Home Articles GIS for planning environmentally sustainable activities in Kulathupuzha reserve forest, Kerala, India

GIS for planning environmentally sustainable activities in Kulathupuzha reserve forest, Kerala, India

A. Deva Kumar Varma
World Bank Project Cell
Forest Headquarters, Trivandrum, Kerala State.
Tel: 0471 – 314610
[email protected]

Planning and management of forests form an integral part of environmental planning. Forests play a vital role in maintaining a balanced environment not only on a regional but also on a global scale. This is particularly so in the case of tropical forests which are known to maintain a unique climatic microcosm. Indiscriminate exploitation within forested areas over the years, in the name of development and otherwise, has lead to serious degradation. And, Geographical Information System (GIS) is increasingly being used to prepare purposeful plans for maintaining a healthy environment for posterity.

GIS technology is being put to use by the Kerala Forest Department (KFD) with World Bank assistance for preparing management plans within its administrative domain. The key areas where GIS technology is employed are (1) demarcation of environmentally degraded areas including potential ones, and (2) develop models to locate centers of viable economic activity to ease pressure on the environment.

At KFD, an integrated system of GIS and remote sensing is used for the demarcation of environmentally sensitive areas. Actual demarcation is performed by GIS based on predefined criteria. The criteria is so defined that it will result in three zones viz., degraded, semi-degraded and no degradation. Plans are prescribed for these three zones separately taking into account the spatial characteristics of each zone.

Economic sustainability is a key factor responsible for environmental degradation, due mostly to over exploitation. GIS is looked upon to provide solutions to wean away people living on the fringes from unsustainable activities. One way to address the issue is to take a relook at the existing centers of economic activity or plan for new ones where none exists. GIS is utilised for doing just that, with the help of spatial modelling coupled with small area geodemographics.

The State of Kerala is endowed with a rich tropical forest cover that is well above the national average and home to some of the rarest and finest varieties of flora and fauna. This vast and fragile resource, a microcosm in its own right, has to be carefully managed for our well being as it plays a vital role in maintaining a balanced environment not only on a regional but also on a global scale. Undoubtedly, the challenge is unique and calls for highly skilled management pratices particularly as they are under threat from unsustaintable activities (Raghunathan, 1994). With a growing awareness that our forests form a part of the whole system responsible for maintaining environmental health, planning and management of forests is increasingly being viewed as an integral part of environmental planning.

The management and conservation of these resources are the responsibilty of the Kerala Forest Department. So far, it has been able to take up these challenges in its stride exihibiting a rare mixture of fine craftmanship and technological ingenuity. As part of its continued effort to keep abreast with modern technological advancements the Department is now embarked upon an ambitious project of inducting GIS and remote sensing tools in its arsenal to provide for economic, fast and reliable information on ground realities to achieve the goal of drawing up purposeful management plans. The project is being implemented with World Bank aid as part of its institutional capacity building programme.

Kulathupuzha Reserve Forest
Kulathupuzha forms a part of the southern most reserve forests of the State. Falling in the SOI sheet No. 58 H/1 Kulathupuzha reserve covers an area under 1000 sq.km. Its forest constitutes predominantly of tropical wet – and semi – evergreens and moist deciduous types. Apart from settlements some parts are occupied by departmental plantations mainly of teak, eucalyptus and acacia. The plantations are grown by planting sapplings on cleared natural forests. Plantations are raised to sustain and supplement the timber needs of a few industries in the State.

Figure 1. Map showing major reserves forests in Kerala.




A major factor contributing towards degradation is the anthropogenic activities from settlers on the forest fringe. Settlers include the indigenous people, pattayam holders (non-indigenous people awarded land ownership by the government) and encroachers. Indigenous people meet all their needs from the surrounding forests and for their livelihood forage into the forest to collect forest produce which are sold in local markets either directly or through intermediaries. Settlers engage in such activities as cattle rearing, farming, clearing, etc., which in most cases are destructive to the surrounding natural forests. At times, especially in the height of summer, forest fires are not uncommon and the cause can be, very often than not, traced to their activities. Such reckless activities when combined with questionable health of many plantations result in a picture, not so colourful, of the state of one of the finest tropical forests in the country.

As a first step towards an earnest effort to monitor and strengthen the forests of Kerala for sustainable development, a combination of remote sensing and geographical information systems is being put in place for Kulathupuzha. The new system will aid in developing micro-level plans for the management of forests. It is also envisaged to bring together small area geodemographics and GIS to leverage the existing programmes and institutions. The methodology identified is briefly described below.

Remote sensing and GIS
In earlier days practical difficulty in monitoring forested areas were many and, even if one were to do so successfully it may take a while before the data gets compiled to make any meaningful decision. This was exploited by unscrupulous traders in gathering forest produce and other items from the forest in an unsustainable manner. But today, the integrated approach utilising remote sensing and GIS has the capability not only to view and gather information over a relatively large area but also to assist in taking better decisions, both in a short time.. This approach is adopted in Kulathupuzha successfully for improved data collection on ground realities using remotely sensed data from IRS-1C satellite.

Imageries from IRS-1C are read for signs of degradation within the forest domain. Zones of degradation are marked from the imagery based on canopy density. Their relationship is widely recognised to be a direct one. Higher the density lesser the degradation and vice versa (ie., lower the density closer it is towards degradation). Crown density can, thus, be directly translated to degree of degradation. One of the aspects exploited very successfully in participatory management is this relationship in an imagery whereby it is easy for the stock holders to visualise the magnitude of degradation (de Boer and Roche, 1998). The three fold zonation followed in this study is more or less similar to the standards followed by the Forest Survey of India, viz., those above 40% is taken as undisturbed, less than 10% as fully disturbed (ie., degraded) and intermediate values as moderately disturbed. Caution, however, is exercised in applying this criteria uniformly as there are areas within natural forests where the crown density could be less but of reasons unrelated to those described above. It could possibly be due to temporal variation (ie., period in which the imagery was acquired), locations of natural reed breaks or even high altitude grasslands. To avoid such misjudgements the forest types were classified into 6 resource types – grasslands, reed breaks and plantations / estates, besides the 3 forest types mentioned earlier. The forest areas are thus, in the first place, classified into 5 types while reading satellite data before attempting to categorise them into different zones. Classification is performed by identifying representative sample plots for each type in the field and their locations precisely noted using a GPS. GPS readings are, subsequently, transferred onto the imagery and their spectral signatures studied, to identified similar types elsewhere in the area.

The objective of the whole exercise being to develop management plans on a micro-level the chosen basic unit is the drainage basin, the natural delimiter. Size or resolution of each unit has been fixed at third order basin or watershed (naming convention as proposed by Horton, 1945). Forested areas categorised and demarcated on a watershed basis are vectorised and transferred to a GIS. Vectorised data on transfer carries along as attributes of its geometry the forest type and its inferred state.

The data, input into a GIS, is stored in a geodatabase (ESRI, 1999). For each watershed in the geodatabase there is a separate feature dataset. Database connection for each feature dataset holds additional data collected from the field. This database contains information on soil, slope, rainfall, regeneration, etc. Within GIS the information is collectively analysed and the degree to which each watershed is environmentally affected is mapped. For example, if forest cover is less than 10%, top soil is poor and a slope higher than moderate (say, above 20 degrees) then the area will be marked as degraded.

Environmental degradation in each watershed is tackled on the basis of established silvicultural practices and is a function of forest type, extent of degradation and the physical conditions existing in the watershed. Selection criteria for each forest type and degree of degradation is built into spatial queries and when executed in a GIS would produce a map clearly identifying which areas within each watershed needs what type of remedial measure.




Spatial Modelling
It has long been recognised that unless economic security and empowerment are assured for the community living around the forests, measures aimed at conservation or sustainable development is unlikely to take off in a meaningful way (Hobley, 1996). A number of institutions and projects are underway to address these aspects by involving them in the management of forests and to engage them in alternate economic activitives that reduce their dependency on forests. An innovative attempt in the study is the introduction of spatial modelling, which is widely applied to problems in economics, geography, engineering and the social sciences. The model, coupled with small area geodemographics, is used to predict the source and destination of people based on the assumption that movement of people between nearby places is more than that between far away places. Furthermore, flow to a particular destination can be increased, obviously, by increasing its attractiveness.

The model is applied in the study to locate an ideal center from a set of centers of economic activity and to identify the source of labour for a given vocational activity. For both applications small area geodemographics is utilised for supplying necessary data for the model parameters viz., attractiveness, distance decay and demand. For the distance decay exponent function with a value of 2 is used in the calculation.

Modelling is performed on settlement feature classes that exist in the geodatabase. GIS is utilised as it can provide an efficient and effective tool to implement this model. The database for each feature class consists of at least three items, one indicating the number of people and the other two the attractiveness and capacity, respectively, at each suggested location in the settlement. What it does is to address the issue by taking a relook at the existing centers of economic activity or plan for new ones where none exists. The advantage of this modelling is to spot an ideal site in a list that is likely to be popular (easily accessible to all) among all settlers. Such spots would of interest to authorities on the look out for siting markets, training centres, etc. A weightage is given to households that possess a particular property or quality deemed significant for the site in question. For instance, while siting a vocational training centre minimum educational qualification is a weightage that is assigned to the household so that the site would favour the target groups. Also, the model helps to identify sources or areas from where settlers are expected to attend a given activity. An example is the issue of locating an educational institution.

Presently, the models are not sufficient in number to warrant a comment on the success of this model. Gathering of geodemographic data for the whole settlement in the area is still on. At this stage, this phase of the study is not fully completed.

The Kerala Forest Department with the help of World Bank is putting in place a remote sensing and GIS system for monitoring and mangement of Kerala’s forest resources in a phased manner. To set the stage Kulathupuzha reserve forest is selected for the study and implementation in its first phase.

IRS-1C satellite imageries, utilised to map the various forest types and their state, are integrated with a GIS, which is a repository holding additional data, to identify environmentally degraded areas based on a set of criteria within Kulathupuzha reserve.

To increase the effectiveness and efficiency of projects aimed at improving the economic security and / or sustainable development an innovative approach is attempted with spatial modelling integrated with small area geodemographics utilising GIS. Though the study is still on-going and, perhaps, it is too early to judge its performance the model is looked upon to provide a means for identifying locations that will carry forward and fulfill the desired objectives of such similar missions.

I sincerely acknowledge the World Bank and, other members of the project cell for their sincere and kind cooperation. The views expressed here need not necessary reflect the views of the Department.


  • ESRI (1999) Building a Geodatabase
  • Hobley, M (1996) ‘Participatory Forestry: The process of Change in India and Nepal’ (ODI: London).
  • Mather, R. de Boer, M. Gurung, M. Roche, N. (1998) ‘Aerial Photographs and ‘Photo-Maps’ for Community Forestry’ in Rural Development Forestry Network Paper 23e Summer 1998 (ODI: London)
  • Raghunathan, M. (1994) Conservation of biological diversity in India: an approach, World Resources Institute.