Informatics Publishing Limited

Sowbhagya ¹, S. Ananda ¹, Rakesh ¹

Affiliations
1 Department of Studies in Chemistry, Manasagngotri, University of Mysore, Mysore-570 006, IN

Abstract

Anodic oxidation with a Ru-doped Pt electrode (RuDPt) can be applied to the remediation of waste waters containing indigocarmine. This environmentally friendly method decontaminates completely aqueous solutions of this dye. The COD value decreases to ~98% of the initial COD. Indigocarmine (IC) is more rapidly removed in RuDPt electrode than in platinum electrode alone. The reaction is carried in presence of dilute HCl acid. The degradation rate increases with increasing current and follows I order kinetics up to 60% of the reaction. The rate increases with [HCl] and decreases with [IC]. The dye is converted into CO₂, H₂O, NH₃ and simpler inorganic salts.

Keywords

Indigocarmine, Anodic Oxidation, Ruthenium-doped Platinum Electrode, Mineralization

Full Text

     

R. Suraj Reddy ¹, Rakesh ¹, C. S. Jha ¹, K. S. Rajan ²

Affiliations
1 Forestry and Ecology Group, National Remote Sensing Centre, Hyderabad 500 037, IN
2 Lab of Spatial Informatics, Indian Institute of Information Technology, Hyderabad 500 032, IN

Abstract

Forest inventories are critical for effective management of forest resources. Recently, the use of terrestrial laser scanning (TLS) to automatically extract forest inventory parameters at tree level (e.g. tree location, diameter at breast height (DBH) and height) has gained significant importance. TLS using both single-scan and multi-scan techniques, not only helps in detailed and accurate measurements of tree objects but also helps increase the measurement frequency. In the current study, we develop an automated solution to extract forest inventory parameters at individual tree level from TLS data by using random sample consensus (RANSAC)-based circle fitting algorithm. The method was evaluated on both single- and multiscan data by characterizing four circular plots of radius 20 m in dry deciduous forests of Betul, Madhya Pradesh (India). Over all the plots, tree detection rates of 75% and 97% were obtained using single- and multi-scan TLS data respectively. Tree detection rates were significantly affected by increase in distance from the scanner, in single-scan approach when compared to multi-scan approach. Field based DBH measurements correlated well using both single (R² = 0.96) and multiple scans (R² = 0.99). The DBH estimates from multi-scan TLS data resulted in low ischolar_main-meansquare error (RMSE) of 2.2 cm compared to that of 4.1 cm using single-scan. Further, tree heights were extracted from TLS data and validated with selectively measured trees on field (R² = 0.98; N = 65). The RMSE of tree height was estimated to be 1.65 m. The current results show the potential use of TLS in automatically deriving forest inventory parameters with reliable accuracy at individual tree level.

Keywords

DBH, Forest Inventory Parameters, Multiscan, Single-Scan, Terrestrial Laser Scanner.

Full Text

   

C. S. Jha ¹, Rakesh ¹, J. Singhal ¹, C. S. Reddy ¹, G. Rajashekar ¹, S. Maity ², C. Patnaik ², Anup Das ², Arundhati Misra ², C. P. Singh ², Jakesh Mohapatra ², N. S. R. Krishnayya ³, Sandhya Kiran ³, Phil Townsend ⁴, Margarita Huesca Martinez ⁵

Affiliations
1 National Remote Sensing Centre, Indian Space Research Organisation, Hyderabad 500 037, IN
2 Space Applications Centre, Indian Space Research Organisation, Ahmedabad 380 015, IN
3 MS University of Baroda, Vadodara 390 002, IN
4 University of Wisconsin, Madison 53706, US
5 University of California, Davis 95616, US

Abstract

Species diversity and vegetation health are two critical components to be monitored for sustainable forest management and conservation of biodiversity. The present study characterizes species dominance and α -diversity of a forest for the selected region in Mudumalai Wildlife Sanctuary (MWS), Western Ghats, which represents one of the most economically important forest types in India – the tropical dry deciduous forest. NASA’s Next-Generation Airborne Visible and Infrared Imaging Spectrometer (AVIRIS-NG) data at spectral resolution of 5 nm and spatial resolution of 5 m were used to analyse the forest matrix. Biodiversity (α -diversity) map thus generated from airborne platform over 14.5 sq. km area mostly represents the forest tree species diversity. Dominant tree species in the study area were also mapped using AVIRIS data for 21.7 sq. km. Canopy emergent dominant species, viz. Anogeissus latifolia, Tectona grandis, Terminalia alata, Grewia tiliifolia, Syzygium cumini and Shorea roxburghii were classified using spectral angle mapper technique and image-based spectra in the MWS study site. The study shows that nearly 40% area is dominated by A. latifolia and 27.5% by T. grandis in the study site. This study concludes that AVIRIS data can be used in the delineation of species and α -diversity mapping at community level; however, the accuracy achieved for species classification is moderate (60%) due to intermixing of species in the study area. For the Shimoga study site in Karnataka, the field spectra were collected using a spectroradiometer and used for the classification for the three dominant tree species using absorption peak decomposition technique. Fieldcollected pure spectra were analysed and species-wise absorption peaks (Gaussian) with central wavelength, peak amplitude and dispersion were used as the endmembers for classification. AVIRIS-NG data over Shoolpaneshwar Wildlife Sanctuary (SWS) study site used for fuel load estimation with narrow band indices calculated from AVIRIS-NG datasets. AVIRIS-NG data for MWS and Shimoga study site were collected during 2 and 5 January 2016, while for SWS site data were collected on 8 February 2016.

Keywords

Airborne Sensors, Forest Health, Hyperspectral Imaging, Species Diversity.

Full Text