Article
Chemistry, Analytical
Linlong Jing, Xinhua Wei, Qi Song, Fei Wang
Summary: A platform based on LiDAR point cloud data was established to rapidly and accurately estimate rice canopy height and leaf area index. By collecting data from multiple plots and analyzing them, the optimal prediction models for these parameters were determined.
Article
Environmental Sciences
Zhuo Lu, Lei Deng, Han Lu
Summary: This study proposes an improved LAI estimation method for field-grown wheat using UAV-based remote sensing. By considering both spectral and structural information, the method significantly improves the accuracy of LAI estimation. Results show that the introduction of canopy height model (CHM) and canopy coverage (CC) enhances the accuracy by 22.6% on multispectral images and 43.6% on RGB images.
Article
Environmental Sciences
Hao Tang, Jason Stoker, Scott Luthcke, John Armston, Kyungtae Lee, Bryan Blair, Michelle Hofton
Summary: NASA's GEDI mission aims to provide high-resolution measurements of forest structure and topography, but current geolocation accuracy limits its applications. Researchers developed a method using lidar data to evaluate and mitigate geolocation errors, finding large errors in the first release of GEDI data but improved accuracy in the second release. This approach provides a short-term solution for improved calibration and validation of GEDI and has the potential to generate biomass products using in-situ data.
REMOTE SENSING OF ENVIRONMENT
(2023)
Article
Environmental Sciences
Yuncheng Deng, Jiya Pan, Jinliang Wang, Qianwei Liu, Jianpeng Zhang
Summary: This study introduces a rapid method for biomass estimation in alpine and canyon areas using space-borne LiDAR data and optical remote-sensing images. By establishing extrapolation and growth models, the aboveground biomass and carbon storage in Shangri-La City were successfully estimated and verified.
Article
Plant Sciences
Zixi Shi, Shuo Shi, Wei Gong, Lu Xu, Binhui Wang, Jia Sun, Bowen Chen, Qian Xu
Summary: This study estimates Leaf Area Index (LAI) using a physical model and data fusion strategy, improving the inversion accuracy, and providing a new inversion strategy for LAI research.
FRONTIERS IN PLANT SCIENCE
(2023)
Article
Environmental Sciences
Sungchan Oh, Jinha Jung, Guofan Shao, Gang Shao, Joey Gallion, Songlin Fei
Summary: The forest canopy height model (CHM) is a crucial tool for analyzing forest stocking and its spatiotemporal variations. This study presents a high-resolution CHM generation method using U.S. Geological Survey (USGS) LiDAR data for the entire state of Indiana, USA. The accuracy of the CHM was validated through comparison with field-based height measurements. Furthermore, the resulting CHM can serve as critical baseline information for monitoring and management decisions, as well as the calculation of other key forest metrics.
Article
Ecology
Hitendra Padalia, Ankit Prakash, Taibanganba Watham
Summary: In order to better understand forest carbon budgets and design forest-based climate change mitigation solutions, accurate biomass estimation is crucial. This study demonstrates the effectiveness of integrating GEDI data with other sensors (optical and SAR data) to provide precise above-ground biomass (AGB) estimation for multi-stage managed forests. By combining GEDI footprint heights, Landsat 8 indices, and Random Forest (RF) algorithms, the study achieved high accuracy in estimating canopy height and AGB. The addition of canopy height data significantly improved the AGB model, reducing the RMSE and expanding the range of AGB estimation.
ECOLOGICAL INFORMATICS
(2023)
Article
Plant Sciences
Cong Xu, Dan Zhao, Zhaoju Zheng, Ping Zhao, Junhua Chen, Xiuwen Li, Xueming Zhao, Yujin Zhao, Wenjun Liu, Bingfang Wu, Yuan Zeng
Summary: Compared to traditional field sampling, LiDAR technology provides a time-saving and cost-effective way to map grassland canopy height. However, UAV LiDAR-based grassland canopy height estimation is usually underestimated due to the complex structure of grassland and small size of individual plants. We developed a canopy height correction method based on scan angle to improve the accuracy of height estimation by compensating for the loss of grassland height.
FRONTIERS IN PLANT SCIENCE
(2023)
Article
Environmental Sciences
Martin Queinnec, Joanne C. White, Nicholas C. Coops
Summary: This study used ICESat-2 data to estimate forest structure in different boreal forest types in Ontario, Canada, including canopy height, cover, and height variability. Results showed strong agreement between ICESat-2 and airborne LiDAR for estimating canopy height in different forest development stages, but ICESat-2 tended to underestimate canopy height variability and cover compared to LiDAR data.
REMOTE SENSING OF ENVIRONMENT
(2021)
Article
Environmental Sciences
Tuo Feng, Laura Duncanson, Paul Montesano, Steven Hancock, David Minor, Eric Guenther, Amy Neuenschwander
Summary: The launch of ICESat-2 by NASA in September 2018 allows for the observation of high-resolution and three-dimensional surface elevations globally. This paper examines the accuracy of ICESat-2 data in boreal forests of North America, and finds strong agreements with the reference dataset LVIS in terms of terrain elevation and canopy height.
REMOTE SENSING OF ENVIRONMENT
(2023)
Article
Environmental Sciences
Farid Atmani, Bodo Bookhagen, Taylor Smith
Summary: This study presents a novel Sparse Vegetation Detection Algorithm (SVDA) using ICESat-2 data to map tree and vegetation heights in a sparsely vegetated savanna ecosystem. The algorithm effectively identifies canopy photons and provides the first estimates of seasonal biomass changes.
Article
Forestry
Md Farhadur Rahman, Yusuke Onoda, Kaoru Kitajima
Summary: Spatial variations of maximum canopy height in a forest-dominated area of Kyoto, Japan were analyzed using ALS data, revealing differences in canopy height among different forest types with the highest canopy height found at mid-elevation, and canopies in valleys taller than on slopes and ridges.
FOREST ECOLOGY AND MANAGEMENT
(2022)
Article
Environmental Sciences
Angela Tsao, Ikenna Nzewi, Ayodeji Jayeoba, Uzoma Ayogu, David B. Lobell
Summary: This study evaluated the performance of existing global canopy height map (CHM) products and a locally trained model using GEDI and optical satellite data in oil palm plantations in Nigeria. It found that existing CHMs performed poorly in the region, but the locally trained model performed well and reduced errors for short trees.
Article
Environmental Sciences
Cangjiao Wang, Andrew J. Elmore, Izaya Numata, Mark A. Cochrane, Shaogang Lei, Christopher R. Hakkenberg, Yuanyuan Li, Yibo Zhao, Yu Tian
Summary: This study proposes a point-surface fusion framework (FPSF-CH) for canopy height mapping using GEDI data. The effectiveness of FPSF-CH was validated, showing improved accuracy compared to other methods. The integration of GEDI data provides a new avenue for accurate wall-to-wall canopy height mapping.
Article
Environmental Sciences
Ibrahim Fayad, Nicolas Baghdadi, Clayton Alcarde Alvares, Jose Luiz Stape, Jean Stephane Bailly, Henrique Ferraco Scolforo, Italo Ramos Cegatta, Mehrez Zribi, Guerric Le Maire
Summary: The study investigated various methods based on waveform metrics and DEM data for estimating stand dominant heights and wood volume across Eucalyptus plantations with different terrain slopes. Results showed models utilizing GEDI metrics were still dependent on topographic slope, while simulation or fitting-based models provided more accurate estimates with reduced dependency on slopes.
Article
Environmental Sciences
Zhuomei Huang, Yichao Tian, Qiang Zhang, Youju Huang, Rundong Liu, Hu Huang, Guoqing Zhou, Jingzhen Wang, Jin Tao, Yongwei Yang, Yali Zhang, Junliang Lin, Yuxin Tan, Jingwen Deng, Hongxiu Liu
Summary: A light gradient boosting model (LGBM) based on particle swarm optimization (PSO) algorithm is proposed for accurate prediction of aboveground biomass of mangroves. The model outperforms other machine learning algorithms in performance and provides more accurate prediction results for large-scale mangroves.
GEOCARTO INTERNATIONAL
(2022)
Article
Environmental Sciences
Baokun Feng, Sheng Nie, Cheng Wang, Xiaohuan Xi, Jinliang Wang, Guoqing Zhou, Haoyu Wang
Summary: This paper explores the potential of UAV-based LiDAR for trunk point extraction and direct diameter at breast height (DBH) measurement. The proposed method achieves high accuracy in trunk point extraction and DBH measurement using UAV LiDAR data. The study also demonstrates the influence of scanning angle and mode on the extraction and measurement process.
Article
Environmental Sciences
Guoqing Zhou, Qingyang Wang, Yongsheng Huang, Jin Tian, Haoran Li, Yuefeng Wang
Summary: This paper introduces a novel true(2) orthoimage map ((TOM)-O-2) generation method, which, compared to traditional D/TOM, can display building facade texture and achieve three-dimensional coordinate measurement. Experimental results show that the 3D measurement accuracy of (TOM)-O-2 can be as high as 0.025 meters.
Article
Environmental Sciences
Feng Wang, Guoqing Zhou, Han Hu, Yuefeng Wang, Bolin Fu, Shiming Li, Jiali Xie
Summary: This paper proposes a novel method for efficient reconstruction of LoD-2 building models guided by facade structures from an oblique photogrammetric point cloud. The method includes constructing a building planar layout based on footprint data and vertical planes, extracting facade profiles using regularity constraints and a binary integer programming model, and generating a 2D building topology combined with the planar layout and profiles.
Article
Construction & Building Technology
Xiao Zhou, Quanhua Dong, Zhou Huang, Ganmin Yin, Guoqing Zhou, Yu Liu
Summary: Using multi-source big data, this study analyzed the effects of built environment characteristics on the integrated usage of dockless bike-sharing (DBS) and public transport. The results showed that factors such as points of interest around public transport stations, length of main road, and length of cycle path significantly influenced the integrated usage. However, the impact of these factors varied in different areas. These findings can be used to create a bike-friendly environment and encourage the connection between DBS and public transport.
SUSTAINABLE CITIES AND SOCIETY
(2023)
Article
Remote Sensing
Jianjun Chen, Zizhen Chen, Renjie Huang, Haotian You, Xiaowen Han, Tao Yue, Guoqing Zhou
Summary: This study investigated the effects of spatial resolution and resampling on the classification results of vegetation species and ground objects, and utilized GEOBIA and various machine learning classifiers to classify remote sensing images in Chewan Town, Lixian County, Hubei Province. The results showed that the optimal scale parameter and processing time decreased as spatial resolution decreased in multi-scale images; the optimal scale parameter of resampled images was higher than that of original images at the same resolution; spectral and texture features in resampled images were more significant than those in original images; different classifiers exhibited similar trends in classification accuracy with spatial resolutions ranging from 1.2 to 5.9 cm, where the overall accuracy increased and then decreased with decreasing spatial resolution, with higher accuracy in original images compared to resampled images.
Article
Optics
Gouqing Zhou, Gangchao Lin, Zhexian Liu, Xiang Zhou, Weihao Li, Xianxing Li, Ronghua Deng
Summary: When a bathymetric LiDAR onboard unmanned ship is close to the water surface less than 50 cm, the laser echo energy from the water surface is much higher than that from the water bottom. This paper proposes an optics system to suppress the amplitude of the echo signal from water surface through suppressing the laser echo energy. The experimental results demonstrate that the proposed system can effectively suppress 80.7% of the amplitude of the echo signal from the water surface when the voltage control of PMT detector is 0.40 V, which can largely improve the detection ability of the echo signals from water bottom in shallow water.
OPTICS AND LASERS IN ENGINEERING
(2023)
Article
Environmental Sciences
Feng Wang, Guoqing Zhou, Jiali Xie, Bolin Fu, Haotian You, Jianjun Chen, Xue Shi, Bowen Zhou
Summary: This paper proposes a divisive hierarchical clustering algorithm that uses shape classification and outliers reassignment to segment LiDAR point clouds in order to effectively identify the various shapes of structures that make up buildings. The method adopts a coarse-to-fine strategy and achieves accurate extraction of geometric primitives.
Article
Environmental Sciences
Jianjun Chen, Yanping Yang, Zihao Feng, Renjie Huang, Guoqing Zhou, Haotian You, Xiaowen Han
Summary: Based on 30 m land use data, this study confirms that a spatial granularity of 120 m and a spatial extent of 7 km are the optimal scales for ecological risk assessment and prediction in Nanning, China. The results show that the overall ecological risk in Nanning is relatively low, with a small area of high ecological risk under the scenario of ecological protection in 2036.
Article
Environmental Sciences
Ertao Gao, Guoqing Zhou
Summary: This study proposes a method for extracting tidal flats using remote sensing techniques, and investigates their dynamic variation characteristics and interaction with mangroves in Beibu Gulf, Southwest China. The results show that the total area of tidal flats decreased by 130 km(2) from 1987 to 2021, with an average annual change of -3.7 km(2)/a. Additionally, a negative correlation between tidal flat change area and mangrove change area was observed in Shankou, Maowei Sea, and Pearl Bay. These results provide valuable references for tidal flats’ resource conservation and vegetation changes in coastal wetlands.
Article
Environmental Sciences
Yichao Tian, Hu Huang, Guoqing Zhou, Qiang Zhang, Xiaokui Xie, Jinhai Ou, Yali Zhang, Jin Tao, Junliang Lin
Summary: This study proposes an innovative framework for assessing and managing mangrove biodiversity using drone low-altitude remote sensing and integrating various data sources. The results show spatial patterns of mangrove biodiversity, with high-biodiversity areas primarily located in the southwest and low-value areas in the north. The proposed method using unmanned-aerial-vehicle LiDAR and hyperspectral technology provides a feasible solution for large-scale biodiversity mapping and conservation strategies.
Article
Environmental Sciences
Bin Hu, Yiqiang Zhao, Guoqing Zhou, Jiaji He, Changlong Liu, Qiang Liu, Mao Ye, Yao Li
Summary: This paper proposes a nonlocal encoder block (NLEB) based on spatial dilated convolution to optimize the feature extraction of adjacent frames. Then, a coupled denoising encoder-decoder network is proposed that takes advantage of the echo correlation in deep-water and shallow-water channels. By stacking full waveforms from different channels, local and nonlocal features are extracted from a 2D tensor. The reconstructed denoised data is obtained by fusing the features of the two channels using a fully connected layer and deconvolution layer.
Article
Environmental Sciences
Guangrui Zhong, Jianjun Chen, Renjie Huang, Shuhua Yi, Yu Qin, Haotian You, Xiaowen Han, Guoqing Zhou
Summary: Fractional vegetation coverage (FVC) is an important indicator of ecosystem change. Currently, FVC products lack high temporal and spatial resolution. This study evaluated four remote sensing inversion models for FVC using high-spatial-resolution imagery and field-measured FVC data. The best inversion model was used to create a FVC product for the Source Region of the Yellow River (SRYR), and spatial-temporal variation characteristics of FVC were analyzed. The study found that the Gradient Boosting Decision Tree (GBDT) model had the highest accuracy and NDVI and elevation were important factors affecting the model's accuracy.
Article
Geochemistry & Geophysics
Guoqing Zhou, Xingxing Liu
Summary: This article presents an orthorectification model that divides distortion into two zones and uses different models and constraints to address the distortion issues of extra-length linear array images. Experimental results demonstrate improved orthorectification accuracy using the proposed method.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Remote Sensing
Zhenyang Hui, Penggen Cheng, Bisheng Yang, Guoqing Zhou
Summary: A multi-level self-adaptive individual tree detection method is proposed in this paper, which combines the advantages of raster-based and point-based methods. Experimental results show that this method outperforms other approaches in terms of accuracy and effectiveness in tree detection.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2022)
Article
Biodiversity Conservation
Yongcui Lan, Jinliang Wang, Qianwei Liu, Fang Liu, Lanfang Liu, Jie Li, Mengjia Luo
Summary: This study focuses on the five major plateau lake basins in central Yunnan, China, and constructs an ecological security pattern using the source-resistance surface-corridor-pinch point framework. The study simulates land use/cover change in the region and identifies early warning regions where future urban expansion poses a threat to current ecological source areas and corridors.
ECOLOGICAL INDICATORS
(2024)
Article
Biodiversity Conservation
Pingping Huang, Feng Zhao, Bailing Zhou, Kuidong Xu
Summary: This study investigates the distribution of benthic microeukaryotes in the China Seas and finds that they can stride over the ecological barrier of 32 degrees N. The study also highlights the significant influence of depth, temperature, and latitude on communities in the China Seas.
ECOLOGICAL INDICATORS
(2024)
Article
Biodiversity Conservation
Federico Morelli, Yanina Benedetti, Jesse Stanford, Leszek Jerzak, Piotr Tryjanowski, Paolo Perna, Riccardo Santolini
Summary: Species distribution models (SDMs) are numerical tools used for predicting species' spatial distribution. This study found that ecological characteristics, such as habitat specialization, play a role in improving the accuracy of SDMs.
ECOLOGICAL INDICATORS
(2024)
Article
Biodiversity Conservation
Xiaoxuan Wu, Hang Liu, Wei Liu
Summary: Global climate change, urbanization, and economic development have increased the need for sustainable human development, urban ecological governance, and low-carbon energy transformation. This study analyzes the green ecological transition in Chengdu based on panel data from 2010 to 2020, exploring its spatiotemporal evolution and key factors. The results show an overall upward trend in Chengdu's green ecological development and positive spatial autocorrelation in certain districts.
ECOLOGICAL INDICATORS
(2024)
Article
Biodiversity Conservation
Castaldi Simona, Formicola Nicola, Mastrocicco Micol, Morales Rodriguez Carmen, Morelli Raffaella, Prodorutti Daniele, Vannini Andrea, Zanzotti Roberto
Summary: Sustainable agricultural practices are increasingly important for global and national environmental policies and economy. This study compared the sustainability of grape production under integrated and organic management using multiple indicators. The results showed that organic management was more beneficial for most environmental aspects of the agroecosystem compared to integrated management, without affecting grape yield.
ECOLOGICAL INDICATORS
(2024)
Article
Biodiversity Conservation
Gaia Vaglio Laurin, Alexander Cotrina-Sanchez, Luca Belelli-Marchesini, Enrico Tomelleri, Giovanna Battipaglia, Claudia Cocozza, Francesco Niccoli, Jerzy Piotr Kabala, Damiano Gianelle, Loris Vescovo, Luca Da Ros, Riccardo Valentini
Summary: Phenology monitoring is important for understanding forest functioning and climate impacts. This research compares the phenological behavior of European beech forests using Tree-Talker (TT+) and Sentinel 2 satellite data. The study finds differences in the information derived by the two sensor types, particularly in terms of season length, phenology changepoints, and leaf period variability. TT+ with its higher temporal resolution demonstrates precision in capturing the phenological changepoints, especially when satellite image availability is limited.
ECOLOGICAL INDICATORS
(2024)
Article
Biodiversity Conservation
Huanhuan Pan, Ziqiang Du, Zhitao Wu, Hong Zhang, Keming Ma
Summary: The land use and cover changes resulting from coal mining activities and ecological restoration have had a significant impact on ecosystem services in mining areas. This study investigates the relationship between ecosystem services and land use intensity in coal mining areas, emphasizing the importance of understanding this interdependence for balanced human-land system development. The research examines the evolving relationship across different reclamation stages in Shanxi, China, using a coupling coordination degree model. The findings suggest the need for timely and judicious reclamation of coalfields, considering the land's bearing capacity.
ECOLOGICAL INDICATORS
(2024)
Article
Biodiversity Conservation
Jingjuan He, Yijun Shi, Lihua Xu, Zhangwei Lu, Mao Feng
Summary: This study examines the spatial interplay between changes in the blue-green spatial distribution and modifications in land surface temperature grades in Shanghai. The findings reveal that the transformation of the blue-green spatial pattern differs between different sectors of the city, and the impact on the thermal environment varies spatially.
ECOLOGICAL INDICATORS
(2024)
Article
Biodiversity Conservation
Yi Xu, Di Zhang, Junqiang Lin, Qidong Peng, Xiaohui Lei, Tiantian Jin, Jia Wang, Ruifang Yuan
Summary: This study analyzed the response relationship between phytoplankton growth and water environmental parameters in the Middle Route of the South-to-North Water Diversion Project in China using long-term monitoring data and machine learning models. The results revealed the differences between monitoring sites and identified the key parameters that affect phytoplankton growth.
ECOLOGICAL INDICATORS
(2024)