Forest Survey of India: success for
operational national forest monitoring
Devendra PANDEY
Fmr DG, Forest Survey of India
Email ID: [email protected]; [email protected]
Workshop on step-wise approaches for national forest
monitoring and REDD+ MRV capacity development Wageningen, Netherlands, 3-5 September 2012
GOFC-GOLD/ CIFOR
Phases of forest monitoring in India
Monitoring at management unit (forest division)
level through local forest inventory
Monitoring at national level
National forest inventory
Biennial forest cover mapping through
remote sensing
2
3
Forest inventory (FI) was introduced in 1856 in one division mainly of teak forests for the preparation of the “Working Plans”/management plan for systematic management of forests.
Until 1884 expansion to other divisions was limited due to lack of skilled human resource.
Gradual expansion of inventory took place particularly after 1919 when maps of forests areas on appropriate scale were made available by Survey of India.
Inventories at MU level is continuing even now because harvesting can’t be done without approved W. Plan as per regulations of Federal Government.
History of monitoring of forests at
management unit (MU) level in India
4
Forest inventories at MU level are limited to forests which are to be worked during next 10-15 years (not the entire area of MU) and are done in a different time frame.
Further, these inventories are not organized to generate estimates at state/national level for a given time frame.
There has been modifications in inventories after the introduction of GIS /RS in the recent decades and in many MUs inventories cover the entire forest area of MU with low intensity of sampling.
Application of modern tools and methodologies are, however, not uniform in all the States/MUs.
Monitoring of forests at management unit
level in India
5
Field inventory of unexplored forest areas started after
the launch of a FAO/UNDP/GOI project named as Pre-
Investment Survey of Forest Resources (PISFR) in 1965
which led the foundation of NFI
From 1965 to 1981
Forest Inventory was confined to project areas for
setting up wood based industries
Sampling design was adopted as per prevailing
condition of areas but were based on systematic
samplings. Aerial photographs were used for identifying
areas and preparing thematic maps
After the project period in 1972 the inventory continued
by catchment area and then switched to district level
National Forest Inventory (NFI)
6
Forest Survey of India was created in 1981 and NFI was
contemplated to be launched but in the absence of
adequate human resource it could not be done. The
focus also shifted over to monitoring of forest cover by
remote sensing technology in 1985.
As per the earlier practice forest inventory covered only
few selected districts each year due to limitation of
manpower.
About 3/4th of the country’s forests were inventoried in
20 years but no reliable estimate at national level of
growing stock could be generated.
National Forest Inventory
The NFI was finally launched by FSI in 2002 with the
existing human resource by modifying the inventory
approach and design followed until then.
The country has been stratified into 14 physiographic
zones- based on climate, vegetation, physiography
Ten percent (60) districts are selected and inventoried in
a two years period. India has about 600 civil districts.
The selection of districts is random from each
physiographic zone with probability proportion to size.
Along with the Forest inventory, vegetation survey of
herbs and shrubs is also carried out.
Measurement of soil and litter carbon is also carried.
Methodology of Growing Stock National Forest Inventory
7
Sample Plots In a District
Inventory of 179 districts
completed out of 612
Sample plots = 22,000
New Biomass Study
FSI launched a new biomass study in 2008 to measure
missing components of forest biomass (not measured by
NFI) as per REDD requirement and completed in 2009.
The study followed two approaches
(a) measure biomass of herb, shrub, climber, dead wood
and litter by laying out sample plots (about 100 plots in
each physiographic zone thus in all 1,400 sample plots)
(b) select 20 to 30 number of trees for each species in
different zones cut and measure their biomass to
generate biomass equations for:
i) Dbh of NFI trees Vs. biomass of branch wood & leaf for
trees above 10 cm dbh.
ii) dbh/collar dia Vs. total biomass of trees below 10 cm
dbh.
10
Outcome of New Biomass Study
National level C stock of forests giving values of different
C pools has been estimated
Based on the data collected in the new biomass study FSI
has developed new regression equations
about 200 new regressions equations for small sized trees/
seedlings for different species below 10 cm diameter
growing in to estimate their biomass
Similarly new equations have been developed to biomass of
branch wood and leaf of trees above 10 cm diameter
measured during regular NFI
11
12
A. Total above ground
Biomass
(Mn Tonnes)
4785
Carbon stock
( Mn Tonnes)
2173
B. Below ground (root) 1509 685
T1. Total live biomass (A+B) 6294 2859
C. Deadwood 31 14
D. Litter 385 162
T2. Total dead biomass (C+D) 461 176
E. Soil Organic Carbon - 4292
Grand total (T1+T2+E) 6709 7328
Carbon stock of India’s forests
After completion of biomass study a new dimension has
been added to the NFI since 2010.
Additional parameters needed to estimate the total
carbon stock of the forests are being measured in the
sample plots of NFI
The estimated cost of inventory and data processing of a
sample plot is about US$ 200.00 per plot of which about
US$110.00 is spent on travel to sample plot, field measurement
including checking by supervisors and the rest on field
preparation, equipment, designing, data entry, processing etc
Methodology of Growing Stock National Forest Inventory
13
Forest Survey of India (FSI) under the Federal Government (Ministry of Environment and Forests) is an organization fully dedicated to monitor the forest resource of the entire country regularly since 1981
Setup of Forest Survey of India (FSI)
North Zone
Shimla
East Zone
Kolkata
Central Zone
Nagpur
South Zone
Bangalore
Headquarters
DEHRADUN
Zonal Offices
16
North Zone
East Zone
Central Zone
South Zone
Existing Area of Operation under the Zonal Offices
Monitoring of Forest Cover by Remote Sensing Technology
Forest Survey of India is monitoring the forest cover of
the country since 1980s. The first report on forest cover
was published in 1987 where satellite imageries of
1983/85 were used.
Since then monitoring of forest cover done on a two year
cycle using wall-to-wall approach and published through
India’s State of Forest Report.
So far forest cover has been monitored 12 times, the last
was in 2011.
17
Monitoring of Forest Cover by Remote Sensing Technology
In the forest cover monitoring, forest are classified in three
categories
Very dense ( more than 70% density)
Moderately dense ( between 40 to 70% density)
Open ( between 10 to 40% density)
Less than 10% density is treated as scrub –non forests
( prior to 2001 there were only two classes dense (more than
40%) and open
Current minimum mapping unit is 1 ha maps on 1:50,000
scale and accuracy assessment with about 4000 sample
plots.
18
Technological developments in Forest Cover
Assessments by FSI over the years Cycle Year of Assessment Satellite & Sensor Resolution Scale
I
II
III
IV
V
VI
VII
VIII
1987
1989
1991
1993
1995
1997
1999
2001
LANDSAT MSS
LANDSAT TM
IRS-1B LISS-II
IRS-1C LISS-III
IRS-1C/1D LISS-III
80m x 80m 1:1million
30m x 30m
36m x 36m
23m x 23m
23m x 23m
1:250,000
1:50,000
IRS-1D, LISS-III 2003/2005 IX/X 23m x 23m 1:50,000
IRS-P6, LISS-III 2007/2009 XI/XII 23m x 23m 1:50,000
GEOMATICS LAB OF FSI at Dehradun
Forest Cover Map of India
FOREST COVER MAP OF INDIA
Very Dense Forest
Dense Forest
Open Forest
Scrub
Non Forest
Water Bodies
District Boundaries
Very Dense Forest
Dense Forest
Open Forest
Scrub
Non Forest
Water Bodies
District Boundaries
PAK
ISTA
N
NEPAL
CHINA
ARABIAN SEA
BAY OF BENGAL
BHUTAN
AFGANISTAN
AN
DA
MA
N &
NIC
OB
AR
ISL
AN
DS
(IND
IA)
BANGLADESH
LAKSHADWEEP
ISLANDS
Monitoring forest carbon stock
Estimation of above ground biomass
Woody biomass of living trees above ground
Biomass of non tree understory vegetation (herb,
shrub, climber)
Biomass of deadwood, woody debris and litter
Estimation of below ground biomass
Below ground biomass (root system)
Soil organic carbon
22
Schematic diagram of Estimation of Carbon stock change in India’s Forests
Step 1. Classify forest cover of the country into 3 canopy densities classes using satellite imagery
Step 2. Overlay the layer of forest types found in the country.
Step 11. Estimate the total biomass and soil carbon of each polygon in the grid, aggregate polygons to get grid carbon and then the total carbon stock of forests .
Step 9. Convert the total above ground biomass per ha into carbon for each stratum.
Step 12. Estimate CO2 emission/ removal by superimposing grids of one FC assessment over next.
Step 5. Attach each forested
polygon within grid with its
attributes density, forest
type, location, soil and
climatic details.
Step 10. Analyze and distribute soil carbon data of NFI into different strata (forest type & density) and estimate carbon per ha.
Step 8. Expand biomass further by adding biomass of Shrubs, herbs, climbers, dead wood and litter of each strata.
Step 4. Use country wide
spatial data base of about
60,000 grids each of size
2½’ x 2½’ in GIS with unique identification.
Step 6. Analyze the distribution of NFI samples into different strata (density & forest type) and estimate volume per ha.
Step 7. Expand volume (biomass) per ha by adding missing components of tree biomass.
Step 3. Identify and
determine the area of forest
cover under each stratum
(about 30) stratified by two
variables (type & density).
Operational success and limitations
Forest Survey of India is a dedicated institution for the
national assessment of forest resources of India with the
Federal Government.
FSI has tried to keep pace with the technological
advances and requirements of the new information.
India’s long experience of forest inventory has been
helpful in building robust forest inventory system with good
control on quality of data.
Comparing the volume work for a country like India, the
size of the institution is too small as results re-
measurement of permanent plots gets delayed to know
biomass change etc.
28
29
THANKS