Gis Sem 4

GIS in biodiversity conservation - The technology trend Depiction of ecosystem harbouring around 120,000 known plants and perhaps another 400,000 as yet undescribed species of plants, microbes and animals is possible with the recent technological advances. Biodiversity is receiving the attention of various scientists/planners/decision-makers due to its importance as a natural reservoir with tremendous economic potential. Conservationists have focussed attention on this fast depleting resource. In-situ conservation using ecosystem approach is popular which also protects various ecological services offered by forest ecosystem. Examples of such services are soil and water conservation, pollutant sink, noise reduction, shelter belts, microclimatic effects etc. Emphasis is on identifying most valuable biodiversity spots that harbour non-timber forest species such as endangered flora and fauna, medicinal plants and wild relatives of cultivated crops. While identifying such spots, it is also important to take into account the landuse and human activities around the forest. Conservation programmes for the 21stcentury are increasingly focused at the ecosystem level. IUCN/UNEP/WWF observe that "conserving biological diversity equals conserving ecosystems". The key question in this case is "Where are such ecosystems and how one is important in comparison to another?" Comprehensive, quality information on the distribution, status and utilisation of India’s biodiversity is the cornerstone for planning its conservation. While a lot of information exists, it is dispersed widely across the subcontinent among a large number of organisations. Moreover, some of it is not easily accessible or available in readily usable electronic form. Also, there are significant gaps in database in many areas. Hence, assessing biodiversity of megadiversity country like India is enormous task. Depiction of ecosystem harbouring around 120,000 known plants and perhaps another 400,000 as yet undescribed species of plants, microbes and animals is possible with the recent technological advances. Over the years, scientists have tried to find practical and simplified approaches to identify vegetation unit that represents unique species composition and diversity. Thus, the term "vegetation type" became popular among ecologists, which can be defined as ‘the assemblage of dominant growth forms of plant species sharing common habitat i.e. landform. In early 90’s, the efforts were focussed on supplementing field-based observations with the remote sensing based observations. The challenge was to prove that units identified on remote sensing data represents unique composition. In pioneer studies carried out at Indian Institute of Remote Sensing, Dehradun, vegetation communities in dry deciduous forests were mapped using Landsat TM data. Field data collected using stratified random sampling was analysed statistically to identify communities existing in the forest. The results showed vegetation units identified on remote sensing image show total agreement with the results of field based observations (Ravan, Roy and Sharma, 1995). The advantage of remote sensing is that it also identifies the vegetation /landuse units which may likely to miss during field surveys because of limitations in sampling techniques. Recent publications from Centre for Ecological Sciences (Indian Institute of Science) have verified above concept in Western Ghats forest by classifying ecological entities differentiated in terms of their composition/configuration to which field investigations of biodiversity can be linked (Nagendra and Gadgil, 1999). Thus, the efforts have resulted in wide acceptance of remote sensing technology in various studies such as wildlife ecology, biodiversity assessment, wetland ecology, biodiversity prioritization, forest and wildlife management etc. The technology that has given many more dimensions to the applicability of remote sensing based vegetation type map is ‘Geographic Information System (GIS)’. To name one, Landscape

Ecology is benefited most with the availability of spatial analysis tool like GIS. Landscape ecology considers vegetation as a mosaic of patches of vegetation with unique landform, species composition and disturbance gradient and focuses on parameters such as patch sizes, patch shapes, patch isolation, interspersion (adjacency of various landuses/landcover), juxtaposition (relative importance of adjacent patches), fragmentation, patchiness etc. All these parameters have direct bearing on the status of biodiversity within forest ecosystem. Spatial analytical capabilities of GIS allow quantifying all above parameters with the remote sensing based vegetation type map alone. Roy et al, 1996 have used GIS to characterise habitat of endangered animal, Mountain Goral, using GIS for evaluating principles of landscape ecology. Ravan and Roy, 1998 have again proved potential of GIS in landscape ecology by mapping disturbance zones in natural ecosystem and quantifying its impact on the biodiversity and biomass accumulation along the disturbance gradient. GIS was used in this study for quantifying patch sizes, shapes, porosity and patchiness of vegetation types. GIS was also used to extrapolate results of ground based estimations such as species richness, diversity index and biomass values. The results of above studies have assured the success in identifying bioprospecting zones for conservation prioritization at regional level by making use of GIS, remote sensing and landscape ecology. With the initiatives of Department of Space and Department of Biotechnology, the concept of Landscape Ecology is being verified in the biodiversity hot-spots of Western Ghats and Himalayas. GIS technology, besides its contribution in scientific studies, has been accepted as the most effective tool for decision-makers. Maharashtra Forest Department, under the leadership of J.S. Grewal (Conservator of Forest) has established GIS for forestry at Nagpur. GIS for forestry at Maharashtra is contributing in 4 different areas such as working plans, biodiversity, village ecodevelopment, and plantation inventory for Forest Development Corporation. Similar efforts have been put in by H.C. Mishra in Andhra Pradesh Forest Department. Many other state governments are also making use of GIS for forest management, the results of such efforts would be visible in near future. NGO sectors such as World Wide Fund for Nature-India (WWF-India) and Tata Energy Research Institute (TERI) have also stepped in the biodiversity conservation efforts using GIS. WWF-India has already computerised third edition of forest cover maps of FSI in GIS environment. In addition, baseline database on important national parks/sanctuaries are also developed. The attempts have also been made to link taxonomic details of rare and endangered species to GIS database. All these NGOs need the support from the custodians (generally govt. organisations) of primary data on biodiversity. Many Research Institutes working in the area of biodiversity conservation have started use of GIS technology. Prominent among them is Wildlife Institute of India. Other institutions are G.B. Pant Institute of Himalayan Environment and Development, Centre for Ecological Sciences (Indian Institute of Science), Kerala Forest Research Institute, Gujrat Institute of Desert Ecology etc. The above trends give impression that Research Institutes, State Forest Departments, Central Government Agencies such as FSI, and NGO Sector can put hands together to save biodiversity, the most valuable resource, of the country. The huge amount of databases being generated by various organisations needs to be structured for evolving information system for forest management. Such information system is scientific tool for the forest managers to perform better in the area of forest/wildlife management and biodiversity conservation.

Biodiversity characterisation at landscape level using satellite remote sensing and GIS A project sponsored by Department of Biotechnology and Department of Space (DOS). The experiences of the R&D work done at Indian Institute of Remote Sensing, Dehradun has resulted into the nation-wide efforts of identifying the bioprospecting areas for conservation. The objectives of the project are   

preparation of biome/ecological zone maps using satellite remote sensing data, incorporating topographical details and biogeographical classification of India, Landscape characterisation to identify disturbance gradient and prioritise area (bioprospecting) for biodiversity conservation.

The project is being executed in the Western Ghats and eastern and western Himalayas. DOS has prepared project manual explaining standard methodology for execution of the project. The project has made landmark contribution in the field of GIS. The software ‘BIO_CAP’ has been customized over Arc/Info GIS and can operate on different standardized databases. It provides facilities for display, overlay, integration, analysis, statistics, modelling of landscape. Phase I of the project is implemented under coordination of Indian Institute of Remote Sensing, Dehradun. The main organizations involved in the project are Natioanal Remote Sensing Agency, Forest Survey of India, Wildlife Institute of India, G.B. Pant Institute of Himalayan Environment and Development, Botanical Survey of India, French Institute (Pondicherry), Maharashtra Remote Sensing Applications Centre, respective State Forest Departments etc. The contact person is Dr. P.S. Roy, Dean, Indian Institute of Remote Sensing, who is also Project Director.

A GIS application for weather analysis and forecasting Abstract With technological progresses and associated need for more and more human comfort, the demands for accurate weather forecasts for different spatial and temporal scales are also increasing. In this context, application of emerging technologies for increasing accuracy and skill of the weather forecast calls for special attention. Use of Geographical Information Systems (GIS) software viz. Arc View to develop an application, for plotting, analysis, visualization, and interpretation of weather data, to serve as an aid in the prognostication of weather is attempted in this paper. The application developed can help the meteorologists in instantaneous plotting of synoptic weather data from different locations at various isobaric levels of the atmosphere. Analysis of this data, for visualization and interpretation of weather systems over wide geographic areas become possible with less effort and error. Facilities available include, provision for superimposition of synoptic weather maps of the past with the present for tracking of movement of weather systems, computation of their persistence, tendencies and trends. Weather maps at different levels, or different days (past, present and future) can be superimposed and removed with the click of the mouse for analysis and visualization of weather developments. Advancing the weather systems forward or backward geographically for visualization of past and future (as forecasted) movement of weather systems across geographical areas becomes easier. Climatological data can also be plotted, departures from normals, tendencies, etc. calculated and presented as charts. Satellite pictures, topographical information, etc. can also be plotted and superimposed with other weather parameters for assistance in weather forecasting. Introduction Atmosphere is the gaseous envelope of the earth in which all its flora and fauna survive. As weather is the statement of its physical conditions at an instant, its forecasting is of concern to one and all living over the earth. As such, since time immemorial weather forecasting was a subject of grave concern for the physical scientists. But, due to extremely complex nature of various physical processes of the atmosphere, which lead to weather, these endeavors have always been met with limited success. Various methods were developed and used by meteorologists for weather forecasting. The most

important methods in vogue currently are the conventional Synoptic, and Numerical Weather Prediction (NWP) methods. The former method is human subjective, and the latter is objective and deterministic. Skill of these forecasts can be enhanced through use of GIS by relating different features of the atmosphere and their proper visualization. Conventional synoptic method In this subjective method, conventional forecasting tools like, trend, persistence, Climatology, and analogue of weather systems, are popularly employed. Each of these methods makes use of some basic assumptions for extrapolating the weather into the future. The forecaster blends these extrapolations with his own experience and the location specific weather quirks like topography, land sea distributions etc. None of these methods seems perfect, as the weather sometimes manifest differently, deviating considerably from the basic concepts on which these methods are founded. The inadequate human understanding of the various complex atmospheric processes leading to the weather development itself is one of the major problems associated with this method. NWP method To forecast weather, the NWP method makes use of numerical solutions (high speed super computers are generally required for this task) of complex system of mathematical prognostic equations/models representing both the physical and dynamical processes occurring in the atmosphere. These models are commonly known as Global Circulation Models (GCMs). In order to integrate the GCM forward in time, the model equations need initialization with precise knowledge of the current state or initial conditions of the atmosphere. To achieve this task, global observations of various atmospheric parameters e.g. temperature, wind speed and direction and humidity, made routinely at standard synoptic hours are usually assimilated into the model using a process known as Variation Analysis. The model integrations into the future automatically produce charts of important parameters such as surface pressure, wind circulations, etc. The forecaster interprets these charts for weather forecasting at the locations of his interest. Medium Range Weather Forecasting in India The National Centre for Medium Range Weather Forecasting (NCMRWF) was established in India under the Department of Science and Technology for issuing weather forecasts in the medium range i.e. 3 to 10 days in advance. The GCM used in the Medium-range Analysis Forecast System (MAFS) of the NCMRWF is an adapted version from NCEP (NMC, 1988). It is a Global Spectral Model having T80 horizontal resolution (about 150 km) and 18 layers in the vertical. The model uses climatological boundary conditions for the sea surface temperature, albedo, ice, snow, soil moisture, soil temperature, and roughness length and plant resistance. The MAFS operational at NCMRWF consists of (1) data processing and quality control, (ii) utilization of non-conventional data, (iii) data assimilation, (iv) model integration, (v) post processing and diagnostic studies, and (vi) preparation of location specific forecasts. Limitations of NWP weather forecasts As of today, there are many limitations in the GCM based method of weather forecasting, firstly, the GCM produced charts represent the atmosphere in general only at levels well above the land surface, due to inadequate representation of land surface processes and topography in the model. In addition, errors in the model forecasts are known to be due to 1) inadequate representations of the initial conditions of the atmosphere, 2) inadequate finite resolution of the model - presents difficulty in the representation of orography, giving rise to differences in station levels, 3) Inadequate parameterizations of the boundary layer and other physical processes, and 4) incorrect representation of ground conditions. These lead to deficiencies in the forecast fields, with the surface forecast being particularly erroneous. Owing to the inherent shortcomings of the NWP model forecasts, human interpretations of the meteorological data generated by the models become a necessity. There have been tremendous improvements in the dynamical and statistical models used in NWP in the last few decades, but still, it will be awhile before totally automated forecasts based on unmodified model output, will be of skill comparable with those produced by

human forecasters who modify such output based on their broad meteorological knowledge and forecasting confidence (Doswell et al., 1995). Sousounis et al. (1999) also opines that despite improvements in GCMs, Statistical models, forecast decision making trees, and forecast rules of thumb, etc. in automated weather forecasting, human synoptic interpretation of meteorological information for a particular situation can yield superior results. It was also, reported that the value added by humans over model forecast quality can be significant at times, especially when the forecast involves convective situations or shallow cold air outbreaks, which operational models still do not handle well (Cortinas and Stensrud, 1995). As such, a man machine mix approach is currently advocated for preparation of weather forecasts from GCM runs, especially in the medium range. Keeping the above limitations of NWP based medium range weather forecasts in view, this paper focuses at improving the human component of the man-machine mix philosophy for improving forecast skill by making use of new technological tools like Geographical Information System (GIS) software for plotting, analyses and visualization of observed meteorological parameters, superior to the conventional techniques otherwise followed for the purpose. The GIS software ArcView has been made use of for developing the application tool for the purpose, and demonstrated how this tool can help the human forecaster in his efforts at producing a better forecast from the model output products. Materials and Methods for the Study The GIS used for the application development is the ArcView GIS of ESRI with extensions of Spatial analyst, and Image analyst. The weather data utilized is the T80 model analysis (initial conditions) for the weather parameters viz. Wind Speed, Wind Direction, temperature and Geopotential height at vertical levels of the atmosphere at 850 hPa and 500 hPa at the T80 model grid points (approximately 150 km apart) over the globe. The 5-day weather forecasts for the same parameters based of the above initial conditions (analysis) were made use of as weather forecasts. Discussion The synoptic weather chart is the main tool of the forecaster. A forecaster need analyze, and interpret numerous weather charts of the past period, before he gets a grip of the current weather situation, in order to evolve likely changes in the weather systems as time advances. Weather analysis is the process of drawing isobars, isohyets, isotachs, etc. and locating pressure systems, fronts, etc. on a base map of an area on which the weather observations from a wide area are plotted, following meteorological conventions. The forecast in general is generated from the observations. Fig. 1. provide the locations of the synoptic weather observation stations over the globe.

Figure 1: Locations of global synoptic weather data observing stations (source: ECMWF, U.K.)

At NCMRWF, data are received from thousands of weather observing stations over the globe for weather analysis and forecasting. After plotting the observations following a synoptic model, the analyst checks the chart for erroneous and inconsistent values of weather parameters, frequently, it becomes necessary for the analyst the suspected reading with neighboring stations and or previous observations and analyses or observations at other levels in the vertical. The Arc View plotted maps can be utilized for comparing the values of a particular parameter with the neighboring stations, at different levels and between observations and analyses for past days, for properly assessing the accuracy of the observation for inclusion in the analysis or exclusion The observations coming from the observing stations, through several processing steps are transferred into weather forecasts. First step in this process is to plot the observations over a base map of the region, global or regional according to the area of interest, after removing possible observational and communication errors.

Figure 2: Wind analysis for 500 hPa on 17th Dec. 2000 at 5.30 A. M. over India and neighborhood areas.

Figure 3: Geoptoential height analysis at 850 hPa level on 17th Dec. 2000 at 5.30 A. M. over India and neighborhood areas. The plotted maps are analyzed to bring out different weather systems in action in the atmosphere

at that particular instant of observation. Fig. 2. shows, such an analyzed chart generated using ArcView GIS at NCMRWF for 5.30 A.M. observation time on 17th December 2000. In the figure, the red arrows represent the wind at 500-hPa level of the atmosphere. The hollow head of the arrow represents the direction towards which the wind is blowing. Fig. 3. presents the geopotential height analysis at 850 hPa on the same day and time. The forecaster draws contours or isobars of pressure and marks the fronts, lows highs etc. on the chart. The contouring can be done by Arc View plotted map using the necessary analysis tools. In this application, Troughs, ridges, highs and lows can be drawn on the chart in appropriate color and style, and saved as a part of the chart or a separate view. The successive movement of these systems also can be drawn on the same chart by super imposing the successive charts. The trends and rate of movement of the systems can be studied either directly from the charts or using the theme attribute table.

Fig. 4. Wind flow pattern over India and neighborhood at 500 hPa on 17th Dec. 2000 at 5.30 A.M (IST). The green line represents the low pressure troughs. The same trough as manifested at 850 hPa is also marked in the chart.

Through combining analyses at various levels with past analyses, the weather forecaster endeavors to visualize in his mind the weather processes at work, like the large-scale vertical motion, convection, radiative or advective cooling, etc. Fig. 4. is an ArcView generated map of the wind flow pattern at 500 hPa with the low pressure trough marked in green. The same trough as manifested at 850 hPa also is marked in the same chart by superimposing the 850 hPa wind flow pattern over the 500 hPa wind flow pattern. The locations of the trough at various levels of the atmosphere helps the forecaster in understanding the tilt, if any of the trough with elevation, which has high bearing on the expected weather of the trough. A forecaster studying the sequence of evolution of a weather system in a current chart requires analyzed chart for the previous hour of observation, and indicate the movement of weather systems like centers of low and high pressure, trough and ridges, etc. This is commonly done by marking positions of the centers of the system at the 6-hourly intervals and joining the successive points by a broken line, resulting tracks give ideas on movement of the system. In the Arc View plotted analyzed maps, the time sequence of maps can be super imposed and locations marked. The distance between successive locations is automatically obtained form the tools available. Conventionally, this work is done by the synoptitian using an illuminated tracing or 'light' table. The successive charts are placed one above the other and successive positions of the systems are marked. In figure 5, the movement of the trough along the 500 hPa level during the period 11th to 19th December 2000 is shown. Superimposing the 500 hPa wind flow pattern successively, for these days in the ArcView GIS created the map. Such maps help the forecaster study the speed and

intensity of the trough in the past days for forecasting its behavior in the coming days. In the GIS distance between successive locations of the trough is readily available through the click of the mouse at the locations of interest, for calculation of its speed of progression.

Fig. 5. Locations of a low pressure trough in the westerlies at 500 hPa at 5.30 A. M. IST during 11th to 19th Dec. 2000. Once the forecaster is able to explain the recent weather evolutions taking place, he will be in a position to make prognosis of their future behavior from the knowledge of the physical and dynamical processes taking place in the atmosphere. It is of paramount importance that the forecaster is able to explain the processes realizing the current situation perfectly well before an attempt on forecasting its future behavior. In the processes of generating satisfactory explanation for weather systems, the forecaster need examine the weather charts of different levels of past few days back and forth. There is a necessity of superimposing the analyzed maps of different weather parameters one above the other for studying the physical processes at work in the atmosphere leading to the manifested weather. . In the figure Fig. 6. the specific humidity analysis is superimposed on the wind flow pattern using GIS, to study the moisture distribution and convergence in the atmosphere, in order to identify potential areas for fog, cloud, and rain formation. Conventionally a forecaster does this manually, and connecting between the weather systems available in the charts is done mentally. Success of this - procedure depends on the mental alertness of the forecaster, his experience and knowledge in the subject. In the case of the weather charts generated through GIS, these works can be carried out any number of times with the click of the mouse. The GIS platform provides opportunity for connecting the weather systems physically across the charts of different days and levels.

Fig. 6. Super imposition of the wind flow pattern and specific humidity (gm/kg) at 5.30 A.M. IST

on 17th Dec. 2000. The red arrows show the wind flow, and the white contour lines with blue colored numbers across show the specific humidity distribution. The multicolored background is the surface created out of the specific humidity values.

Fig. 7. Super imposition of the wind flow pattern and specific humidity (gm/kg) at 850 hPa level at 5.30 A.M. IST on 17th Dec. 2000, over the surface topography. The red arrows show the wind flow, and the green contour lines with blue colored numbers across show the specific humidity distribution. The multicolored background is the surface created out of the ten minute interval orography of the area. A forecaster need examine the occurrence of all systems of cloud, precipitation, fog, stratus, drizzle, etc. in relation to orographic influences, coastal influences, etc, and also give special attention to diurnal cycles in weather behavior. Only by long experience and close examination of successive weather charts and particularly of current ones, which can be related by the forecaster to the existing weather in his own area, can ability be acquired in applying to actual weather forecasting the physical principles and other meteorological information underlying the weather process as such. The capability of GIS in superimposing the surface topographic features over the atmospheric analysis for interpretation of the dynamics and physical processed in the atmosphere is given in Fig. 7.

Fig. 8. Super imposition of the wind flow pattern and specific humidity (gm/kg) at 850 hPa level at 5.30 A.M. IST on 17th Dec. 2000, over the surface topography. The red arrows show the wind

flow, and the green contour lines with blue colored numbers across show the specific humidity distribution. The purple colored contours with black numbers across represent the ten minute interval orography of the area. In fig. 8, the same information provided in Fig. 7 is provided with contour values of topography instead of the orographic surface. This figure shows an example of various ways of presentation of the weather parameters in order to study and understand atmosphere with various angles and perspectives. It is also possible to superimpose the various satellite pictures of cloud, moisture etc. over the weather maps for better interpretation and forecasting of weather. Use of GIS in weather forecasting will certainly improve the capability of the meteorologist in forecasting weather with better skill and accuracy in the days to come. Summary A GIS application has been developed using ArcView of ESRI to serve as an aid in the man machine - mix approach for preparation of medium range weather forecasts. Weather and climate are integral parts of the geography of a place. In order to prepare weather forecasts, the forecaster plots information of the atmosphere around the globe on a weather chart. The plotted data is analyzed with the help of contours and surfaces to bring out the weather systems in the atmosphere at various levels. The analyzed weather becomes initial condition for the conventional synoptic weather forecasts and GCMs for prognostication of weather in the coming days. The capability of GIS software in handling the spatial data in an easier way coupled with the different analysis tools available make it a viable tool for its adoption in weather forecasting.

Role of Remote Sensing in Forest Management Abstract The satellite aplications for effective forest management on a more scientific basis commensurating with the priorities set at state, District and Micro levels studies. The shift in priority of forest management towards ecologically sustainable forest resources management call for reliable spatial database with a provision to update and retrieve for management decisions at various levels. The application of satellite data for various priorities & objectives leading to resources assessment have been discussed. The utilisation of GIS for data base creation and requirement of forest resources information system involving effective inventory data analysis packages supporting volume yield and cull factor analysis has been discussed in detail. The concept of NRIS in the country using remote sensing has been emphasised. Introduction Historically Forestry has been concerned mainly with the assessment of timber resources and the management and utilisation of closed forests for the production of wood. Actention was occassionally given to the other resources of the land sustaining closed forest. In the 19th century some working plant in continental Europe considered not only timber production but also wild life and or for protection. Forestry in urope based on conifers was also aidly expanded, but in the tropics, subtropics and north America, the closed natural forests were increasingly exploited for timber. During the british regime, the forest survey and sound forest management was extended to all lands bearing trees in India and to minor forest products (e.g. gum arabic). As early as in 1856 a forest department was established in Burma by the British and the concepts of environmental Forestrywere being applied in India before the end of the nineteennth century. As viewed by the FAO established by the Bretton wood conference in 1944, forest have become widely recognised as " all lands bearing a vegetation association dominated by trees of any size, exploited or not capable of producing wood or other products, of exerting an influence on climate or on the water regime or providing shelter for live stock and wildlife (Loetsch and Holler 1964). It was not, however until the oil crisis of 1973 that world wide interest was re-focussed on the long-standing

importance of forests as the major source of energy in may countries. Arecent European study (ECE, 1986) Suggest that over 40% of one votoe european Forests is used as a source of energy and that energy remains the single most important use of wood in volume terms. With the uncertainity of energy prices in the future and of the growth world wide in the consumption of energy, predicted to exceed 2% a year , the demand for wood energy can be expected continued increasing. Within a decade the most urgent need of many local communities in the developing countries will be the massive harnessing of their resources to renew forest supplied through plantations and agro- Forestry, and where preactised the "Slash - and burn" of natural forests based on short cutting cycles. In response to the situation remote sensing can be expected to be used increasingly to collect urgently needed data, especially as related to monitoring changes in forest cover, assessing landus and frorest land degradation, evaluationg the productivity of the land and providing information not only for forest inventory but also for direct inputs to forest management and strategic planning. The increased awareness due to mounting population exerting pressure on forests for fuel and timber besides grazing for cattle. This has led to most of India's forest left with poor carrying capacity. The forests began to dwindle. And now the country have much less of its land area under forest cover than is required to maintain its environmental stability and ecological security. The extent of biotic pressure on forests could be judged from the fact that with less than 2% of the total forests areas in the world, India supports 15% of the world population and nearly 14% of the cattle population. Considering the fact, India is currently carrying out biennial monitoring of forest cover using satellite data on 1:250,000 scale. However the system of forest management in India is almost 120 years old and remained as a state subject. The policy formulation and strategic planning is at the central level. For effective management of forest resources the various basic requirements and priorities are essentially of three tier system i.e., State level District level and Micro level information requirements. The priorities are (1) distribution (3) plantation monitoring (4) estimation of forest growing stock (5) forest inventory and volume estimation (6) preparation of stock tables and yield calculation (7) preparation of treatment/ zonation areas (8) assessment of ecological and bio-diversity (9) forest change and conversion studies (10) Forest damage assessment due to forest fires (11) Grassland identification & productivity assessments (12) biomass and fuel wood assessments (13) GIS applications (14) implementation of forest resources in formation system and (15) future thrust areas on forecasting and prediction models using remote sensing and other collateral data. The present scenario of remote sensing applications in forest management is widely applied in the areas of: Forest Cover Monitoring/ Surveillance The forest cover at the national level is being biennially monitored using remote sensing data and it is estimated that India has 19.47% of forest cover (1989-91) out of the total expected 33% of forest cover as per India's forest policy. So far Forest Survey of India (FSI) has broughtout sucessfully four assessments on the status of forest cover in India (Table.) This information is more relevant in the context of assessing rate of degradation grossly at the state/district level in terms of closed and open forests. However, the extended use of this information for effective utilisation for the management purpose at the state level could be better achieved by supplementing the data each reserve forest boundaries thereby enlisting the districts having ore degraded areas. This approach enables to prepare treatment area maps at the state level which would serve as a strategic plan inputs for prioritisation and categorisation of areas for better silvicultural practics.

Table 1 Status of Forest Cover in India (Based on Satellite Remote Sensing) Area in million Hectares within brackets Forest Category 1972-75 1981-83 1985-87 1987-89 1989-91 Dense/

14.12

10.99

11.51

11.71

11.72

Closed

(46.45)

(36.14)

(37.84)

(38.50)

(38.55)

7.38

8.41

7.83

7.60

7.61

(24.28)

(27.65)

(25.74)

(24.99)

(25.04)

0.10

0.12

0.13

0.13

0.13

(0.30)

(0.40)

(0.42)

(0.42)

(0.42)

21.60 (71.03)

19.52 (64.20)

19.47 (64.01)

19.44 (63.92)

19.47 (64.01)

Open

Mangrove Total%

The extended use surveillance maps for the treatment area maps would need a serious consideration by all the state forest departments for prioritisation: CLOSED FORESTS (40% and above crown density) treatment area I for consideration to conservation zone. OPEN FORESTS (less than 40% crown density) treatment area II for consideration as forest produce zone for careful management. DEGRADED FORESTS (less than 10% crown density) treatmen area III for gap planting, JFM activities by peoples involvement. Thus for the above treatment area maps the satellite based remote sensing especiallyusing the digital methods would prove to be an effecctive tool and in generation of information within a short span of ltime and a digital data base. Forest Type Mapping and Assessment of Distribution: India has been divided into broadly sixteen forest types by Champion and Seth (1968) based on rainfall and altitude. However, with changing climate and man's impact on environment particularly in forests, change the composition of tree species resulting spatial disturbances on the occurrence of forest types. In this context the study of spatial ditribution of forest types. In this context the study of spatial distribution of forest types would help greatly in forest management for accounting the changes that have resulted in the chaning quality and composition of forests. The case studies carried out in parts of Western Gahts Viz. Coorg district and Uttar Kanara District, brings out the feasibility of satellite aplications in preparation of spatial forest maps at the block level. The changing scenario of natural forests into artificial forests could well be discerned by generation of a baseline data of forest types which are independent of each district. The availability of such maps have greater ecological significance and provide better insights to the working plan officials as to what type of species need to be introduced by replacement of natural forests or regener4ation of degraded forests in the area on a more scientific and reliable distribution at the block level on 1:50 ,000 scale would prove an essential component in the scientific management of forests. Forest Stock Mappping and Preparation of Working Plan Inputs The satellite data analysis is found adequate for differentiating three levels of stocking i.e. closed (40 and above), open (10-40%) and degraded (below 10%) crown cover classes on 1:250,000 scale. However, the property of stocking levels generally required at the working plan level is of 20% crown cover intervals, The adoption of spectral based stock maps appear get saturated beyond40% crown cover, However, in certain areas of Madhya pradesh it is found, based on tone

and texture associated with spectral separability as a function of time has been found suitable to provide 40 60% stocking level in addition. This study indicated greater scope for future exploitation and utilisation of various algorithms for optimising time window and spectral bands may be feasible to explore satellite based forest stock map preparation. The studies using NDVI as a function of stocking level needs review as it provide information pixel level on the vigour of the canopy with lwss degree structural relationship of canopy closure. The studies within NRSA indicate the saturation of NDVI levels beyond 40% cover is observed. However the development of suitable algorithms using textureal function might prove to be an effective method for quick assessment of stocking levels. The terrain contributed noise due to change in aspect and elevation could also be integrated by development of suitable digital elevation models as background to minimise the noise for preparation of dependable stock maps. While the spectral based models appear feasible the spatial resolution would contribute only interms of small patches and their associated stocking levels. With the experience on IRS LISS II data, is adequate for accounting canopy closure level as that much spatial resolution would be minimum required as a spectral function from a representable area of the forests for coorelations on the ground cover conditions. The studies carried out in Uttar Kannara by comparitive evaluation of detailed stock map prepared from aerial photograbphy and confirmity and confidence in adopting satellite data for preparation of stock maps with suitable modifications. However, the satellite based stock maps showed. The aggregation of patches due to the limitation of resolution and contribution of terrain noise, In any case the level of information obtained with respect to stocking is of the order of 70% and above. The study broughtout the scope of reconnaisance level stock map preparations at the district level for preparation of management plans. Forest Inventory and Sampling The forest enumeration and surveying is generally carried out at the district level for detailed working plan inputs preparation generally on 1:15,840 (4' = 1 mile) on predecided percent area enumeration (5% , 10% etc.) The working plan enumeration inputs is based on chain surveys across the forests on a systematic way. The conventional way of systematic sampling suffer due to accounting various strata and burdened with intense field work & expensive procedures, The satellite data facilitate in generation of primary stratifucation units at the district level either throudh use of forest density maps or forest type classification it is possible to stratify the area into homogenous forest strata. Based on the apriori knowledge the minimum sample size can be selected and the field inventory can be accomplished by suitable proportional allocation of samples in all the strata The stratified sampling procedures provide a reliable quantification of forest resources depending on the objective set during the inventory. The study carried out in parts of western Ghats of Karnataka demonstrated the feasibility and to build volume from the enumerated data on a time & cost effective manner. The Forest Volume Estimation and Generation of Volume Tables The satellite based multi phase approach forest inventories with defined objectives provide ample data for further processing and computation of volume and yield tables. The enumerated data during the inventory could be systematically organised strata wise ad a suitable local and stand regressions could be generated fr further computation of species wise volumes. The predominant species volume equations thus generated would form the base for computation of tatal standing volume based on the plot enumeration data. The inventory data analysis in the Uttar kanara Circle using satellite base stratification sampling approaches have yielded better observations in development of local and stand tables and to compute stand volume. The standing volume information through inventory data analysis would form as a baseling data to bring out correlation with ground crown density maps. This in a way to say once the relationships are established which are generally local specific with respect to volume and density it is possible to estimate the total growing stock of the area by generation of stack maps and conversion through establised volume functions. The experience in generation of such stock to volume estimations in western Gats have shown promissing to explore to avoid cumber some, field inventories. The study also

discussed in detail the importance of cull factor for estimating merchantable yield. Stock Tables Prepartion and Yield Calculation From the stratifield sampling and inventory data analysis it is feasible to calculate and generate stock tables with respect to number of species diameter and height wise distribution. Such an information with the available knowledge of minimum girth area for extraction it is possible to calculate the yield and also to compute the annual coupes based on equiproductive areas. The technique of data analysis and generation of stock tables developed in parts working plans project have revealed greater scope for extending towards management information system specifically for the working plans at district level on stock tables and yield calculations. Ecological Consideration and Zonation of Forests With the increased pressure on forest all over the world as well as in India the growing concern of forest management has shown shift in its priority from production foresty to conservation Forestry. In the light of thi the scientific management of forest and categorisation of the area into different zones have been adopted by the Karantaka State forest department as part of Western Ghats Eco-restoration project. Towards this NRSA and Karnataka Forest Department jointly carrying out a project in a area of 10,280 sq. km in Uttar Kanara forest circle by generation of multi-thematic information on 1:25,000 scale using aero-space techniques. The thematic information generated are forest density and height maps, forest type maps, slope and aspect maps, drainage map upto first order channels, volume class maps besides consultation of contour maps with the available topographical sheets. The availability of such an enormous data base when feed into the Geographic Information System enhances interpretability of the data and to classify the area into different zones required for effective forests management practices on a scientific footing. Accordingly the forests are proposed for categorization of zones for specific management practices, the zonation is the process of describing the physical consequences of the management plans, which have been understood for sustainable forests resources in the area. It is essentially link between management practices. The zonation in the process of describing the physical consequences of the management plans which have been understood for sustainable forests resources in the area. It is essentially link between management objectives and physical operations on the ground. Accordingly using multi-thematic information the zonation of any area could be prepared with the below given logic. (Table 2) The below given process com The study carried out in the parts of Western Ghats showed adequacy of the tool and approach. Table 2 Forest Zonation Matrix RF D

H(M) Slope% Elevation (M) Village

Type Managroves Grassland

Zone 1 +

4.5

>20

>50

High

Zone 2 +

3.5

>20

>35-50 Medium

Sparse/Nill Any Type

Zone 3 +

2.3

>20

>35-50 Medium

Inhabited

Any Type

Zone 4 +

<0.25 All

>35

Habitated

-Do-

Rolling

Nil+

Zone 5 Reve All Lands Falling in "C" and "D" Lands

W. L

Remote Sensing and Biodiversity Studies The forest management while through its forest inventory and zonation of the area can revolve ecologically sensitive and diversity wish rich areas through use of satellite data applications in conjunctive use of other ancillary data discussed as above in the zonation. It is estimated that the tree diversity is estimated to around 200 species in the northern parts as Western Ghats exhibited a great diversity between the plots and along the gradients. The extended application of forest

inventory and enumeration including shrub layer and herb layer would enhance forest management system for preservation of ecologically rich zones and to account diversity of the areas. The initial probabilistic diversity zones should be narrow down using satellite data and the consistency of patchiness as a function of landscape dynamics could be used as an element for bio-diversity studies. Forestry Conversion Studies With the rapid destruction of forests and encroachment the use of multi-temporal satellite data using digit analysis procedure provide spatial change maps by image differencing methods and logical operations. The study carried out using multi-temporal satellite data of 1983 & 1993 in parts of Andhra Pradesh of Adilabad District showed the area decreased upto 25% of the total area studied whereas improvement in the quality of the area is only 6-7% out of the 1,512 sq. km area studied, The methodology recommends for detailed investigations at district level for accounting forest changes over the years within the reserved forests areas. Forest Fire Damange The use of multi-mission IRS data has demonstrated amply the feasibility to identify forest ground fire damaged areas with the combined use of IRS 1A and IRS 1B. The studies carried out during 1991 in parts of Nagarghole wild life sanctuary facilitated accounting damage of an area of 68 sq. km. Quite recently in the month of March 1994 the central part of the India in the Simplipal reserve forests the extent of fire damage was assessed using IRS 1B and estimated the ground fire damage to an area of 600 sq. km against 200 sq. km reported. The use of in season data would enhance capability in identifying hot spot areas which are annually prone to fires could be of use to the forest management for mounting fire operation measures during the vulnerable periods. GIS Applications in Forestry The scientific and effective forest management information could be operationalised using the GIS approach at district level as a functional unit. The organization of data base, data inputting, updating, retrieval and analysis for specific purposes and to obtain outputs apparently is feasible cost effectively at the district level rather than aiming at state level as a central facility. The data base in GIS should necessarily preceded by generation of reliable spatial maps preferably on 1:25.000 scale to begin with which can be later inputted to GIS for proper data utilization and to obtain outputs with greater degree of accuracy relevant for district level management decision. The organization of data feasibility adopting micro scale to macro scale may be a viable approach rather than adopting top to bottom approach stasr6ting with coarse resolution data which may fail to reveal any meaningful outputs required at the working level. The organization and aggregation of data base at district level would enhance efficient forest working most needed in the district level. The use of GIS at taluk level for preparation of zonation map revealed micro scale details without sacrificing accuracies for management decisions. While the GIS data base is being parallel evolved simultaneously with the improved spatial maps the requirement on development of forest resources information system at the district level in the form of MIS should form a major management aspect which facilitate aggregation at the state level for strategic decisions The concept of National Natural Resources Information System (NRIS) as part of NNRMS activity of Dept. Of Space would be the fore runner in evolving a reliable operational forest management information system.