A checklist of the flowering plants of Katerniaghat Wildlife Sanctuary, Uttar Pradesh, India

Katerniaghat Wildlife Sanctuary, a tropical moist deciduous forest along the Indo-Nepal boarder comprises of 778 species of angiosperms, out of which 613 species are dicots under 386 genera and 91 families and 165 species are monocots under 103 genera and 23 families.  It contains 82 species that are in cultivation and/or growing as alien invasives.  The species include 149 trees, 81 shrubs, 445 herbs and 103 climbers.  Fabaceae with 100 species and Poaceae with 65 species occupy the first position in dicots and monocots, respectively.  Cyperus with 14 species has been found to be the largest genus represented while 355 genera are represented by solitary species.  The present study enumerates all species of flowering plants occurring in the sanctuary area with their correct name along with first citation and some important references pertaining to the flora of the study area.  Important synonyms have also been provided.  For majority of species the representative voucher specimens have also been supplied.  The paper also briefly deals with the vegetation types of the area. The outcome of the work is based on extensive field survey of the area conducted during 2008–2011, study of literature and examination of specimens of earlier collections housed at BSA, BSIP, CDRI and LWG.</div

A checklist of the flowering plants of Katerniaghat Wildlife Sanctuary, Uttar Pradesh, India

Katerniaghat Wildlife Sanctuary, a tropical moist deciduous forest along the Indo-Nepal boarder comprises of 778 species of angiosperms, out of which 613 species are dicots under 386 genera and 91 families and 165 species are monocots under 103 genera and 23 families.  It contains 82 species that are in cultivation and/or growing as alien invasives.  The species include 149 trees, 81 shrubs, 445 herbs and 103 climbers.  Fabaceae with 100 species and Poaceae with 65 species occupy the first position in dicots and monocots, respectively.  Cyperus with 14 species has been found to be the largest genus represented while 355 genera are represented by solitary species.  The present study enumerates all species of flowering plants occurring in the sanctuary area with their correct name along with first citation and some important references pertaining to the flora of the study area.  Important synonyms have also been provided.  For majority of species the representative voucher specimens have also been supplied.  The paper also briefly deals with the vegetation types of the area. The outcome of the work is based on extensive field survey of the area conducted during 2008–2011, study of literature and examination of specimens of earlier collections housed at BSA, BSIP, CDRI and LWG.</div

Species-level classification and mapping of a mangrove forest using random forest—utilisation of AVIRIS-NG and sentinel data

Although studies on species-level classification and mapping using multisource data and machine learning approaches are plenty, the use of data with ideal placement of central wavelength and bandwidth at appropriate spatial resolution, for the classification of mangrove species is underreported. The species composition of a mangrove forest has been estimated utilising the red-edge spectral bands and chlorophyll absorption information from AVIRIS-NG and Sentinel-2 data. In this study, three dominant species, Heritiera fomes, Excoecaria agallocha and Avicennia officinalis, have been classified using the random forest (RF) model for a mangrove forest in Bhitarkanika Wildlife Sanctuary, India. Various combinations of reflectance/backscatter bands and vegetation indices derived from Sentinel-2, AVIRIS-NG, and Sentinel-1 were used for species-level discrimination and mapping. The RF model showed maximum accuracy using Sentinel-2, followed by the AVIRIS-NG, in discriminating three dominant species and two mixed compositions. This study indicates the potential of Sentinel-2 data for discriminating various mangrove species owing to the appropriate placement of central wavelength and bandwidth in Sentinel-2 at ≥10 m spatial resolution. The variable importance plots proved that species-level classification could be attempted using red edge and chlorophyll absorption information. This study has wider applicability in other mangrove forests around the world

Predicting the Forest Canopy Height from LiDAR and Multi-Sensor Data Using Machine Learning over India

Forest canopy height estimates, at a regional scale, help understand the forest carbon storage, ecosystem processes, the development of forest management and the restoration policies to mitigate global climate change, etc. The recent availability of the NASA’s Global Ecosystem Dynamics Investigation (GEDI) LiDAR data has opened up new avenues to assess the plant canopy height at a footprint level. Here, we present a novel approach using the random forest (RF) for the wall-to-wall canopy height estimation over India’s forests (i.e., evergreen forest, deciduous forest, mixed forest, plantation, and shrubland) by employing the high-resolution top-of-the-atmosphere (TOA) reflectance and vegetation indices, the synthetic aperture radar (SAR) backscatters, the topography and tree canopy density, as the proxy variables. The variable importance plot indicated that the SAR backscatters, tree canopy density and the topography are the most influential height predictors. 33.15% of India’s forest cover demonstrated the canopy height 20 m). This study advocates the importance and use of GEDI data for estimating the canopy height, preferably in data-deficit mountainous regions, where most of India’s natural forest vegetation exists

India’s contribution to mitigating the impacts of climate change through vegetation management

The changes in natural ecosystems provide opportunity to increase vegetation carbon sink capacity and thereby contribute to mitigation of climate change impacts. The Indian tropics and the large ecological variation within the country afford the advantage of diverse niches and offer opportunities to reveal the role of biotic factors at different levels of organization from populations to ecosystems. The last 4 decades of research and development in the Indian space science community has been primarily application driven in response to the government space programme for national development. The expenditure in R&amp;D over next 5 year suggest that scientific research is higher on the country's agenda. The Indo-UK Terrestrial Carbon Group (IUTCG) comprising both Indian and UK scientists, funded jointly by the Department of Science and Technology, India and the Department of Business, Innovation and Skills organised a workshop to explore ways in which Earth observation data can be effectively utilised in mitigating the impacts of climate change through vegetation management. Effective integration of field observations, collected through various monitoring networks, and satellite sensor data has been proposed to provide country-wide monitoring

New vegetation type map of India prepared using satellite remote sensing: Comparison with global vegetation maps and utilities

International audienceA seamless vegetation type map of India (scale 1: 50,000) prepared using medium-resolution IRS LISS-III images is presented. The map was created using an on-screen visual interpretation technique and has an accuracy of 90%, as assessed using 15,565 ground control points. India has hitherto been using potential vegetation/forest type map prepared by Champion and Seth in 1968. We characterized and mapped further the vegetation type distribution in the country in terms of occurrence and distribution, area occupancy, percentage of protected area (PA) covered by each vegetation type, range of elevation, mean annual temperature and precipitation over the past 100 years. A remote sensing-amenable hierarchical classification scheme that accommodates natural and semi-natural systems was conceptualized, and the natural vegetation was classified into forests, scrub/shrub lands and grasslands on the basis of extent of vegetation cover. We discuss the distribution and potential utility of the vegetation type map in a broad range of ecological, climatic and conservation applications from global, national and local perspectives. We used 15,565 ground control points to assess the accuracy of products available globally (i.e., GlobCover, Holdridge’s life zone map and potential natural vegetation (PNV) maps). Hence we recommend that the map prepared herein be used widely. This vegetation type map is the most comprehensive one developed for India so far. It was prepared using 23.5 m seasonal satellite remote sensing data, field samples and information relating to the biogeography, climate and soil. The digital map is now available through a web portal (http://bis.iirs.gov.in)