P. Rama Chandra Prasad

Folklore medicinal plants of North Andaman Islands, India.

The rural folk of North Andaman, India use the traditional medicine for their primary health care. Folklore medicinal uses of 72 interesting medicinal plant species along with botanical name, local name, family, habit, part used, disease for which the drug is administrated, mode of administration are presented. These 72 plant species which provide the crude drugs pertain to 67 genera and 43 families of Magnoliophyta from tropical rainforests. These plants used to cure 40 ailments. Most remedies were taken orally, accounting for 76% of medicinal use. Most of the remedies were reported to have been from trees (55.6%) and herb (22.2%) species. The most widely sought after plant parts in the preparation of remedies in the areas are the stem bark (33.8%) and root (23.9%).

Assessment of tsunami and anthropogenic impacts on the forest of the North Andaman Islands, India

Forests are being depleted drastically at higher rates to cater to the needs of growing population. In this context, an attempt was made to identify the drivers of forest changes on the vegetation of the North Andaman islands by broadly categorising the changes as anthropogenic and natural disturbances (tsunami) using satellite images of 1976, 1999 and 2005. The images were classified using visual interpretation technique to generate land cover maps of the area under study. A detailed change analysis of the 1976, 1999 and 2005 images showed that a high proportion of the natural vegetation has been converted into agriculture, settlement, sand and water. The overall forest change from 1976 to 2005 is 11,670 ha with a deforestation rate of 389 ha yr−1. The tsunami of 26 December, 2004 was found to be a major cause of deforestation of coastal forests in the North Andaman Islands, deforesting an area of 3292.5 ha. Simulation of forest cover in the next 25 and 50 years predicted a deforestation of 13,100 and 22,700 ha with a corresponding increase in non‐forest land cover to 19,600 and 29,600 ha respectively. It is predicted that after 50 years the forest area of 131,200 ha, estimated from the 1999 satellite data, may reduce to 108,500 ha, if proper conservation measures are not taken.

Assessing forest canopy closure in a geospatial medium to address management concerns for tropical islands - Southeast Asia.

The present study outlines an approach to classify forest density and to estimate canopy closure of the forest of the Andaman and Nicobar archipelago. The vector layers generated for the study area using satellite data was validated with the field knowledge of the surveyed ground control points. The methodology adopted in this present analysis is three-tiered. First, the density stratification into five zones using visual interpretation for the complete archipelago. In the second step, we identified two island groups from the Andaman to investigate and compare the forest strata density. The third and final step involved more of a localised phytosociological module that focused on the North Andaman Islands. The results based on the analysis of the high-resolution satellite data show that more than 75% of the mangroves are under high- to very high-density canopy class. The framework developed would serve as a significant measure to forest health and evaluate management concerns whilst addressing issues such as gap identification, conservation prioritisation and disaster management—principally to the post-tsunami assessment and analysis.

Tsunami and tropical island ecosystems: a meta-analysis of studies in Andaman and Nicobar Islands

Tropical islands are special and sensitive ecosystems which are subjected to various disturbances imposed by human activities and natural disasters. A detailed study about the changing landscape scenarios of these fragile island systems induced by various driving factors could be used for setting up measurements in support of conservation and sustainable development projects. The current research is a meta-analysis of the studies carried out in Andaman and Nicobar islands which analyzed the impact of tsunami of 2004 using geospatial tools. Based on the analysis, it was observed that the Nicobar islands were more affected compared to the Andaman islands. The majority of the researchers used pre- and post-tsunami satellite imagery and adopted visual interpretation method to delineate the changed classes. The study infers uplift of land in Andaman (exposing) and subsidence in Nicobar islands (inundation) with severe damage to the coastal elements like mangroves, coral reefs, plantations and in few cases interior forest. The analysis showed there were no records of the damage for some small islands. Finally, it is concluded that utility of microwave satellite data for change analysis will prove better in regions like Andaman and Nicobar where it is difficult to get cloud free optical data because of the high monsoon periods in these islands. It is also suggested that future work utilizing suitable temporal satellite imagery should focus on the extent of recovery of vegetation and other coastal elements which suffer the impact of disaster.

A conceptual framework to analyse the land-use/land-cover changes and its impact on phytodiversity: a case study of North Andaman Islands, India

Phytodiversity is affected both by natural and anthropogenic factors and in Island ecosystems these impacts can devastate or reduce diversity, if the native vegetation is lost. In addition to rich species richness and diversity, Island systems are the sites of high endemism and any threat to these ecosystems will consequently lead to loss and extinction of species. To understand the dynamics including feedbacks of these changes in phytodiversity of North Andaman Islands, a conceptual framework is proposed which focuses on understanding the land-use and land-cover changes and its impact with phytodiversity. In considering land-use and land-cover changes this work highlights the direct and indirect drivers of changes—socio-economic, biophysical and climatic factors. Migration of population, their socio economic needs and government policies were identified as major driving forces threatening the phytodiversity of these Islands. Apart from human beings, natural disasters like tsunami and introduced herbivorous animals like elephants also contributed to forest destruction in these Islands. The integrated analysis based on such framework will provide insights for holistic resource management including ecological conservation.

Prediction of vegetation dynamics using NDVI time series data and LSTM

Understanding and analyzing the changes in vegetation cover is very important in several aspects including climatic changes, water budget, ecological balance and specially to undertake necessary conservation measures. The concept of neural network has gained much significance in the analysis of vegetation dynamics using remote sensing satellite data. In the current study an attempt has been made to predict the vegetation dynamics using MODIS NDVI time series data sets and long short term memory network, an advanced technique adapted from the artificial neural network. The dataset of 861 NDVI images from January 2000 to June 2016 is used for making the time series. The data is segregated into three sets which comprises of training set (70%), validation set (20%), and testing set (10%). To check the reliability of the experiment we have finalised two different regions after extensive research for investigation. These include different terrains in the Great Nicobar Islands, one region along the coast where vegetation has severe ecological damage due to 2004 Indian Ocean tsunami and the other, an interior region which remained imperturbable during the tsunami. Long short term memory network, an advanced neural network is trained with these NDVI values for both the regions separately to predict the future vegetation dynamics. To measure the accuracy of the LSTM network, root mean square error is calculated. The resulting plots from both the experiments indicate that the long short-term memory neural network follows the series in addition to coinciding with the required time series. Also, an unanticipated change in the trend of the NDVI series were well adapted by the network and was able to predict the future NDVI values with good accuracy maintaining RMSE less than 0.03 without providing any supplementary data. By adopting the prescribed method in the paper, anticipation of vegetation changes can be done accurately much ahead of time and take proactive measures accordingly to safeguard and improve the vegetation in any area.

Human-Bird Conflicts and Management Issues: A Case Study of Birds at Uppalapadu Lake, Andhra Pradesh, India

The current research focused on the issues related to human-bird conflicts and subsequent alternatives adopted by the migratory birds at Uppalapadu Lake (India). The study collates the information from field observations and literature surveys and draws conclusions based on the observation data. The study highlights the ways the local community, Forest Department, activist groups and other organizations participate in protecting the birds from harm. It also focuses on some of the management initiatives taken by the Forest Department that are helping the birds during their breeding periods. Overall, the research identifies the ecological importance of the lake with respect to birds and stresses the need for its protection and further expansion.

Geospatial Assessment of Spatio-Temporal Changes in Mangrove Vegetation of Pichavaram Region, Tamil Nadu, India

The present work is a multi-temporal satellite based spatial dynamic study of an important coastal habitat, the Pichavaram mangrove ecosystem, over a period of 15 years. The study discusses the importance and the status of mangroves on both global and regional scales. Maximum likelihood estimate method of supervised classification technique has been used to classify the land use-land cover changes in the Pichavaram Reserve Forest, Killai Reserve Forest and Pichavaram Extension. The status of the classes has been monitored using Landsat ETM+ of 2000, 2006, 2011, and OLI of 2016 satellite imageries. The total area of the Pichavaram mangrove showed a net increase of approximately 11.41% of the total study area within a span of 15 years (2000–2016).

Assessment of forest fire danger using automatic weather stations and MODIS TERRA satellite datasets for the state Madhya Pradesh, India

Forest fires are the most frequently occurred phenomenon during summer seasons in the state Madhya Pradesh. Monitoring and assessment of forest fires are the crucial steps in effective forest fire management. Forest fire danger estimation helps the disaster management authorities to take necessary mitigation measures for minimizing the losses and to evacuate the local people. Fire danger rating systems predict the fire danger based on the meteorological station parameters and ground datasets. McArthur Forest Fire Danger Index (FFDI) is the most popularly used fire danger rating systems using in the country Australia. This index requires large amount of ground datasets for the computation of drought parameter. In India, it is very difficult to compute the drought parameter due to the unavailability of instruments and man power. In the present research, McArthur Fire Danger Index was modified by inducing Normalized multiband drought index (NMDI) that was generated from Moderate Resolution Imaging Spectroradiometer (MODIS) TERRA surface reflectance product MOD09GA as a substitute for fuel availability parameter. To test the robustness of modified FFDI, the research was carried out on Madhya Pradesh state for the assessment of forest fire danger. The results obtained from modified McArthur fire danger index were validated by using MODIS active fire hot spot location data (MOD14) and achieved an overall accuracy of 82%. The research concludes that modified FFDI can be used for assessing the forest fire danger in case of unavailability of fuel availability data for a particular forest.

Estimation of biomass density andcarbon storage in the forests of AndhraPradesh, India, with emphasis on theirdeforestation and degradation conditions

Abstract The current study evaluates the growing stock, biomass and carbon content of Andhra Pradesh state’s forest (India) along with its current status of forest degradation and loss. For this purpose, the study used the growing stock data collected by state forest department in 2010 for the calculation of biomass and carbon storage using the standard conversion and expansion factors given by IPCC. The analysis shows low biomass and carbon values for the state’s forest in comparison to the mean values recorded in different studies made for Andhra Pradesh. It is also observed to be lower when compared with the average carbon and biomass for Indian forests. Overall, the analysis showed degradation and loss of forest in the state, coupled with reduction in biomass and carbon sink.