FOREST COVER MAPPING AND GROWING STOCK ESTIMATION OF

INDIA’S FORESTS

GOFC-GOLD Workshop On Reducing Emissions from Deforestations 17-19 April

2007 in Santa Cruz, Bolivia

Devendra PANDEYForest Survey of India, Dehradun, INDIA

www.fsi.nic.in

Forests constitute a very important natural resource for India.

It is a major land-use and occupy about 23% land area of the country (77 mn ha) but the actual forest cover is only about 20.64% (67.8 mn ha)

India’s population being more than a 1 billion the per capita forests is too low (600 m2) against world’s average of 6000 m2

The pressure on forests is therefore high also because more than 70% India’s population has rural based economy

FOREST SURVEY OF INDIA, DEHRADUN

SATELLITE IMAGERY INTERPRETATION LAB

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-III2003IX 23m x 23m 1:50,000

Forest Cover Assessments Over The Years in India

AGENCIES USING R.S and GIS IN FORESTRY IN INDIA

Forest Survey of India (FSI)- main agency for wall to wall mapping for the entire country every 2 years

Some State Forest departments

NRSA and Regional Remote Sensing Centers and SAC of Deptt of Space

Private agencies

Forest Cover AssessmentForest Cover AssessmentINPUTSINPUTS

Satellite data of the entire country from National Remote SensinSatellite data of the entire country from National Remote Sensing g Agency (NRSA) IRS ID/IRSAgency (NRSA) IRS ID/IRS--P6 (23.5m spatial resolution)P6 (23.5m spatial resolution)SOI Topographic sheets SOI Topographic sheets -- 1: 50,0001: 50,000

METHODOLOGYMETHODOLOGYDigital Interpretation/visualDigital Interpretation/visualGround Verification Ground Verification Minimum map able area is I haMinimum map able area is I ha

OUTPUTSOUTPUTSForest cover maps on 1:50,000 scale in digital or hard copy forForest cover maps on 1:50,000 scale in digital or hard copy form m showing following forest cover classes:showing following forest cover classes:CATEGORYCATEGORY CANOPY DENSITYCANOPY DENSITYVery Dense Forest Very Dense Forest More than 70% canopy More than 70% canopy Moderately Dense ForestModerately Dense Forest 4040--70%70%Open ForestOpen Forest 1010--40%40%ScrubScrub Less than 10% in forest landsLess than 10% in forest landsMangrovesMangroves

SATELLITE DATA(IRS ID/IC- LISS III)

GEOMETRICCORRECTION

CONTRAST ENHANCEMENT

SOI TOPOSHEETS

SCENE SUBSETTING

MASKING FOREST &NON-FOREST AREAS

GROUND REFERENCE DATA

DENSITY SLICING

EDITING ACCURACY ASSESSMENT

OVERLAY OF BOUNDARIES

POST CLASSIFICATION

CORRECTION

LAND COVER MAP( STATE WISE)

UNSUPERVISEDCLASSIFICATION /NDVI TRANSFORMATION

FLOW CHART FOR FOREST COVER MAPPING

Forest Cover Assessment Forest Cover Assessment --20052005LATEST RESULTSLATEST RESULTSSatellite dataSatellite data––Resource satResource sat--1 (IRS P6) LISS1 (IRS P6) LISS--III III Data period Data period –– Nov/Dec 2004/ Feb 2005Nov/Dec 2004/ Feb 2005Loss of Forest cover Loss of Forest cover –– 728 Km2 728 Km2 Reasons of major lossesReasons of major losses

-- Tsunami (Dec 2004)Tsunami (Dec 2004)--Diversion of forests for Irrigation projectDiversion of forests for Irrigation project--dam dam and reservoirand reservoir--Removal of root stock for Removal of root stock for fuelwoodfuelwood and charcoaland charcoal-- Human induced Forest fireHuman induced Forest fire-- in the North Eastern in the North Eastern StatesStates-- slash and burn/ shifting cultivation slash and burn/ shifting cultivation practicepractice

IRS-P6 AWiFS DEC. 21, 2004 IRS-P6-AWiF FEB.16,2005

PRE-TSUNAMI POST-TSUNAMI

HIT BY TSUNAMI KATCHALL-ISLAND(Andaman & Nicobar Is)

Loss in Forest Cover- 2,589 ha (DF- 2567 ha, OF- 22 ha)

HIT BY TSUNAMI TRINKAT-ISLAND (Andaman & Nicobar)

PRE-TSUNAMI POST-TSUNAMI POST-TSUNAMI

IRS-P6-LISS III JAN.4, 05IRS-P6-AWiFS DEC.21, 04IRS-P6-AWiFS FEB.16, 04

Loss in Forest Cover- 287 ha (DF- 285 ha, OF- 2 ha

Accuracy assessment (Forest Cover)Accuracy assessment (Forest Cover)Accuracy assessment of forest cover is done by usingAccuracy assessment of forest cover is done by using

Field inventory data Field inventory data -- high resolution satellite data (5.8m)high resolution satellite data (5.8m)Out of the 8000 points inside forest, 3509 points were Out of the 8000 points inside forest, 3509 points were selected to provide spatial representation of the whole selected to provide spatial representation of the whole forest area for preparation of forest area for preparation of error matrix.error matrix.Ground truth data for these points giving land use class Ground truth data for these points giving land use class at each points were recorded with the help of field at each points were recorded with the help of field inventory data and high resolution satellite data in an inventory data and high resolution satellite data in an area of 1.0 ha. area of 1.0 ha. Over all accuracy level found is 92.03% in 2005 Over all accuracy level found is 92.03% in 2005 assessment.assessment.

Growing Stock estimationGrowing Stock estimation

Inventory of forestsInventory of forestsInventory of trees outside forests (TOF)Inventory of trees outside forests (TOF)--Inventory of trees in rural areas using high Inventory of trees in rural areas using high resolution satellite data (5.8 m) multiresolution satellite data (5.8 m) multi--spectralspectral--Inventory of trees in urban area Inventory of trees in urban area

The basic goal is to estimate a national level growing The basic goal is to estimate a national level growing stock (wood volume) on a two year cycle and improve stock (wood volume) on a two year cycle and improve the estimate in subsequent cycles. the estimate in subsequent cycles. For this purpose, the country has been stratified into 14 For this purpose, the country has been stratified into 14 physiographic zonesphysiographic zones-- based on climate, vegetation, based on climate, vegetation, physiographyphysiographyTen percent (60) districts are covered in a two year Ten percent (60) districts are covered in a two year cycle. India has about 600 civil districts.cycle. India has about 600 civil districts.The districts are selected randomly from each zone with The districts are selected randomly from each zone with probability proportion to size. probability proportion to size. Along with the Forest inventory, vegetation survey of Along with the Forest inventory, vegetation survey of herbs and shrubs is also carried out.herbs and shrubs is also carried out.Measurement of soil and litter carbon is also carried.Measurement of soil and litter carbon is also carried.

Methodology of NFI since 2001

Physiographic Zones of India

Physiographic Zones on Forest Cover

Randomly Selected 60 Sample Districts for Inventory

Topographic sheets on scale 1:50,000 (15'×15' Grid) divided into 5 '×5' Sub Grids

5’ X 5’ QUADRANT IS DIVIDED INTO FOUR GRIDS OF 2½’ X 2½’INTERVAL

EACH 2½’ X 2½’ GRID IS FURTHER DIVIDED INTO 1¼’X 1¼’ INTERVAL GRID

Marking of Plots

At grid centre a plot of 0.1 ha is laid out all At grid centre a plot of 0.1 ha is laid out all parameters preparameters pre--decided for forest inventory are decided for forest inventory are measured and recordedmeasured and recorded

Four sub plots of 1 sq. m are laid out at all corners of the sample plot of 0.1 ha to collect sample for litter and humus and soil carbon

Nested quadrates of 3x 3 m and 1x1 m for enumeration of shrubs and herbs are laid at 30 m distance from the center of 0.1 ha plot in all four corners to assess biodiversity.

On average 4000 temporary sample plots are laid out every year in forests.

Methodology of NFI since 2001

Parameters of Forest inventoryParameters of Forest inventory

Species and diameter class wise trees Species and diameter class wise trees Crown DiameterCrown DiameterSoil & leaf litter for estimation of carbonSoil & leaf litter for estimation of carbonListing Herbs & Shrubs for Biodiversity IndicesListing Herbs & Shrubs for Biodiversity IndicesRegeneration statusRegeneration statusFire incidenceFire incidenceGrazing incidenceGrazing incidencePresence of weedsPresence of weedsCrop injuryCrop injuryInformation on bambooInformation on bamboo

TOF resource has become most important in TOF resource has become most important in todaytoday’’s context in India as most of timber s context in India as most of timber requirement of industries have to met from TOFrequirement of industries have to met from TOFIn the present methodology, high resolution In the present methodology, high resolution satellite data (5.8 m) is used to identify TOF satellite data (5.8 m) is used to identify TOF patches and stratify the same into patches and stratify the same into

--block, block, --linear and linear and --scattered stratascattered strata

After the stratification appropriate sample plots After the stratification appropriate sample plots are laid on the ground for field inventory.are laid on the ground for field inventory.On average 4000 sample plots are laid every year.On average 4000 sample plots are laid every year.

Inventory of Trees Outside Forests (TOF)

BLOCK PLANTATION OF EUCALYPTUSBLOCK PLANTATION OF EUCALYPTUS24

TREES GROWING IN AGRICULTURAL TREES GROWING IN AGRICULTURAL FIELDSFIELDS

AILANTHUS EXCELSA & ACACIA AILANTHUS EXCELSA & ACACIA NILOTICA ON FARM BUNDSNILOTICA ON FARM BUNDS

29

Tamrind cultivated with Amla

METHODOLOGY FOR ASSESSMENT OF TREE OUTSIDE FOREST USING REMOTE S ENSING DATASatellite Data

LISS III Data PAN Data

Geometric and Radiometric Correction & fusion

Fused Data

India Map with District boundaries

District Boundary Toposheets

Mosaic

Digitization of Green wash

Green Wash Map

Masking out of Green Wash from Fused Data

Classification of fused data without Green wash

Classified MapBlock

Scattered

Linear

Generation of Random PointsField data collection

Data Analysis & Report Generation

Green wash

Block

Linear

Scattered

Trees in Group Scattered Water Bodies

BlockLinear Elimination of area < 0.1 ha.

StrataStrata Plot sizePlot size No. of SamplesNo. of SamplesBlockBlock 0.1 ha0.1 ha 3535LinearLinear 10x125 m10x125 m 5050ScatteredScattered 3.0 ha3.0 ha 5050Scattered (Hill)Scattered (Hill) 0.5 ha0.5 ha 9595

-- Random points Random points for block, linear & scattered for block, linear & scattered stratum along with coordinates communicated stratum along with coordinates communicated to to field units for surveyfield units for survey

-- Sample points in field are approached by using Sample points in field are approached by using GPS & data recorded in prescribed formatsGPS & data recorded in prescribed formats

Plot Size & Number of Samples in rural TOF per district

UFS Block Map

UFS Block – Block No 8

Field Inventory of Urban TOFField Inventory of Urban TOF

Urban trees have mainly environmental functionsUrban trees have mainly environmental functions--

In India urban areas are categorized into 5 classes In India urban areas are categorized into 5 classes (strata) based on population(strata) based on populationUrban Frame Survey (USF) blocks of National Sample Urban Frame Survey (USF) blocks of National Sample Survey Organization (NSSO) are taken as sampling Survey Organization (NSSO) are taken as sampling units by FSIunits by FSIOptimum number of UFS blocks are selected in each Optimum number of UFS blocks are selected in each district for the survey as followsdistrict for the survey as followsIfIf UFS blocks < 500 UFS blocks < 500 10 % selection10 % selection

min 20 blocksmin 20 blocksUFS blocks > 500 UFS blocks > 500 5 % selection5 % selection

min 50 or max 60 blocksmin 50 or max 60 blocksData is collected on the designed formats on various Data is collected on the designed formats on various parametersparameters

CLASSIFIED MAPCLASSIFIED MAP-- Trees outside ForestsTrees outside Forests

BLOCK

LINEAR

SCATTERED

Overall accuracy of classification = 92%

CONCLUDING REMARKS

There exists many gaps in the methodology aspect of inventory of forests and TOF as well as forest cover assessment.

One important challenge is to integrate RS data with field inventory so that reliable estimate on wood volume/ biomass/ carbon stock can be made rapidly.

Capacity building and continuous skill up-gradation to adopt new methods and technology.

THANKS