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  1. AU="Singh, Ronak"
  2. AU=Forcados Gilead Ebiegberi
  3. AU="Kasperbauer, Jan L."
  4. AU="Xiang, Fangfei"
  5. AU=Bhattacharyya Rupam
  6. AU="Stefanski, R J"
  7. AU="Huiyuan Zhang"
  8. AU="Garg, Shivam Kumar"
  9. AU="Bart J. A. Rijnders"
  10. AU="Malaise, D"
  11. AU="Ahammad, Rijwan U"
  12. AU="Wong, Man Yu"
  13. AU="Yilmaz, Adnan"
  14. AU="Turkyilmaz, Ayberk"
  15. AU="Ryan, Sophia C"
  16. AU="Stino, Heiko"
  17. AU=Fischbeck K H
  18. AU="Giadinis, Nektarios D"
  19. AU="Patten, Scott"
  20. AU="Verma, Deepika"
  21. AU="Foo, Anthony Tun Lin"
  22. AU="Georgia Panagiotakos"
  23. AU="Tennankore, Karthik K."
  24. AU=Kubota Kenji
  25. AU="Vieille, Peggy"
  26. AU="Kan, Yin-Shi"
  27. AU="Jasińska-Balwierz, Agata"
  28. AU="Hargitai, Rita"
  29. AU=Ueda Kazumitsu
  30. AU="Andrew N. Jordan"
  31. AU="Millemaggi, Alessia"
  32. AU=Paulsen Paige
  33. AU="Fan, Su-Su"
  34. AU="de Azeredo, Andressa Cardoso"
  35. AU="Miller, Russell"
  36. AU="A Mombet"

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  1. Artikel ; Online: Evaluating automated endmember extraction for classifying hyperspectral data and deriving spectral parameters for monitoring forest vegetation health

    Singh, Ronak / Kumar, Vinay

    Environ Monit Assess. 2023 Jan., v. 195, no. 1 p.72-72

    2023  

    Abstract: The hyperspectral remote sensing datasets possess high capability in differentiating the spectrally similar features, and thus, they are immensely important in various forestry activities, especially vegetation classifications. But extracting endmembers ... ...

    Abstract The hyperspectral remote sensing datasets possess high capability in differentiating the spectrally similar features, and thus, they are immensely important in various forestry activities, especially vegetation classifications. But extracting endmembers for data training is a challenging task. The present study is focused on the use of automated endmember extraction technique for deriving endmembers during the unavailability of ground spectra. We used the Sequential Maximum Angle Convex Cone (SMACC) method on EO-1 Hyperion data for endmember extraction in the Barkot forest range of Dehradun district, Uttarakhand which were used for classification of the study area using support vector machine (SVM). Further, we estimated the vegetation health of the region by assigning the threshold weights for various derived environmental variables such as NDVI (Normalised Difference Vegetation Index), CRI (Carotenoid Reflectance Index), Anthocyanin Reflectance Index (ARI), Modified Simple Ratio (MSR), Modified Chlorophyll Absorption Ratio Index (MCARI) and WBI (Water Band Index). Then, to further validate the health of the forest types, we correlated it with the Land Surface Temperature (LST) from LANDSAT 5 ETM + data. The results showed a high classification accuracy of 89.13%. The healthy vegetation area coverage of the area was about 78.6% with most healthy class as Tectona grandis and Shorea robusta and its correlation with LST showed lower temperature range in healthy vegetation areas and vice versa. The study was useful in determining the superiority of SMACC automated endmember extraction and estimating the vegetation health.
    Schlagwörter Landsat ; Shorea robusta ; Tectona grandis ; absorption ; anthocyanins ; automation ; carotenoids ; chlorophyll ; data collection ; forestry ; forests ; normalized difference vegetation index ; reflectance ; support vector machines ; surface temperature
    Sprache Englisch
    Erscheinungsverlauf 2023-01
    Umfang p. 72.
    Erscheinungsort Springer International Publishing
    Dokumenttyp Artikel ; Online
    ZDB-ID 782621-7
    ISSN 1573-2959 ; 0167-6369
    ISSN (online) 1573-2959
    ISSN 0167-6369
    DOI 10.1007/s10661-022-10576-w
    Datenquelle NAL Katalog (AGRICOLA)

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  2. Artikel ; Online: Evaluating automated endmember extraction for classifying hyperspectral data and deriving spectral parameters for monitoring forest vegetation health.

    Singh, Ronak / Kumar, Vinay

    Environmental monitoring and assessment

    2022  Band 195, Heft 1, Seite(n) 72

    Abstract: The hyperspectral remote sensing datasets possess high capability in differentiating the spectrally similar features, and thus, they are immensely important in various forestry activities, especially vegetation classifications. But extracting endmembers ... ...

    Abstract The hyperspectral remote sensing datasets possess high capability in differentiating the spectrally similar features, and thus, they are immensely important in various forestry activities, especially vegetation classifications. But extracting endmembers for data training is a challenging task. The present study is focused on the use of automated endmember extraction technique for deriving endmembers during the unavailability of ground spectra. We used the Sequential Maximum Angle Convex Cone (SMACC) method on EO-1 Hyperion data for endmember extraction in the Barkot forest range of Dehradun district, Uttarakhand which were used for classification of the study area using support vector machine (SVM). Further, we estimated the vegetation health of the region by assigning the threshold weights for various derived environmental variables such as NDVI (Normalised Difference Vegetation Index), CRI (Carotenoid Reflectance Index), Anthocyanin Reflectance Index (ARI), Modified Simple Ratio (MSR), Modified Chlorophyll Absorption Ratio Index (MCARI) and WBI (Water Band Index). Then, to further validate the health of the forest types, we correlated it with the Land Surface Temperature (LST) from LANDSAT 5 ETM + data. The results showed a high classification accuracy of 89.13%. The healthy vegetation area coverage of the area was about 78.6% with most healthy class as Tectona grandis and Shorea robusta and its correlation with LST showed lower temperature range in healthy vegetation areas and vice versa. The study was useful in determining the superiority of SMACC automated endmember extraction and estimating the vegetation health.
    Mesh-Begriff(e) Environmental Monitoring/methods ; Forests ; Chlorophyll ; Support Vector Machine
    Chemische Substanzen Chlorophyll (1406-65-1)
    Sprache Englisch
    Erscheinungsdatum 2022-11-04
    Erscheinungsland Netherlands
    Dokumenttyp Journal Article
    ZDB-ID 782621-7
    ISSN 1573-2959 ; 0167-6369
    ISSN (online) 1573-2959
    ISSN 0167-6369
    DOI 10.1007/s10661-022-10576-w
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  3. Artikel ; Online: Buchanania cochinchinensis (Lour.) M.R. Almedia habitat exhibited robust adaptability to diverse socioeconomic scenarios in eastern India.

    Garai, Sanjoy / Mishra, Yogeshwar / Malakar, Ayushman / Kumar, Rikesh / Singh, Ronak / Sharma, Jassi / Tiwari, Sharad

    Environmental monitoring and assessment

    2023  Band 195, Heft 8, Seite(n) 1005

    Abstract: One of the greatest challenges to ecosystems is the rapidity of climate change, and their ability to adjust swiftly will be constrained. Climate change will disrupt the ecological balances, causing species to track suitable habitats for survival. ... ...

    Abstract One of the greatest challenges to ecosystems is the rapidity of climate change, and their ability to adjust swiftly will be constrained. Climate change will disrupt the ecological balances, causing species to track suitable habitats for survival. Consequently, understanding the species' response to climate change is crucial for its conservation and management, and for enhancing biodiversity through effective management. This research intends to examine the response of the vulnerable Buchanania cochinchinensis species to climate change. We modeled the potential suitable habitats of B. cochinchinensis for the present and future climatic scenario proxies based on the Shared Socioeconomic Pathways (SSP), i.e. SSP126, 245, 370 and 585. Maxent was used to simulate the potential habitats of B. cochinchinensis. The study found that ~28,313 km
    Mesh-Begriff(e) Ecosystem ; Prospective Studies ; Environmental Monitoring ; Biodiversity ; Climate Change ; Socioeconomic Factors
    Sprache Englisch
    Erscheinungsdatum 2023-07-28
    Erscheinungsland Netherlands
    Dokumenttyp Journal Article
    ZDB-ID 782621-7
    ISSN 1573-2959 ; 0167-6369
    ISSN (online) 1573-2959
    ISSN 0167-6369
    DOI 10.1007/s10661-023-11611-0
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  4. Artikel ; Online: Flood mapping and damage assessment due to the super cyclone Yaas using Google Earth Engine in Purba Medinipur, West Bengal, India

    Khatun, Masjuda / Garai, Sanjoy / Sharma, Jassi / Singh, Ronak / Tiwari, Sharad / Rahaman, Sk Mujibar

    Environ Monit Assess. 2022 Dec., v. 194, no. 12 p.869-869

    2022  

    Abstract: This study maps flood inundation and estimates the damage caused by super cyclone Yaas in Purba Medinipur, India. We used Google Earth Engine (GEE) to create a flood inundation map of the research area using pre and post-cyclone Sentinel-1 SAR data. ... ...

    Abstract This study maps flood inundation and estimates the damage caused by super cyclone Yaas in Purba Medinipur, India. We used Google Earth Engine (GEE) to create a flood inundation map of the research area using pre and post-cyclone Sentinel-1 SAR data. Using ESRI 2020 land cover data, flood damage was analysed. The flood affected 5% (239.69 km²) of the land of Purba Medinipur. The northern and southern regions were affected the most. 95% and 3% of the total flooded area are comprised of agricultural and vegetation, respectively. Kolaghat (24 km²) and Nandigram-II (1 km²) sustained the greatest damage to both agriculture and vegetation. The areas below 18 m were impacted by flooding, with the worst damage occurring below 5 m. The GEE platform was cost-effective, efficient, and faster at calculating with enhanced precision. The outcomes of this study will aid in the management of cyclone-induced hazards. We advocate planting native and salt-tolerant crops to reduce flood damage.
    Schlagwörter Internet ; cost effectiveness ; flood damage ; land cover ; salt tolerance ; vegetation ; India
    Sprache Englisch
    Erscheinungsverlauf 2022-12
    Umfang p. 869.
    Erscheinungsort Springer International Publishing
    Dokumenttyp Artikel ; Online
    ZDB-ID 782621-7
    ISSN 1573-2959 ; 0167-6369
    ISSN (online) 1573-2959
    ISSN 0167-6369
    DOI 10.1007/s10661-022-10574-y
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  5. Artikel ; Online: Flood mapping and damage assessment due to the super cyclone Yaas using Google Earth Engine in Purba Medinipur, West Bengal, India.

    Khatun, Masjuda / Garai, Sanjoy / Sharma, Jassi / Singh, Ronak / Tiwari, Sharad / Rahaman, Sk Mujibar

    Environmental monitoring and assessment

    2022  Band 194, Heft 12, Seite(n) 869

    Abstract: This study maps flood inundation and estimates the damage caused by super cyclone Yaas in Purba Medinipur, India. We used Google Earth Engine (GEE) to create a flood inundation map of the research area using pre and post-cyclone Sentinel-1 SAR data. ... ...

    Abstract This study maps flood inundation and estimates the damage caused by super cyclone Yaas in Purba Medinipur, India. We used Google Earth Engine (GEE) to create a flood inundation map of the research area using pre and post-cyclone Sentinel-1 SAR data. Using ESRI 2020 land cover data, flood damage was analysed. The flood affected 5% (239.69 km
    Mesh-Begriff(e) Cyclonic Storms ; Environmental Monitoring ; Floods ; India ; Search Engine
    Sprache Englisch
    Erscheinungsdatum 2022-10-12
    Erscheinungsland Netherlands
    Dokumenttyp Journal Article
    ZDB-ID 782621-7
    ISSN 1573-2959 ; 0167-6369
    ISSN (online) 1573-2959
    ISSN 0167-6369
    DOI 10.1007/s10661-022-10574-y
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  6. Artikel: Repeat investigation during social preference behavior is suppressed in male mice with prefrontal cortex

    Hackett, Jonathan / Nadkarni, Viraj / Singh, Ronak S / Carthy, Camille L / Antigua, Susan / Hall, Baila S / Rajadhyaksha, Anjali M

    bioRxiv : the preprint server for biology

    2023  

    Abstract: Impairments in social behavior are observed in a range of neuropsychiatric disorders and several lines of evidence have demonstrated that dysfunction of the prefrontal cortex (PFC) plays a central role in social deficits. We have previously shown that ... ...

    Abstract Impairments in social behavior are observed in a range of neuropsychiatric disorders and several lines of evidence have demonstrated that dysfunction of the prefrontal cortex (PFC) plays a central role in social deficits. We have previously shown that loss of neuropsychiatric risk gene
    Sprache Englisch
    Erscheinungsdatum 2023-06-26
    Erscheinungsland United States
    Dokumenttyp Preprint
    DOI 10.1101/2023.06.24.546368
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  7. Artikel ; Online: Climate change and dispersion dynamics of the invasive plant species Chromolaena odorata and Lantana camara in parts of the central and eastern India

    Sharma, Jassi / Singh, Ronak / Garai, Sanjoy / Rahaman, Sk Mujibar / Khatun, Masjuda / Ranjan, Ashish / Mishra, Shambhu Nath / Tiwari, Sharad

    Ecological Informatics. 2022 Dec., v. 72 p.101824-

    2022  

    Abstract: Lantana camara and Chromolaena odorata are categorized as the most obnoxious invasive flora globally. Their ability to combat the regeneration and proliferation of neighbouring flora, expansive nature, and robust adaptability to diverse habitats, drew ... ...

    Abstract Lantana camara and Chromolaena odorata are categorized as the most obnoxious invasive flora globally. Their ability to combat the regeneration and proliferation of neighbouring flora, expansive nature, and robust adaptability to diverse habitats, drew global attention. Investigating the potential mutual dispersion phenomenon of these two invasive species under the climate change scenario was the primary objective of this study. The present and future (2050) prospective distribution scenarios for these two species were determined using MaxEnt in the eastern and central Indian regions encompassing the states of Jharkhand, Chhattisgarh, and West Bengal. Future projections for 2050 were derived using IPSL-CM5A-LR & MIROC5 and IPSL-CM6A-LR & MIROC6 models for different representative concentration pathways (RCPs 2.6, 4.5, 6.0, and 8.5), and Shared Socioeconomic Pathways (SSPs 126, 245, 370 and 585), respectively. The investigation revealed that currently ∼31% and ∼ 24% of the study area are susceptible to infestation of L. camara and C. odorata, respectively. Compared to the current scenario, the results showed a probable future increase of ∼1.53% in C. odorata infestation and a decrease of ∼4.95% for L. camara. The True Skill Statistics (TSS) and Kappa coefficient (in %) values of 0.71 & 76.50 for L. camara and 0.52 & 63.38 for C. odorata indicated a good model fit. Collectively, both the species exhibited robust resilience to climate change, with C. odorata outcompeting L. camara. Using both RCP and SSP pathways under the multiple climate scenarios offered a comprehensive and novel approach to acquiring greater insights into likely interactions, dominance, and distribution scenarios of these species. The results provide prior information on sensitive sites prone to future invasion, allowing management to formulate preventative measures to control infestation.
    Schlagwörter Chromolaena odorata ; Lantana camara ; climate ; climate change ; flora ; invasive species ; statistics ; India ; C. odorata ; L. camara ; Global Climate Models ; MaxEnt
    Sprache Englisch
    Erscheinungsverlauf 2022-12
    Erscheinungsort Elsevier B.V.
    Dokumenttyp Artikel ; Online
    ZDB-ID 2212016-6
    ISSN 1878-0512 ; 1574-9541
    ISSN (online) 1878-0512
    ISSN 1574-9541
    DOI 10.1016/j.ecoinf.2022.101824
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