National Mission on Himalayan Studies (NMHS) NMHS Annual Progress Report – Pro forma

Kindly fill the NMHS Annual Progress Report segregated into following 11 segments, as applicable to the objectives & quantifiable outcomes of your NMHS Project. 1. Project Information 2. Project Site Details 3. Project Activities Chart w.r.t. Timeframe [Gantt or PERT] 4. Financial and Resource Information 5. Equipment and Asset Information 6. Expenditure Statement and Utilization Certificate (UC) 7. Project Beneficiary Groups 8. Project Progress Summary (as applicable to the project) 9. Project Linkages (with concerned Institutions/ State Agencies) 10. Knowledge Products – Publication, recommendations, etc. 11. Project Concluding Remarks

Kindly attach a descriptive Annexure/ Files separately for the segments marked for the detailed description required. Please let us know in case of any query at: [email protected]

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NMHS Progress Report (Period from 2019. to 2020)

1. Project Information

Project ID: GBPNI/NMHS-2017-18/MG Sanction Date: 26-02-2018

Project Title: Hyperspectral Imaging for sharper definitions of Himalayan Ecosystems and its high- value plant species under climate uncertainties. BTG: Biodiversity Conservation and Management

PI and Affiliation Dr Prashant Kumar Srivastava (Institution): Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi, Uttar Pradesh Name & Address • Prof. Rajesh Kumar Mall, Professor, Coordinator DST Mahamana Centre for of the Co-PI, if Excellence in Climate Change Research, Institute of Environment and any: Sustainable Development, Banaras Hindu University, Varanasi, UP • Prof. AS Raghubanshi, Professor, Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi, UP • K. Chandra Sekhar, Scientist F, G.B. Pant National Institute of Himalayan Environment & Sustainable Development, Almora, Uttarakhand • Dr Irfan Rashid, Assistant Professor, Department of Earth Sciences, University of Kashmir • Dr K V Ramesh, CSIR Fourth Paradigm Institute, NAL Belur Campus, Bangalore, India

Structured Background: - Quantification of biophysical and biochemical parameters are very Abstract - crucial for monitoring the high value plants in Himalayan region, its sustainable detailing the utilization as well as the conservation of related resources. current year Objectives: - There are six objectives in the project. First one is creation of Spectral progress library and standardization for selected medicinal and threatened species. Second one is Spectral and image analysis for discrimination of selected economically important plant species followed by Model building for retrieval of Biochemical and Biophysical properties of selected species. Projection and scenario for distribution of selected species is the fourth objective followed by fifth objective of fine scaling of space-time map of the high value species in the Himalaya. The final objective is management and conservation of species based on previous objectives. Methodology and Results: -To fulfil these objectives, field sampling was conducted in End of September 2019 and End of February 2020 in Pindari Glacier and Almora, Kausani, Jageswer, Ranikhet respectively. A rigorous sampling resulted in a collection of around 215 species. The collected species were utilized for the preparation of their spectral libraries where the spectra’s in form of reflectance was prepared using hyperspectral Spectroradiometer. The First objective is over with the creation of spectral libraries of the identified species. Sentinel-2, Sentinel-5P, Moderate Resolution Imaging Spectroradiometer (MODIS), ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) and Shuttle Radar Topography Mission (SRTM) along with other climatic variables were used to map the species distribution over the sampling regions. Several machine learning algorithms were also incorporated to establish the relation between physical and climatic variables to estimate the probability distribution of species. For classifying the species through collected spectra, PRISMA and other available Hyperspectral data were acquired. Several classification

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techniques namely Support Vector Machine (SVM) and neural networks were used to classify the species over the acquired Hyperspectral data. The identified species from Pindari region were used for the retrieval of biochemical parameters through lab-based methods as well as through Automated Radiative Transfer Models Operator (ARTMO) for retrieval of various vegetation parameters. In the region of Jammu and Kashmir, preparation of land use land cover map of the Dachigam National Park for 2019 was carried out. The Accuracy Assessment was made with 2018 LULC data. The Historical land system changes (1972-2019) was evaluated and LULC mapping of the Dachigam National Park/Dal Lake catchment was conducted using satellite data of 1980, 1990 and 2001 and LULC map for the year 2010 was drawn for Dachigam National Park and finally, Landscape fragmentation was carried out for 1980 and 2019. High-resolution weather information is generated for the study region for 2000-2016 CMIP6 climate scenarios are organized. The reliability assessment of the CMIP5 models is going on. Development of Hourly high-resolution climate for the study region is generated during 2001-2015. Validation of this data against observation needs to be carried out. For the time being, simulation work is over. Conclusion: -In terms of quantifiable deliverables, spectral library of species is done, the spectral and image analysis of 2 species Rhododendron arboretum, Acacia dealbata is over and the validation is being done with the help of ground data. The testing of the model for the retrieval of biophysical and biochemical parameters is underway for species Taxus wallichiana. After validation of CMIP6 climate scenarios, organization of climate projections will be conducted. The work is in progress for other deliverables. Recommendations: - It is recommended to make more field sampling to observe climatic impacts on the species. Also, the models generated should be applied to all the species.

Project Partner Affiliations Role & Responsibilities Name Partner 1 Dr. Prashant Kumar Srivastava, Prof. To detect and identify the medicinal plants and Rajesh Kumar Mall, Prof. AS threatened plants concerning pedological and Raghubanshi climatic conditions using the handheld hyperspectral spectroradiometer; Spectral library of the economically important plant species to use with the hyperspectral satellite and airborne data; Development of knowledge-based planning of an appropriate management system to Safeguard medicinal and threatened species. Partner 2 Dr. K. Chandra Sekar Identification and Management of the economically and Medicinally important plant species to be used with the hyperspectral satellite and airborne data; Development of knowledge-based planning of an appropriate management system to Safeguard medicinal and threatened species. Partner 3 Dr Irfan Rashid Identification and Management of the economically and Medicinally important plant species to be used with the hyperspectral satellite and airborne data; Partner 4 Dr K V Ramesh Detection and identification of the future climate scenarios are carried out through the study of past climate data by simulating the

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climate scenario and downscaling. The validation of high-resolution climate with station observations would be conducted to identify the reliable climate models for the study area.

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2. Project Site Details Project Site: • Dachigam National Park, J & K

• Pindari Basin, Uttarakhand

• Almora and nearby areas

IHR States Covered: • Jammu and Kashmir,

• Uttarakhand

Site Maps* (No.): Used and Attached in Annexure I. Site Photographs* (No.): Used and Attached in Annexure IV and Annexure V

*Attach a separate Descriptive Annexure/ Files (.JPG, .TIFF, etc.). 3. Project Activities Chart w.r.t. Timeframe [Gantt or PERT]

Qtr 1 Qtr 2 Qtr 3 Qtr 4 PROJECT DESCRIPTION OF WORK QUANTIFIABLE ACTIVITIES UNDERTAKEN (YEAR OUTPUTS 2019-2020) Field ✓ ✓ ✓ The field sampling was conducted The details of the Sampling in End of September 2019 and field sampling area End of February 2020 in Pindari are given in Glacier and Almora, Kausani, Annexure-I Jageswer, Ranikhet respectively. A rigorous sampling resulted in a collection of around 215 species for which several activities were conducted, such as preparation of spectral libraries, identification of biophysical and biochemical parameters along with their herbarium documentation. The Pindari Region of Bageshwar district, Uttarakhand consisted of areas namely, Jaikuni, Dwali and Furkiya where the samples were collected having high medicinal and economical value. The areas in Almora district, Uttarakhand consisted of areas namely, Jageswer, Ranikhet, Kausani and lower suburban Himalayan regions from Bhimtal and Nainital in Uttarakhand. Preparation of ✓ ✓ ✓ The collected species were The details of few Spectral utilized for the preparation of their of the species are Libraries of spectral libraries where the given in Annexure- the collected spectra’s in form of reflectance III and the spectral species. using FieldSpec 4 libraries of the Spectroradiometer. collected species are given in Annexure IX.

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Land Use ✓ ✓ ✓ ✓ Preparation of a land use land The details are Land Cover cover map of the Dal Lake given in Annexure Mapping catchment/ Dachigam National IV. Park for 2019 was carried out. The Accuracy Assessment was made with 2018 LULC data. The Historical land system changes within Dal Lake (1972-2019) was evaluated and LULC mapping of the Dachigam National Park/Dal Lake catchment was conducted using satellite data of 1980, 1990 and 2001 and LULC map for the year 2010 was drawn for Dachigam National Park and finally, Landscape fragmentation was carried out for 1980 and 2019. Collection and ✓ ✓ ✓ ✓ For classifying the species The details of the Processing of through collected spectra, species distribution Hyperspectral PRISMA and other available are given in Images. Hyperspectral data were acquired. Annexure-V Several classification techniques namely Support Vector Machine (SVM) and neural networks were used to classify the species over the acquired Hyperspectral data. The species from Pindari were identified from the GPS enabled field sampled data and then species distribution mapping was drawn to evaluate the spread of the species at various altitude. Processing of ✓ ✓ ✓ The identified species from The details are Biophysical Pindari region were used for the given in Annexure and retrieval of biochemical VI. Biochemical parameters through lab-based Vegetation methods as well as through Parameters of Automated Radiative Transfer the collected Models Operator (ARTMO) for species. retrieval of various vegetation parameters. Climate ✓ ✓ ✓ High-resolution weather The output of this simulation and information is generated for the activity cannot be downscaling: study region for 2000-2016 represented. past climate & CMIP6 climate scenarios are Future climate organized. The reliability scenarios for assessment of the CMIP5 models the Study is going on. region

Analysis and ✓ Development of Hourly high- The output of this data modelling resolution climate for the study activity cannot be region is generated during 2001- represented. 2015. Validation of this data

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against observation needs to be carried out. For the time being, simulation work is over. After this, the organization of climate projections were conducted. Sentinel-2, Sentinel-5P, Moderate Resolution Imaging Spectroradiometer (MODIS), ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) and Shuttle Radar Topography Mission (SRTM) along with other climatic variables were also used to map the species distribution over the sampling regions. Several machine learning algorithms were also incorporated to establish the relation between physical and climatic variables to estimate the probability distribution of species.

Project ✓ Five days’ Workshop on Management Techniques in Hyperspectral and interaction Data Analysis and Processing at with IESD BHU, Varanasi, 27th st stakeholders January-31 January 2020.

One day brainstorming meeting to “Developing methodologies to characterize ecosystems in the Indian Himalayas” at CSIR 4PI, Bangalore 12th Feb 2020

Workshop on “System Dynamical modelling for livelihood and river management” at CSIR 4PI, Bengaluru was organized during 13-14 Feb 2020

4. Financial and Resource Information Note: A separate bank account is expected to be opened for NMHS Project as per the provision of Direct Beneficiary Account (DBA) as laid out by the Govt. of India and also facilitate the audit of accounts. The interest earned out of the NMHS project funds should be reported clearly in the utilization certificate.

Total Grant: Rs.2,23,74,560.00/- (Rupees Grant Received Date: Rs.1,27,01,680.00/- (Rupees One Two Crore Twenty-Three Crore Twenty-Seven Lakh One Lakh Seventy-Four Thousand Six Hundred Eighty only) Thousand Five Hundred Sixty only)

Project Affiliations/ Institution Budget Allocated to Work Done by each Project Partner(s) Partner

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Partner 1 Dr K V Ramesh and V Rs. 4,54,000.00/-Sanctioned on Climate simulation and downscaling: Rakesh, CSIR Fourth 27-12-2018 of past climate data was conducted Paradigm Institute, NAL with the help of this partner. Belur Campus, Bangalore, India Partner 2 Dr Irfan Rashid, Rs. 5,24,000.00/- Sanctioned on The work around Dal Catchment and Assistant Professor, 11-09-2018 Dachigam National Park was Department of Earth conducted with the help of this Sciences, University of partner. Kashmir Partner 3 K. Chandra Sekhar, Rs. 11,10,560.00/- The collection of species during field Scientist F, G.B. Pant sampling was conducted with the Sanctioned on 11-09-2018 National Institute of help of this partner. Himalayan Environment & Sustainable Development, Almora, Uttarakhand

Partner 4 Dr Prashant Kumar Rs. 1,06,13,1,20.00/- Field Sampling, Preparation of Srivastava, Institute of Spectral Libraries of the collected Sanctioned on 11:09:2018 Environment and species, Collection and Processing of Sustainable Development, Hyperspectral Images, Processing of Banaras Hindu Biophysical and Biochemical University, Varanasi, Vegetation Parameters of the Uttar Pradesh collected species was conducted by this project partner.

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Project Staff Information: S. No. Name Qualification Designation Fellowship/ Wages paid Remarks 1. Dr Manish PhD Research 47000+16% HRA Kumar Associate Pandey 2. Dr Kapil PhD Research 47000+8% HRA Bisht Associate 3. Akash Anand MTech. JRF 31000+16% HRA 4. Aishwarya MTech. JRF 31000+24% HRA Pampapathi 5. Sheikh MTech. JRF 31000+8% HRA Aneaus 6. Sunil Joshi M. Sc. Project 12000/month (Consolidated) Assistant

5. Equipment and Asset Information S. Equipment Details Cost Date of Photographs Lowest No. Name (Qty) (Make/ Installation of Quotation, if Model) Equipment* not purchased 1. ASD FieldSpec 4 Spectral Rs 01-08-2019 Details are Spectroradiometer Range-350- 4983020.00 given in 2500 nm Annexure-VII Sampling Interval-1.4 nm @350-1000nm 1.1 nm @1001- 2500 nm Spectral Resolution - 3nm @700 nm 8nm @ 14000/2100 nm Note: Attach a Descriptive Annexure/ File separately.

6. Expenditure Statement and Utilization Certificate Please update the annual Expenditure Statement and Utilization Certificate (UC) periodically.

Expenditure Information: S. Financial Position/Budget Head Funds Sanctioned Expenditure % of Total cost No. I Salaries/Manpower cost 2251680.00 2150698 95.51526 II Travel 550000.00 478689 87.03436 III Expendables &Consumables 600000.00 487667 81.27783 IV Contingencies 400000.00 206134 51.5335 NMHS 2020 NMHS-Annual Progress Report (APR) Pro Forma Page 9 of 72

V Activities & Other Project cost 800000.00 779987 97.49838 VI Institutional Charges VII Equipments 8100000.00 61.51877 4983020 Total 1,27,01,680.00 90,86,195 Interest accrued 436605.00 Grand Total 1,31,38,285

Period Expenditure Statement* Utilization Certificate (UC)* Annual SE 19-20 is Attached as an Annexure II. UC 19-20 is Attached as an Annexure II.

*Attach the descriptive Annexure/ File in the prescribed NMHS format.

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7. Project Beneficiary Groups

Beneficiary Groups Target Achieved [Capacity Building] No. of Beneficiaries with income -- -- generation: No. of stakeholders trained, -- -- particularly women: No. of capacity building Workshops/ 3 3 trainings: No. of Awareness & outreach 01 01 programmes: No. of Research/ Manpower 50 50 developed:

8. Project Progress Summary* (as applicable to the project) Description (Name of Description Total (Numeric) descriptive Annexure/ File attached) * The details of the field sampling IHR States Covered 2 area are given in Annexure-I

Project Site/ Field Stations Developed: 2 The details are given in Annexure-I

No. of Patents filed (Description): 1 The publication work is in progress

Article/ Review/ Research Paper/ 4 The publication work is in progress Publication: • Estimating and extracting biophysical variables from remotely sensed canopy information has been investigated many times in the past. Now, with the availability of hyperspectral data more techniques are experimented to process this huge amount of data present between the 350-2500nm range. The development of indices like Zarco-Tejada, Miller New Methods/ Modellings Developed 2 index (ZMI), red edge (description in 250 words): normalized difference vegetation index (rNDVI), for retrieval biochemical parameter chlorophyll concentration using hyperspectral data paved the way for more such research. concentration. Many of these spectral indices (SI) are developed based on experimental studies. In the current study, the spectroradiometer data with some in-situ and ex-situ data were NMHS 2020 NMHS-Annual Progress Report (APR) Pro Forma Page 11 of 72

collected between the altitude 2750-3060 meter. The spectroradiometer data were put through three different types of filter Average Mean, Savitzky Golay, and Fast Fourier Transform (FFT) one at a time followed by feature selection on each denoised spectra to smooth the spectra for better estimation Taxol content (TC). In-situ and ex-situ data were used as measured values to test the statistical performance of SI and the model developed for Taxol. The normalized difference type index and simple ratio type index using the wavelength selected from Average Mean filter in combination with feature selection performs best for Taxol spectral indices generation and model development. Model LTC- TC 5 and LTC-TC 8 showed a correlation of 0.719, 0.718, and relative root mean square error (RMSEr) value of 0.578 and 0.576 both of which are relatively equivalent. • Integration of ecological and atmospheric characteristics for biodiversity management is one of the fundamental necessities for long-term ecosystem conservation. The explicit modelling of regional ecological responses and their impact on individual species is a significant prerequisite for making any adaptation strategy. The present study focuses on predicting the regional distribution of Rhododendron arboretum within the foothills of Himalayas. Species Distribution Models (SDM) namely BIOCLIM and Maxent were used to model the potential distribution of Rhododendron arboretum which are frequently used in ecological as well as biogeographical studies and works on the principle of predefined hypothesis. But the hypothesis tends to vary with the change in locations and thus, a more robust model is required to establish nonlinear complex relation between input parameters. Thus, to address this nonlinear relation, a CNN architecture is proposed, designed and tested in the current NMHS 2020 NMHS-Annual Progress Report (APR) Pro Forma Page 12 of 72

study, which eventually gave much better accuracy than BIOCLIM and Maxent models. All the three models were given 16 input parameters, including ecological and atmospheric variables, all were statistically resampled and then used in establishing the linear, and nonlinear relationship to better fit the occurrence scenarios. The input parameters were mostly acquired from the recent satellite missions including MODIS, Sentinel-2, Sentinel-5p and ECOSTRESS. The performance across all the thresholds are evaluated using the Area Under Curve (AUC) value. The AUC for CNN based species distribution prediction was found to be 0.877 whereas the value with the Maxent and BIOCLIM was found to be 0.669 and 0.639 respectively, which indicates the superiority of CNN based probabilistic modelling over other two models. The detail is given in Annexure No. of Trainings (No. of Beneficiaries): 1 VIII. • Five days’ Workshop on Techniques in Hyperspectral Data Analysis and Processing at IESD BHU, Varanasi, 27th January-31st January 2020. The detail is given in Annexure VIII. • One day brainstorming meeting to “Developing methodologies to Workshop: 3 characterize ecosystems in the Indian Himalayas” at CSIR 4PI, Bangalore 12th Feb 2020 • Workshop on “System Dynamical modelling for livelihood and river management” at CSIR 4PI, Bengaluru was organized during 13-14 Feb 2020

Demonstration Models (Site): 3 Attached in Annexures IV, V and VI

Livelihood Options: 1 Preparation of the manual is in Training Manuals: progress.

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Processing Units:

Species Collection: 235 • Attached in Annexures IX

Species identified: 235 • Attached in Annexures IX Database (Numeric/Images/GIS Maps, Attached in Annexures I, IV, V and 253 etc.): VI *Attach a separate descriptive Annexure/ File. Note: Numeric Database should be provided in .xls format. Photos/Maps should be submitted in high quality (min. 300 dpi res.) compatible formats viz., JPEG, .JPG, .PNG, .SHP, etc. along with suitable figure legend/ caption. 9. Project Linkages (with concerned Institutions/ State Agencies) S. No. Institute/ Organization Type of Linkages Brief Description 1 CSIR Fourth Paradigm The objectives were shared with To detect and identify future Institute, NAL Belur Campus, the Institute. climate scenarios through the Bangalore, India study of past climate data by simulating the climate scenario and downscaling. The validation of high-resolution climate with station observations would be conducted to identify the reliable climate models for the study area. 2 Department of Earth Sciences, The objectives were shared with Identification and Management University of Kashmir the Department. of the economically and Medicinally important plant species to be used with the hyperspectral satellite and airborne data; 3 G.B. Pant National Institute of The objectives were shared with Identification and Management Himalayan Environment & the Institute. of the economically and Sustainable Development, Medicinally important plant Almora, Uttarakhand species to be used with the hyperspectral satellite and airborne data;

Note: Attach a separate, descriptive Annexure/ File. 10. Knowledge Products – Publication, recommendations, etc. Time Period Publications (Research Papers, Information Material, Policy drafts, Patents, etc.)

Note: Attach a separate, descriptive Annexure/