Environmental Impact Assessment Land Use and Land Cover CISMHE 7.1 INTRODUCTION

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7 LAND USE AND LAND COVER 7.1 INTRODUCTION The knowledge of land use and land cover is important for many planning and management activities as it is considered an essential element for modeling and understanding the earth system. The term land use relates to the human activity or economic function associated with a specific piece of land, while the term land cover relates to the type of feature present on the surface of the earth (Lillesand and Kiefer, 2000). Land cover maps are presently being developed from local to national to global scales. The use of panchromatic and medium scale aerial photographs to map land use has been an accepted practice since the 1940s. More recently, small scale aerial photographs and satellite images have been utilized for land use and land cover mapping. The satellite remote sensing technology has found its acceptance worldwide for rapid resource assessment and monitoring, particularly in the developing world. National Aeronautical and Space Administration (NASA) of USA has made most significant contributions with satellite based remote sensing techniques. Since 1972, after the Landsat-1 was launched, remote sensing technology and its application has undergone a tremendous change in terms of sensing development, aerial flights with improved sensors, satellite design development and operations including data reception, processing, interpretation, and utilization of satellite images. All these advancement have widened the applicability of remotely sensed data in various areas, like forest cover, vegetation type mapping, and their changes on a regional scale. If satellite data is judiciously used along with the sufficient ground data, it is possible to carry out detailed forest inventories, monitoring of land use, and vegetation cover at various scales. The present work is an attempt of the same in Lower Siang H.E. Project area. Lower Siang H.E. Project 7-1

7.2 OBJECTIVE The objective of the present work is to produce land use and land cover map using hybrid digital classification technique. Also, to produce land cover data set appropriate for wide variety of applications like Catchment Area Treatment (CAT) planning. 7.3 DATABASE The details of primary data in the form of digital data on CDROMs for interpretation and analysis are given in Table 7.1. The mask of the entire Siang catchment area including the project site was generated from the IRS-P6 data. Table 7.1 Database used for land use and land cover mapping of the Siang catchment Satellite Sensor Path/Row Date Data type & Bands IRS P6 LISS-IV 112/51 05-12-2006 Digital (1,2,3,4) IRS P6 LISS-IV 113/51 15-12-2006 Digital (1,2,3,4) LANDSAT 7 ETM+ 135/40 15-11-2001 Digital (1,2,3,4,5,7) LANDSAT 7 PAN 135/40 15-11-2001 Digital (8) Survey of India (SOI) toposheets Nos.78M/7, 82H/15, 82L/2, 82L/3, 82L/5, 82L/6, 82L/7, 82L/9, 82L/10, 82L/11, 82L/12, 82L/13, 82L/14, 82L/15, 82L/16, 82P/2, 82P/3, 82P/4, 82P/5, 82P/6, 82P/7, 82P/8, and 82P/12 on 1:50,000 scale were used for the preparation of base and drainage maps. 7.4 METHODOLOGY Land use and land cover mapping of the Lower Siang H.E. Project in East Siang district of Arunachal Pradesh was carried out by following standard methods of analysis of remotely sensed data, like digital image processing (DIP) supported by ground truth collection. For this purpose digital data on CDROMs was procured from National Remote Sensing Agency (NRSA), Hyderabad. DIP of the satellite data, preparation of various thematic maps, and their interpretation were achieved at Computer GIS Lab, using Erdas Imagine 9.0 of Leica Geosystems. Lower Siang H.E. Project 7-2

Before digitally processing of any image for image enhancement, transformation or classification, pre-processing was done for band separation. Different bands were downloaded into the workstation using Erdas Imagine 9.0. The images were checked for occasional shortcomings in the quality of radiometric and line dropouts. Band separation and windowing of the study area with the help of Survey of India (SOI) toposheets was performed. The registration of image was performed using the nearest neighbor resampling algorithm (Jensen, 1996). The scene was geometrically corrected with toposheets using proper identification of GCPs with a root-mean-square (RMS) error of 0.0002 to 0.003 pixels. Indian Remote Sensing data was radiometrically corrected using dark pixel subtraction technique. They were then co-registered with SOI toposheets using UTM Zone 44 N WGS84 projection systems. Geo-referencing of the composite image was done using digital vector layer of drainage, road network, water bodies, and other permanent ground features extracted from SOI toposheets. Distinguishable Ground Control Points (GCPs) both on image and vector database were identified. By using these GCPs the image was resample and geo-coded. Sub-pixel image to map registration accuracy was achieved through repeated attempts. The image enhancement techniques like edge detection, filters, manipulation of contrast and brightness, histogram equalization etc. was performed by using different combinations for best image contrast. Standard false colour composite (FCC) image of the catchment area was prepared using bands 2, 3 and 4 of IRS-P6 and discrimination of features was made by visual interpretation on this image. The interpretation key was based on the relationships between ground features and image elements like texture, tone, shape, location, and pattern. In order to provide higher resolution of base image (IRS-P6 LISS III), panchromatic (PAN) image was fused with MSS LISS III image. In this process, a portion of high resolution PAN band, which corresponds to an area of interest (AOI) in the multi-spectral LISS III image was extracted. Thereafter, both the images were co-registered and LISS-III image was resampled for merging with PAN image. Merging or image fusion was done by special enhancement module in Erdas Imagine 9.0. The digital vector layers like contour, drainage network, snow, glacier, forest, settlements etc. of the Lower Siang H.E. Project site were prepared from the SOI toposheets in 1:50,000 scale. The vector layers were also prepared for nearby free-draining catchment areas. Further, the drainage Lower Siang H.E. Project 7-3

network was classified into various sub-watersheds. Major morphomotric parameters like drainage length, density, area etc. were calculated in each sub-watershed for determining basin characters. In the preliminary analysis, image classification was done by unsupervised classification method by performing ISODATA training. It helped in assigning the classification of the image into land use categories. However, the boundaries of water bodies were separately mapped from SOI toposheets for image classification. The doubtful areas or wrongfully interpreted areas owing to various physical features controlling the study area were marked for ground truth collection. After ground truth collection, supervised classification was assigned for the final image classification. The classified map was regrouped and merged. The classified raster map thus, prepared was then converted to vector format for GIS analysis and the preparation of required thematic maps using ArcGIS 9.1 and GeoMedia Professional 5.2. 7.5 FOREST COVER OF ARUNACHAL PRADESH INCLUDING EAST SIANG DISTRICT The land use and land cover of Arunachal Pradesh include forest areas, areas under agriculture and human settlements, snow covered areas, lakes and water bodies, large sand bodies along the wide river channels, mountain slopes under shifting/jhum cultivation, and areas affected by old and active landslides (Table 7.2). Based on satellite data of November-December, 2004 and February, 2005, 80.93% of the total geographic area of Arunachal Pradesh is covered by forest, out of which very dense forest covers 14,411 sq km, moderate dense forest covers 37, 977 sq km, and open forest constitutes 15,389 sq km (FSI, 2005). About one fourth of the very dense forests of the country exist in this state. When compared to the land use/ land cover derived from the satellite data of Nov-Dec, 2002 and Jan-Feb, 2003, there has been a decrease of 34 sq km area in very dense forests and 107 sq km in moderately dense forests. On the other hand, an increase of 226 sq km in open forests and 10 sq km in scrub forest has been reported (FSI, 2005). Out of the total geographical area of Arunachal Pradesh (83, 74,000 ha), the land utilization is reported for 54,98,000 ha (Land use Statistic Report, Ministry of Agriculture, Govt. of India, 2005). At present, 93.74% of the land utilization is covered with forest of different types and only 2.98% of the total area of the state is net sown (FSI, 2005). Lower Siang H.E. Project 7-4

Table 7.2 Area (sq km) of the different categories of land use/ land cover in the Arunachal Pradesh Forest covers Area (ha) Percentage of Geographic Area Arunachal Pradesh (Geographic area: 83, 74,000 ha) Reporting area for land utilization 54, 98,000 100.00 Forest 51, 54,000 93.74 Not available for cultivation 26,000 0.47 Permanent pastures and other grazing 4,000 0.07 Lands Land under misc, tree crops & groves 36,000 0.65 Culturable Wasteland 37,000 0.67 Fallow lands other than current fallows 47,000 0.85 Current Fallows 30,000 0.55 Net area sown 164,000 2.98 (As per Agricultural census 1995-96 Except total cropped area) East Siang District (Geographic area: 36, 55, 000 ha) Very Dense Forest 54,400 19.14 Moderately Dense Forest 1,74,400 61.38 Open Forest 55,300 19.46 Total Forest Cover 2,84,100 100 Source: State of Forest Report, FSI, 2005. 7.6 FALSE COLOUR COMPOSITE (FCC) FCC image generated from IRS-P6 LISS-III of Siang catchment area is presented in the Figure 7.1. Based on visual interpretation on FCC image, several geomorphological features have been identified in the catchment area. Areas covered with snow and glacier is marked by white colour and they are situated towards the northwestern part of the catchment. Some areas with data error on the image are also displayed by white colour. However, these areas are observed in the southern part of the catchment. Areas occupied by forest lands are marked by deep red to brown colour in FCC and most part of the catchment is occupied by this features. Areas of less vegetation and no vegetation (barren land) are displayed by light red and brown colours respectively, while areas covered with thick vegetation is marked by deep red colour. Most part of the catchment area is occupied by this unit. Surface water bodies are displayed by deep blue to bluish black colour. Cultivation lands and settlement areas are displayed by grey and cyan colours respectively. These Lower Siang H.E. Project 7-5

features are commonly distributed near the main river courses. There are many lineaments observed in the catchments. Several geological structures, like thrusts, faults and lineaments have also been identified on the FCC image. Distribution of straight river channels is marked as lineaments and is common along the main river courses and its tributaries. The presence of thrusts and faults are marked by tonal variation. 7.7 LAND USE/LAND COVER The total catchment area in Indian territory for the proposed project up to the dam site is about 14038.00 sq km. The project site lies under Siang catchment which includes its major tributaries like the Siyom, the Yamne and the Simang rivers. The land use/ land cover of the catchment area consists of 12 categories (Fig. 7.2), out of which maximum area of about 1017987.16 ha i.e, (72.52%) is under forest lands (Table 7.3). Open forest covers 471235.11 ha (33.57%), dense forest occupies 420595.35 ha (29.96%), scrub/ Alpine scrub126156.70 ha (8.99%) and degraded forest 35682.21ha (2.54%). Barren/ rockyland with moraines together occupy 174689.92 ha (12.44%) of the total catchment area. Snow/ glacier contributes 95333.13 ha (6.79%) in the catchment, while cultivations and settlement (including Jhum cultivation) covers 26233.65 ha (1.87%). River and sand body together contributes 6273.84 ha (0.45%) of the total catchment area. Table 7.3 Areas of different categories of land use/ land cover of the Lower Siang H.E. Project Sl. No. Land use /land cover categories Area (Ha) Percentage 1 Dense forest 420595.35 29.96 2 Open forest 471235.11 33.57 3 Scrub/Alpine scrub 126156.70 8.99 4 Degraded forest 35682.21 2.54 5 Barren and rocky land 76987.38 5.48 6 Moraines 97702.54 6.96 7 Cultivation/ settlement 23328.17 1.66 8 Jhum cultivation 2905.48 0.21 9 River 5284.66 0.38 10 Sand 989.18 0.07 11 Snow/ Glacier 95333.13 6.79 Lower Siang H.E. Project 7-6

12 Unclassified 47600.09 3.39 Total area 1403800.00 7.7.1 Land use/land cover of Submergence Area Total length of the reservoir is 106 km, out of which 77.5 km is along the Siang river and 28.5 km is along the Siyom river. Total area of the reservoir (at 230 m FRL) is around 5151 ha. The land use/ land cover map of the submergence area is shown in the Figure 7.3. The maximum submergence area is under forests (34.18 %) out of which, the area under open forest occupies 17.55% (903.95 ha), while dense forest covers 8.01 % (412.65 ha), degraded forest covers 7.19% (370.49 ha) and scrubs covers 1.43% (73.86) (Table 7.4). Around 8.55% of the total area of submergence area is presently under cultivation land and settlements. Jhum cultivation occupies 1.67% of the total submergence area. 3.15% of the submergence area is occupied by moraines. 15.71% of the submergence area falls under unclassified category. Because, the Siang valley is wide, the sand and channel deposit occupies 4.05% (208.82 ha) of the total submergence area. Table 7.4 Areas under different categories of land use/ land cover in the submergence area of the Lower Siang H.E. Project. Sl.No. Land use/ land cover categories Area (Ha) Percentage 1 Dense forest 412.65 8.01 2 Open forest 903.95 17.55 3 Scrub 73.86 1.43 4 Degraded forest 370.49 7.19 5 Cultivation land and settlement 440.66 8.55 6 Jhum cultivation 85.79 1.67 7 Moraines 162.46 3.15 8 Barren land 75.73 1.47 9 Sand 208.42 4.05 10 River 1608.05 31.22 11 Unclassified 809.06 15.71 Total area 5151.12 Lower Siang H.E. Project 7-7