Zobrazeno 1 - 10
of 666
pro vyhledávání: '"PROSAIL"'
Publikováno v:
Science of Remote Sensing, Vol 10, Iss , Pp 100148- (2024)
This paper describes the selected algorithm for the ESA climate change initiative vegetation parameters project. Multi- and hyper-spectral, multi-angular, or multi-sensor top-of-canopy reflectance data call for an efficient generic retrieval system w
Externí odkaz:
https://doaj.org/article/b5cde5fbf8764051b7bfecd93f8bf8a8
Autor:
Hang Li, Kai Liu, Banghui Yang, Shudong Wang, Yu Meng, Dacheng Wang, Xingtao Liu, Long Li, Dehui Li, Yong Bo, Xueke Li
Publikováno v:
International Journal of Digital Earth, Vol 17, Iss 1 (2024)
ABSTRACTInverting grassland above-ground biomass (AGB) presents a significant challenge due to difficulties in characterizing leaf physiological states and obtaining accurate ground-truth data. This study introduces an innovative hybrid model for AGB
Externí odkaz:
https://doaj.org/article/38af3cdb3f2d40659d2d9172756a6f22
Publikováno v:
International Journal of Digital Earth, Vol 17, Iss 1 (2024)
ABSTRACTAccurate monitoring of the leaf area index (LAI) and aboveground biomass (AGB) using remote sensing at a fine scale is crucial for understanding the spatial heterogeneity of vegetation structure in mountainous ecosystems. Understanding discre
Externí odkaz:
https://doaj.org/article/62ce8298c29d40069f2b794297947a13
Autor:
Anting Guo, Wenjiang Huang, Binxiang Qian, Huichun Ye, Quanjun Jiao, Xiangzhe Cheng, Chao Ruan
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 132, Iss , Pp 104076- (2024)
Chlorophyll is both a cornerstone of plant photosynthesis and an important indicator for assessing crop growth and health. Although many previous studies have explored the use of remote sensing to retrieve chlorophyll content, there is room for impro
Externí odkaz:
https://doaj.org/article/1abf620d1559469aa0d29125b61ff0ed
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 127, Iss , Pp 103644- (2024)
Currently, hyperspectral remote sensing technology used for vegetation monitoring mainly uses empirical and semi-empirical statistical methods to calculate heavy metal content. Combining physical models and machine learning algorithms is an effective
Externí odkaz:
https://doaj.org/article/c4286d16a00e4de8a9e8de65e76188a7
Autor:
Demei Zhao, Jianing Zhen, Yinghui Zhang, Jing Miao, Zhen Shen, Xiapeng Jiang, Junjie Wang, Jincheng Jiang, Yuzhi Tang, Guofeng Wu
Publikováno v:
Remote Sensing in Ecology and Conservation, Vol 9, Iss 3, Pp 370-389 (2023)
Abstract Leaf area index (LAI) is a vital parameter reflecting vegetation structure, physio‐ecological process and growth development. Accurate estimation of mangrove LAI is fundamental for assessing the ecological restoration and sustainable devel
Externí odkaz:
https://doaj.org/article/30bd58988a5f4164b35192884bce8347
Autor:
Philemon Tsele, Abel Ramoelo
Publikováno v:
Geocarto International, Vol 39, Iss 1 (2024)
Biophysical variables such as leaf area index (LAI) and leaf chlorophyll content (LCC) are cited as essential biodiversity variables. A comprehensive comparison and integration of retrieval methods is needed for the estimation of biophysical variable
Externí odkaz:
https://doaj.org/article/21cf54871af94bf888545bfaffb7d2b1
Publikováno v:
Redai dili, Vol 43, Iss 3, Pp 545-553 (2023)
Fuel moisture content (FMC), which is the ratio of equivalent water thickness (EWT) to dry matter content (DMC), plays a crucial role in the estimation of vegetation ignition probability and the fire propagation rate. The PROSAIL model can adequately
Externí odkaz:
https://doaj.org/article/321a3bc7d4e74ad1b9c4cf9abea6ed9c
Autor:
Yongxia Zhou, Xuejian Li, Chao Chen, Lv Zhou, Yinyin Zhao, Jinjin Chen, Cheng Tan, Jiaqian Sun, Lingjun Zhang, Mengchen Hu, Huaqiang Du
Publikováno v:
Forests, Vol 15, Iss 6, p 946 (2024)
Parameters such as the leaf area index (LAI), canopy chlorophyll content (CCH), and canopy carotenoid content (CCA) are important indicators for evaluating the ecological functions of forests. Currently, rapidly developing unmanned aerial vehicles (U
Externí odkaz:
https://doaj.org/article/81865558388442d5a6ba04f4b255e95a
Publikováno v:
Forests, Vol 15, Iss 4, p 614 (2024)
Forest canopy fuel moisture content (FMC) is a critical factor in assessing the vulnerability of a specific area to forest fires. The conventional FMC estimation method, which relies on look-up tables and loss functions, cannot to elucidate the relat
Externí odkaz:
https://doaj.org/article/a3fa941e27b8493db718f44eb0c38d2e