Results 161 to 170 of about 203,605 (295)

Ultrafast Catalytic Decomposition Reaction Using a ZIF‐67@Celluolose Nanofiber Composite‐Based Cobalt/ Nitrogen Co‐Doped Nanoporous Carbon for Water Treatment

Rare Metals, EarlyView.
ABSTRACT Recently, cobalt/nitrogen co‐doped materials have emerged as heterogeneous catalysts to activate peroxymonosulfate (PMS) and have been applied to advanced oxidation processes for environmental remediation. However, their recyclability and reusability remain major barriers to practical application.
Wen‐Kai Zhu, Ye Song, Du‐Juan Wu, Zhuo‐Xin Liao, Donggyun Kim, Jinhyeon Park, Jungmok You, Minsu Han, Song Li, Guang‐Yao Li, Chao‐Hai Wang, Jeonghun Kim   +11 more
wiley   +1 more source

Multi-stakeholder perspectives on urban regeneration: a spatial gradient analysis of heat and pollution effects. [PDF]

Int J Biometeorol
Zhang J, Gu X.
europepmc   +1 more source

Recent advances in fluorescent materials innovation and film‐based sensing application

Responsive Materials, EarlyView.
This review systematically summarizes recent advances in high‐performance film‐based fluorescent sensors (FFSs), specifically covering the innovative strategies for engineering porous sensing films, and the sensitive and rapid detection for diverse target analytes. Current challenges for the further development of the sensors are discussed, guiding the
Xinyu Gou, Junxia Peng, Yu Fang
wiley   +1 more source

A model for assessing the urban heat Island effect in urban regeneration areas: case of mamak and the north ankara. [PDF]

Int J Biometeorol
Ozenen Kavlak M, Senyel Kurkcuoglu MA, Cabuk A, Cabuk SN, Cetin M.   +4 more
europepmc   +1 more source

ECOSTRESS‐derived semi‐arid forest temperature and evapotranspiration estimates demonstrate drought and thinning impacts

Remote Sensing in Ecology and Conservation, EarlyView.
This study demonstrates that ECOSTRESS lands surface temperature (LST) data are sensitive to forest thinning, regional drought, and their interaction. Consistent with high‐resolution UAV images, ECOSTRESS LST data indicate thinned forest had significantly greater temperature across years.
Temuulen Tsagaan Sankey, Thu Ya Kyaw, Julia Tatum, George W. Koch, Thomas Kolb, Rayni Lewis, Helen M. Poulos, Andrew M. Barton, Blase LaSala, Andrea Thode   +9 more
wiley   +1 more source

How an urban regeneration programme impact people's health and wellbeing: an evaluation from citizen's perception using concept mapping. [PDF]

BMC Public Health
Urtaran-Laresgoiti M, Novoa AM, Martin S, Pérez K.   +3 more
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

Developing decision making framework on built-up site suitability assessment for urban regeneration in the industrial cities of Eastern India. [PDF]

Sci Rep
Manna H, Mallick SK, Sarkar S, Roy SK.
europepmc   +1 more source

Assessing transformative capacity for sustainable urban regeneration: A comparative study of three South Korean cities. [PDF]

Ambio, 2019
Wolfram M.
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