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Dr. Sudhakar Reddy Chintala
Forest Biodiversity and Ecology Division, National Remote Sensing Centre, Indian Space Research Organisation, Hyderabad, India

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0 Forest Ecology
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Journal article
Published: 30 July 2021 in Agriculture
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Apple cultivation in the Kinnaur district of the northern Indian State of Himachal Pradesh faces challenges from climatic changes and developmental activities. Farmers in the neighboring districts have already faced a major loss of livelihood due to seasonal changes. Therefore, it is important to study the extent of seasonal variations in the apple growing locations of this region. This study makes that attempt by assessing seasonality variations during a 15-year period from 2004 to 2018 when maximum construction activities occurred in this region. The study uses geospatial and statistical techniques in addition to farmer perceptions obtained during a field visit in November 2019. A temporal pattern using a normalized difference vegetation index (NDVI) based on Moderate Resolution Imaging Spectroradiometer (MODIS) was studied for seven apple-growing locations in the district. The results show high seasonal variations and reduced snowfall at lower elevations, resulting in less chilling hours, which are necessary for the healthy growth of apples. The normalized difference snow index (NDSI) and rainfall show a high correlation with apple growth. Local farmers are unprepared for future seasonal disturbances, as they lack early warning systems, insurance for apple crops, and alternative livelihood options.

ACS Style

Himangana Gupta; Lakhvinder Kaur; Mahbooba Asra; Ram Avtar; C. Reddy. MODIS NDVI Multi-Temporal Analysis Confirms Farmer Perceptions on Seasonality Variations Affecting Apple Orchards in Kinnaur, Himachal Pradesh. Agriculture 2021, 11, 724 .

AMA Style

Himangana Gupta, Lakhvinder Kaur, Mahbooba Asra, Ram Avtar, C. Reddy. MODIS NDVI Multi-Temporal Analysis Confirms Farmer Perceptions on Seasonality Variations Affecting Apple Orchards in Kinnaur, Himachal Pradesh. Agriculture. 2021; 11 (8):724.

Chicago/Turabian Style

Himangana Gupta; Lakhvinder Kaur; Mahbooba Asra; Ram Avtar; C. Reddy. 2021. "MODIS NDVI Multi-Temporal Analysis Confirms Farmer Perceptions on Seasonality Variations Affecting Apple Orchards in Kinnaur, Himachal Pradesh." Agriculture 11, no. 8: 724.

Review paper
Published: 07 June 2021 in Biodiversity and Conservation
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Global biodiversity monitoring systems through remote sensing can support consistent assessment, monitoring, modelling and reporting on biodiversity which are key activities intended for sustainable management. This work presents an overview of biodiversity monitoring components, i.e. biodiversity levels, essential biodiversity variables, biodiversity indicators, scale, biodiversity inventory, biodiversity models, habitat, ecosystem services, vegetation health and biogeochemical heterogeneity and discusses what remote sensing through Earth Observations has contributed to the study of biodiversity. The technological advancements in remote sensing have enabled information-rich data on biodiversity. Remote sensing data are making a strong contribution in providing unique information relevant to various biodiversity research and conservation applications. The extensive use of Earth observation data are not yet realized in biodiversity assessment, monitoring and conservation. The development of direct remote sensing approaches and the techniques for quantifying biodiversity at the community to species level is likely to be a great challenge for comprehensive earth observation-based monitoring strategy.

ACS Style

C. Sudhakar Reddy. Remote sensing of biodiversity: what to measure and monitor from space to species? Biodiversity and Conservation 2021, 30, 2617 -2631.

AMA Style

C. Sudhakar Reddy. Remote sensing of biodiversity: what to measure and monitor from space to species? Biodiversity and Conservation. 2021; 30 (10):2617-2631.

Chicago/Turabian Style

C. Sudhakar Reddy. 2021. "Remote sensing of biodiversity: what to measure and monitor from space to species?" Biodiversity and Conservation 30, no. 10: 2617-2631.

Journal article
Published: 28 April 2021 in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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Accurate assessment of carbon stock of trees is essential to model carbon dynamics in the forest ecosystem. Estimation of carbon stock at regional level involves successive quantitative modeling at various scales. While developments in aerial and satellite remote sensing at greatly reduced the uncertainty in up scaling of plot level biomass carbon stock estimates to regional or national estimates. A substantial amount of uncertainty in the system comes when carbon stock of each tree in a plot is estimated from established allometric equations. In this study 12 trees were destructively measured for their carbon stock value and the same was estimated using Terrestrial Laser Scanning technique, local allometric equations and global allometric equations. The carbon content estimates from terrestrial Laser Scanning method (26.01% RMSE relative to mean) were consistently closer to destructive measurements as compared to local allometric equations (42.58%-101.88% RMSE relative to mean) and global allometric equations (38.8%-50.69% RMSE relative to mean). Field measurement of sample wood density and sample carbon content significantly reduced the uncertainty in local allometric equations. The sources of error and applicability of each technique are discussed in this study.

ACS Style

Jayant Singhal; Gaurav Srivastava; C. Sudhakar Reddy; Gopalakrishnan Rajashekar; Chandra Shekhar Jha; P.V. Narsimha Rao; Gillella Ravi Shankar Reddy; Parth Sarathi Roy. Assessment of Carbon Stock at Tree Level Using Terrestrial Laser Scanning Vs. Traditional Methods in Tropical Forest, India. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2021, 14, 5064 -5071.

AMA Style

Jayant Singhal, Gaurav Srivastava, C. Sudhakar Reddy, Gopalakrishnan Rajashekar, Chandra Shekhar Jha, P.V. Narsimha Rao, Gillella Ravi Shankar Reddy, Parth Sarathi Roy. Assessment of Carbon Stock at Tree Level Using Terrestrial Laser Scanning Vs. Traditional Methods in Tropical Forest, India. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2021; 14 (99):5064-5071.

Chicago/Turabian Style

Jayant Singhal; Gaurav Srivastava; C. Sudhakar Reddy; Gopalakrishnan Rajashekar; Chandra Shekhar Jha; P.V. Narsimha Rao; Gillella Ravi Shankar Reddy; Parth Sarathi Roy. 2021. "Assessment of Carbon Stock at Tree Level Using Terrestrial Laser Scanning Vs. Traditional Methods in Tropical Forest, India." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 14, no. 99: 5064-5071.

Research article
Published: 06 April 2021 in International Journal of Remote Sensing
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Haze is a common atmospheric disturbance that adversely affects the quality of optical data, thus often restricting their usability. Since these effects are inherent in the process of spaceborne Earth sensing, it is important to develop effective methods to remove them. This work proposes a novel method for de-hazing satellite imagery and outdoor camera images. It is developed by modifying the transmission map used in Dark Channel Prior (DCP) method. A Weighted Variance Guided Filter (WVGF) is introduced for enhancing the image quality, which included a two-stage image decomposition and fusion process. The method also optimally combines the radiance and transmission components along with an additional stage modelling a fusion-based transparency function. A final guided filter-based image refinement scheme is incorporated to improve the processed image quality. The optimal tuning of the image-dependent parameters at various stages is achieved using the newly proposed Adaptive Black Widow Optimization (ABWO) algorithm, which makes the proposed de-hazing scheme fully automatic. Qualitative and quantitative performance analyses, and the results are compared with other state-of-the-art methods. The experimental results reveal that the proposed method performs better as compared with others, independent of the haze density, without losing the natural look of the scene.

ACS Style

Shilpa Suresh; Ragesh Rajan M.; Jagalingam Pushparaj; Asha Cs; Shyam Lal; Chintala Sudhakar Reddy. Dehazing of Satellite Images using Adaptive Black Widow Optimization-based framework. International Journal of Remote Sensing 2021, 42, 5068 -5086.

AMA Style

Shilpa Suresh, Ragesh Rajan M., Jagalingam Pushparaj, Asha Cs, Shyam Lal, Chintala Sudhakar Reddy. Dehazing of Satellite Images using Adaptive Black Widow Optimization-based framework. International Journal of Remote Sensing. 2021; 42 (13):5068-5086.

Chicago/Turabian Style

Shilpa Suresh; Ragesh Rajan M.; Jagalingam Pushparaj; Asha Cs; Shyam Lal; Chintala Sudhakar Reddy. 2021. "Dehazing of Satellite Images using Adaptive Black Widow Optimization-based framework." International Journal of Remote Sensing 42, no. 13: 5068-5086.

Article
Published: 14 January 2021 in Environmental Monitoring and Assessment
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The main focus in biodiversity is to conserve species diversity with specific emphasis on endemic species. This study has analysed the distribution of endemic floral and faunal species and their representativeness in protected areas of India. The number of endemic species has been estimated as 29787 (30.35%) and 12696 (26.33%) of Indian fauna and flora respectively. Overall, 2055 animal species and 1983 plant species were discovered from India from 2009 to 2018. The number of new distributional records to India reported during the last decade is 1242 species of plants and 1086 species of animals. The species discovery data indicate that there are more species yet to be described. According to the Cramer coefficients, the elevation was strongly correlated with endemism, followed by precipitation, temperature, land cover, and biogeographic zone. The study of endemic floral and faunal species including new species and protected areas provides the first prototype national gap analysis in assessing the representativeness of coverage of protected areas. The patterns of geographic distribution of endemic species and the gap analysis present a novel finding for conservation priorities. The highest number of new species was discovered from protected areas i.e. Periyar, Mundathurai, Khangchendzonga, Mehao, Thattekadu Bird, Eravikulam, Mukurthi, Saddle Peak, Malabar, and Anamalai. Although the total area protected is significant in India, their geographic coverage is almost the contrary to patterns of endemism. The results provide a valued direction for the advancement of management strategies for biodiversity conservation.

ACS Style

C. Sudhakar Reddy; Anuja Joseph; Gija Anna Abraham; Minu Merin Sabu. Patterns of animal and plant discoveries, distribution and endemism in India—implications on the effectiveness of the protected area network. Environmental Monitoring and Assessment 2021, 193, 1 -16.

AMA Style

C. Sudhakar Reddy, Anuja Joseph, Gija Anna Abraham, Minu Merin Sabu. Patterns of animal and plant discoveries, distribution and endemism in India—implications on the effectiveness of the protected area network. Environmental Monitoring and Assessment. 2021; 193 (2):1-16.

Chicago/Turabian Style

C. Sudhakar Reddy; Anuja Joseph; Gija Anna Abraham; Minu Merin Sabu. 2021. "Patterns of animal and plant discoveries, distribution and endemism in India—implications on the effectiveness of the protected area network." Environmental Monitoring and Assessment 193, no. 2: 1-16.

Review paper
Published: 06 November 2020 in Biodiversity and Conservation
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The strong contribution of remote sensing has led to the development of the concept of the Remote Sensing enabled Essential Biodiversity Variables which represents a set of variables that can be monitored from space. This work synthesizes current state of research and technological development in use of remote sensing enabled essential biodiversity variables. The issue of scale, satellite observation requirements and status of remote sensing have been discussed in the context of monitoring of community composition, plant functional types, vegetation structure, canopy diversity, targeted animal groups, fragmentation, disturbances and as an input for biodiversity modelling, and Earth Observations based variables. This work highlighted existing approaches for addressing community level biodiversity and discusses in the context of Earth Observations as which are key components for biodiversity monitoring strategy. Biodiversity monitoring could be improved by using new satellite sensors and the synergy of remotely sensed data from multiple sensors which are providing hyperspatial, hyperspectral and hypertemporal observations. The use of remote sensing for operational monitoring of biodiversity is still under development as existing approaches and techniques have not holistically addressed the metrics of essential biodiversity variables.

ACS Style

C. Sudhakar Reddy; Ayushi Kurian; Gaurav Srivastava; Jayant Singhal; A. O. Varghese; Hitendra Padalia; N. Ayyappan; G. Rajashekar; C. S. Jha; P. V. N. Rao. Remote sensing enabled essential biodiversity variables for biodiversity assessment and monitoring: technological advancement and potentials. Biodiversity and Conservation 2020, 30, 1 -14.

AMA Style

C. Sudhakar Reddy, Ayushi Kurian, Gaurav Srivastava, Jayant Singhal, A. O. Varghese, Hitendra Padalia, N. Ayyappan, G. Rajashekar, C. S. Jha, P. V. N. Rao. Remote sensing enabled essential biodiversity variables for biodiversity assessment and monitoring: technological advancement and potentials. Biodiversity and Conservation. 2020; 30 (1):1-14.

Chicago/Turabian Style

C. Sudhakar Reddy; Ayushi Kurian; Gaurav Srivastava; Jayant Singhal; A. O. Varghese; Hitendra Padalia; N. Ayyappan; G. Rajashekar; C. S. Jha; P. V. N. Rao. 2020. "Remote sensing enabled essential biodiversity variables for biodiversity assessment and monitoring: technological advancement and potentials." Biodiversity and Conservation 30, no. 1: 1-14.

Journal article
Published: 01 February 2020 in Science of The Total Environment
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Tropical mangrove represents one of the most threatened ecosystems despite their huge contribution to ecosystem services, carbon (C) sequestration and climate change mitigation. Understanding the system in light of seasonal fluctuations on greenhouse gases (GHGs) emissions due to human interferences and the tidal effect is important for devising site-specific real-time climate change mitigation strategies. In order to capture the seasonal variations, the three modes of transport of GHGs through pneumatophore, ebullition as bubbles and water-soluble diffusion was quantified. The three unique techniques for the gas collection were used to estimate the GHGs [methane (CH4), nitrous oxide (N2O) and carbon dioxide (CO2)] emission, at three degraded-mangrove sites in Sundarban, India. We identified three degraded mangrove ecologies based on the remote sensing data of 1930 and 2013 (mangrove-covered area in Sundarban; 2387, 2136 km2, respectively). Samples were collected and analyzed for four seasons [winter (November-January), summer (February-April), pre-monsoon (May-June) and monsoon (July-October)], at three representative sites (Sadhupur, Dayapur, and Pakhiralaya). Monsoonal CH4 and CO2 fluxes (0.353 ± 0.026 and 64.5 ± 6.1 mmol m-2 d-1, respectively) were higher than winter and summer. However, the soil labile C pools showed the opposite trend i.e. more in summer followed by winter and monsoon. In contrast, the N2O fluxes were more during summer (54.2 ± 3.2 μmol m-2 d-1). The stagnant water had higher dissolved GHGs concentration compared to tidewater due to less salinity and a long time of stagnation. The mode of transport of GHGs through pneumatophore, ebullition, and water-soluble diffusion was also significantly varied with seasons, soil‑carbon status and tidewater intrusion. Therefore, seasonal fluctuations of GHGs emission and tidal effect must be considered along with soil labile C pools for GHG-C budgeting and climate change mitigation in the mangrove ecosystem.

ACS Style

S.R. Padhy; P. Bhattacharyya; P.K. Dash; Sudhakar Reddy; A. Chakraborty; H. Pathak. Seasonal fluctuation in three mode of greenhouse gases emission in relation to soil labile carbon pools in degraded mangrove, Sundarban, India. Science of The Total Environment 2020, 705, 135909 .

AMA Style

S.R. Padhy, P. Bhattacharyya, P.K. Dash, Sudhakar Reddy, A. Chakraborty, H. Pathak. Seasonal fluctuation in three mode of greenhouse gases emission in relation to soil labile carbon pools in degraded mangrove, Sundarban, India. Science of The Total Environment. 2020; 705 ():135909.

Chicago/Turabian Style

S.R. Padhy; P. Bhattacharyya; P.K. Dash; Sudhakar Reddy; A. Chakraborty; H. Pathak. 2020. "Seasonal fluctuation in three mode of greenhouse gases emission in relation to soil labile carbon pools in degraded mangrove, Sundarban, India." Science of The Total Environment 705, no. : 135909.

Article
Published: 01 December 2019 in Environmental Monitoring and Assessment
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The land, oceans, and atmosphere are tightly linked and form the most dynamic component of the climate system. Studies on terrestrial and ocean science enhance the understanding on the impacts of climate change. Across India and the world over, human-driven land use and climate changes are altering the structure, function, and extent of natural terrestrial ecosystems and in turn regional biogeochemical feedbacks. In this special issue, we present 29 manuscripts; those discuss wide-ranging aspects of terrestrial and oceanic characterization and dynamics. These contributions are based on selected presentations made at the 2nd International Workshop on Biodiversity and Climate Change (BDCC-2018) held on 24-27 February 2018 at the Indian Institute of Technology Kharagpur, India. The manuscripts are arranged in five sections such as Ecological Assessment, Plant Invasion, Carbon Dynamics, Ecosystem Characterization, and Ocean Dynamics. We realized that the utility of satellite remote sensing data has been emerging as a dominant trend in environmental monitoring and assessment studies in India.

ACS Style

M. D. Behera; Sudhakar Reddy; Mohammed Latif Khan. Advances in terrestrial and ocean dynamics studies in India. Environmental Monitoring and Assessment 2019, 191, 811 -6.

AMA Style

M. D. Behera, Sudhakar Reddy, Mohammed Latif Khan. Advances in terrestrial and ocean dynamics studies in India. Environmental Monitoring and Assessment. 2019; 191 (3):811-6.

Chicago/Turabian Style

M. D. Behera; Sudhakar Reddy; Mohammed Latif Khan. 2019. "Advances in terrestrial and ocean dynamics studies in India." Environmental Monitoring and Assessment 191, no. 3: 811-6.

Article
Published: 01 December 2019 in Environmental Monitoring and Assessment
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India is home of the largest remaining population of the Asian elephant (Elephas maximus L.) in the South and Southeast Asia. The forest loss and fragmentation is the main threat to the long-term survival of Asian elephants. In the present study, we assessed forest loss and fragmentation in the major elephant ranging provinces in India, viz., north-eastern, north-western, central, and southern since the 1930s. We quantified forest cover changes by generating and analyzing forest cover maps of 1930, 1975, and 2013, whereas fragmentation of contiguous forest areas was quantified by applying landscape metrics on the temporal forest cover maps. A total of 21.49% of the original forest cover was lost from 1930 to 1975, while another 3.19% forest cover was lost from 1975 to 2013 in the elephant ranges in India. The maximum forest loss occurred in the southern range (13,084 km2) followed by north-eastern (10,188 km2), central (5614 km2), and north-western (4030 km2) elephant ranges in the past eight decades. The forests in the central range were the most fragmented followed by southern, north-eastern, and north-western elephant ranges. The forest fragmentation in the southern range occurred at the fastest rate than central, north-eastern, and north-western ranges. The core forest areas shrunk by 39.6% from 1930 to 2013. The causative factors of forest change and situation of elephant-human conflict have been discussed. Study outcomes would be helpful in planning effective conservation strategies for Asian elephants in India.

ACS Style

Hitendra Padalia; Surajit Ghosh; C. Sudhakar Reddy; Subrata Nandy; Sarnam Singh; A. Senthil Kumar. Assessment of historical forest cover loss and fragmentation in Asian elephant ranges in India. Environmental Monitoring and Assessment 2019, 191, 1 -13.

AMA Style

Hitendra Padalia, Surajit Ghosh, C. Sudhakar Reddy, Subrata Nandy, Sarnam Singh, A. Senthil Kumar. Assessment of historical forest cover loss and fragmentation in Asian elephant ranges in India. Environmental Monitoring and Assessment. 2019; 191 (3):1-13.

Chicago/Turabian Style

Hitendra Padalia; Surajit Ghosh; C. Sudhakar Reddy; Subrata Nandy; Sarnam Singh; A. Senthil Kumar. 2019. "Assessment of historical forest cover loss and fragmentation in Asian elephant ranges in India." Environmental Monitoring and Assessment 191, no. 3: 1-13.

Article
Published: 01 December 2019 in Environmental Monitoring and Assessment
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Forest fire is considered as one of the major threats to global biodiversity and a significant source of greenhouse gas emissions. Rising temperatures, weather conditions, and topography promote the incidences of fire due to human ignition in South Asia. Because of its synoptic, multi-spectral, and multi-temporal nature, remote sensing data can be a state of art technology for forest fire management. This study focuses on the spatio-temporal patterns of forest fires and identifying hotspots using the novel geospatial technique "emerging hotspot analysis tool" in South Asia. Daily MODIS active fire locations data of 15 years (2003-2017) has been aggregated in order to characterize fire frequency, fire density, and hotspots. A total of 522,348 active fire points have been used to analyze risk of fires across the forest types. Maximum number of forest fires in South Asia was occurring during the January to May. Spatial analysis identified areas of frequent burning and high fire density in South Asian countries. In South Asia, 51% of forest grid cells were affected by fires in 15 years. Highest number of fire incidences was recorded in tropical moist deciduous forest and tropical dry deciduous forest. The emerging hotspots analysis indicates prevalence of sporadic hotspots, followed by historical hotspots, consecutive hotspots, and persistent hotspots in South Asia. Of the seven South Asian countries, Bangladesh has highest emerging hotspot area (34.2%) in forests, followed by 32.2% in India and 29.5% in Nepal. Study results offer critical insights in delineation of fire vulnerable forest landscapes which will stand as a valuable input for strengthening management of fires in South Asia.

ACS Style

C. Sudhakar Reddy; Natalia Grace Bird; S. Sreelakshmi; T. Maya Manikandan; Mahbooba Asra; P. Hari Krishna; C. S. Jha; P. V. N. Rao; P. G. Diwakar. Identification and characterization of spatio-temporal hotspots of forest fires in South Asia. Environmental Monitoring and Assessment 2019, 191, 791 .

AMA Style

C. Sudhakar Reddy, Natalia Grace Bird, S. Sreelakshmi, T. Maya Manikandan, Mahbooba Asra, P. Hari Krishna, C. S. Jha, P. V. N. Rao, P. G. Diwakar. Identification and characterization of spatio-temporal hotspots of forest fires in South Asia. Environmental Monitoring and Assessment. 2019; 191 (3):791.

Chicago/Turabian Style

C. Sudhakar Reddy; Natalia Grace Bird; S. Sreelakshmi; T. Maya Manikandan; Mahbooba Asra; P. Hari Krishna; C. S. Jha; P. V. N. Rao; P. G. Diwakar. 2019. "Identification and characterization of spatio-temporal hotspots of forest fires in South Asia." Environmental Monitoring and Assessment 191, no. 3: 791.

Research article
Published: 20 November 2019 in Journal of the Indian Society of Remote Sensing
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This is the first of its kind work on the assessment of forest burnt area and fire hotspots of Myanmar using Landsat OLI data and spatial statistics tool. Burnt area analysis indicates 15.2% of vegetation area was affected by fires in 2017. Analysis of burnt area at state level indicates Kayah affected by more fires in 2017. Of the total vegetation fire occurrences from 2003 to 2017 about 44.7% were observed in the forested landscapes of Myanmar. The emerging hotspot analysis had shown the highest spatial extent of persistent hotspots followed by oscillating hotspots. Forest fire hotspots are mainly found in the states of Kayah, Shan, Bago, Nayi Pyi Taw, Magway, Mandalay, Chin, and Kayin. Overall earth observations based on 2003 to 2017 fire occurrences indicate a declining trend of fires in Myanmar. A comparison of the fire occurrences recorded by MODIS and VIIRS indicates that VIIRS is capable of detecting a greater number of fire incidences. The findings of the study would support in assessing the impact of fires on forest, its structure, composition, function, and provide valuable input for nationwide forest fire management.

ACS Style

Anjaly Unnikrishnan; C. Sudhakar Reddy. Characterizing Distribution of Forest Fires in Myanmar Using Earth Observations and Spatial Statistics Tool. Journal of the Indian Society of Remote Sensing 2019, 48, 227 -234.

AMA Style

Anjaly Unnikrishnan, C. Sudhakar Reddy. Characterizing Distribution of Forest Fires in Myanmar Using Earth Observations and Spatial Statistics Tool. Journal of the Indian Society of Remote Sensing. 2019; 48 (2):227-234.

Chicago/Turabian Style

Anjaly Unnikrishnan; C. Sudhakar Reddy. 2019. "Characterizing Distribution of Forest Fires in Myanmar Using Earth Observations and Spatial Statistics Tool." Journal of the Indian Society of Remote Sensing 48, no. 2: 227-234.

Research article
Published: 19 July 2019 in Journal of the Indian Society of Remote Sensing
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Deforestation, fragmentation and fires are habitat transformers and responsible for loss of biodiversity. This study attempts to evaluate threat status of forest ecosystems by determining regional-level hot spots of deforestation, fragmentation and fires in Myanmar. The states of Ayeyarwady, Mandalay and Nay Pyi Taw have the highest annual rate of deforestation from 2005 to 2016. There is a significant reduction in spatial extent of large core forest. Mandalay and Nay Pyi Taw had shown more than 20% of loss in large core forest from 2005 to 2016. Geospatial analysis indicates all the major forest types were affected by fires during 2003 to 2017. The study found that dry deciduous forests were highly affected by fires. More than 60% of the forest area of Magway, Mandalay, Chin, Kayah, Kayin and Shan had found to be under forest fire hot spot. Comparative spatial assessment was carried out on fire hot spots, deforested and fragmented landscapes to provide overview of priority conservation areas. The study identified five states in Myanmar affected by multiple threats and categorised as Conservation Priority Hot Spot I, eight states as Conservation Priority Hot Spot II and two states as low-risk areas categorised as Conservation Priority Hot Spot III. The analysis of hot spots of deforestation, fragmentation and fires provides a consistent way of ecosystem monitoring and biodiversity conservation in Myanmar. The study demonstrates repeatable earth observations as an important prerequisite for sustainable forest management in Myanmar.

ACS Style

C. Sudhakar Reddy; Anjaly Unnikrishnan; Mahbooba Asra; T. Maya Manikandan; R. Jaishanker. Spatial Conservation Prioritisation of Threatened Forest Ecosystems in Myanmar. Journal of the Indian Society of Remote Sensing 2019, 47, 1737 -1749.

AMA Style

C. Sudhakar Reddy, Anjaly Unnikrishnan, Mahbooba Asra, T. Maya Manikandan, R. Jaishanker. Spatial Conservation Prioritisation of Threatened Forest Ecosystems in Myanmar. Journal of the Indian Society of Remote Sensing. 2019; 47 (10):1737-1749.

Chicago/Turabian Style

C. Sudhakar Reddy; Anjaly Unnikrishnan; Mahbooba Asra; T. Maya Manikandan; R. Jaishanker. 2019. "Spatial Conservation Prioritisation of Threatened Forest Ecosystems in Myanmar." Journal of the Indian Society of Remote Sensing 47, no. 10: 1737-1749.

Journal article
Published: 10 April 2019 in Current Science
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ACS Style

C. S. Jha; J. Singhal; Sudhakar Reddy; G. Rajashekar; S. Maity; C. Patnaik; Anup Das; Arundhati Misra; C. P. Singh; Jakesh Mohapatra; N. S. R. Krishnayya; Sandhya Kiran; Phil Townsend; Margarita Huesca Martinez. Characterization of Species Diversity and Forest Health using AVIRIS-NG Hyperspectral Remote Sensing Data. Current Science 2019, 116, 1 .

AMA Style

C. S. Jha, J. Singhal, Sudhakar Reddy, G. Rajashekar, S. Maity, C. Patnaik, Anup Das, Arundhati Misra, C. P. Singh, Jakesh Mohapatra, N. S. R. Krishnayya, Sandhya Kiran, Phil Townsend, Margarita Huesca Martinez. Characterization of Species Diversity and Forest Health using AVIRIS-NG Hyperspectral Remote Sensing Data. Current Science. 2019; 116 (7):1.

Chicago/Turabian Style

C. S. Jha; J. Singhal; Sudhakar Reddy; G. Rajashekar; S. Maity; C. Patnaik; Anup Das; Arundhati Misra; C. P. Singh; Jakesh Mohapatra; N. S. R. Krishnayya; Sandhya Kiran; Phil Townsend; Margarita Huesca Martinez. 2019. "Characterization of Species Diversity and Forest Health using AVIRIS-NG Hyperspectral Remote Sensing Data." Current Science 116, no. 7: 1.

Original paper
Published: 19 February 2019 in Biodiversity and Conservation
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The focus of the study was to develop a nation-wide forest cover database of Myanmar by assessing and predicting the forest cover changes in the period of 1950 to 2027. This study estimated the net changes in forests at regional level along with spatial patterns of forest fragmentation using multi-source data. The results indicate forest area representing as 77.1%, 65.3%, 54.1% and 50.6% of the total geographical area of Myanmar during 1950, 1975, 2005 and 2016 respectively. This study predicted the forest cover changes in Myanmar using Module for Land use change evaluation. The five spatial variables were used to determine the relationship between deforestation and explanatory variables. The predicted forest cover of Myanmar for 2027 shows 48.4% of total geographical area under forest. The model predicted a further decrease of 14,878 km2 of forest area in Myanmar between 2016 and 2027. The forest cover loss analysed using the classified maps of 1950 and 2016 indicated an overall loss of 34.4% of the forest cover. Ayeyarwady, Mandalay and Nayi Pyi Taw were found to be showing the highest rate of deforestation in the recent period of 2005–2016. This study has provided an insight for understanding of long-term deforestation trends of Myanmar. It offers a valuable inputs for effective management of forest resources and restoration programs as it delineates and forecast the spatial changes in forests from past to future.

ACS Style

C. Sudhakar Reddy; S. Vazeed Pasha; Kv Satish; Anjaly Unnikrishnan; Sapana B. Chavan; C. S. Jha; P. G. Diwakar; V. K. Dadhwal. Quantifying and predicting multi-decadal forest cover changes in Myanmar: a biodiversity hotspot under threat. Biodiversity and Conservation 2019, 28, 1129 -1149.

AMA Style

C. Sudhakar Reddy, S. Vazeed Pasha, Kv Satish, Anjaly Unnikrishnan, Sapana B. Chavan, C. S. Jha, P. G. Diwakar, V. K. Dadhwal. Quantifying and predicting multi-decadal forest cover changes in Myanmar: a biodiversity hotspot under threat. Biodiversity and Conservation. 2019; 28 (5):1129-1149.

Chicago/Turabian Style

C. Sudhakar Reddy; S. Vazeed Pasha; Kv Satish; Anjaly Unnikrishnan; Sapana B. Chavan; C. S. Jha; P. G. Diwakar; V. K. Dadhwal. 2019. "Quantifying and predicting multi-decadal forest cover changes in Myanmar: a biodiversity hotspot under threat." Biodiversity and Conservation 28, no. 5: 1129-1149.

Original paper
Published: 05 December 2018 in Biodiversity and Conservation
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An ecosystem approach is the only way to conserve habitats and the enormous number of species. The related area-based Aichi biodiversity target of the convention on biological diversity aims to conserve at least 17% of terrestrial environment by 2020. This is the first regional study to recognize a network of key habitats to achieve conservation goals. It is essential to have a spatial framework by creating the indicator using existing remote sensing-based data. In this work, conservation principles were integrated at the ecosystem level covering irreplaceability and vulnerability along with representativeness. Forest persistence, ecosystem rarity, forest intactness, landscape-level ecosystem, biomass carbon stocks, and biological richness were among the biological criteria used to analyze ecosystem irreplaceability. The proxies used for ecosystem vulnerability are high fragmentation, fire hotspots and proximity to disturbance factors. A unique value is assigned to each individual pixel in the prioritization map. Overall representation of habitat coverage in protected area network of South Asian countries indicates under-representation of several forest types with less than 17% coverage. The overlay of the priority areas proposes that there is a possibility of conserving many species with the notification of protected areas. This study demonstrates the conservation priorities by identifying key habitats based on multiple conservation principles.

ACS Style

C. Sudhakar Reddy; V. S. Faseela; Anjaly Unnikrishnan; C. S. Jha. Earth observation data for assessing biodiversity conservation priorities in South Asia. Biodiversity and Conservation 2018, 28, 2197 -2219.

AMA Style

C. Sudhakar Reddy, V. S. Faseela, Anjaly Unnikrishnan, C. S. Jha. Earth observation data for assessing biodiversity conservation priorities in South Asia. Biodiversity and Conservation. 2018; 28 (8-9):2197-2219.

Chicago/Turabian Style

C. Sudhakar Reddy; V. S. Faseela; Anjaly Unnikrishnan; C. S. Jha. 2018. "Earth observation data for assessing biodiversity conservation priorities in South Asia." Biodiversity and Conservation 28, no. 8-9: 2197-2219.

Article
Published: 08 November 2018 in Journal of the Geological Society of India
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Earth Observation with large suite of sensors and with capabilities to address natural resources at multiple scales has proven to be a critical resource in setting conservation priorities of a region. The role of earth observation data was recognized towards achieving international biodiversity targets by 2020. Ecosystem irreplaceability and ecosystem vulnerability are two concepts key to understanding and preparing conservation priority maps. This study presents spatial conservation prioritization analysis for forests of ‘Western Ghats biodiversity hotspot’. Earth observation data products have been used for prioritization of areas of irreplaceability and vulnerability that are significant for conservation planning. The spatial surrogates of biodiversity in terms of very dense forest, biological richness, intactness and rarity of habitat are analyzed for evaluation of ecosystem irreplaceability. Fragmentation, forest fires, plant invasion and disturbance index are surrogates included for spatial analysis of ecosystem vulnerability. Vegetation type wise analysis indicates dry deciduous forests are under high vulnerability, followed by moist deciduous forests. The high concentration of irreplaceability is observed in Shola followed by wet evergreen forests and semi-evergreen forests. Spatial prioritization approach has identified about 18% of the forest area as irreplaceable which represents overlapped area of very dense forest, shola, intact forest and high biological richness. We observed that the overlap of forest areas of irreplaceability with vulnerability in southern Western Ghats, which needs high priority of conservation. This study is the first of its kind wherein multi-source earth observation data has been analysed to examine the quantitative criteria at regional level in Western Ghats.

ACS Style

Sudhakar Reddy; C. S. Jha; V. K. Dadhwal. Earth Observations based Conservation Prioritization in Western Ghats, India. Journal of the Geological Society of India 2018, 92, 562 -567.

AMA Style

Sudhakar Reddy, C. S. Jha, V. K. Dadhwal. Earth Observations based Conservation Prioritization in Western Ghats, India. Journal of the Geological Society of India. 2018; 92 (5):562-567.

Chicago/Turabian Style

Sudhakar Reddy; C. S. Jha; V. K. Dadhwal. 2018. "Earth Observations based Conservation Prioritization in Western Ghats, India." Journal of the Geological Society of India 92, no. 5: 562-567.

Articles
Published: 02 September 2018 in Journal of Map & Geography Libraries
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Geospatial technologies have evolved as a science for location-based problem solving at varying scales – from local, regional, national and even global levels. Location intelligence is the core strength of geospatial technology and enables efficient public administration and ensures proper delivery of government services. Technical advancements in geospatial technology enabled new modes of government services through the g-governance toolkit. At the heart of this articulation lies the conceptualization of g-Governance as a geospatial plug-in for e-Governance. Emphasis has been given on harnessing geospatial technology for enabling governments to do the public services by exhibiting high-quality and cost-effective operations, delivery of services, citizen engagement, bringing transparency, and accountability in the public administration process. The need of g-Governance in various service verticals was analyzed and compiled in this article.

ACS Style

Dandabathla Giribabu; Sitiraju Srinivasa Rao; Sudhakar Reddy; Peddineni V.V. Prasada Rao. Coordination with the Help of Geographical Coordinates: g-Governance in India. Journal of Map & Geography Libraries 2018, 14, 75 -100.

AMA Style

Dandabathla Giribabu, Sitiraju Srinivasa Rao, Sudhakar Reddy, Peddineni V.V. Prasada Rao. Coordination with the Help of Geographical Coordinates: g-Governance in India. Journal of Map & Geography Libraries. 2018; 14 (2-3):75-100.

Chicago/Turabian Style

Dandabathla Giribabu; Sitiraju Srinivasa Rao; Sudhakar Reddy; Peddineni V.V. Prasada Rao. 2018. "Coordination with the Help of Geographical Coordinates: g-Governance in India." Journal of Map & Geography Libraries 14, no. 2-3: 75-100.

Articles
Published: 27 August 2018 in International Journal of Sustainable Development & World Ecology
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The five largest social safety net (SSN) programmes in the world are being implemented in India, China and Brazil. Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) is one of these programmes and regarded as the world’s largest SSN. MGNREGA aims at enhancing livelihood security of households in rural India by providing guaranteed wage employment. The scheme has resulted in the creation of sustainable assets that promote the economic and infrastructure development. More than 33 million assets were built in the process of MGNREGA. These assets were spread out in 262,380 smallest units of administration covering 6887 sub-districts with the participation of more than 250 million human manpower. The Sustainable Development Goals (SDG) aims to end poverty, protect the planet and ensure that all people enjoy peace and prosperity. The 17 goals tackle the root cause of poverty and attempts to make a positive change for both people and planet. Ecological regeneration or rejuvenation during the development of the assets generated numerous tangible and intangible benefits to the community in a sustainable way. MGNREGA, a federal government-sponsored scheme, using a decentralized approach is directly or indirectly helping to achieve all the 17 goals of sustainable development in India. This article takes a holistic approach to correlate and map the concepts and outcomes of MGNREGA programme with SDG. This article emphasises the fact that community-based participation in the planning and development activities at the regional levels will yield benefits to the biosphere, society and economy at the national level.

ACS Style

D. Giribabu; C. Mohapatra; Sudhakar Reddy; P. V.V. Prasada Rao. Holistic correlation of world’s largest social safety net and its outcomes with Sustainable Development Goals. International Journal of Sustainable Development & World Ecology 2018, 26, 113 -128.

AMA Style

D. Giribabu, C. Mohapatra, Sudhakar Reddy, P. V.V. Prasada Rao. Holistic correlation of world’s largest social safety net and its outcomes with Sustainable Development Goals. International Journal of Sustainable Development & World Ecology. 2018; 26 (2):113-128.

Chicago/Turabian Style

D. Giribabu; C. Mohapatra; Sudhakar Reddy; P. V.V. Prasada Rao. 2018. "Holistic correlation of world’s largest social safety net and its outcomes with Sustainable Development Goals." International Journal of Sustainable Development & World Ecology 26, no. 2: 113-128.

Journal article
Published: 01 February 2018 in Ecological Indicators
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ACS Style

Abhishek Chakraborty; M.V.R. Seshasai; C. Sudhakar Reddy; V.K. Dadhwal. Persistent negative changes in seasonal greenness over different forest types of India using MODIS time series NDVI data (2001–2014). Ecological Indicators 2018, 85, 887 -903.

AMA Style

Abhishek Chakraborty, M.V.R. Seshasai, C. Sudhakar Reddy, V.K. Dadhwal. Persistent negative changes in seasonal greenness over different forest types of India using MODIS time series NDVI data (2001–2014). Ecological Indicators. 2018; 85 ():887-903.

Chicago/Turabian Style

Abhishek Chakraborty; M.V.R. Seshasai; C. Sudhakar Reddy; V.K. Dadhwal. 2018. "Persistent negative changes in seasonal greenness over different forest types of India using MODIS time series NDVI data (2001–2014)." Ecological Indicators 85, no. : 887-903.

Research article
Published: 10 January 2018 in Journal of the Indian Society of Remote Sensing
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This study aims to analyse the spatial pattern of deforestation and fragmentation in forests of Kinnerasani wildlife sanctuary and surroundings, Telangana, India. This study has found the annual deforestation rates between 2005 and 2015 as 1.38% and 1.50% inside and surroundings of the study area respectively. The fragmentation analysis reveals the high reduction in large core areas over the period of 2005–2015. Temporal forest cover change analysis was linked with predictive modelling to generate future forest cover scenario. The multi-layer perceptron neural network modelling was used for forecasting the deforestation for 2025. This study evaluates the nature of changes in deforestation and its affecting explanatory drivers such as slope (in degrees), elevation (in m), and the shortest distance to roads (in m), the shortest distance to nearest settlements (in m) and the distance from water bodies (in m). Spatial modelling has forecasted the annual change rate of forest as 0.19% in Kinnerasani wildlife sanctuary which indicates decreasing trend of forest loss in near future. The results of the study are useful as spatial input for conservation of forests in Kinnerasani wildlife sanctuary, Telangana, India.

ACS Style

Sapana B. Chavan; Sudhakar Reddy; S. Srinivasa Rao; K. Kameswara Rao. Assessing and Predicting Decadal Forest Cover Changes and Forest Fragmentation in Kinnerasani Wildlife Sanctuary, Telangana, India. Journal of the Indian Society of Remote Sensing 2018, 46, 729 -735.

AMA Style

Sapana B. Chavan, Sudhakar Reddy, S. Srinivasa Rao, K. Kameswara Rao. Assessing and Predicting Decadal Forest Cover Changes and Forest Fragmentation in Kinnerasani Wildlife Sanctuary, Telangana, India. Journal of the Indian Society of Remote Sensing. 2018; 46 (5):729-735.

Chicago/Turabian Style

Sapana B. Chavan; Sudhakar Reddy; S. Srinivasa Rao; K. Kameswara Rao. 2018. "Assessing and Predicting Decadal Forest Cover Changes and Forest Fragmentation in Kinnerasani Wildlife Sanctuary, Telangana, India." Journal of the Indian Society of Remote Sensing 46, no. 5: 729-735.