Download - FRA Nepal

one can measure the whole cluster (6 points) in two working days. It can be assumed that from one camp you can fairly easily
reach several clusters in the Terai area, where the network of roads and trails is relatively dense.
Since field observations are expensive, they must be concentrated on the most forested areas. Such concentration can be
achieved by two different means. Firstly, different 2 nd phase sampling intensity will be applied for each of the 5
physiographical zones of Nepal. Secondly, within each zone, the 2 nd phase sample will be selected according to the number
of wooded sample points in the cluster (wooded=forest or other land with tree cover and accessible). The 2 nd phase sample
could consist e.g. of every 4 th of the clusters with 5 or 6 wooded points; every 6 th of the clusters with 3 or 4 wooded points;
every 8 th of the clusters with 2 wooded points; every 10 th of the clusters with one wooded point; and a very small fraction of
clusters with 0 wooded points. These percentages are to be changed after checking the 1 st phase sample and distribution of
clusters by number of wooded sample points. The idea is to select such percentages that clusters with several points in forest
or other land with tree cover are more frequent in the 2 nd phase sample than the less wooded clusters.
The described design can be used in a flexible way together with various remote sensing techniques and materials depending
on the information needs in each geo-physiographical region and applicability of remote sensing tools as indicated in Table
2. In the previous inventory an aerial photo interpretation grid of 4 km x 4 km was used in the hilly area in addition to the 12
km x 12 km field sample grid. Apart from forests, the survey should this time cover other vegetation classes as defined in
Table 3, as well as other land-use classes, e.g. national parks, wildlife reserves and other conservation areas.
The FRA data can in most favorable cases provide a basis (baseline data) for further, more intensive forest inventories for
management or other special purposes. With this design, it is possible to calculate the results for sub-units. The results by
development regions (5 sub-units), by geo-physiographical zones (5 sub-units) and by federal states (6 to 14 sub-units) can
still be regarded to be fairly accurate. The results for individual districts (75 sub-units) are not statistically reliable and they
are subject to high errors due to the low number of field samples.
3 Application of LiDAR for the LiDAR Working area
Depending on the decisions to use LiDAR laser scanning either by strip scanning or wall-to-wall scanning the required
supporting materials are investigated and acquired for the LiDAR Working Area (one of earlier selected stratum). The
LiDAR strips or the full-cover LiDAR data are classified using measured 2 nd phase field plots and additional field plots.
Through the LiDAR data processing, analysis and applications the LiDAR data will be generalized for the entire working
area (e.g. biomass estimates for all forested areas).
The preliminary plan could be to find LiDAR partners from Nepal to have bigger areas laser scanned. One proposal is that
the two southern physiographical zones (i.e. Churia Area in Terai and Siwaliks), around 40.000 km2, could be laser scanned
to obtain the LiDAR data.
4 Trees outside forests and shrub land
Trees outside forests (TOFs) make a remarkable resource of fodder, fuel wood, timber, fruits, etc. for people in the
countryside. These trees occur as tree rows along roads, between agricultural fields, at the edges of terraces and as scattered
trees on shrub land and grassland. All tree groups below the minimum size of forest definition belong to this group.
Traditionally, these wood resources have not been included in forest inventories in Nepal. However, in recent years some
pilot inventories of TOFs have been done in Nepal (e.g. Morang and Dhanusa districts, 2007; Nawalparasi district, 2008) and
valuable experience compiled. It should also be noticed that in India continuous inventory of TOFs has been carried out since
1991. In Bangladesh the TOFs are being continuously surveyed by using integrated approaches.
Shrub land covers considerable part of Nepal, especially, in the hills. The area of shrub has increased as indicated by
successive forest inventories. This suggests that a remarkable proportion of the present shrub area is in fact degraded forest
land. Shrub lands, which are actually degraded forests, are probably located closer to the inhabitation and these areas are
easier to access. The areas, which are shrub due to the physiological conditions (poor soil fertility, low precipitation, high
altitude, low temperature, etc.) are obviously more remote ones and to a great degree inaccessible. Shrub in general may have
as significant value to the local people as forests providing them with pasture land, fuel wood, fodder and cattle bedding.
Shrub land has in many cases high potential for enhanced production of woody biomass and development into high forest.
The assessment of TOFs and shrub can be done using two phase sampling with very high resolution remote sensing material
such as ALOS/Prism, IKONOS/Geo, RapidEye, GeoEye, IRS, Quick Bird or Kompsat, aerial photos in the scale of 1:50,000
or higher or airborne laser scanning (LiDAR) and field sampling. The key question is the availability of suitable remote
sensing material, its quality and sufficient funding to acquire such materials or to apply LiDAR Technology.
55