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Tropical deciduous forests are unique in terms of their geographical distribution, strong seasonality and their contribution to global carbon dynamics, but yet their carbon sequestration potential is poorly sampled. In the current study, we report the carbon balance of 65-year-old tropical dry deciduous forest in central India using the multi-year eddy covariance measurements from November 2011 to May 2019. Over the study period, the forest site was observed to be a net sink of atmospheric CO2 with a mean annual net ecosystem productivity (NEP) of 524 (± 40; ±1 SD across different years) g C m−2 yr−1 with a 233 (±15) day growing season. The NEP was partitioned into gross primary productivity (GPP) of 3358 (± 167) g C m−2 yr−1 and annual carbon loss due to respiration and decomposition (Reco) of 2834 (± 157) g C m−2 yr−1. The ecosystem showed a strong seasonality as a source of carbon during the leaf-off season (March to June), and as a carbon sink during the rest of the year with significant sequestration during the winter season (October to December). The intra-annual analysis suggested that CO2 flux is primarily controlled by canopy greenness with mean Reco/GPP ratio varying from 1.90 (± 0.12) to 0.79 (± 0.04) during leaf-off to leaf-on seasons. The monthly C fluxes in the growing season are found to be strongly correlated to the environmental variables rather than in the leaf-off season, while variability in monthly ecosystem respiration was better explained by air temperature during the leaf-off season than the growing season. Further, the inter-annual variability of NEP was mainly dependent on growing season length and mean annual temperature. The variations in annual GPP and Reco were directly dependent on the increase in mean annual temperature. The eddy covariance-based NEP was complemented by close independent biometric estimates, imparting confidence in our measurements. In conclusion, this tropical dry deciduous forest site is a substantial carbon sink and would add crucial information regarding carbon budgeting of tropical forests in global carbon balance models.
Suraj Reddy Rodda; Kiran Chand Thumaty; Mss Praveen; Chandra Shekhar Jha; Vinay Kumar Dadhwal. Multi-year eddy covariance measurements of net ecosystem exchange in tropical dry deciduous forest of India. Agricultural and Forest Meteorology 2021, 301-302, 108351 .
AMA StyleSuraj Reddy Rodda, Kiran Chand Thumaty, Mss Praveen, Chandra Shekhar Jha, Vinay Kumar Dadhwal. Multi-year eddy covariance measurements of net ecosystem exchange in tropical dry deciduous forest of India. Agricultural and Forest Meteorology. 2021; 301-302 ():108351.
Chicago/Turabian StyleSuraj Reddy Rodda; Kiran Chand Thumaty; Mss Praveen; Chandra Shekhar Jha; Vinay Kumar Dadhwal. 2021. "Multi-year eddy covariance measurements of net ecosystem exchange in tropical dry deciduous forest of India." Agricultural and Forest Meteorology 301-302, no. : 108351.
Sameer Saran; Geert Sterk; S. P. Aggarwal; V. K. Dadhwal. Coupling Remote Sensing and GIS with KINEROS2 Model for Spatially Distributed Runoff Modeling in a Himalayan Watershed. Journal of the Indian Society of Remote Sensing 2021, 49, 1121 -1139.
AMA StyleSameer Saran, Geert Sterk, S. P. Aggarwal, V. K. Dadhwal. Coupling Remote Sensing and GIS with KINEROS2 Model for Spatially Distributed Runoff Modeling in a Himalayan Watershed. Journal of the Indian Society of Remote Sensing. 2021; 49 (5):1121-1139.
Chicago/Turabian StyleSameer Saran; Geert Sterk; S. P. Aggarwal; V. K. Dadhwal. 2021. "Coupling Remote Sensing and GIS with KINEROS2 Model for Spatially Distributed Runoff Modeling in a Himalayan Watershed." Journal of the Indian Society of Remote Sensing 49, no. 5: 1121-1139.
A reliable estimate of the crop production prior to harvest is important for determining the prices, import–export decisions, and various food procurement policies that would enable the Government to take advance action in terms of surplus or scarcity production. Crop yield forecasting models could potentially be applied to small areas where all the necessary data are available. For large area data availability becomes critical, and the techniques of regression modeling and remote sensing are favored over growth simulation modeling. In this study, various weather parameters based statistical models have been developed to forecast the sugarcane yield during autumn and spring planting for Muzaffarnagar District of Uttar Pradesh. Last 35 year historical weather data from 1981 to 2015 were used for analysis. Various weighted and un-weighted weather indices have been utilized in developing the statistical model. The developed model using regression techniques for the spring season (Model-S4) and autumn season (Model-A5) showed a good relationship between predicted and observed values of yield. Model-S4 error ranges from − 0.063 to + 5.81%, whereas Model-A5 error varying from − 3.54 to + 3.51%. In all the developed models, weighted weather indices have been found to be significantly more effective rather than un-weighted weather indices.
Amit Kumar Verma; Pradeep Kumar Garg; K. S. Hari Prasad; Vinay Kumar Dadhwal; Sunil Kumar Dubey; Arvind Kumar. Sugarcane Yield Forecasting Model Based on Weather Parameters. Sugar Tech 2020, 23, 158 -166.
AMA StyleAmit Kumar Verma, Pradeep Kumar Garg, K. S. Hari Prasad, Vinay Kumar Dadhwal, Sunil Kumar Dubey, Arvind Kumar. Sugarcane Yield Forecasting Model Based on Weather Parameters. Sugar Tech. 2020; 23 (1):158-166.
Chicago/Turabian StyleAmit Kumar Verma; Pradeep Kumar Garg; K. S. Hari Prasad; Vinay Kumar Dadhwal; Sunil Kumar Dubey; Arvind Kumar. 2020. "Sugarcane Yield Forecasting Model Based on Weather Parameters." Sugar Tech 23, no. 1: 158-166.
A terrain-following ocean general circulation model is implemented for simulating tidal and residual circulation patterns in the Hooghly Estuary and its adjacent coastal oceans (HECO) on the east coast of India. The model is forced with time-varying tidal levels and momentum fluxes at the eastern and southern open boundaries, and winds at the air–sea interface. Simulated tidal levels and currents are compared well with the observations. Based on model solutions, spatial patterns of semi-diurnal and diurnal tides and circulation are described. The residual circulation shows prevalence of ocean-ward along channel flow from north to south with distinct differential circulation patterns on its right and left flanks of the outer estuary. A mesoscale eddy associated with residual circulation has been occurring in the southwestern flank of the HECO, adjacent to the Digha coast. This is associated with enriched chlorophyll_a concentration (Chla), causing the region as the suitable place for the fishing activity. The residual currents in the left of the channel (toward the Sunderban) in the southeastern flank of the HECO are eastward and diverging in nature and are associated with reduced Chla.
S. K. Mishra; R. K. Nayak; P. C. Mahanty; M. V. R. Seshasai; V. K. Dadhwal. Tidal Circulation in the Hooghly Estuary and Adjacent Coastal Oceans. Journal of the Indian Society of Remote Sensing 2019, 47, 705 -714.
AMA StyleS. K. Mishra, R. K. Nayak, P. C. Mahanty, M. V. R. Seshasai, V. K. Dadhwal. Tidal Circulation in the Hooghly Estuary and Adjacent Coastal Oceans. Journal of the Indian Society of Remote Sensing. 2019; 47 (4):705-714.
Chicago/Turabian StyleS. K. Mishra; R. K. Nayak; P. C. Mahanty; M. V. R. Seshasai; V. K. Dadhwal. 2019. "Tidal Circulation in the Hooghly Estuary and Adjacent Coastal Oceans." Journal of the Indian Society of Remote Sensing 47, no. 4: 705-714.
Flood is one of the most the most re-occurring natural hazard in the state of Bihar, as well as in India. The major rivers responsible for flood in the state of Bihar are Kosi, Gandak, Ghagra and Bagmati, which are the tributary rivers of Ganges. The head water catchment area of these rivers lies in the Himalayan state of Nepal. The high rainfall in Nepal, siltation of hydraulic structures, rivers and low topography of North Bihar causes flood occurrence in these areas on regular basis. Remote sensing and GIS plays an important role in mapping, monitoring and providing spatial database for all flood related studies. The present work focuses on the use remote sensing based topography and images in GIS environment for integrated flood study of Bagmati River, which is one of the most flood prone rivers of North Bihar. The Digital Elevation Model (DEM) from shuttle radar topography mission (SRTM) was used to create detailed sub-basin and river network map of entire Bagmati basin. The floods of July–August 2002 were mapped using RADARSAT-1 data using threshold based method. The SRTM DEM and ground based river cross-section from Dheng to Benibad stretch of Bhagmati River were used to create 1-dimensional hydrodynamic (1-D HD) model for simulating flood water level, discharge and flood inundation. Validation of simulated flood flows was done using observed water level of central water commission (CWC) from Dheng to Runisaidpur stations, with coefficient of correlation of 0.85. Finally, an integrated framework for flood modelling and management system is proposed.
A. K. Rastogi; P. K. Thakur; G. S. Rao; S. P. Aggarwal; V. K. Dadhwal; P. Chauhan. INTEGRATED FLOOD STUDY OF BAGMATI RIVER BASIN WITH HYDRO PROCESSING, FLOOD INUNDATION MAPPING & 1-D HYDRODYNAMIC MODELING USING REMOTE SENSING AND GIS. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences 2018, IV-5, 165 -172.
AMA StyleA. K. Rastogi, P. K. Thakur, G. S. Rao, S. P. Aggarwal, V. K. Dadhwal, P. Chauhan. INTEGRATED FLOOD STUDY OF BAGMATI RIVER BASIN WITH HYDRO PROCESSING, FLOOD INUNDATION MAPPING & 1-D HYDRODYNAMIC MODELING USING REMOTE SENSING AND GIS. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2018; IV-5 ():165-172.
Chicago/Turabian StyleA. K. Rastogi; P. K. Thakur; G. S. Rao; S. P. Aggarwal; V. K. Dadhwal; P. Chauhan. 2018. "INTEGRATED FLOOD STUDY OF BAGMATI RIVER BASIN WITH HYDRO PROCESSING, FLOOD INUNDATION MAPPING & 1-D HYDRODYNAMIC MODELING USING REMOTE SENSING AND GIS." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences IV-5, no. : 165-172.
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.
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 StyleSudhakar 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 StyleSudhakar 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.
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.
N. R. Patel; Hitendra Padalia; S. P. S. Kushwaha; Subrata Nandy; Taibanganba Watham; Joyson Ahongshangbam; Rakesh Kumar; V. K. Dadhwal; A. Senthil Kumar. CO2 Flux Tower and Remote Sensing: Tools for Monitoring Carbon Exchange over Ecosystem Scale in Northwest Himalaya. Remote Sensing of Northwest Himalayan Ecosystems 2018, 313 -327.
AMA StyleN. R. Patel, Hitendra Padalia, S. P. S. Kushwaha, Subrata Nandy, Taibanganba Watham, Joyson Ahongshangbam, Rakesh Kumar, V. K. Dadhwal, A. Senthil Kumar. CO2 Flux Tower and Remote Sensing: Tools for Monitoring Carbon Exchange over Ecosystem Scale in Northwest Himalaya. Remote Sensing of Northwest Himalayan Ecosystems. 2018; ():313-327.
Chicago/Turabian StyleN. R. Patel; Hitendra Padalia; S. P. S. Kushwaha; Subrata Nandy; Taibanganba Watham; Joyson Ahongshangbam; Rakesh Kumar; V. K. Dadhwal; A. Senthil Kumar. 2018. "CO2 Flux Tower and Remote Sensing: Tools for Monitoring Carbon Exchange over Ecosystem Scale in Northwest Himalaya." Remote Sensing of Northwest Himalayan Ecosystems , no. : 313-327.
Vinay K. Dadhwal; Senthil Kumar. George Joseph and C. Jeganathan: Fundamentals of Remote Sensing. Journal of the Indian Society of Remote Sensing 2018, 46, 1553 -1554.
AMA StyleVinay K. Dadhwal, Senthil Kumar. George Joseph and C. Jeganathan: Fundamentals of Remote Sensing. Journal of the Indian Society of Remote Sensing. 2018; 46 (9):1553-1554.
Chicago/Turabian StyleVinay K. Dadhwal; Senthil Kumar. 2018. "George Joseph and C. Jeganathan: Fundamentals of Remote Sensing." Journal of the Indian Society of Remote Sensing 46, no. 9: 1553-1554.
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 StyleAbhishek 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 StyleAbhishek 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.
C. Sudhakar Reddy; K.R.L. Saranya; S. Vazeed Pasha; Kv Satish; C.S. Jha; P.G. Diwakar; V.K. Dadhwal; P.V.N. Rao; Y.V.N. Krishna Murthy. Assessment and monitoring of deforestation and forest fragmentation in South Asia since the 1930s. Global and Planetary Change 2018, 161, 132 -148.
AMA StyleC. Sudhakar Reddy, K.R.L. Saranya, S. Vazeed Pasha, Kv Satish, C.S. Jha, P.G. Diwakar, V.K. Dadhwal, P.V.N. Rao, Y.V.N. Krishna Murthy. Assessment and monitoring of deforestation and forest fragmentation in South Asia since the 1930s. Global and Planetary Change. 2018; 161 ():132-148.
Chicago/Turabian StyleC. Sudhakar Reddy; K.R.L. Saranya; S. Vazeed Pasha; Kv Satish; C.S. Jha; P.G. Diwakar; V.K. Dadhwal; P.V.N. Rao; Y.V.N. Krishna Murthy. 2018. "Assessment and monitoring of deforestation and forest fragmentation in South Asia since the 1930s." Global and Planetary Change 161, no. : 132-148.
P. Chandrasekhar; K. Chandra Mouli; D. P. Rao; V. K. Dadhwal. Subsurface Geological Structure and Tectonics as Evidenced from Integrated Interpretation of Aeromagnetic and Remote Sensing Data over Kutch Sedimentary Basin, Western India. Current Science 2018, 114, 1 .
AMA StyleP. Chandrasekhar, K. Chandra Mouli, D. P. Rao, V. K. Dadhwal. Subsurface Geological Structure and Tectonics as Evidenced from Integrated Interpretation of Aeromagnetic and Remote Sensing Data over Kutch Sedimentary Basin, Western India. Current Science. 2018; 114 (1):1.
Chicago/Turabian StyleP. Chandrasekhar; K. Chandra Mouli; D. P. Rao; V. K. Dadhwal. 2018. "Subsurface Geological Structure and Tectonics as Evidenced from Integrated Interpretation of Aeromagnetic and Remote Sensing Data over Kutch Sedimentary Basin, Western India." Current Science 114, no. 1: 1.
Sudhakar Reddy; K.R.L. Saranya; C.S. Jha; V.K. Dadhwal; Y.V.N. Krishna Murthy. Earth observation data for habitat monitoring in protected areas of India. Remote Sensing Applications: Society and Environment 2017, 8, 114 -125.
AMA StyleSudhakar Reddy, K.R.L. Saranya, C.S. Jha, V.K. Dadhwal, Y.V.N. Krishna Murthy. Earth observation data for habitat monitoring in protected areas of India. Remote Sensing Applications: Society and Environment. 2017; 8 ():114-125.
Chicago/Turabian StyleSudhakar Reddy; K.R.L. Saranya; C.S. Jha; V.K. Dadhwal; Y.V.N. Krishna Murthy. 2017. "Earth observation data for habitat monitoring in protected areas of India." Remote Sensing Applications: Society and Environment 8, no. : 114-125.
Detailed inventory of glacial lakes in a Glacial Lake Outburst Flood (GLOF) prone area is vital for disaster mitigation. Availability of cheaper high resolution satellite data from Indian remote sensing satellites enables us to create up-to-date inventory for use in prioritisation of glacial lakes for GLOF risk assessment. Earlier inventories show presence of more glacial lakes in Brahmaputra basin in Indian Himalaya. Teesta River is one of the tributary of Brahmaputra and previous studies have shown that the inventory of glacial lakes in Teesta basin varies from 143 to 320. In the present study, the inventory carried out using satellite data of years 2000, 2007 and 2014 show presence of 301 (25.789 km2), 302 (26.081 km2) and 644 (29.706 km2) glacial lakes in Teesta basin respectively. The steep increase in number of lakes in the latest inventory is primarily due to the finer spatial resolution of satellite data used. Analysis of water spread area of glacial lakes at different altitudes shows that most of the lakes in the higher altitudes are small in size. It is observed that more than 66% of lakes are in the altitude beyond 4500 m and of size less than 50,000 sqm (5 ha). Out of 301 glacial lakes inventoried during 2000, water spread area of 6 lakes have decreased in 2014 and 31 lakes have shown increase in area. Out of these 31 lakes, 17 lakes are classified as end moraine dammed lakes and among them, 14 are located in Upper Teesta sub-basin and in higher altitudes (beyond 5000 m). The prioritisation of these lakes for GLOF risk needs to be carried out with detailed field investigation.
K. Abdul Hakeem; S. Abirami; V. V. Rao; P. G. Diwakar; V. K. Dadhwal. Updated Inventory of Glacial Lakes in Teesta Basin Using Remote Sensing Data for Use in GLOF Risk Assessment. Journal of the Indian Society of Remote Sensing 2017, 46, 463 -470.
AMA StyleK. Abdul Hakeem, S. Abirami, V. V. Rao, P. G. Diwakar, V. K. Dadhwal. Updated Inventory of Glacial Lakes in Teesta Basin Using Remote Sensing Data for Use in GLOF Risk Assessment. Journal of the Indian Society of Remote Sensing. 2017; 46 (3):463-470.
Chicago/Turabian StyleK. Abdul Hakeem; S. Abirami; V. V. Rao; P. G. Diwakar; V. K. Dadhwal. 2017. "Updated Inventory of Glacial Lakes in Teesta Basin Using Remote Sensing Data for Use in GLOF Risk Assessment." Journal of the Indian Society of Remote Sensing 46, no. 3: 463-470.
A study on seasonal and inter-annual variability of the atmospheric CO2 is carried out based on National Oceanic and Atmospheric Administration Carbon Tracker (NOAACT) re-analysis and satellite measurements of mid-troposphere CO2 by Atmosphere Infrared Sounder on board NASA’s Aqua and lower troposphere CO2 by Greenhouse-gas Observing Satellite. Seasonal and non-seasonal components of each time series were extracted by means of least square based harmonic analysis procedure. The data of surface CO2 fluxes used in the NOAACT are also analyzed to examine its relationship with the atmosphere CO2 variability at different time scales. There exists good consistency between NOAACT analysis and satellite observations in their respective seasonal harmonics and climatology. Surface layer CO2 exhibits large climatological mean over the regions of major anthropogenic sources together with strong seasonal cycle over the humid and cold climatic terrestrial regions especially over the northern hemisphere. Existence of high coherency with the different components of the surface fluxes shows that surface layer atmosphere CO2 seasonality is primarily contributed from the terrestrial ecosystem exchanges and secondarily by anthropogenic and oceanic exchanges. The mid-troposphere CO2 exhibits large values associated with climatology and amplitudes of semi-annual and annual cycles over the northern extra tropics and Polar Regions along with a gradual decreasing trend from northern to southern hemisphere. Inter-annual variability of atmospheric CO2 in the NOAACT in some extent is consistent with the satellite observations. Large scale circulation patterns, its fluctuations associated with ENSO events and large scale ecosystem disturbances have significant influence on the inter-annual variability.
M. Krishnapriya; A. Bhuvana Chandra; Rabindra K. Nayak; N. R. Patel; P. V. N. Rao; V. K. Dadhwal. Seasonal and inter-annual variability of atmosphere CO2 based on NOAA Carbon Tracker analysis and satellite observations. Journal of the Indian Society of Remote Sensing 2017, 46, 309 -320.
AMA StyleM. Krishnapriya, A. Bhuvana Chandra, Rabindra K. Nayak, N. R. Patel, P. V. N. Rao, V. K. Dadhwal. Seasonal and inter-annual variability of atmosphere CO2 based on NOAA Carbon Tracker analysis and satellite observations. Journal of the Indian Society of Remote Sensing. 2017; 46 (2):309-320.
Chicago/Turabian StyleM. Krishnapriya; A. Bhuvana Chandra; Rabindra K. Nayak; N. R. Patel; P. V. N. Rao; V. K. Dadhwal. 2017. "Seasonal and inter-annual variability of atmosphere CO2 based on NOAA Carbon Tracker analysis and satellite observations." Journal of the Indian Society of Remote Sensing 46, no. 2: 309-320.
Forest plays a significant role in regulating the carbon budget and mitigating climate change in long term. However, lack of spatially explicit and accurate information on carbon exchange components from diverse forest ecosystem types in India limits carbon budgeting on a regional scale. Remote-sensing-driven ecosystem models are well-established tools for estimating gross primary productivity (GPP) over large areas but they are seldom found erroneous if implemented without proper calibration of biome-specific parameters. The present study evaluates the combined use of eddy covariance (EC) data and satellite-derived variables for estimating GPP over large areas. Four remote-sensing-driven models, (i) temperature–greenness (TG) model, (ii) greenness–radiation (GR) model, (iii) light use efficiency (LUE) model, and (iv) remote-sensing-based LUE (LUERS) model, were parameterized with EC measurements and compared with 8-day Moderate Resolution Imaging Spectroradiometer (MODIS) GPP products for a moist Shorea robusta forest in northern part of India. EC observed 8-day average GPP varied from 5.38 to 12.42 g C m−2 day−1. Among the four tested models, TG model had the highest root mean square error (RMSE) of 1.28 g C m−2 day−1, while GR and LUERS models had moderate RMSE of 0.99 g C m−2 day−1 and 0.98 g C m−2 day−1, respectively. The closest GPP estimate was given by LUE model with RMSE of 0.93 g C m−2 day−1. The RMSE for all four models were four times lower than that of MODIS GPP. Lower maximum LUE (and uncertainty in the environmental scalar used in MODIS GPP algorithm could have contributed to higher RMSE. More accurate modelling of GPP can help in better understanding of forest ecological functions with the changing climate.
T. Watham; N. R. Patel; S. P. S. Kushwaha; V. K. Dadhwal; A. Senthil Kumar. Evaluation of remote-sensing-based models of gross primary productivity over Indian sal forest using flux tower and MODIS satellite data. International Journal of Remote Sensing 2017, 38, 5069 -5090.
AMA StyleT. Watham, N. R. Patel, S. P. S. Kushwaha, V. K. Dadhwal, A. Senthil Kumar. Evaluation of remote-sensing-based models of gross primary productivity over Indian sal forest using flux tower and MODIS satellite data. International Journal of Remote Sensing. 2017; 38 (18):5069-5090.
Chicago/Turabian StyleT. Watham; N. R. Patel; S. P. S. Kushwaha; V. K. Dadhwal; A. Senthil Kumar. 2017. "Evaluation of remote-sensing-based models of gross primary productivity over Indian sal forest using flux tower and MODIS satellite data." International Journal of Remote Sensing 38, no. 18: 5069-5090.
P. Mahesh; G. Biswadip; P. V. N. Rao; V. K. Dadhwal; G. Sreenivas; A. L. Kanchana; K. Mallikarjun. A new ground-based FTIR spectrometer reference site at Shadnagar (India) and preliminary columnar retrievals of CH 4 and N 2 O. International Journal of Remote Sensing 2017, 38, 4033 -4046.
AMA StyleP. Mahesh, G. Biswadip, P. V. N. Rao, V. K. Dadhwal, G. Sreenivas, A. L. Kanchana, K. Mallikarjun. A new ground-based FTIR spectrometer reference site at Shadnagar (India) and preliminary columnar retrievals of CH 4 and N 2 O. International Journal of Remote Sensing. 2017; 38 (14):4033-4046.
Chicago/Turabian StyleP. Mahesh; G. Biswadip; P. V. N. Rao; V. K. Dadhwal; G. Sreenivas; A. L. Kanchana; K. Mallikarjun. 2017. "A new ground-based FTIR spectrometer reference site at Shadnagar (India) and preliminary columnar retrievals of CH 4 and N 2 O." International Journal of Remote Sensing 38, no. 14: 4033-4046.
C. Sudhakar Reddy; C. S. Jha; G. Manaswini; V. V. L. Padma Alekhya; S. Vazeed Pasha; K. V. Satish; P. G. Diwakar; V. K. Dadhwal. Nationwide Assessment of Forest Burnt Area in India Using Resourcesat-2 AWiFS Data. Current Science 2017, 112, 1521 .
AMA StyleC. Sudhakar Reddy, C. S. Jha, G. Manaswini, V. V. L. Padma Alekhya, S. Vazeed Pasha, K. V. Satish, P. G. Diwakar, V. K. Dadhwal. Nationwide Assessment of Forest Burnt Area in India Using Resourcesat-2 AWiFS Data. Current Science. 2017; 112 (7):1521.
Chicago/Turabian StyleC. Sudhakar Reddy; C. S. Jha; G. Manaswini; V. V. L. Padma Alekhya; S. Vazeed Pasha; K. V. Satish; P. G. Diwakar; V. K. Dadhwal. 2017. "Nationwide Assessment of Forest Burnt Area in India Using Resourcesat-2 AWiFS Data." Current Science 112, no. 7: 1521.
Large scale assessment of aboveground biomass (AGB) in tropical forests is often limited by the saturation of remote sensing signals at high AGB values. Fourier Transform Textural Ordination (FOTO) performs well in quantifying canopy texture from very high-resolution (VHR) imagery, from which stand structure parameters can be retrieved with no saturation effect for AGB values up to 650 Mg·ha−1. The method is robust when tested on wet evergreen forests but is more demanding when applied across different forest types characterized by varying structures and allometries. The present study focuses on a gradient of forest types ranging from dry deciduous to wet evergreen forests in the Western Ghats (WG) of India, where we applied FOTO to Cartosat-1a images with 2.5 m resolution. Based on 21 1-ha ground control forest plots, we calibrated independent texture–AGB models for the dry and wet zone forests in the area, as delineated from the distribution of NDVI values computed from LISS-4 multispectral images. This stratification largely improved the relationship between texture-derived and field-derived AGB estimates, which exhibited a R2 of 0.82 for a mean rRMSE of ca. 17%. By inverting the texture–AGB models, we finally mapped AGB predictions at 1.6-ha resolution over a heterogeneous landscape of ca. 1500 km2 in the WG, with a mean relative per-pixel propagated error <20% for wet zone forests, i.e., below the recommended IPCC criteria for Monitoring, Reporting and Verification (MRV) methods. The method proved to perform well in predicting high-resolution AGB values over heterogeneous tropical landscape encompassing diversified forest types, and thus presents a promising option for affordable regional monitoring systems of greenhouse gas (GhG) emissions related to forest degradation.
Sourabh Pargal; Rakesh Fararoda; Gopalakrishnan Rajashekar; Natesan Balachandran; Maxime Réjou-Méchain; Nicolas Barbier; Chandra Shekhar Jha; Raphaël Pélissier; Vinay Kumar Dadhwal; Pierre Couteron. Inverting Aboveground Biomass–Canopy Texture Relationships in a Landscape of Forest Mosaic in the Western Ghats of India Using Very High Resolution Cartosat Imagery. Remote Sensing 2017, 9, 228 .
AMA StyleSourabh Pargal, Rakesh Fararoda, Gopalakrishnan Rajashekar, Natesan Balachandran, Maxime Réjou-Méchain, Nicolas Barbier, Chandra Shekhar Jha, Raphaël Pélissier, Vinay Kumar Dadhwal, Pierre Couteron. Inverting Aboveground Biomass–Canopy Texture Relationships in a Landscape of Forest Mosaic in the Western Ghats of India Using Very High Resolution Cartosat Imagery. Remote Sensing. 2017; 9 (3):228.
Chicago/Turabian StyleSourabh Pargal; Rakesh Fararoda; Gopalakrishnan Rajashekar; Natesan Balachandran; Maxime Réjou-Méchain; Nicolas Barbier; Chandra Shekhar Jha; Raphaël Pélissier; Vinay Kumar Dadhwal; Pierre Couteron. 2017. "Inverting Aboveground Biomass–Canopy Texture Relationships in a Landscape of Forest Mosaic in the Western Ghats of India Using Very High Resolution Cartosat Imagery." Remote Sensing 9, no. 3: 228.
K. H. V. Durga Rao; A. Shravya; V. Venkateshwar Rao; V. K. Dadhwal; P. G. Diwakar. Flash Flood Disaster Threat to Indian Rail Bridges:A Spatial Simulation Study of Machak River Flood, Madhya Pradesh. Current Science 2017, 112, 1028 .
AMA StyleK. H. V. Durga Rao, A. Shravya, V. Venkateshwar Rao, V. K. Dadhwal, P. G. Diwakar. Flash Flood Disaster Threat to Indian Rail Bridges:A Spatial Simulation Study of Machak River Flood, Madhya Pradesh. Current Science. 2017; 112 (5):1028.
Chicago/Turabian StyleK. H. V. Durga Rao; A. Shravya; V. Venkateshwar Rao; V. K. Dadhwal; P. G. Diwakar. 2017. "Flash Flood Disaster Threat to Indian Rail Bridges:A Spatial Simulation Study of Machak River Flood, Madhya Pradesh." Current Science 112, no. 5: 1028.
Sourav Das; Sandip Giri; Isha Das; Abhra Chanda; Amit Ghosh; Anirban Mukhopadhyay; Anirban Akhand; S.B. Choudhury; V.K. Dadhwal; Sourav Maity; T. Srinivasa Kumar; Aneesh A. Lotliker; D. Mitra; Sugata Hazra. Nutrient dynamics of northern Bay of Bengal (nBoB)—Emphasizing the role of tides. Regional Studies in Marine Science 2017, 10, 116 -134.
AMA StyleSourav Das, Sandip Giri, Isha Das, Abhra Chanda, Amit Ghosh, Anirban Mukhopadhyay, Anirban Akhand, S.B. Choudhury, V.K. Dadhwal, Sourav Maity, T. Srinivasa Kumar, Aneesh A. Lotliker, D. Mitra, Sugata Hazra. Nutrient dynamics of northern Bay of Bengal (nBoB)—Emphasizing the role of tides. Regional Studies in Marine Science. 2017; 10 ():116-134.
Chicago/Turabian StyleSourav Das; Sandip Giri; Isha Das; Abhra Chanda; Amit Ghosh; Anirban Mukhopadhyay; Anirban Akhand; S.B. Choudhury; V.K. Dadhwal; Sourav Maity; T. Srinivasa Kumar; Aneesh A. Lotliker; D. Mitra; Sugata Hazra. 2017. "Nutrient dynamics of northern Bay of Bengal (nBoB)—Emphasizing the role of tides." Regional Studies in Marine Science 10, no. : 116-134.