Use of satellite imagery for natural resources development has come a long way after the launch of first American satellite Earth Resource Technology Satellite (ERTS), now known as Landsat-1 in the year 1972. Subsequently, a number of satellites have been launched from different countries with improved spatial, spectral, radiometric and temporal resolutions for the development of natural resources throughout the world. The most important factors responsible for the utilisation of satellite technology for development are the non-availability or easy accessibility of aerial photography in many developing countries and ever increasing use of information derived from satellite imagery in the decision making process. Scientists associated with natural resources development and management today are able to expand scope of applications each time satellite imagery with better resolution in spatial, spectral, radiometric, temporal and stereoscopic coverage become available. From various studies conducted using different high resolution satellite data, it was believed that high resolution would always provide a better interpretation and delineation of boundaries of diverse land cover categories easily. However, it is not always true from the point of view of varied levels of planning processes being carried out in the developing countries. Let us examine the role of high resolution data in meeting information needs of different planning levels in developing economies.

The Development Planning Scenario
The plans prepared earlier by and large concentrated mainly on economic development with various shortcomings, viz.,

1. the plan was treated as an end product.
2. it used to take long time for preparation and approval
3. it did not provide any short term actions and perspectives.
4. it was not participatory in nature
5. there were no mandatory monitoring and review mechanisms
6. the plan did not provide for integration of physical and socio-economic criteria and
7. did not strive for sustainable development. However, the present planning scenario has changed to generate the plan for the spatio-economic development of the countries instead of just concentrating on the economy. In this context, preparation of an "Integrated Sustainable Development Plan" is advocated throughout the world. The integrated plan is expected to serve as a guideline to promote both spatial and economic development. The integrated planning is generally followed in developed countries such as U.K., U.S.A, The Netherlands etc. The planning system in developing countries including India, also follows the integrated planning approach consisting of a set of four inter-related planning levels as follows:
   Regional planning, synonymous with macro level at scales ranging from 1:250,000 to 1:1000,000. This is a very long-term plan covering a state or a cluster of states. This is meant for spatio-economic development of the region.
   Perspective planning which is also synonymous with macro level (District level) at 1:50,000 to 1: 250,000 scale. This is also a long-term planning exercise and addresses the policy issues relating to spatio-economic development of the district or cluster of districts. The purpose here is to provide a policy framework for further detailing and guidance for preparation of development plan.
   Development planning, synonymous with meso-level (Block level) at 1:25,000 to 1:50,000 scales are conceived within the framework of the approved perspective plan. It is a medium duration plan covering a span of five years.
   Project (Scheme) Planning, synonymous with micro-level (micro-watershed or village level) at scales from 1:5,000 to even larger than 1:1000, is a detailed annual work layout for an executing agency. It is prepared within the framework of development plan.

The Above development planning exercises have to be viewed in the context of specific problems associated with developing countries which emanates primarily due to rapid population growth and limited resource availability resulting in regional and intra-district imbalances at the socio-economic development levels. These problems find further manifestation in the form of low income levels, smaller land holdings, poor social services, inferior infrastructure, poor literacy and hygiene, environmental degradation etc.

Apart from the spatio-economic development problems, the developing countries face a host of other problems related to technological backwardness and availability of institutional as well as technical infrastructure to support the holistic approach of integrated planning as mentioned above. In the context of spatial planning support, some of these problems are:

• Non availability of country wide latest topographic as well as the cadastral base.
• Non-availability of technological know-how at working level.
• Lack of institutional back-up for implementing and monitoring the development plans.
• Security restriction problems related to the use of either topographic base, wherever available, or the use of high spatial resolution data.

Use of Satellite Imagery for Developmental Planning
Considering various levels of development planning discussed above, a typical planner deals with areas to be analyzed and planned on maps at a variety of scales. While a map dealing with a macro level planning exercise requires information at regional level such as broad physical features, agricultural land, forest land, water bodies, waste and derelict land, transportation network, location and spatial distribution of settlements at scales varying from 1:250,000 to 1:1,000, that dealing with micro level planning exercise needs detailed information on cropping pattern, forest species, biomass, infrastructure (water, energy, drainage, sanitation, solid waste disposal and communication), facilities (education, medical, and recreational) and transportation network etc. at scales varying from 1:1000 to 1:5000. These maps do require a different level of generalization and detailing. While a small polygon at a regional scale could represent a large area (district), a map at an urban (or local) scale would require differentiating the various residential, industrial, commercial, public, semi-public and recreational uses and their sub-classification within these classes. Studies have indicated that when working at a regional scale, imagery with coarse spatial resolution is actually more useful than imagery with fine resolution. For example, crop acreage and production of mono cropped areas, Geological mapping, Ground water exploration and metropolitan planning in a regional context require imagery with a coarse resolution providing synoptic view of the region under study. It sieves out unnecessary details, which would be useful only at the local level and very disturbing at regional level. The same is true for identification of changing extent of the crops, water bodies, forest types, urban land uses and infrastructure. The overall application scenario with respect to various planning level vis-a-vis different satellite imagery resolutions are given in Table-1. Different satellite sensors covering a large range of spatial resolutions operating currently are given in Table-2 below.

Resolution - some issues
Spatial, spectral, radiometric and temporal resolution in which the sensors collect the remotely sensed data are the important parameters for any type of mapping related to the development activity. Fine resolution satellite imagery will be very useful for working at local scales and a coarse resolution imagery will continue to have an upper edge while working at the national and regional scales with a reasonable coast benefit ratio. Fine spatial resolution allows smaller objects to be seen and mapped, specific choice of spectral bands enhances the discriminating ability between the land covers, fine radiometric resolution differentiate the smallest change in the spectral reflectance/emittance between various targets and the high temporal resolution allows one to study the variability of the object through time. The requirements of these resolutions vary from one developmental project to another developmental project. Therefore, the high resolution is a relative term and the requirement of this varies from agricultural application through applications in forestry and biodiversity, environmental planning, water resources planning, disaster management, mining, rural development, urban development and to utilities (power, health, transportation and telecom) planning. For example, If one wants to carry out a study related to "National level Crop Production for major crops in the country", a resolution of 188m (IRS WiFS) is sufficient. But if one wants to carry out a micro level study related to the discrimination of mixed crops, their acreage and crop production, one needs to use a high resolution data of the order of 1 to 5 m.

High-resolution imagery (1m pan and 4 m MS) provided by IKONOS has opened up possibilities of carrying out detailed planning at village/ micro-watershed level. These include:

1. Agriculture and Forestry; covering Crop Forecasting and Yield Management, Forestry Health Assessment, Erosion Management, Infestation Assessment and Habitat Monitoring.
2. Environmental Monitoring; including Compliance Monitoring and Habitat Mapping and,
3. Mapping and Surveying; including site selection, construction project planning and tracking, pipeline monitoring, property insurance for natural disasters, mineral exploration (lineaments at micro level - faults, fractures & folds), zoning for various types of land use at detailed level, transportation planning, emergency management and relief.

The Cost Implications of using High Resolution data
Although the availability of high-resolution imagery has opened up many exciting opportunities for development planning at micro-level, it is important to consider the associated cost implications commensurate with different applications given in Table-1.

If we consider the micro level planning in the context of rural development including micro-watershed development planning, the typical micro-watershed size is about 500 hectares. One has to acquire a minimum of one scene covering 11 X 11 sq. km area at the cost of about 2 lakh rupees. This cost is exorbitantly high considering the fact that the same job can be done by ground surveys at much lesser cost. Accordingly the cost of various other high-resolution satellite imagery (Table-3) could be examined.

However, there are many niche applications where the time factor overrides the cost and therefore these applications can afford the cost of using high resolution satellite imagery. These could be the applications where overall project cost itself is very high and the project needs to follow very stringent time schedules, for example, site selection for various infrastructure development projects including dams, highways, canal, industries and power plants. Apart from these, the emergency response requirements like post disaster relief management could also justify the high cost of using high-resolution imagery for meeting immediate and emergency response requirements.

Technology Convergence - The need of Today
The spatial data handling activities for development planning have been in practice for many centuries using conventional wisdom. These have been made more and more efficient and objective with the gradual advent of modern data gathering technologies, like Remote Sensing & GPS and data handling and analysis tools provided in Geographic Information Systems (GIS).

The ultimate effectiveness of the spatial technologies, like GIS, GPS, Photogrammetry, & Remote Sensing, for providing planning and decision support will depend on whether these technologies can be brought to a level from where the end-users can themselves have direct interaction with the technology tools for finding solutions. Bringing these complicated technologies within the reach of end-users requires very careful and dedicated efforts towards synergization and customization. Ultimately the delivery of the information content at the doorstep of end-users will decide on the efficacy of these technologies. The current development trends in the area of Internet access needs to be seriously kept note of. In India, a systematic effort at Nation-wide scale, is being attempted in form of National (Natural) Resources Information System (NRIS).

National (Natural) Resources Information System ( NRIS)
NRIS is the programme launched by the Department of Space (DOS) jointly with the State Remote Sensing Centres. It is oriented towards providing information for decision makers and encompasses information on natural resources related to land, water, forests, minerals, soils, oceans etc. and socio-economic information such as demographic data, amenities, infrastructure etc. The integration of these sets of data would aid the decision making process for systematic resources utilization and also aid sustainable development goals of the country. NRIS is visualized as a network of GIS based nodes covering the districts and states and the entire country. These nodes are the repositories of resource information in the spatial domain and are assigned to provide vital inputs to decision-making at district/state/centre levels.

The ultimate end users of the NRIS system are expected to be the planners and decision makers, experts in their respective areas/ disciplines, who need not be the experts in the technologies like GIS and Remote Sensing. The mechanisms for access of the database elements are therefor made easy and explicit. On the one hand NRIS facilitates standards/ protocols/ procedures for database creation/ organization, updating and database access using appropriate GIS and other software packages, but also includes customized shells for decision support. These shells focus on providing the user a transparent access to the database and software package environments and address the user specific planning problems. The shells are customized based on the analysis models specified by the users and the customization tools provided within the GIS and other packages.

NRIS design and organization had been specifically focussed at providing information systems support to the Integrated Mission for sustainable development (IMSD). IMSD is the major programme launched by ISRO-DOS for generating and implementing the locale specific, integrated land and water resources development plans for 175 problem districts in the country. These plans are based on the inputs generated from remote sensing and other collateral sources on Landuse/Landcover, Soils, Groundwater prospects, slope and drainage and other collateral sources on Slope combined with resources analysis considering the local socio-economic scenario. While the NRIS is being extensively used for generating the integrated land and water development plans as envisaged under IMSD, it is exhaustive enough to provide development planning support in general.

High resolution (temporal, spectral and spatial) images of future systems are based to improve the data content of NRIS which then can address developmental problems upto cadastral levels.

Conclusions

• The high-resolution satellite imagery will be very useful for working at local scales for big budget applications like site selection for infrastructure development projects including dams, highways, canals, industries and power plants. Apart from these, the emergency response requirements like post disaster relief management could also justify the high cost of using high-resolution imagery.
• In many applications related to rural development, like micro-watershed/ village development, the high cost of high-resolution imagery, perhaps, is a deterrent today atleast in countries like Inia.
• Medium to coarse resolution imagery will continue to have an upper edge while working at the national and regional scales due to advantages of synoptic coverage coupled with a reasonable cost benefit ratio.
• Convergence of various spatial technologies, like GIS, GPS, Photogrammetry, & Remote Sensing, for providing planning and decision support at local level is the need of today.

Table - 1 : Satellite Imagery for Different Levels of Development Planning
	Low Resolution	Medium Resolution	High Resolution
	80 – 360 M	20-40 M	1-5 M
Level of Planning	Macro Level (Regional & Perspective)	Meso Level ( District/ Development)	Micro Level ( Project, Micro-watershed, Village)
Scale Mapping	1: 50000 to 1:1M	1:25000 to 1: 50000	1:1000 to 1:5000
Application Area	Demonstrated Applications		Prospects
Crop acreage and Production Forecast	Mono-crop areas - large extents	Multi-crop areas -medium extents	Mix-crop areas Cropping System Studies Parcel size for crops grown - input to precision farming
Landuse Planning	Land use mapping at Level 1 classification Wasteland mapping at level-1 Wetland mapping at level-1	Mapping at Level 2/3 classification (Taluk/mandal level) Land use change analysis Wasteland mapping at level-2/3 Wetland mapping at level-2/3	Cadastre/ field level mapping - classification level – 3 & 4 (Village/mandal) Inputs for tourism development
Rural Development Planning	Regional maps Settlement network	Land and water resources development maps	Cadastral level landuse maps Land parcel maps Micro level watershed/ village planning
Urban Planning	Urban Sprawl analysis Urban land use at level-1 Transportation network (Highways, Railways etc.)	Urban landuse mapping (level-1) Urban suitability analysis Mapping of major transport network Updation of city guide maps	Urban landuse mapping (level 1 & 2) Slum typology Mapping of street level Urban road network Mapping of property parcels Inputs for infrastructure development Utilities and service maps Population estimation
Soils	Soil family Association mapping Land degradation (Water logged, salt affected, erosion prone)	Soil series association Land degradation at level 2	Soil series Land degradation at micro level
Water Resources	Watershed characterization & prioritization Glacier Inventory	Groundwater prospects Watershed Prioritization Snow melt run-off estimation	Micro Watershed Planning Monitoring of development schemes Drinking water site selection
Forest	Forest type & density Mapping	Forest type & density Mapping Detection of Degraded forest areas Forest fire monitoring	Forest Species identification Inputs for working plan generation Habitat mapping Biomass Estimation
Geology & Minerals	Regional Geological maps	Detailed geological mapping	Oil, Gas and Mineral Exploration
Infrastructure Planning	Regional level corridor planning	Broad Site Suitability analysis Mapping of major road network	Specific Project Site Analysis Dams Highways Canal Industries Power Plants
Disaster	Flood Prone Area Maps Cyclone Monitoring Drought Monitoring & Forecast Earthquake prone areas Landslide prone area mapping Slope stability mapping	Post Disaster Damage assessment Property Insurance for Natural Disasters	Post Disaster Relief Management Support Tracing of approach routes Waste disposal and solid waste management
Meteorology & Oceanography	Monsoon Forecast Sea-surface temp Wind vectors Waves spectra Sea surface topography	-	-

Table - 2 : Operational Satellites
Operational Systems Satellite	Data Provider	Prime	Launch	Resolution (m)/Swath Width (km)			Repeat Cycle (days)
				Panchro-matic	Multi-spectral	Radar
Landsat 5 ERS-2 Radarsat 1 IRS-1C Orbview 2 IRS-1D Spot 4 Landsat-7 IRS-P4 Ikonos	EDC DAAC Eurimage Radarsat Eosat, NRSA Orbimage Eosat, NRSA Spot Image EDC DAAC NRSA Space Imaging	Orbital Sci. Dornier Spar Aerospace ISRO Orbital Sci. ISRO Matra Macroni Orbital Sci. ISRO Eosat	Mar 84 Apr 95 Nov 95 Dec 95 Aug 97 Sep 97 Mar 98 April ‘99 May 99 Sep. 99	- - - - 5.8/70 10/117 -     - 1/11x11	30-80/185 36.25/131 - - 23.5-70.5 /142 1000/2800 23.5-70.5/142 20/117 4000/1150 15/185 360/1420 4m/11x11	- 26/102 7.6-100/50-500 - - - - - - - - -	16 35 24 24 16 24 26 -   26 16 2 3

Table-3: Cost of high resolution satellite imagery
S.No.	System	Reso- lution (meters)	Product	Scene Price	Average Area (sq km)	Price sq km
1. 2. 3. 4. 5. 6. 7. 8. 9.	Radarsat Radarsat Ikonos Ikonos IRS IRS Landsat SPOT SPOT	10 30 01 04 05 20 25 10 10	C-band synthetic aperture radar C-band SAR Master pan, orthorectified, archive Master MS, orthorectified, archive IRS Master pan, orthorectified IRS Master MS, orthorectified Thematic mapper, terrain corrected US MetroView pan archive US Statewide pan, orthocorrected, archive	$4,500 $3,750 $162 $162 $1,300 $3,000 $5,950 $550 $1,650	2,500 10,000 2.56 2.56 529 19,600 31,450 640 2,560	$1.80 $9.38 $63.28 $63.28 $2.46 $0.15 $0.19 $0.86 $0.64