Results 241 to 250 of about 249,018 (315)

Peran Jerman dalam demonstration activity–reducing emission from deforestation and forest degradation (Da-Redd+) program forest and climate change (Forclime) di Indonesia Periode 2007-2012

, 2016
Ayu Suningsih
openalex   +1 more source

Interpolating Socioeconomic Data for the Analysis of Deforestation: A Comparison of Methods

, 2012
Michelle Farfán Gutiérrez, Jean‐François Mas, Laura Paulina Osorio   +2 more
openalex   +2 more sources

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

Household air pollution: another threat to Indigenous people in Brazil. [PDF]

J Bras Pneumol
Mizutani RF, Santos UP.
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

Corals Ba/Ca records uncover mid-twentieth century onset of land use change associated with industrial deforestation in Malaysian Borneo. [PDF]

Sci Rep
Naciri W, Boom A, Browne N, Evans NJ, Rankenburg K, McDonald BJ, Nagarajan R, McIlwain J, Zinke J.   +8 more
europepmc   +1 more source

The contribution of remote sensing for the development of a Green-Holistic IoT Platform for Forest Management and Monitoring: Reforestation and Deforestation Modules [PDF]

Μαρία Προδρόμου, Marios Tzouvaras, Christodoulos Mettas, Andreas Konstantinidis, Andreas Pamboris, Iasonas Iasonos, Diofantos Hadjimitsis   +6 more
openalex   +1 more source

Evaluating land–sea linkages using land cover change and coral reef monitoring data: A case study from northeastern Puerto Rico

Remote Sensing in Ecology and Conservation, EarlyView.
Land cover change that leads to increased nutrient and sediment runoff is an important driver of change in coral reef ecosystems. In this study, we combined satellite remote sensing and field monitoring to assess concomitant changes in watershed land cover and coral cover in northeastern Puerto Rico in 2000–2015.
Pirta Palola, Sasha Hills, Simon J. Pittman, Edwin A. Hernández‐Delgado, Antoine Collin, Lisa M. Wedding   +5 more
wiley   +1 more source

Global forest conservation policies and the Sustainable Development Goals

Britz W, Wilts R, Wuepper D.
europepmc   +1 more source

Geospatial dataset on deforestation and urban sprawl in Dhaka, Bangladesh: A resource for environmental analysis. [PDF]

Data Brief
Khan MF, Islam MR, Basak SK, Imtiaz A, Bhowmik A, Nandi D, Rahman M, Karmaker D.   +7 more
europepmc   +1 more source