Hitendra Padalia

Development of Decadal (1985–1995–2005) Land Use and Land Cover Database for India

India has experienced significant Land-Use and Land-Cover Change (LULCC) over the past few decades. In this context, careful observation and mapping of LULCC using satellite data of high to medium spatial resolution is crucial for understanding the long-term usage patterns of natural resources and facilitating sustainable management to plan, monitor and evaluate development. The present study utilizes the satellite images to generate national level LULC maps at decadal intervals for 1985, 1995 and 2005 using onscreen visual interpretation techniques with minimum mapping unit of 2.5 hectares. These maps follow the classification scheme of the International Geosphere Biosphere Programme (IGBP) to ensure compatibility with other global/regional LULC datasets for comparison and integration. Our LULC maps with more than 90% overall accuracy highlight the changes prominent at regional level, i.e., loss of forest cover in central and northeast India, increase of cropland area in Western India, growth of peri-urban area, and relative increase in plantations. We also found spatial correlation between the cropping area and precipitation, which in turn confirms the monsoon dependent agriculture system in the country. On comparison with the existing global LULC products (GlobCover and MODIS), it can be concluded that our dataset has captured the maximum cumulative patch diversity frequency indicating the detailed representation that can be attributed to the on-screen visual interpretation technique. Comparisons with global LULC products (GlobCover and MODIS) show that our dataset captures maximum landscape diversity, which is partly attributable to the on-screen visual interpretation techniques. We advocate the utility of this database for national and regional studies on land dynamics and climate change research. The database would be updated to 2015 as a continuing effort of this study.

Modeling potential invasion range of alien invasive species, Hyptis suaveolens (L.) Poit. in India: Comparison of MaxEnt and GARP

article i nfo Bushmint (Hyptis suaveolens (L.) Poit.) is one among the worlds most noxious weeds. Bushmint is rapidly invad- ing tropical ecosystems across the world, including India, and is major threat to native biodiversity, ecosystems and livelihoods. Knowledge about the likely areas under bushmint invasion has immense importance for taking rapid response and mitigation measures. In the present study, we model the potential invasion range of bushmint in India and investigate prediction capabilities of two popular species distribution models (SDM) viz., MaxEnt (Maximum Entropy) and GARP (Genetic Algorithm for Rule-Set Production). We compiled spatial layers on 22 climatic and non-climatic (soil type and land use land cover) environmental variables at India level and selected least correlated 14 predictor variables. 530 locations of bushmint along with 14 predictor variables were used to predict bushmint distribution using MaxEnt and GARP. We demonstrate the relative contribution of predictor variables and species-environmental linkages in modeling bushmint distribution. A receiver operating character- istic (ROC) curve was used to assess each models performance and robustness. GARP had a relatively lower area under curve (AUC) score (AUC: 0.75), suggesting its lower ability in discriminating the suitable/unsuitable sites. Relative to GARP, MaxEnt performed better with an AUC value of 0.86. Overall the outputs of MaxEnt and GARP matched in terms of geographic regions predicted as suitable/unsuitable for bushmint in India, however, predic- tions were closer in the spatial extent in Central India and Western Himalayan foothills compared to North-East India, Chottanagpur and Vidhayans and Deccan Plateau in India.

Forest tree species discrimination in western Himalaya using EO-1 Hyperion

Abstract The information acquired in the narrow bands of hyperspectral remote sensing data has potential to capture plant species spectral variability, thereby improving forest tree species mapping. This study assessed the utility of spaceborne EO-1 Hyperion data in discrimination and classification of broadleaved evergreen and conifer forest tree species in western Himalaya. The pre-processing of 242 bands of Hyperion data resulted into 160 noise-free and vertical stripe corrected reflectance bands. Of these, 29 bands were selected through step-wise exclusion of bands (Wilks Lambda). Spectral Angle Mapper (SAM) and Support Vector Machine (SVM) algorithms were applied to the selected bands to assess their effectiveness in classification. SVM was also applied to broadband data (Landsat TM) to compare the variation in classification accuracy. All commonly occurring six gregarious tree species, viz., white oak, brown oak, chir pine, blue pine, cedar and fir in western Himalaya could be effectively discriminated. SVM produced a better species classification (overall accuracy 82.27%, kappa statistic 0.79) than SAM (overall accuracy 74.68%, kappa statistic 0.70). It was noticed that classification accuracy achieved with Hyperion bands was significantly higher than Landsat TM bands (overall accuracy 69.62%, kappa statistic 0.65). Study demonstrated the potential utility of narrow spectral bands of Hyperion data in discriminating tree species in a hilly terrain.

Impact of tsunami on the forest and biodiversity richness in Nicobar Islands (Andaman and Nicobar Islands), India

Occurrences of extreme events are likely to cause major decline in global biodiversity. In one such event, on December 26, 2004 tsunami caused extensive damage and irreparable losses to the ecology and biodiversity of low-lying areas of the countries located around the Indian Ocean region. Archipelago of Andaman and Nicobar Islands, one of the richest centre of endemism and biodiversity in the Indo-Malayan region, suffered great loss of forests and coastal biodiversity owing to its closeness to the epicenter of tsunami, i.e. just off the coast of Indonesia. There is little insight into the resilience and rate of recovery pattern of tropical coastal habitats consequent to catastrophic impacts of tsunami. It’s important to study the impacts of tsunami on the forest and biodiversity in order to suggest mitigation, restoration measures and long-term conservation planning. Here we have assessed the immediate after-effects of December 26, 2004 tsunami on the forests and areas prioritized for biodiversity conservation analyzing pre and post tsunami satellite imageries. The effect of topographic patterns of Island’s coastal areas and their distance from the epicenter of tsunami with respect to changes in the forests and different levels of biologically rich areas modeled for prioritization for different groups of Islands in Nicobar has been studied. Great Nicobar accounted for higher proportion of total forest area damaged and submerged in Nicobar, followed by Central Nicobar and Car Nicobar. Mangroves, littoral forest, beach forest and low land swamps and Syzygium swamps were most affected. Study brings out spatially explicit scenario of damaged, submerged and lost forest areas and corresponding area statistics, vital for understanding and mitigating medium and long term effects of tsunami an extreme event.

Nicobari Tribe of the Car Nicobar Island: Keeping in Pace with Time

Abstract Tropical rain forests worldwide are home to millions of tribal population belonging to diverse communities. During last few decades population pressure and migration of settlers in tribal areas for developmental needs have currently threaten the existence of the aboriginals. Most of the ethnobotanical knowledge in India is concentrated in remote tribal areas. The use of plant species in sustainably with nature lies hidden with native people, living in vicinity with nature.

Indian Bioresource Information Network (IBIN)

The bioresource or biological resource includes all components of biological diversity with actual or potential value for humanity and the sustainability of the living systems. It is generally understood as the biotic component of ecosystems that includes organisms, parts thereof, populations, genetic resources and any other element that are of tangential and non-tangential benefit. Indian sub-continent supports varied bioclimatic regions and biodiversity. Despite several attempts from both the national and international survey organizations, we still have incomplete information about several taxonomic groups (e.g. plants, insects and other lower life forms) on their conservation status. This is because we have not been able to generate the comprehensive data on their distribution and population status. Even more, we hardly have reliable information on the levels of harvesting of these species from the natural habitats, their economic value and ecological significance.

CO2 Flux Tower and Remote Sensing: Tools for Monitoring Carbon Exchange over Ecosystem Scale in Northwest Himalaya

Carbon accounts for nearly half of the total dry mass of all living things (Schlesinger 1991). Forests are the major reservoir of terrestrial carbon on the Earth and play vital role in balancing the steadily rising concentration of carbon dioxide in the atmosphere owing to fossil fuel and biomass burning (IPCC 2005). A forest is called the sink or source of carbon dioxide depending on net removal or release of carbon dioxide into the atmosphere. India supports a vast mosaic of forest ecosystems and contributes significantly to its carbon dynamics (Chhabra and Dadhwal 2004). Accurate quantification of carbon fluxes of forest ecosystems at local, regional, and global scales is necessary for understanding the feedback mechanism between the terrestrial biosphere and the atmosphere. Deep insight into the role of forests in the regional carbon cycle is critical for taking policy-oriented decisions on forest-based initiatives to mitigate global warming.

Species Mapping Using Citizen Science Approach Through IBIN Portal: Use Case in Foothills of Himalaya

In this era of rapid global change, biodiversity monitoring and improving species repository to meet requirements toward conservation is costly affairs and needs a practical solution to identify and locate species with habitats. The integrated approach of citizen science and information technologies has proven to be effective solution for geographical and taxonomical data collection with public engagement, covering local to national scale. As a first step, a mobile app is designed and developed for the IBIN (Indian Bioresource Information Network), a digitized collection of the biological resources of India that serves as a common platform to access spatial and non-spatial information on biorecources can host their data through this single and intuitive platform with full privileges and authenticity. IBIN mobile app can be seen as an efficient and rapid solution to record data on species, utilizing GPS and camera features of mobile devices. Present paper deals with the citizen science approaches, its contribution in biodiversity field, outlines the design and development of IBIN mobile app and its first case study carried out at foothills of Himalaya.

Characterization and classification of freshwater marshy wetland using synthetic aperture radar polarimetry: a case study from Loktak wetland, Northeast India

Abstract. Loktak is the largest natural wetland of Northeast India, the last home of endangered brow-antlered deer, and a site of global significance recognized under Ramsar convention. Ecological and human-meditated spatial patterns of Loktak wetland were characterized and classified using a Radarsat-2 C band synthetic aperture radar (SAR) satellite data. Radarsat-2 quad-pol scene of dry season was preprocessed and classified using PolSARpro software. Eigen vector–eigen value decomposition of coherency matrix (T3) was performed to characterize the scattering properties of wetland targets based on entropy (H)/anisotropy (A)/alpha angle (α) segmentation. Results illustrate that RGB color display of H/A/α images is a useful indicator of wetland structure and composition, and provide clear visual discrimination of open water, floating phumdi, permanent phumdi cover, and associated man-made features. Six classes, namely, floating phumdi, permanent phumdi, scrub/shrub, fallow land, built-up, and open water were mapped using Wishart classification of H/A/α images. Scattering mechanisms of natural and man-made targets synthesized from PolSAR data, and their classification using Wishart algorithm have been validated through a visually classified map and field reference points. The land cover generated would be useful for conservation and management of Loktak wetland and brow-antlered deer population.