Zobrazeno 1 - 10
of 132
pro vyhledávání: '"Mukunda Dev Behera"'
Autor:
Karun Jose, Rajiv Kumar Chaturvedi, Chockalingam Jeganathan, Mukunda Dev Behera, Chandra Prakash Singh
Publikováno v:
Remote Sensing, Vol 15, Iss 24, p 5642 (2023)
Our understanding of the impact of climate change on forests is constrained by a lack of long-term phenological monitoring. It is generally carried out via (1) ground observations, (2) satellite-based remote sensing, and (3) near-surface remote sensi
Externí odkaz:
https://doaj.org/article/ea2c32f846a448d8b849f9337701cb77
Publikováno v:
Remote Sensing, Vol 15, Iss 7, p 1756 (2023)
Sea surface temperature (SST) substantially influences the land climate conditions through the co-variability of multiple climate variables, which in turn affect the structural and functional characteristics of terrestrial vegetation. Our study explo
Externí odkaz:
https://doaj.org/article/69e0394867294f39be475d3b45133899
Autor:
Pulakesh Das, Mukunda Dev Behera, Saroj Kanta Barik, Sujoy Mudi, Buddolla Jagadish, Swarup Sarkar, Santa Ram Joshi, Dibyendu Adhikari, Soumit Kumar Behera, Kiranmay Sarma, Prashant Kumar Srivastava, Puneet Singh Chauhan
Publikováno v:
Trees, Forests and People, Vol 7, Iss , Pp 100183- (2022)
Identifying shifting cultivation areas and assessing their spatio-temporal dynamics are essential in framing climate-adaptive policies for efficient forest management and agriculture practices for the benefit of people. The current study attempts to
Externí odkaz:
https://doaj.org/article/1644636c664e4e008ae7211cd4ef81c7
Autor:
Vikas Dugesar, Koppineedi V. Satish, Manish K. Pandey, Prashant K. Srivastava, George P. Petropoulos, Akash Anand, Mukunda Dev Behera
Publikováno v:
Forests, Vol 13, Iss 12, p 1973 (2022)
Understanding ecosystem functional behaviour and its response to climate change necessitates a detailed understanding of vegetation phenology. The present study investigates the effect of an elevational gradient, temperature, and precipitation on the
Externí odkaz:
https://doaj.org/article/e16569d8565b4c6cbca6ba309f8bfcfa
Autor:
Beependra Singh, Chockalingam Jeganathan, Virendra Singh Rathore, Mukunda Dev Behera, Chandra Prakash Singh, Parth Sarathi Roy, Peter M. Atkinson
Publikováno v:
Remote Sensing, Vol 13, Iss 21, p 4474 (2021)
Understanding the spatio-temporal pattern of natural vegetation helps decoding the responses to climate change and interpretation on forest resilience. Satellite remote sensing based data products, by virtue of their synoptic and repetitive coverage,
Externí odkaz:
https://doaj.org/article/e1c4716bfcac4366bbe7f4277154fba8
Autor:
Mukunda Dev Behera, Surbhi Barnwal, Somnath Paramanik, Pulakesh Das, Bimal Kumar Bhattyacharya, Buddolla Jagadish, Parth S. Roy, Sujit Madhab Ghosh, Soumit Kumar Behera
Publikováno v:
Remote Sensing, Vol 13, Iss 11, p 2027 (2021)
Although studies on species-level classification and mapping using multisource data and machine learning approaches are plenty, the use of data with ideal placement of central wavelength and bandwidth at appropriate spatial resolution, for the classi
Externí odkaz:
https://doaj.org/article/2e88df53c6ba4b64a6b1a5621347d66d
Publikováno v:
PLoS ONE, Vol 14, Iss 6, p e0218322 (2019)
IntroductionKnowledge of species richness patterns and their relation with climate is required to develop various forest management actions including habitat management, biodiversity and risk assessment, restoration and ecosystem modelling. In practi
Externí odkaz:
https://doaj.org/article/b5711d42cf4f42348e0afb63a6f0e2c8
Autor:
Swapna Mahanand, Mukunda Dev Behera, Partha Sarathi Roy, Priyankar Kumar, Saroj Kanta Barik, Prashant Kumar Srivastava
Publikováno v:
Remote Sensing, Vol 13, Iss 2, p 159 (2021)
A dynamic habitat index (DHI) based on satellite derived biophysical proxy (fraction of absorbed photosynthetically active radiation, FAPAR) was used to evaluate the vegetation greenness pattern across deserts to alpine ecosystems in India that accou
Externí odkaz:
https://doaj.org/article/437ab8d82fb5412da1be099f8fff890f
Publikováno v:
Remote Sensing, Vol 12, Iss 9, p 1519 (2020)
Canopy height serves as a good indicator of forest carbon content. Remote sensing-based direct estimations of canopy height are usually based on Light Detection and Ranging (LiDAR) or Synthetic Aperture Radar (SAR) interferometric data. LiDAR data is
Externí odkaz:
https://doaj.org/article/c169cf8cf6984547aede8818b9222888
Autor:
Somnath Paramanik, Nikhil Raj Deep, Mukunda Dev Behera, Bimal Kumar Bhattacharya, Jadunandan Dash
Publikováno v:
Remote Sensing Letters. 14:522-533