Forest policies and programs affecting vulnerability and adaptation to climate change

Due to large scale afforestation programs and forest conservation legislations, India's total forest area seems to have stabilized or even increased. In spite of such efforts, forest fragmentation and degradation continues, with forests being subject to increased pressure due to anthropogenic factors. Such fragmentation and degradation is leading to the forest cover to change from very dense to moderately dense and open forest and 253 km(2) of very dense forest has been converted to moderately dense forest, open forest, scrub and non-forest (during 2005-2007). Similarly, there has been a degradation of 4,120 km(2) of moderately dense forest to open forest, scrub and non-forest resulting in a net loss of 936 km(2) of moderately dense forest. Additionally, 4,335 km(2) of open forest have degraded to scrub and non-forest. Coupled with pressure due to anthropogenic factors, climate change is likely to be an added stress on forests. Forest sector programs and policies are major factors that determine the status of forests and potentially resilience to projected impacts of climate change. An attempt is made to review the forest policies and programs and their implications for the status of forests and for vulnerability of forests to projected climate change. The study concludes that forest conservation and development policies and programs need to be oriented to incorporate climate change impacts, vulnerability and adaptation.

Forest area estimation and reporting: implications for conservation, management and REDD

Periodic estimation, monitoring and reporting on area under forest and plantation types and afforestation rates are critical to forest and biodiversity conservation, sustainable forest management and for meeting international commitments. This article is aimed at assessing the adequacy of the current monitoring and reporting approach adopted in India in the context of new challenges of conservation and reporting to international conventions and agencies. The analysis shows that the current mode of monitoring and reporting of forest area is inadequate to meet the national and international requirements. India could be potentially over-reporting the area under forests by including many non-forest tree categories such as commercial plantations of coconut, cashew, coffee and rubber, and fruit orchards. India may also be under-reporting deforestation by reporting only gross forest area at the state and national levels. There is a need for monitoring and reporting of forest cover, deforestation and afforestation rates according to categories such as (i) natural/primary forest, (ii) secondary/degraded forests, (iii) forest plantations, (iv) commercial plantations, (v) fruit orchards and (vi) scattered trees.

Hills, dams and forests. Some field observations from the Western Ghats

Man’s attempts to intensify the use of natural resources can often result in the exhaustion of the resource or deterioration of other interacting resources. The single-minded pursuit of the development of the water resources of the rivers of the Western Ghats shows many examples of this view, particularly in the unnecessary destruction of the dwindling forest resources. This destruction may be caused by (i) problems o f rehabilitation, e.g. the Ramanagar settlement of the Kalinadi project (ii) the impact of labourers, e.g. the destruction of evergreen sholas on the Upper Nilgiri plateau (iii) the access to encroachers and poachers, e.g. Panshet and Kalinadi (iv) faulty planning, e.g. Linganamakki and Kalinadi. This destruction of forest cover has had a number of deleterious consequences in (i) worsening the shortages of forest resources, (ii) hastening the siltation of the reservoirs, (iii) ecological imbalances as in the rapid spread ofEupatorium in the Kalinadi project area and (iv) the decimation of biological diversity, as in the great reduction of evergreen forests in the Western Ghats, threatening the survival of lion-tailed macaque and the extinction of grass species,Hubbardia heptaneuron. It is stressed that the only sustainable and therefore true development is environmentally sound development. The interests of the weaker sections of the society often provide a good index of the soundness of the development from an environmental point of view. The planning of the development process with this perspective is a great scientific and technological challenge that must be taken up.

Vegetation Status in Uttara Kannada District

Uttara Kannada is the only district in Karnataka, which has a forested area of about 80% and falls in the region of the Western Ghats. It is considered to be a very resourceful in terms of abundant natural resources and constitutes an important district in Karnataka. The forest resources of the district are under pressure as a large portion of the forested area has been converted to non-forestry activities since independence owing to the increased demands from human and animal population resulting in degradation of the forest ecosystem. This has led to poor productivity and regenerative capacity which is evident in the form of barren hill tops, etc in Coastal taluks of Uttara Kannada, entailing regular monitoring of the forest resources very essential. The classification of forest is a prerequisite for managing forest resources. Geographical Information System (GIS), allows the spatial and temporal analysis of the features of interest, and helps in solving the problem of deforestation and associated environmental and ecological problems. Spatial and temporal tools such as GIS and remotely sensed data helps the planners and decision makers in evolving the sustainable strategies for management and conservation of natural resources. Uttara Kannada district was classified on the basis of the land-use using supervised hard classifiers. The land use categories identified were urban area, water bodies, agricultural land, forest cover, and waste land. Further classification was carried out on the basis of forest type. The types of forest categorised were semi-evergreen, evergreen, moist deciduous, dry deciduous, plantations and scrub, thorny and non-forested area. The identified classes were correlated with the ground data collected during field visits. The observed results were compared with the historic data and the changes in the forest cover were analysed. From the assessment made it was clear that there has been a considerable degree of forest loss in certain areas of the district. It was also observed that plantations and social forests have increased drastically over the last fifteen years, and natural forests have declined.

Vegetation Analysis in Uttara Kannada District Using GIS and Remote Sensing Techniques

Uttara Kannada is the only district in Karnataka, which has a forested area of about 80% and falls in the region of the Western Ghats. It is considered to be a very resourceful in terms of abundant natural resources and constitutes an important district in Karnataka. The forest resources of the district are under pressure as a large portion of the forested area has been converted to non-forestry activities since independence owing to the increased demands from human and animal population resulting in degradation of the forest ecosystem. This has led to poor productivity and regenerative capacity which is evident in the form of barren hill tops, etc in Coastal taluks of Uttara Kannada, entailing regular monitoring of the forest resources very essential. The classification of forest is a prerequisite for managing forest resources. Geographical Information System (GIS), allows the spatial and temporal analysis of the features of interest, and helps in solving the problem of deforestation and associated environmental and ecological problems. Spatial and temporal tools such as GIS and remotely sensed data helps the planners and decision makers in evolving the sustainable strategies for management and conservation of natural resources. Uttara Kannada district was classified on the basis of the land-use using supervised hard classifiers. The land use categories identified were urban area, water bodies, agricultural land, forest cover, and waste land. Further classification was carried out on the basis of forest type. The types of forest categorised were semi-evergreen, evergreen, moist deciduous, dry deciduous, plantations and scrub, thorny and non-forested area. The identified classes were correlated with the ground data collected during field visits. The observed results were compared with the historic data and the changes in the forest cover were analysed. From the assessment made it was clear that there has been a considerable degree of forest loss in certain areas of the district. It was also observed that plantations and social forests have increased drastically over the last fifteen years,and natural forests have declined.

Rough Core Vector Clustering

Support Vector Clustering has gained reasonable attention from the researchers in exploratory data analysis due to firm theoretical foundation in statistical learning theory. Hard Partitioning of the data set achieved by support vector clustering may not be acceptable in real world scenarios. Rough Support Vector Clustering is an extension of Support Vector Clustering to attain a soft partitioning of the data set. But the Quadratic Programming Problem involved in Rough Support Vector Clustering makes it computationally expensive to handle large datasets. In this paper, we propose Rough Core Vector Clustering algorithm which is a computationally efficient realization of Rough Support Vector Clustering. Here Rough Support Vector Clustering problem is formulated using an approximate Minimum Enclosing Ball problem and is solved using an approximate Minimum Enclosing Ball finding algorithm. Experiments done with several Large Multi class datasets such as Forest cover type, and other Multi class datasets taken from LIBSVM page shows that the proposed strategy is efficient, finds meaningful soft cluster abstractions which provide a superior generalization performance than the SVM classifier.

Socio-cultural protection of endemic trees in humanised landscape

Culturally protected forest patches or sacred groves have been the integral part of many traditional societies. This age old tradition is a classic instance of community driven nature conservation sheltering native biodiversity and supporting various ecosystem functions particularly hydrology. The current work in Central Western Ghats of Karnataka, India, highlights that even small sacred groves amidst humanised landscapes serve as tiny islands of biodiversity, especially of rare and endemic species. Temporal analysis of landuse dynamics reveals the changing pattern of the studied landscape. There is fast reduction of forest cover (15.14-11.02 %) in last 20 years to meet up the demand of agricultural land and plantation programs. A thorough survey and assessment of woody endemic species distribution in the 25 km(2) study area documented presence of 19 endemic species. The distribution of these species is highly skewed towards the culturally protected patches in comparison to other land use elements. It is found that, among the 19 woody endemic species, those with greater ecological amplitude are widely distributed in the studied landscape in groves as well as other land use forms whereas, natural population of the sensitive endemics are very much restricted in the sacred grove fragments. The recent degradation in the sacred grove system is perhaps, due to weakening of traditional belief systems and associated laxity in grove protection leading to biotic disturbances. Revitalisation of traditional practices related to conservation of sacred groves can go a long way in strengthening natural ecological systems of fragile humid tropical landscape.

Constrained Linear Spectral Unmixing Technique for Regional Land Cover Mapping Using MODIS Data

Over the last few decades, there has been a significant land cover (LC) change across the globe due to the increasing demand of the burgeoning population and urban sprawl. In order to take account of the change, there is a need for accurate and up-to-date LC maps. Mapping and monitoring of LC in India is being carried out at national level using multi-temporal IRS AWiFS data. Multispectral data such as IKONOS, Landsat-TM/ETM+, IRS-ICID LISS-III/IV, AWiFS and SPOT-5, etc. have adequate spatial resolution (similar to 1m to 56m) for LC mapping to generate 1:50,000 maps. However, for developing countries and those with large geographical extent, seasonal LC mapping is prohibitive with data from commercial sensors of limited spatial coverage. Superspectral data from the MODIS sensor are freely available, have better temporal (8 day composites) and spectral information. MODIS pixels typically contain a mixture of various LC types (due to coarse spatial resolution of 250, 500 and 1000 in), especially in more fragmented landscapes. In this context, linear spectral unmixing would be useful for mapping patchy land covers, such as those that characterise much of the Indian subcontinent. This work evaluates the existing unmixing technique for LC mapping using MODIS data, using end-members that are extracted through Pixel Purity Index (PPI), Scatter plot and N-dimensional visualisation. The abundance maps were generated for agriculture, built up, forest, plantations, waste land/others and water bodies. The assessment of the results using ground truth and a LISS-III classified map shows 86% overall accuracy, suggesting the potential for broad-scale applicability of the technique with superspectral data for natural resource planning and inventory applications. Index Terms-Remote sensing, digital

Contrained linear spectral unmixing technique for regional land cover mapping using MODIS data

Over the last few decades, there has been a significant land cover (LC) change across the globe due to the increasing demand of the burgeoning population and urban sprawl. In order to take account of the change, there is a need for accurate and up- to-date LC maps. Mapping and monitoring of LC in India is being carried out at national level using multi-temporal IRS AWiFS data. Multispectral data such as IKONOS, Landsat- TM/ETM+, IRS-1C/D LISS-III/IV, AWiFS and SPOT-5, etc. have adequate spatial resolution (~ 1m to 56m) for LC mapping to generate 1:50,000 maps. However, for developing countries and those with large geographical extent, seasonal LC mapping is prohibitive with data from commercial sensors of limited spatial coverage. Superspectral data from the MODIS sensor are freely available, have better temporal (8 day composites) and spectral information. MODIS pixels typically contain a mixture of various LC types (due to coarse spatial resolution of 250, 500 and 1000 m), especially in more fragmented landscapes. In this context, linear spectral unmixing would be useful for mapping patchy land covers, such as those that characterise much of the Indian subcontinent. This work evaluates the existing unmixing technique for LC mapping using MODIS data, using end- members that are extracted through Pixel Purity Index (PPI), Scatter plot and N-dimensional visualisation. The abundance maps were generated for agriculture, built up, forest, plantations, waste land/others and water bodies. The assessment of the results using ground truth and a LISS-III classified map shows 86% overall accuracy, suggesting the potential for broad-scale applicability of the technique with superspectral data for natural resource planning and inventory applications.

Characterisation of Landscape with Forest Fragmentation Dynamics

Land cover (LC) and land use (LU) dynamics induced by human and natural processes play a major role in global as well as regional patterns of landscapes influencing biodiversity, hydrology, ecology and climate. Changes in LC features resulting in forest fragmentations have posed direct threats to biodiversity, endangering the sustainability of ecological goods and services. Habitat fragmentation is of added concern as the residual spatial patterns mitigate or exacerbate edge effects. LU dynamics are obtained by classifying temporal remotely sensed satellite imagery of different spatial and spectral resolutions. This paper reviews five different image classification algorithms using spatio-temporal data of a temperate watershed in Himachal Pradesh, India. Gaussian Maximum Likelihood classifier was found to be apt for analysing spatial pattern at regional scale based on accuracy assessment through error matrix and ROC (receiver operating characteristic) curves. The LU information thus derived was then used to assess spatial changes from temporal data using principal component analysis and correspondence analysis based image differencing. The forest area dynamics was further studied by analysing the different types of fragmentation through forest fragmentation models. The computed forest fragmentation and landscape metrics show a decline of interior intact forests with a substantial increase in patch forest during 1972-2007.

Random forest algorithm with derived geographical layers for improved classification of remote sensing data

Effective conservation and management of natural resources requires up-to-date information of the land cover (LC) types and their dynamics. The LC dynamics are being captured using multi-resolution remote sensing (RS) data with appropriate classification strategies. RS data with important environmental layers (either remotely acquired or derived from ground measurements) would however be more effective in addressing LC dynamics and associated changes. These ancillary layers provide additional information for delineating LC classes' decision boundaries compared to the conventional classification techniques. This communication ascertains the possibility of improved classification accuracy of RS data with ancillary and derived geographical layers such as vegetation index, temperature, digital elevation model (DEM), aspect, slope and texture. This has been implemented in three terrains of varying topography. The study would help in the selection of appropriate ancillary data depending on the terrain for better classified information.

Forest observational studies in India: Past developments and considerations for the future

Long term forest research sites in India, going by different names including Linear Tree Increment Plots, Linear Increment Plots, Linear Sample Plots and Permanent Preservation Plots, cover diverse plant communities and environmental conditions. Presently, some of these long-term observational studies are functional, some are disturbed and others have almost been lost. The accumulated data will become increasingly important in the context of environmental modelling and climate change, especially if the plots and data can be maintained and/or revived. This contribution presents the history and current state of forest research plots in India, including details of locations and re-measurements. We provide a brief introduction of the National Forest Inventory (NFI), Preservation Plots in natural forests, the 50-ha Mudumalai Forest Dynamics Plot as part of the Centre for Tropical Forest Science and Smithsonian Institution Global Earth Observatories network (CTFS-SIGEO), and research plots established in plantations for tree growth studies and modelling. We also present some methodological details including assessment and analysis for two types of observational studies, the Tree Count Plots (TCP) and Tree Re-measurement Plots (TRP). Arguments are presented in favour of enumeration and analysis methods which are consistent with current approaches in forest ecological research. (c) 2013 Elsevier B.V. All rights reserved.

Satellite-derived direct radiative effect of aerosols dependent on cloud cover

Aerosols from biomass burning can alter the radiative balance of the Earth by reflecting and absorbing solar radiation(1). Whether aerosols exert a net cooling or a net warming effect will depend on the aerosol type and the albedo of the underlying surface(2). Here, we use a satellite-based approach to quantify the direct, top-of-atmosphere radiative effect of aerosol layers advected over the partly cloudy boundary layer of the southeastern Atlantic Ocean during July-October of 2006 and 2007. We show that the warming effect of aerosols increases with underlying cloud coverage. This relationship is nearly linear, making it possible to define a critical cloud fraction at which the aerosols switch from exerting a net cooling to a net warming effect. For this region and time period, the critical cloud fraction is about 0.4, and is strongly sensitive to the amount of solar radiation the aerosols absorb and the albedo of the underlying clouds. We estimate that the regional-mean warming effect of aerosols is three times higher when large-scale spatial covariation between cloud cover and aerosols is taken into account. These results demonstrate the importance of cloud prediction for the accurate quantification of aerosol direct effects.

Impact of Grazing, Fire and Extraction on the Bamboo (Dendrocalamus-Strictus and Bambusa-Arundinacea) Populations of Karnataka

Dendrocalamus strictus and Bambusa arundinacea are monocarpic, gregariously flowering species of bamboo, common in the deciduous forests of the State of Karnataka in India. Their populations have significantly declined, especially since the last flowering. This decline parelleis increasing incidence of grazing, fire and extraction in recent decades. Results of an experiment in which the intensities of grazing and fire were varied, indicate that while grazing significantly depresses the survival of seedlings and the recruitment of new eulms of bamboo clumps, fire appeared to enhance seedling survival, presumably by reducing competition of lass fire-resistant species. New shoots of bamboo are destroyed by insects and a variety of herbivorous mammals. In areas of intense herbivore pressure, a bamboo clump initiates the production of a much larger number of new culrm, but results in many fewer and shorter intact culms. Extraction renders the new shoots more susceptible to herbivore pressure by removal of the protective covering of branches at the base of a bamboo clump. Hence, regular and extensive extraction by the paper mills in conjuction with intense grazing pressure strongly depresses the addition of new culms to bamboo clumps. Regulation of grazing in the forest by domestic livestock along with maintenance of the cover at the base of the clumps by extracting the culms at a higher level should reduce the rate of decline of the bamboo stocks.

Space and time efficiency of the forest-of-quadtrees representation

A forest of quadtrees is a refinement of a quadtree data structure that is used to represent planar regions. A forest of quadtrees provides space savings over regular quadtrees by concentrating vital information. The paper presents some of the properties of a forest of quadtrees and studies the storage requirements for the case in which a single 2m × 2m region is equally likely to occur in any position within a 2n × 2n image. Space and time efficiency are investigated for the forest-of-quadtrees representation as compared with the quadtree representation for various cases.