community forests, “Close broadleaved to Open broadleaved” 4.42 ha and 4 ha area is transferred between 2002–2009 and 2009–2012 respectively. While "Open broadleaved to Close broadleaved" 29.25 ha and 31.1 ha area is converted in seven years (2002–2009) and in three years (2009–2012) respectively. Coefficient of determination (R2) 0.833 achieved through a line-intercept transect between number of segmented and observed tree crowns. Maximum numbers of the counted trees exist below 20 m2, which show the forest of the study area is not mature and has capacity to sequestrate more and more carbon in coming years. A linear regress model obtained (AGB = 0.0543*CPA – 62.078 with R2 = 0.76) by plotting the delineated crowns from satellite image and field based biomass values at 1ha grid. The present study was conducted in order to analyse, the performance of community forestry to achieve REDD+ goals by considering a sample of pilot project site in Nepal.

Conference paper (PDF, 906 KB)


Citation: Gilani, H., Krishna Gautam, S., Murthy, M. S. R., Koju, U. A., Uddin, K., and Karky, B.: Monitoring the performance of community forestry to achieve REDD+ goals through geospatial methods, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-8, 1295-1300, https://doi.org/10.5194/isprsarchives-XL-8-1295-2014, 2014.

BibTeX EndNote Reference Manager XML