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Maharashtra working plan incorporates GIS


Application of GIS to Working Plan preparation
Forestry being a long term business, foresters have been preparing perspective plans for minimum time horizons of 10 to 15 years. The smallest unit of management in India is considered a compartment. Based on physiography and crop characteristics each compartment is allotted to a particular working circle and a package of management practices is prescribed for each working circle. The underlying assumption in this conventional approach is that physiographic features and crop are uniform in the whole compartment. This was true to some extent till about half a century ago when pressures on forests were not as high as these are today. If we look at the compartments today we find a lot of variability within each compartment both in terms of the crop as well as the other conditions prevailing there. To illustrate the point a typical forest cover map is shown.



The area shown in the map is from North Dhulia Forest Division. Dark green colour represents well-stocked forest, light green colour signifies under-stocked forest and yellow colour is for barren patches. Such a situation is very common in all our forests these days. Such varied conditions cannot be addressed to properly by allotting the compartment as a unit to any particular working circle. This is especially so when we are trying to step up our effort in the direction of intensive management. Solution lies in prescribing many types of treatments within each compartment by delineating it into sub-units. But unlike compartments these sub-units of the compartment cannot be of permanent nature and hence cannot be permanently delineated on the ground. Such a concept has been adopted in our approach to working plans for the past some years. Working plan officer prescribes that each coupe be delineated into the following types of areas:
  • Areas with more than 25° slope
  • 20 m wide buffer along the drainage network
  • Under stocked areas (crown density 0.1 to 0.4)
  • Blanks (crown density <0.1)
  • Well stocked areas (crown density >0.4)


Different type of treatment is specified for each of the above categories of areas. The actual task of judging and delineating the areas on the ground is left to the last man in the field. Each division has hundreds of coupes due for working each year hence the above task is assigned to many persons with varying degrees of experience and knowledge. The treatment map is prepared based on ocular estimation. This process results in rather inaccurate and inconsistent treatment maps. All the treatments are supposed to be carried out according to these treatment maps. Hence the weakness of the present practice is self-evident.

Working plan officer too has to base his calculations on rough estimations, as he does not have very accurate and consistent stock maps to work with. Moreover the input for him is rather fixed and it is almost impossible for him to generate many alternate strategies before picking the best ones.

This task of preparation of treatment maps/ stock maps can be achieved quickly with much more accuracy and consistency by using remotely sensed data in GIS environment. Working plan officers can not only provide the territorial staff with accurate treatment maps but they can improve their own calculations of yield etc. also. This has been achieved for more than half a dozen divisions in the state of Maharashtra and all future revisions of working plans are proposed to be based on this approach.

Besides delineating the coupe areas on the basis of crown density and physiographic features working plan officer requires an extensive forest inventory data to base his prescriptions in terms of different treatments. We are using random start systematic line sample plot method for inventory data collection. The whole area of the division is divided into grids of 600m X 600m on the Survey of India topo sheets. These maps are provided to the field inventory units. They locate these points on the ground by chain & compass survey and then layout sample plots for tree enumeration and regeneration survey. So for every 36 ha. area on the ground we have a sample plot.

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