Presentation on theme: "Application of Remote Sensing in studying forest cover conditions of protected areas in Himachal Pradesh, India Vandana Kumari Chauhan & Ruchika Acharya."— Presentation transcript:
Application of Remote Sensing in studying forest cover conditions of protected areas in Himachal Pradesh, India Vandana Kumari Chauhan & Ruchika Acharya Project Assistants Biodiversity Division Palampur- 176 061 (H.P.) India Website: http://www.ihbt.res.in EPABX: 91-233338-39, 230742-43, 230431 FAX: 91-1894-230433/230428
FOREST COVER ??? “An area more than 1 hectare in extent and having tree canopy density of 10% and above” IMPORTANCE is one of many factors which affect climate at the global level as well as regionally and locally. is important element in the global cycling of carbon, oxygen, and other gases of importance which influences the composition of the earth’s atmosphere. is source of wood, timber, forage, edible products including fruit, honey, mushrooms, fungi, meat (from wildlife) and medicinal & aromatic plants. provide habitat for wildlife have been a source of inspiration for people who have often identified forests, forest groves or even individual trees as sacred places or objects.
“A clearly defined geographical space, recognized, dedicated and managed, through legal or other effective means, to achieve the long-term conservation of nature with associated ecosystem services and cultural values” (Dudley, 2008) IMPORTANCE in supporting species to adapt to changing climate patterns and sudden climate events by providing refuges and migration corridors. in protecting people from sudden climatic events and reducing vulnerability to floods, droughts and other weather- induced problems; PROTECTED AREA Forest cover assessment in protected area, which is devoid of anthropogenic interferences provides real time information on forest conditions prevailing on the ground.
Great Himalayan National Park (GHNP) Conservation Area, Kullu, Himachal Pradesh, India STUDY AREA Geographical extent: 31° 33' -31°56'" N to 77°17'- 77°52'E Geographical area: 1171 km 2 Altitude: 1334 to 6194 m amsl Drained by Jiwa, Sainj, Tirthan and Parvati rivers. Subdivisions Core area (754.40 km 2 ) Sainj Wildlife Sanctuary (90 km 2 ) Tirthan Wildlife Sanctuary (61 km 2 ) Ecozone (265.60 km 2 ).
Preparation of forest cover map using Satellite remote sensing. Calculation of forest cover density. Calculations of altitudinal variations in forest cover density. Verification of forest density with NDVI results. OBJECTIVES
Scanned map of GHNP SCANNING, GEO-REFERENCING AND DIGITIZATION OF STUDY AREA MAPS Hard copy maps of the study area were scanned to image files (digital raster format) using SLC 1036C Widecom single line contact scanner. Scanned maps were Geo-referenced using latitudinal (x) and longitudinal (y) information provided on the maps. Digitization of the boundaries were performed on Geo- referenced map in ArcView 3.3. Geo-referenced & Digitized map of GHNP Methodology
PREPARATION OF ELEVATION MAP CARTOSAT (30m) Digital Elevation Model (DEM) from National Remote Sensing Centre (NRSC) was used for the preparation of Elevation map of study area. DEM of the study area was clipped using Area of Interest (AOI) of GHNP boundary. Clipped DEM was converted into ESRI grid format and elevation map was prepared by categorizing DEM in to various altitudinal zones like Alpine (>3600m), Sub-alpine (3300- 3600m), Upper temperate (2800-3300 m) and Mid temperate (<2800 m). CARTOSAT (30 m) DEM of GHNP DEM converted into ESRI GRID Different Altitudinal Zones of GHNP Methodology
LANDUSE/ LANDCOVER CLASSIFICATION LANDSAT TM satellite image of study area was classified into two broad classes i.e. forest area and non forest area using Hybrid (supervised and unsupervised) classification technique. LANDSAT IMAGE CLASSIFIED IMAGE Methodology
CALCULATION OF FOREST COVER DENSITY Methodology Forest cover density (%) = (Forest cover area / Total land area)*100 GHNP GHNP Sub-divisions Forest area Altitudinal zones 1 km X 1 km mesh
CATEGORIZATION OF GHNP FOREST AREA 1Km x 1km Mesh 1 km Methodology The forest cover densities were grouped into four different classes Scrub (<10%), Open forest (10–40 %), Moderate dense forest (40–70 %) Very dense forest (> 70 %) based on the criteria followed by Forest Survey of India
Calculation ofNormalized Difference Vegetation Index (NDVI) Calculation of Normalized Difference Vegetation Index (NDVI) NDVI was calculated from LANDSAT TM image using: IR-R/IR+R Methodology Correlation between Forest cover density and NDVI The forest cover density was significantly correlated with NDVI (γ=0.93). It was also observed that the NDVI in various altitudinal regions increased with forest cover density and decreased with decrease in the forest cover density.
The result of this study revealed that the forest cover density of GHNP was 31.94 %. Overall, more than 50 % of the forest in GHNP was categorized as Very dense forest owing to canopy cover >70 %. Forest cover density of GHNP RESULTS
The Core area had lowest forest cover density (15.73 %) because most of its area is occupied by alpine zone. Highest forest cover density was observed in Eco Zone (72.18 %). The Tirthan wildlife sanctuary and Sainj wildlife sanctuary had 56.13 % and 40.5 % area under forest cover, respectively. Altitude wise, the forest cover density was observed highest in upper temperate region (90 %) followed by mid-temperate region (73.34 %), sub-alpine region (52.78 %) and alpine region (0.26 %) respectively. Results The study concluded in GHNP highest forest cover density conditions prevails in upper and mid temperate regions, which is an indication of healthy forest conditions in the study area
A network of Permanent Monitoring Plots (PMPs) have been marked in various altitudinal zones of GHNP as well as some other areas for Long Term Ecological Research (LTER). PERSUING PROGRAMMES Recording of data on the Biotic, Environmental and Ecological aspects of forest is being done from the LTER for studying the impact of global warming on the forest health. Change Detection studies using Temporal satellite Images.
Miss Vandana Kumari Chauhan, Project Assistant CSIR-Institute of Himalayan Bioresource Technology Council of Scientific and Industrial Research (CSIR) Palampur, Himachal Pradesh – 176 061, India E-mail: firstname.lastname@example.org Miss Ruchika Acharya, Project Assistant CSIR-Institute of Himalayan Bioresource Technology Council of Scientific and Industrial Research (CSIR) Palampur, Himachal Pradesh – 176 061, India E-mail: email@example.com Mr. Amit Kumar, Scientist CSIR-Institute of Himalayan Bioresource Technology Council of Scientific and Industrial Research (CSIR) Palampur, Himachal Pradesh – 176 061, India E-mail: firstname.lastname@example.org Dr. R.D. Singh, Head of Department CSIR-Institute of Himalayan Bioresource Technology Council of Scientific and Industrial Research (CSIR) Palampur, Himachal Pradesh – 176 061, India E-mail: email@example.com Team Members Acknowledgements Council of Scientific and Industrial Research (CSIR) is acknowledged for financial grant to “exploratory studies on climate change and adaptation of species complexes (NWP-0020)”.