The advent of new spaceborne imaging spectrometers offers new opportunities for ecologists to map vegetation traits at global scales. However, to date most imaging spectroscopy studies exploiting satellite spectrometers have been constrained to the landscape scale. In this paper we present a new method to map vegetation traits at the landscape scale and upscale trait maps to the continental level, using historical spaceborne imaging spectroscopy (Hyperion) to derive estimates of leaf mass per area, nitrogen, and carbon concentrations of forests in Québec, Canada. We compare estimates for each species with reference field values and obtain good agreement both at the landscape and continental scales, with patterns consistent with the leaf economic spectrum. By exploiting the Hyperion satellite archive to map these traits and successfully upscale the estimates to the continental scale, we demonstrate the great potential of recent and upcoming spaceborne spectrometers to benefit plant biodiversity monitoring and conservation efforts.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10567784 | PMC |
| http://dx.doi.org/10.1038/s41598-023-44384-0 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
YOLO-Dynamic: A Detection Algorithm for Spaceborne Dynamic Objects.
Sensors (Basel)
November 2024
Opto-Electronics Engineering College, Changchun University of Science and Technology, Changchun 130022, China.
Ground-based detection of spaceborne dynamic objects, such as near-Earth asteroids and space debris, is essential for ensuring the safety of space operations. This paper presents YOLO-Dynamic, a novel detection algorithm aimed at addressing the limitations of existing models, particularly in complex environments and small-object detection. The proposed algorithm introduces two newly designed modules: the SC_Block_C2f and the LASF_Neck.
View Article and Find Full Text PDFAn assessment of mangrove forest in northwestern Mexico using the Google Earth Engine cloud computing platform.
PLoS One
December 2024
Instituto de Ciencias del Mar y Limnología, Unidad Académica Procesos Oceánicos y Costeros, Universidad Nacional Autónoma de México, Coyoacán, Ciudad de México, Mexico.
Article Synopsis
- Mangrove forests are mapped using remote sensing due to the difficulties of conducting fieldwork, but this often requires a lot of manual image processing, prompting the use of cloud computing for better accuracy in classifications.
- The study focused on the spatial distribution and changes in red mangroves and other species along the northwestern coast of Mexico from 2015 to 2020, using data processed through Google Earth Engine.
- Findings revealed a total of 42865 ha of red mangrove and 139602 ha of other species in 2020, with a decrease of 1817 ha since 2015, mainly due to aquaculture and hurricanes; the study aims to aid decision-making for conservation and climate initiatives.
Manifestations of a glacier surge in central Himalaya using multi-temporal satellite data.
Environ Sci Pollut Res Int
December 2024
Wadia Institute of Himalayan Geology, Dehradun, 248001, India.
Our understanding of identifying and monitoring surge-type glacier distribution patterns, fluctuations, periodicities, and occurrence mechanism under the changing climate is challenging and scarce due to small numbers, limitations on the spatiotemporal coverage of remote sensing observations, and insufficient field-based glaciological data from the High Mountain Asia. The surging glaciers have caused major hazards, and their movement can destroy peripheral and downstream areas like roads, connecting bridges, villages, and hydropower stations and trigger a glacial lake outburst flood or form a dammed (moraine or ice) lake in High Mountain Asia (HMA) in the recent past. Many glaciers have experienced a mass loss and retreat due to ongoing climate change in HMA in recent decades, whereas studies conducted in the Karakorum, Pamir, Tien Shan, and Kunlun Shan regions have reported the surging of the glaciers.
View Article and Find Full Text PDFThis study evaluates the performance of moderate-resolution Imaging spectroradiometer (MODIS) in aerosol optical depth(AOD) and Ångström exponent(AE) retrievals under high aerosol loading conditions across various aerosol types, utilizing ground-based and space-borne aerosol measurements in Shouxian, China. The intercomparison reveals cloud-aerosol LiDAR with orthogonal polarization's (CALIOP) efficacy in detecting significant aerosol layers and the refinement of sunphotometer-based aerosol type classification through CALIPSO, achieving approximately 80% accuracy. Analysis of 2016-2017 data indicates substantial aerosol presence in Shouxian, with monthly mean AODs ranging from 0.
View Article and Find Full Text PDFEnhanced SAR Compression through Multi-Look Doppler Compensation and Auto-Focusing Technique.
Sensors (Basel)
October 2024
The School of Electronic Engineering, Soongsil University, Seoul 06978, Republic of Korea.
This paper presents a simple and streamlined compensation technique for improving the quality of synthetic aperture radar (SAR) images based on the Range Doppler Algorithm (RDA). Incorrect Doppler estimation in the space orbit, caused by unexpected radar motion errors, orbit mismatches, and other factors, can significantly degrade SAR image quality. These inaccuracies result in mismatches between the azimuth-matched filter and the received Doppler chirp signal.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!