Results 211 to 220 of about 253,265 (282)

An improved grey wolf optimizer with multi-stage differentiation strategies coverage in three-dimensional wireless sensor network. [PDF]

Sci Rep
Liu Z, Ou Y, Wang S.
europepmc   +1 more source

Wall‐to‐wall Amazon forest height mapping with Planet NICFI, Aerial LiDAR, and a U‐Net regression model

Remote Sensing in Ecology and Conservation, EarlyView.
Tree canopy height is a key indicator of forest biomass and structure, yet accurate mapping across the Amazon remains challenging. Here, we generated a canopy height map of the Amazon forest at ~4.8 m resolution using Planet NICFI imagery and a deep learning U‐Net model trained with airborne LiDAR data.
Fabien H. Wagner, Ricardo Dalagnol, Griffin Carter, Mayumi C. M. Hirye, Shivraj Gill, Le Bienfaiteur Sagang Takougoum, Samuel Favrichon, Michael Keller, Jean P. H. B. Ometto, Lorena Alves, Cynthia Creze, Stephanie P. George‐Chacon, Shuang Li, Zhihua Liu, Adugna Mullissa, Yan Yang, Erone G. Santos, Sarah R. Worden, Martin Brandt, Philippe Ciais, Stephen C. Hagen, Sassan Saatchi   +21 more
wiley   +1 more source

Terrain-Informed UAV Path Planning for Mountain Search: A Slope-Based Probabilistic Approach. [PDF]

Sensors (Basel)
Wang X, Wang X, Zhao P, Tan W, Zhang H, Chen L, Zhou L.   +6 more
europepmc   +1 more source

Improving forest age estimation to understand subtropical forest regrowth dynamics using deep learning image segmentation of time‐series historical aerial photographs

Remote Sensing in Ecology and Conservation, EarlyView.
Accurately estimating forest age is key to understanding how forests recover and evaluating restoration success. We developed a two‐step deep learning approach using historical greyscale aerial photographs to map forest age at fine spatial scales. By combining a pre‐trained model with localized fine‐tuning, our U‐Net + ResNet50 architecture achieved ...
Ying Ki Law, Yi‐Fei Gu, Shuwen Liu, Guangqin Song, Aland H. Y. Chan, Cham Man Tse, Zhonghua Liu, Martha J. Ledger, Billy C. H. Hau, Sawaid Abbas, Jin Wu   +10 more
wiley   +1 more source

Protocol to discover terrain-precipitation relationships with interpretable artificial intelligence. [PDF]

STAR Protoc
Xu H, Chen Y, Zeng Z, Li N, Li J, Zhang D.   +5 more
europepmc   +1 more source

On the compatibility of single‐scan terrestrial LiDAR with digital photogrammetry and field inventory metrics of vegetation structure in forest and agroforestry landscapes

Remote Sensing in Ecology and Conservation, EarlyView.
The single‐scan approach to terrestrial laser scanning (TLS) and the self‐terrain‐normalized form of drone‐based digital aerial photogrammetry (DAP) offer practical options for rapid assessment of the vegetation structure in tropical landscapes.
Magnus Onyiriagwu, Nereoh Leley, Caleb W. T. Ngaba, Anthony Macharia, Henry Muchiri, Abdalla Kisiwa, Martin Ehbrecht, Delphine Clara Zemp   +7 more
wiley   +1 more source

Urban traffic digital twin system development in unity. [PDF]

Sci Rep
Gong L, Ding M.
europepmc   +1 more source

Hyperspectral species maps and LiDAR‐based structured population models show future forest fire frequency may compromise forest resilience

Remote Sensing in Ecology and Conservation, EarlyView.
Monitoring forest recovery from disturbances at scale requires tracking tree dynamics, yet traditional ground‐based approaches are resource‐intensive. We present a pipeline to parameterize integral projection models (IPMs) using LiDAR data and hyperspectral‐based species maps to assess post‐fire recovery across large, forested areas at the Caribou ...
Jessica McLean, Tommaso Jucker, Alice Rosen, Sean M. McMahon, Roberto Salguero‐Gómez   +4 more
wiley   +1 more source

New Possibilities of Field Data Survey in Forest Road Design. [PDF]

Sensors (Basel)
Lovrinčević M, Papa I, Janeš D, Hodak L, Pentek T, Đuka A.   +5 more
europepmc   +1 more source

Large‐scale characterization of horizontal forest structure from remote sensing optical images

Remote Sensing in Ecology and Conservation, EarlyView.
Sub‐meter resolution remote sensing data and tree crown segmentation techniques hold promise in offering detailed information that can support the characterization of forest structure from a horizontal perspective, offering new insights in the tree crown structure at scale.
Xin Xu, Martin Brandt, Xiaowei Tong, Maurice Mugabowindekwe, Yuemin Yue, Sizhuo Li, Qiue Xu, Siyu Liu, Florian Reiner, Kelin Wang, Zhengchao Chen, Yongqing Bai, Rasmus Fensholt   +12 more
wiley   +1 more source