Browsing by Author "Manmohan J.R. Dobriyal"

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An overview of remote sensing technology in forest management
(Elsevier, 2025) Aishwarya; Meenu V.V.N.L.Sudha Rani; Preeti Kumari; Pankaj Lavania; Garima Gupta; Prabhat Tiwari; Ram Kumar Singh; Manoj Kumar; Manmohan J.R. Dobriyal; Manish Srivastav; Pavan Kumar
Remote sensing technology has revolutionized the field of forest management, offering unparalleled capabilities for monitoring, assessing, and managing forested landscapes. This overview paper explores the diverse applications and advancements of remote sensing techniques in forest management. It delves into the various remote sensing technologies, including satellite imaging, LiDAR (Light Detection and Ranging), and drones equipped with high-resolution cameras, highlighting their roles in data collection, analysis, and interpretation. This chapter discusses the utilization of remote sensing data for forest inventory, species identification, habitat assessment, and monitoring of forest disturbances such as wildfires, pests, and diseases. Furthermore, it emphasizes the integration of remote sensing with Geographic Information Systems (GIS) and machine learning algorithms for enhanced accuracy in mapping, modeling, and decision-making processes. Challenges and limitations inherent in remote sensing applications within forest management are also addressed, including issues related to data accuracy, processing techniques, and cost-effectiveness. Additionally, the paper explores future trends and potential advancements in remote sensing technology, emphasizing the need for continued research and development to further improve its efficacy in sustainable forest management practices. This chapter aims to provide a comprehensive understanding of the role and significance of remote sensing technology in modern forest management, emphasizing its potential to contribute to informed decision-making, conservation efforts, and the sustainable utilization of forest resources. © 2026 Elsevier Inc. All rights reserved..
Assessing soil organic carbon and its relation with biophysical and ecological parameters in tropical forest ecosystem India
(Taylor and Francis Ltd., 2025) Haroon Sajjad; Pavan Kumar; Prashant Kumar Srivastava; Shakti Om Pathak; Meraj Ahmed; Vikas Kumar; Manmohan J.R. Dobriyal; Preeti Kumari; Prem C. Pandey
Organic matter in soil is an essential parameter for assessing the agrodynamic productivity of soils. Forest productivity and health largely depend on soil organic carbon (SOC). This study aims to assess SOC levels and analyze their relationship with biophysical parameters in tropical forests. SOC was predicted using normalized difference vegetation index (NDVI) values derived from Sentinel-2A imagery. A total of 30 samples were collected through stratified random sampling based on NDVI values to estimate SOC. Regression analysis was performed between the estimated and predicted SOC, showing a strong correlation. The results indicated that SOC decreased with increasing soil depth in the Sariska Tiger Reserve, ranging from 8.27 - 26.54 t/ha at 5 cm depth and 1.9- 12.4 t/ha at 10 cm depth. NDVI was positively correlated with SOC, while the Bare Soil Index (BSI) showed a negative correlation. Additionally, soil pH and SOC were positively correlated, indicating high SOC levels. © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.