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Fig. 150: Interface of the Model
Fig. 150: Interface of the Model
Species Mapping
The upscaled spectrum obtained from SEMULS is resampled to the CHRIS bands format. It is easy to convert as the upscale spectrum is in 1nm difference from 400 to 2500nm. Then those resampled spectra are given as the input for the classification. The angle was fixed as 0.1 radians for all the data collected for different seasons.
The classified map generated is validated manually with field-collected GPS locations of 10 tree species. There are about 55 locations obtained from the field (from three seasons), and all the pixels in those locations are classified correctly. Validating with 55 points may not be sufficient but can be considered keeping given the size of the study area. Cross-validation is performed to know if all the data locations in the field are classified accordingly as 55 locations are not visited on all field surveys.
Use of Geospatial Technologies
The project used spectra extracted from multi-temporal CHRIS PROBA Hyperspectral data. The spectra extracted for the selected species from satellite data are correlated with canopy spectra derived from leaf reflectance spectra obtained from the field using SEMULS. The outputs of the model are validated for their applicability by comparing with upscaled spectra derived from popular PROSPECT. The SEMULS model is unique in retaining the minute dips and peaks of the spectra, which are important in discriminating (80% matching at 5deg or less threshold) species, unlike other models that smoothen spectra using different filters. The upscaled canopy spectra (SEMULS) are further used to classify selected species in the study area from CHRIS-PROBA satellite data, using the SAM method and validated based on GPS locations observed from the field. Key Outputs
A spectral database was developed for selected tree species using hyperspectral satellite imagery and to build a canopy upscaling model.
Outcomes Achieved
Product/Process developed/ technology transfer
The SEMULS model is created for upscaling the leaf spectrum to the canopy level. Parameters like LAI, chlorophyll, nitrogen, lignin, cellulose, protein, water content and the leaf spectrum from the field are inputs for the model. The model converts the leaf biochemical parameters at the canopy level and upscales the spectrum with the canopy biochemical parameters
Reference: Salghuna N.N, P. Rama Chandra Prasad, and N. Rama Rao 2021. Semi-Empirical Model for Upscaling Leaf Spectra (SEMULS): A novel approach for modelling canopy spectra from in situ leaf spectra. Geocarto International, 36:15, 1665-1684 DOI: 10.1080/10106049.2019.1665716 Spectral database
The spectral database was created and organized for 70 samples of 10 tree species (study area: Araku, Eastern Ghats). Each species has seven samples for a different phenological time frame. (One sample in winter, three samples in summer and rainy seasons individually). For every single sample species three spectra are included in the database: - leaf reflectance from the field, upscaled reflectance using the SEMULS model, and CHRIS satellite derived spectrum. The database of a spectrum has other details like the species description, its biochemical – physical values, economic uses, and field – satellite (date and time of acquisition) information, etc. These are uploaded to the server of nisa.geos.iitb.ac.in Port 443.
Academic Achievements
Æ One PhD degree conferred Æ Five Research Publications published in reputed international journals and conferences
Contact Information
Name of Contact Person: Designation: Organization Name: Email: Phone: Dr Rama Chandra Prasad Pillutla
Associate Professor International Institute of Information Technology, Hyderabad. rcprasad@iiit.ac.in, rcpncmsl@gmail.com 040-66531343
Alignment with the IGIF Strategic Pathways
S.no IGIF Strategic pathway Remarks
SP4 Data The example shows data partnerships and management methods for leaf biochemical analysis.
SP7 Partnerships A partnership between IIIT Hyderabad and the Indian Institute of Space Technology, Trivandrum was established for the study.
SP9 Communication and Engagement The database thus generated is uploaded to the NISA portal which will serve current and future researchers, in identifying the species without field inventory, and/or for any spectra-related research.
