58th International Astronautical Congress, Hyderabad, India, 24-28 September 2007. Copyright IAF/IAA. All rights reserved. SOCIAL ASPECTS OF CADASTRAL LEVEL SUSTAINABLE DEVELOPMENT PLAN USING REMOTE SENSING AND GIS A. Jeyaram, Saikat Paul*, D. Chakraborty, Y.K. Srivastava, Singh Kanti, V. Jayaraman** Regional Remote Sensing Service Centre, Kharagpur, India, *Indian Institute of Technology, Kharagpur, India, **Indian Space Research Organisation (ISRO), Kharagpur, India Indian Space Research Organization (ISRO), Bangalore, India Abstract Cadastral maps are detailed scalable maps with information regarding ownership boundaries along with features such as roads, forest, temples, etc with out any specified projection and associated with record of information. Considering the numerous benefits of a digital cadastral database, a methodology has been developed for generating geo-referenced digital cadastral database for Lohardagga district, Jharkhand state, India which covers an area about 1491 sq.km consisting 354 villages spread over 5 blocks. Cadastral map of ownership boundaries in association with natural resource database derived from high resolution satellite data (IRS LISS III, PAN, and IRS LISS IV ) provided information on current status of parcel wise land utilization. Farmers of large land holdings and small/marginal land holdings were identified based on digital cadastral maps and current status of land utilization. Detailed socioeconomic analysis has been carried out and people below poverty line, target groups ( SC and ST) and other low income groups have been analysed. The land use/land cover derived from multi-spectral high resolution data provided information on agricultural crop, agricultural plantation, wastelands, water bodies, marsh lands, forest etc. Logical grouping of these landuse has been carried out by combining wastelands, uncultured water bodies, marsh lands and other unutilized land as current unproductive land. Current status of agricultural activity also indicated that only kharif crop is only the major source of agro-economy. Statistical correlation of current unproductive land with total target group persons below poverty level, landless labourers and small farmers have been carried out using multi-variate statistical analysis. The analysis indicated a direct correlation of unproductive land with various social groups. Cadastral level sustainable development plans have been generated for Bhamandiha village in Lohardaga block, addressing the various social groups and government schemes for the upliftment of poorer sector.
INTRODUCTION Natural Resources compelled with socio economic variables based planning with conjunction with Government policies and schemes is an important and sustainable in nature for overall development at the region. A holistic approach for achieving sustainable development to meet the growing needs of the increasing population through Integrated Mission combining space remote sensing inputs on land and water resources with collateral socioeconomic information (Rao, 1996). Operationally, such a strategy requires an effective and accountable local institution at the level of a village or cluster. The imperative of having such an institution has gained wide recognition. In India the Constitution was amended in 1992 to provide for such an institution (panchayat) elected by the local population every 5-years, to plan holistically at each village level for economic development and social justice. Several countries in Asia have embarked on innovative land use systems such as "Estate farming" or "community farming", in which modern practices are uniformly applied to best tap the land s natural productivity (Paul S Teng, 2002). The satellite data form very important inputs for deriving natural resources database. Therefore, remote sensing is inevitable technique for natural resources planning and management. Geographic Information System also play a very important role in assessing the various geo environmental parameters and making decisions towards generation of sustainable development plan and also for decision making. Cadastral maps due to its inherent nature in general, the utility of these maps in spatial domain is limited. Remote sensing and GIS techniques have opened up the enormous utility of these cadastral maps in spatial domain towards development in general also enhancing even revenue collection by the state Government. The implementation of various development plans are based on cadastral maps by various departments of state government. The technique of geo-referencing of cadastral maps and its utilization potentials were significantly demonstrated and documented in the state of Chattisgarh by Krishnamurthy et.al 2000). The Chattisgarh model is based for carrying out the present investigation in Lohardagga district, Jharkhand state, India. OBJECTIVE A comprehensive pilot study has been carried out in the area covering Logardagga district to generate large scale implementable action plan addressing problems and potentials, natural resources various socially backward groups, below poverty families and schemes of central and state governments. The major objectives of the present investigation are
?? Geo referencing of cadastral maps using high resolution satellite data?? Generation of natural resources database using satellite and collateral data.?? Analysis of social groups and their relationship with natural resources?? Integration and generation of development plans to be implemented using cadastral maps based information?? Development of comprehensive software package?? Generation of action plan addressing social groups of SC, ST, BPL and landless labourers in conjunction with current unproductive lands utilizing the government schemes. MATERIAL AND METHOD The Lohardaga district of Jharkhand covering an area of about 1491 Sq.km falling in central parts of India which receives average annual rainfall of 700 900 mm. The district area has 31.38 per cent of forest, 9.8 percent of waste lands and also endowed with good reserves of bauxite deposit. The agricultural land constitutes around 55.8 per cent which are monsoon dependent rain-fed crops are being taken. The district is divided into five blocks covering 356 villages, out of which 287 villages where socially backward population is above 50 per cent. The following table 1 provides various socially backward groups in block-wise in the district. Table 1. Socially backward population of Lohardagga district. Block SC(%) ST(%) Kisko 22.34 19.08 Kuru 40.42 21.29 Lohardaga 10.87 21.29 Sneha 18.87 21.58 Bhandra 8.02 17.98 The recent survey of below poverty families (BPL) by the state government indicate that 47 per cent of the families in the district are below poverty line. The following high resolution satellite data have been used for the present investigation. 1. IRS 1C LISS-III 23 m (XL) 2. IRS 1D LISS-IV 5.8 m (XL) 3. IRS 1 D PAN 5.8 m Cadastral maps and Khatian data (ownership details) collected from district authority have been used for present investigation. In addition to the above, maps of Geological Survey of India, maps of National Bureau of Soil Survey and Land Use Planning (NBSS&LUP) have also been consulted along with topographic maps of Survey of India. METHODOLOGY The IRS-IC/ID satellite data, available in 3 spectral windows of 23.5 meters resolution and panchromatic data of 5.8 meters resolution are used for referencing the cadastral boundaries. IRS LISS III data is digitally processed and enhanced by a factor of 4 (four) in both directions to generate a pixel
size similar to the PAN data. These results are smoothened with a 3 * 3 low pass filter to eliminate the blocky appearance introduced by the 4 times enlargement. Image to image control points were interactively selected to register the LISS III data onto the PAN data. Hue-Intensity- Saturation method is used to merge the information contents of both data sets. The resultant output was an high resolution, edge enhanced, Color Composite (HREECC) depicting the natural and man made boundaries like river/ stream / nullah, transport network, canals, tanks, etc. The survey boundaries of farm level information also could also be identified in the digitally enhanced product. The 0verall methodology is given the figure 1. The method of georeferencing the cadastral maps has been followed based on Krishnamurthy, et. al (2000). The cadastral maps are digitally scanned using CIS S/W on DOS environment for generating the digital database. Specific S/W has been developed in EASI/PACE environment for generating the digital cadastral database and subsequent overlaying of cadastral images on satellite image data. The cadastral image is registered with rectified satellite data using image to image transformation model. Large number of GCP s are required to minimize the warping effect of the cadastral maps. Fig.2 shows georeferenced cadastral maps and mosaic of these maps. A registration accuracy of less than two pixels of standard residual error is achieved while image to image tie down. Collateral Natural Resource database Satellite data Generation of District Dev. plans Gov. Schemes Rectification Socio-economic Cadastral Digitisation and Georeferencing of Cadastral maps Village wise Dev. plan Attribute Generation of Marginal & Small land holdings and backward social groups Fig. 1. Flow Chart of Methodology The specific software is used for image to image registration without artifacts and null points, a kernelbased line thinning, followed by editing and polygon labeling. The cadastral boundaries are further vectorised to overlay on satellite data (Fig. 3). Natural resources namely lithology, structures, geomorphology, land use land cover etc have been derived from satellite data and collateral data. Soil map published by NBSS & LUP has been used. Drainage, water
bodies, DEM. Slope, aspect and all administrative boundaries have also been derived from various sources. A customized software package BIRSA VASUDHA has been developed for district natural resources and village-wise cadastral data base along with attributes. Natural resources data, collateral data, cadastral ownership maps and attributes have integrated into the package for modeling. Various categories of land holding sizes and socially backward population have been analysed. District development plan and village wise development plans were generated by integrated the above data base for village level implementation. RESULTS AND DISCUSSIONS The analysis of natural resources database of land use /land cover indicate that Scrub lands and barren uplands are the major waste lands in the district. These wastelands are combined together and derived current unproductive land (wasteland). The degraded forest land (mostly blank) has also been considered for analysis. Correlation of socially backward classes in each of the blocks with currently unproductive lands show that there is direct correlation exist between unproductive land with socially backward population. The analysis indicates that socially backward (SC) population is directly correlated with amount of current unproductive lands. The False colour composite of IRS LISS III and PAN merged (Fig. 4) indicate that the Western part of the districts covered with forest. The Easter part of the district is mild undulating terrain with isolated hills. Fig. 4 False Colour Composite IRS LISS III and PAN data Digital Terrain model has been generated using SRTM data and slope aspect maps have been derived (Fig. 5). Fig. 5 Lohardagga District Digital Elevation model of Lohardagga district Supervised classification technique has been adopted for land use / land cover classification. Wasteland and
other degraded lands are shown in figure 6. The land use/land cover data indicate that 55.51 per cent of the area is covered with agricultural land and 31.23 per cent of the area is under forest ( Fig. 7). Land use/land cover per cent in Lohardagga District Analysis of cadastral maps indicate that more than 90 per cent of the parcels are under marginal land holding size of 1 ha and less (Fig. 8). This also indicate that the economic backwardness in the district area. Table 2 shows status of land holding size in the district. 31.23 Fig. 7 9.74 1.53 1.98 Agriculture 55.51 Landuse statistics of Lohardagga district. Kharif crop is the only crop being taken in 90 per cent of the agriculture area, which is mostly of rainfed crop. The soil map of National Bureau of Soil Survey & Landuse Planning has been used analysis (Fig. 4). The large amount of potential exist for integrated watershed development program. Ground Water Resource Forest Wasteland Water Built-up The district area is occupied by granite/granite gneiss associated with lineaments. The aquifer is of unconfined aquifer with poor ground water availability. The ground water is restricted to fractures and faults in the area. At places in the western parts, the rocks are outcropping indicating the shallow weathered zone. Government Schemes Area Development Programme like DPAP, DDP and IWDP of Government of India are being implemented by the DRDA under the supervision of the State Governments. Instructions have been issued for preparation of district-wise perspective plans for treatment of wastelands/watersheds showing the physical and financial requirement for next five years. The State Governments should identify and prioritize the area for development of wastelands and complete the preparation of these plans using remote sensing data, field data and GIS on priority. The following government schemes of land based developments are being used for the upliftment of the socially backward groups in the area 1. National Rural Employment Guarantee Act (NREGA) 2. Sampoorna Grameen Rozgar Yojana (SGRY) 3. Swaranjayanti Gram Swarozgar Yojana (SGSY) 4. Indira Awas Yojana 5. Sardar Patel Awas Yojana 6. Dr. Ambedkar Awas Yojana
District Perspective Plan: Watershed development Based on the analysis of natural resources, water resources development become paramount importance. The district area is divided in to micro watersheds and detailed wastelands have been mapped. GIS analysis has been carried out and water resource development plan has been generated (Fig. 9). The activity of water conservation measures have been divided in to water harvesting and soil and water conservation measures. The water harvesting structures recommended for the area based on the potentials of the natural resources and current cropping pattern. The following water harvesting structures have been recommended, 1. Percolation tanks / Recharge tanks 2. Irrigation tanks 3. Nala bund 4. Check dams 5. Farm ponds 6. Sub surface dykes The soil and water conservation measures include, contour trenching, stone wall, Gabion structures, gully plugging etc. The above activities have been planned in micro watershed wise for the entire watershed. The water resource plan, if implemented will hold substantial amount of water for utilization in the watershed. Apart from this, deepening / desiltation of the existing tanks/ponds, widening of few rivers/nala. The water resource plan address ridge to valley treatment along with soil and water conservation mechanism. Percolation tanks have been suggested in the plan, upland tracts where more wastelands are occurring. Small nala bund and check dams have been proposed in the second and third order streams in the close vicinity of wastelands and current unproductive lands. VILLAGE WISE DEVELOPMENT PLAN Water conservation measures are superimposed over false colour composite of IRS LISS IV covering Bamandiha village is shown in figure 10. Geomorphological features along with other natural resources have been analysed for various water resources measures. Various multi-purpose water conservation structures have been suggested implementation. Unconsolidated sediments confined along small drainage is suitable for check dams and under ground bandaras. Areas of percolation tanks/recharge tanks and farm ponds have been suggested so that dug wells in the surrounding area will get benefited due to recharge. The area is suitable for exploitation of ground water through dug wells. Geophysical survey may provide locations of tube wells in the area. Land resource action plan indicate that various measures of intensive agriculture, agro-forestry and agroplantation activities are suitable in the village (Fig. 11). Parcels indicated in yellow colour are in low lying areas which is suitable for
intensive agriculture activities. Red colour parcels are suitable for agroforestry with fast growing trees. The rest of the area are suitable for agroplantation activities. Implementing Strategy Village wise water and land resources development plans generated using remote sensing and GIS form very important input for development of the villages in the lohardagga district. Village wise land & water resources plan Cadastral Maps Identification of marginal & socially backward families Various schemes like National Employment Guarantee Yojana (NREGA), Sampoorna Gramin Rozgar Yojana (SGRY) and Swaranjayanti Gram Swarozgar Yojana (SGSY) of government of India identify socially backward groups like SC, ST and families of below poverty line. Job cards were issued in the above schemes for employment. The schemes also reccognise the self help groups existing in the block/village area. The funds for taking up developmental activities identified in the development plan are identified from National watershed program of government of India Fig. 12). Using the socially backward and employment needy man power through the above schemes, a committee of working group is being formed and familiarized the water and land resources activities to be under taken. Implementation of land water dev. plan Gov. land Commu nity land Formation of Community working groups Employment guarantee Small & Marginal Holdings Fig. 12 Flow chart of Implementation strategy CONCLUSION Micro level planning process need to be strengthened. Key activities should be identified keeping in view with the aptitudes of socially backward workers, availability of raw materials. District level officers are involved in the planning process to identify need & resource based activities. High resolution satellite data provided very vital information for planning water conservation measures. Customised GIS package helped in decision making towards developmental plan generation utilizing cadastral data base.
REFERENCES Rao U.R., (1996), Space Technology for Sustainable Dvelopment, Tata McGraw Hill, Jan 1996 Paul S Teng, (2002), Food security and basic human needs, Delhi Sustainable Development Summit- 2002,Ensuring sustainable livelihoods: challenges for governments, corporates, and civil society at Rio+10 8-11 February 2002, New Delhi Y.V.N. Krishna Murthy, S. Shriniva Rao, D.S. Shrinivanan & S. Ardiga, 2000, Land Information System (LIS) for rural development, Technical proceedings, Geomatics 2000.
Table 2: Land holding sizes of Lohardagga District, Jharkhand Block Name Marginal Holdings Small (less than holdings =1 ha) ( 1-2 ha) Semi medium holdings (2-4 ha) Medium holdings (4 10 ha) Large holdings (above 10 Total No of ha) Parcels BHANDRA 71560 1203 234 83 32 73112 KISKO 72188 1701 508 290 441 75128 KURU 101090 1158 259 134 106 102747 LOHARDAGA 71829 699 125 66 32 72751 SNEHA 88501 1980 533 229 230 91473 Lohardagga Wasteland Degraded forest Water body Figure 6. Wasteland mapping of Lahardagga district, Jharkhand
Fig. 2. Georeferenced cadastral maps of villages and mosaicked Fig. 3 Cadastral boundaries superimposed over IRS LISS III + PAN data
Areas of Farm Ponds Areas of irrigation Tanks Area of Percolation Tanks Forest Settlement Water bodies ( River & Tanks) Farm Ponds Irrigation Tanks Recharge/ Percolation Tanks Fig. 9 District water resource development plan a part showing water conservation structures
Percolation Tanks Farm Ponds Dug wells (Exploitation structure) Check Dams Water Resources Dev. Plan Bamandiha Village Lohardagga Block & District Jharkhand state IRS LISS IV March 2007 Fig. 10 Water Conservation structures superimposed over IRS LISS IV data
Marginal Farmers Small Farmers Small to semi medium Farmers Medium Farmers Large Farmers Land holding size of Bamandih Village, Lohardagga District, Jharkhand Intensive Agriculture Agro Forestry Agro Plantation Land Resource Plan of Bamandih Village,Lohardagga District, Jharkhand Fig. 8 Land holding size Fig. 11 Village level land resources development plan