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Application of Satellite Based Remote Sensing for Monitoring and Mapping of India’s Forest and Tree Cover
Flow chart of methodology of dynamic forest cover mapping using remote
sensing is shown in figure-1
Figure1- Flow chart of Forest cover mapping using remote sensing
The output includes forest cover maps on 1:50,000 scale. These maps show forest
cover in three classes- (i) Dense forest, having canopy density of more than 40%, (ii)
Open Forests with canopy density between 10-40% and (iii) Scrub which are forest areas
having less than 10% canopy density. These maps are also generated for district and
States/Union Territories by overlaying the respective District/State/UT administrative
boundary. Area under forest cover at District/State/country level is then assessed. Change
maps are also prepared to depict changes taking place under different land cover classes.
In its latest assessment of 2001, taking advantage of advancements in remote sensing and improvement in digital interpretation qualities, FSI has provided a much
more comprehensive status of forest cover in the country than in the previous
assessments. Some of the new features incorporated in this assessment are:
- For the first time FSI has interpreted the satellite data of the entire country digitally.
In earlier estimates, interpretation has been largely visual. Digital interpretation has
the advantage of overcoming subjectivity prevalent in visual method.
- Due to absorption of digital image processing technique, it has been possible for FSI
to interpret the data on 1:50,000 scale. This has resulted in providing more realistic
information on forest cover as areas having forest cover down to 1 ha could be
delineated while in earlier assessments, forest cover down to 25 ha could only be
delineated. Similarly blanks down to 1 ha within forested areas can be separated. The
entire exercise has resulted in new base-line information on forest cover.
- As perennial woody vegetation (including bamboos, palms, coconut, apple, mango
etc.) has been treated as tree and thus all lands with tree crops, such as agro-forestry
plantations, fruit orchards, tea and coffee estates with trees etc., have been included in
forest cover.
- Mangrove cover has been classified into dense and open mangrove cover. The area of
mangrove cover so assessed has been merged in the respective area figures of dense
and open forest cover.
- A classification is not complete unless its accuracy is assessed. For the first time an
independent and systematic assessment of accuracy of satellite data interpretation was
made. An error matrix was generated by comparing classified forest cover with the
actual forest cover on the ground at 3,608 locations spread throughout the country.
High resolution PAN data was used as proxy for ground verification. The overall
accuracy of forest cover classification was found to be 95.9%.
- Though forest cover in areas as less as 1 ha in extent could be assessed using satellite
data, significant tree cover exists in patches of less than 1 ha and in linear shapes
along roads, canals, etc. and scattered trees that can not be assessed using remote
sensing. An attempt is made for the first time to assess such tree cover using ground
inventory method.
The abstract of forest cover assessment 2001 is given in Table 1.
Table 1: Forest Cover as per 2001 assessment
| Class | Area (km2) | Percent of Geographic Area |
| Forest Cover |
| a) Dense | 416,809 | 12.68 |
| b) Open | 258,729 | 7.87 |
| Total Forest Cover* | 675,538 | 20.55 |
| Non-forest |
| Scrub | 47,318 | 1.44 |
| Total Non-forest** | 2,611,725 | 79.45 |
| Total Geographic Area | 3,287,263 | 100.00 |
*includes 4,482 km2 under mangroves (0.14 percent of country’s geographic area)
**includes scrub
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