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Forest Survey of India says forest cover estimate is done with field data tallied with Satellitebased Interpretation
Amid criticism from experts of its methodology to map forest cover in the country, the Forest Survey of India (FSI) has said that the forest cover is estimated from the field inventory data, which corroborate the figures obtained from satellite-based interpretation. It claimed that the criticism of its findings was based on perception and done more to generate sensation.
Sticking to its assessment which shows how both forest and tree cover increased in India in the past two years, taking the total green cover to nearly one-fourth of the country’s geographical area (GA) in 2021, the FSI has elaborated on how it did its biennial survey, based on globallyaccepted standards, which was backed by an elaborate ground-truthing exercise.
FSI’s ‘India State of Forest Report (ISFR), 2021’ was released by Environment minister Bhupender Yadav, which shows that ‘forests’ and ‘trees outside recorded forest areas’, put together, reported an increase of 2,261 sq km (0.3%) last year compared to the previous assessment in 2019. The increase took the overall green cover to 8,09,537 sq km (24.6% of GA) which includes 7,13,789 sq km of forest cover (21.7% of GA).
Critics, however, questioned the FSI’s claim with one of them, M D Madhusudan, ecologist and cofounder of the Nature Conservation Foundation, even highlighting that the purported gains come largely from FSI’s “problematic and perverse redefinition of ‘forest’ to include tea gardens, coconut plantations, urban built-up areas, native grasslands wrecked by invasive trees, and even treeless desert scrub”. In his social media post, he said, “There is little evidence to show that India’s natural forest cover has actually increased. In fact, it has very likely declined.”
Calling such remarks “factually incorrect”, the FSI said it carried out an inventory of forest and trees outside forest on adequate sample points spread over the entire country. “The forest cover is also estimated from the field inventory data which corroborate the figures of forest cover obtained from satellite-based interpretation. Change polygons are ground-truthed by FSI as well as state governments, then only is the interpretation accepted,” it said.
The FSI emphasised that it carries out “wall to wall forest cover mapping of the country”, using remote sensing based methodology at two year intervals, and noted that the points raised by the critics were their “perception”.
On critics’ point on counting of tea gardens and coconut plantations as forest, the FSI flagged the definition of ‘forest cover’, used in the ISFR, where it is defined as “all lands, more than one hectare in area, with a tree canopy density of more than 10% irrespective of ownership and legal status. Such lands may not necessarily be a recorded forest area. It also includes orchards, bamboo, palm etc.”
Referring to this globally accepted definition, the FSI said, “Those areas of tea gardens, which satisfy the above conditions and are captured by the satellite sensor are treated as forest cover, mainly due to the tree cover existing there. Depending upon the canopy density, they are categorised as ‘open forest’, ‘moderately dense forest’ and ‘very dense forest’.”
On the critics’ point that the ISFR, bizarrely, not only report forest cover for a new assessment year, but often go back and tweak forest cover values of previous years, the FSI said, “The experience gained over the years is helpful in better interpretation in successive cycles. The improved quality of data, better interpretation, extensive ground truthing and geographical area corrections resulted in revised estimates of previous cycles. Thus whenever, it is felt that we have better data for the previous cycle, the estimates are revised in order to give a true picture of real change.”
There are many experts who, in fact, supported FSI’s scientific method of assessment and questioned the critics, saying most of the points raised by them are “rooted in a lack of understanding of the difference between forest cover and tree cover on one hand and, and on the other hand, the need for retrospective corrections in assessments necessitated by advances in remote sensing technology that have brought in increased accuracy in assessments”.
“Tea estates have been reported under tree cover (and not forest cover) because most tea plantations have shade trees raised to manage sunshine on the tea bushes. Wherever these shade trees provide more than 10% cover these are included in the tree cover,” said forestry expert and retired Indian Forest Service (IFS) officer Promode Kant.
“Coffee and tea, coconut, and farm forestry plantations also provide ecological services much better than barren land in addition to providing livelihood systems to local people. Nowhere in the report, they have been equated with natural forests,” said Bala Prasad, another retired IFS officer and former additional secretary, Panchayati Raj.https://timesofindia.indiatimes.com
China has released a new comprehensive geologic map of the moon to a scale of 1:2,500,000, the most detailed to date. Chinese scientists from multiple research institutes and universities have created the high resolution topographic map based on data from China’s lunar exploration Chang’e project and other data and research findings from international organizations.
The map includes 12,341 impact craters, 81 impact basins, 17 rock types and 14 types of structures, providing abundant information about geology of the moon and its evolution. It is expected to make a great contribution to scientific research, exploration and landing site selection on the moon. The Institute of Geochemistry of Chinese Academy of Sciences has led the project, along with other organizations such as Chinese Academy of Geological Science, China University of Geosciences and Shandong University. Previously, USGS Astrogeology Science Center completed and released a moon map to a scale of 1:5,000,000 in 2020. https://news.cgtn.com
RailTel Corporation of India Ltd., Ministry of Railways and Esri India have signed an MoU to provide Cloudbased GIS Solutions to their users in the ‘Government Sector’. This collaboration will address the strong emerging demand for ‘GIS on Cloud’. With this partnership, ‘Indo ArcGIS on Cloud’ would now be available on RailTel Cloud, giving customers the much-needed advantage of scalability, agility and cost-efficiency. www.railtelindia.com
Open Maps for Europe has released an Open Cadastral Map prototype, which provides large-scale coverage for four countries. The data is now available via the Open Maps interface and this first iteration includes Poland, The Netherlands, Czech Republic and Spain. The map takes INSPIRE open data and allows the user to find out what is available from national sources in one place before obtaining the data from the official provider. The cadastral map comprises four data types: Administrative Units, Cadastral Parcels (and Cadastral Zones), Buildings (and Building Parts) and Addresses. https://eurogeographics.org
Cadcorp launches new hosted Data Service
Cadcorp has updated its cloud services offering to include a new Data Service. The managed service provides direct access to a wide range of open data directly from a secure Cadcorp datastore. The service will allow customers to easily access data overlays within Cadcorp SIS Desktop and Cadcorp SIS WebMap. www.cadcorp.com
Doors open on world-leading European Glider Service Centre
The National Oceanography Centre (NOC) has partnered with Teledyne Marine, to open a new European Glider Service Centre. It will expand glider usage for both science and industry and provide scientific support and repair facilities for Teledyne Slocum Gliders. https://noc.ac.uk
AiDash has announced its Disaster and Disruption Management System (DDMS). DDMS is a satellite- and AI-powered SaaS offering that helps utility and energy companies as well as governments and cities, manage the impact of natural disasters, including storms and wildfires. The new system works in near real-time before, during, and after a major natural disaster or extreme weather event. The AI-powered system fuses satellite imagery, real-time weather data, span-level vegetation data, and historic outage and resource usage data for insights before, during, and after a major weather event. www.aidash.com