Article
Ecology
Qian Sun, Liping Chen, Xiaohe Gu, Sen Zhang, Menglei Dai, Jingping Zhou, Limin Gu, Wenchao Zhen
Summary: This study aims to monitor the canopy nitrogen status and lodging severity in maize using UAV hyperspectral technology. The key findings include the greater variation of CNVD compared to CNC in different lodging types, the stronger correlation between CNVD and canopy hyperspectrum, and the successful development of CNC and CNVD estimation models using the RFECV and GBR algorithms. This research effectively reduces hyperspectral data dimensionality and enhances the estimation accuracy and computational efficiency for assessing canopy nitrogen nutrient status in lodging maize.
ECOLOGICAL INFORMATICS
(2023)
Article
Multidisciplinary Sciences
Yanli Lu, Xiaoyu Zhang, Yuezhi Cui, Yaru Chao, Guipei Song, Caie Nie, Lei Wang
Summary: Spectral technology is effective in diagnosing N stress in maize, but it is affected by varietal differences. The responses to N stress, leaf N spectral diagnostic models, and varietal differences were analyzed in this study. The diagnostic stages for Jiyu 5817 and Zhengdan 958 were identified, and considering varietal effect in the diagnostic model improved its fit and RMSE.
SCIENTIFIC REPORTS
(2023)
Article
Environmental Sciences
Wei Liu, Chaofei Sun, Yanan Zhao, Fei Xu, Yuli Song, Jieru Fan, Yilin Zhou, Xiangming Xu
Summary: This study investigated the effects of nitrogen input levels on monitoring wheat powdery mildew and estimating grain yield using hyperspectral reflectance data. The findings suggest that hyperspectral indices can be used for these purposes, but their sensitivities to nitrogen input levels vary.
Article
Biodiversity Conservation
Kenny Helsen, Leonardo Bassi, Hannes Feilhauer, Teja Kattenborn, Hajime Matsushima, Elisa Van Cleemput, Ben Somers, Olivier Honnay
Summary: Leaf mass per area (LMA), leaf dry matter content (LDMC) and leaf water content/ equivalent water thickness (EWT) are commonly used functional plant traits in ecology, and spectroscopy has proven to be a powerful tool to collect such trait information. However, the accuracy of reflectance-based trait predictions may vary across different plant species, with species-specific PLSR models showing the highest correlation accuracy.
ECOLOGICAL INDICATORS
(2021)
Article
Horticulture
Renan Tosin, Isabel Pocas, Helena Novo, Jorge Teixeira, Natacha Fontes, Antonio Graca, Mario Cunha
Summary: This study developed two models to estimate Psi(pd) in a commercial vineyard, utilizing spectral data and machine learning algorithms. The first model estimated Psi(pd) based on vine canopy reflectance and selected suitable vegetation indices, while the second model optimized variables for Psi(pd) estimation based on pigments' concentrations assessed through hyperspectral reflectance. The B-MARS algorithm produced the best results with a RRMSE between 13-14% in validation.
SCIENTIA HORTICULTURAE
(2021)
Article
Environmental Sciences
Yi Lin, Siyuan Liu, Lei Yan, Kai Yan, Yelu Zeng, Bin Yang
Summary: Directional area scattering factor (DASF) is a critical parameter for vegetation monitoring. The current method to estimate DASF has biases due to neglecting variations in biochemical constituents. This study proposes a new approach that accounts for variations in concentrations and improves DASF estimation.
REMOTE SENSING OF ENVIRONMENT
(2023)
Review
Computer Science, Artificial Intelligence
Rui Silva, Pedro Melo-Pinto
Summary: Various dimensionality reduction techniques were applied to hyperspectral reflectance images of wine grape berries, with PCA showing superior performance in predicting oenological parameters. The study demonstrated the feasibility of achieving accurate predictions across different vintage years without the need for additional training.
APPLIED SOFT COMPUTING
(2021)
Article
Spectroscopy
Yongkai Xie, Yutong Qiu, Jinyu Wang, Rui Yao, Hongming Chen
Summary: This study analyzed the law of yield change under different water stress conditions using Jindazaohuang No. 2 as the test material. By monitoring the soybean canopy height under different water stress treatments, the rule of yield variation was explored and the response rule of canopy spectral reflectance to water stress was studied. The study found that the higher the degree of water stress, the lower the yield of soybean. The research also constructed a multiple linear regression monitoring model based on soybean yield characteristic band, with a coefficient of determination R2 of 0.791.
SPECTROSCOPY LETTERS
(2023)
Article
Environmental Sciences
Jing-Jing Zhou, Ya-Hao Zhang, Ze-Min Han, Xiao-Yang Liu, Yong-Feng Jian, Chun-Gen Hu, Yuan-Yong Dian
Summary: The study demonstrated that hyperspectral reflectance can accurately detect water stress in fruit trees and assess leaf photosynthetic traits early on, with machine-learning algorithms like random forest showing high predictive power for photosynthetic parameters. This technology has great potential for monitoring water stress and increasing yields in large-scale orchards.
Article
Agronomy
Yiping Peng, Lu Wang, Li Zhao, Zhenhua Liu, Chenjie Lin, Yueming Hu, Luo Liu
Summary: This study introduced a new method to improve the estimation of soil nutrient content based on hyperspectral remote-sensing techniques, successfully mapping soil TK content at a regional scale. The GBDT-GABP and LASSO-GABP methods were identified as the most accurate estimation methods for soil TN/TP and TK, respectively.
Article
Biochemical Research Methods
Yan Gong, Kaili Yang, Zhiheng Lin, Shenghui Fang, Xianting Wu, Renshan Zhu, Yi Peng
Summary: This study explores a simple method to remotely estimate Leaf Area Index (LAI) of different rice cultivars using Unmanned Aerial Vehicle (UAV) imaging. Results show a significant hysteresis in the relationship between Vegetation Indices (VI) and LAI in rice, which can be reduced by using the product of VI and canopy height to estimate LAI with errors under 24% throughout the entire growing season. The model developed in this study combines remotely sensed canopy height and VI information, improving rice LAI estimation at both pre- and post-heading stages without requiring re-parameterization.
Article
Agriculture, Multidisciplinary
Shu Meiyan, Dong Qizhou, Fei ShuaiPeng, Yang Xiaohong, Zhu Jinyu, Meng Lei, Li Baoguo, Ma Yuntao
Summary: Estimating the water status of maize using UAV digital and hyperspectral data can provide high-quality information for crop growth evaluation and precision irrigation. This study developed new canopy water indicators using canopy coverage instead of leaf area index, and found that the revised canopy fuel moisture content (r-FMCc) was the most effective indicator with a strong correlation to the difference vegetation index (DVI) derived from UAV hyperspectral images. The results suggest that UAV imaging technology combined with canopy water indicators can accurately monitor maize water status.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2022)
Article
Multidisciplinary Sciences
Jingang Zhang, Runmu Su, Qiang Fu, Wenqi Ren, Felix Heide, Yunfeng Nie
Summary: Hyperspectral imaging captures abundant spatial and spectral information, but the expensive and complicated devices hinder its application in consumer electronics. Computational spectral imaging methods can reconstruct hyperspectral information from RGB images, eliminating the need for spectral camera hardware. This review investigates state-of-the-art spectral reconstruction methods and categorizes them into prior-based and data-driven methods. It identifies challenges and trends for future work, highlighting the potential of learnable methods with fine feature representation abilities.
SCIENTIFIC REPORTS
(2022)
Article
Chemistry, Analytical
Sulaymon Eshkabilov, John Stenger, Elizabeth N. Knutson, Erdem Kucuktopcu, Halis Simsek, Chiwon W. Lee
Summary: The influence of nitrogen, phosphorus, and potassium compounds on the growth dynamics of hydroponically grown lettuce was studied, and optimal wavebands were found for estimating the nutrient levels. The results showed a high correlation between hyperspectral imaging data and laboratory-measured data.
Article
Multidisciplinary Sciences
Hong Li, Wunian Yang, Junjie Lei, Jinxing She, Xiangshan Zhou
Summary: This study proposed three new spectral absorption indices for estimating leaf equivalent water thickness (EWT) and fuel moisture content (FMC) in different plant types. SAI(1200) showed the best performance in estimating EWT, while SAI(970) and SAI(1660) were more suitable for FMC estimation.
Article
Zoology
Fangyuan Yu, Yiwen Sun, Tiejun Wang, Andrew K. Skidmore, Changqing Ding, Xinping Ye
Summary: The study integrated ecological niche dynamics into the species distribution modeling of the Asian crested ibis in East Asia. The research found that the crested ibis retained similar ecological niches over time.
The current suitable habitat for crested ibis has decreased by 39.6% compared to historical range, with human activity having a greater impact than climate change on their distribution. Future potentially suitable habitat may shift northeastward and northwestward, possibly expanding by 18.7% compared to historical range.
INTEGRATIVE ZOOLOGY
(2022)
Article
Agronomy
Xu Ma, Tiejun Wang, Lei Lu, Huaguo Huang, Jiangli Ding, Fei Zhang
Summary: This study proposed a three-dimensional clumping index model based on area for measuring the leaf area index of crops, using digital cover photography data captured by digital cameras. Validation showed that the 3D model improved the prediction accuracy of LAI by 20.9% compared to the 1D model, addressing the underestimation issue and improving calculation accuracy in agriculture.
FIELD CROPS RESEARCH
(2022)
Article
Forestry
Chunxiao Wang, Shuyu Huang, Junjie Wang
Summary: This study focused on the dike-pond landscape in the Shunde District of Foshan, China. Through remote sensing images and modeling, the spatial and temporal evolution characteristics of the dike-pond landscape pattern were analyzed, and the changes in ecosystem service value were visualized. The results indicate significant landscape changes and a continuous decline in ecosystem service value.
Article
Environmental Sciences
Yi-Wei Zhang, Tiejun Wang, Yanpei Guo, Andrew Skidmore, Zhenhua Zhang, Rong Tang, Shanshan Song, Zhiyao Tang
Summary: This study compares the performance of four non-parametric regression models in estimating plant community traits using UAV-based hyperspectral imaging. The results show that visible and near-infrared hyperspectral imaging can accurately estimate multiple plant community traits.
Article
Ecology
Isla Duporge, Genevieve E. Finerty, Festus Ihwagi, Stephen Lee, Jane Wathika, Zijing Wu, David W. Macdonald, Tiejun Wang
Summary: This study analyzed changes in boma distribution and density in the Laikipia-Samburu ecosystem of northern Kenya from 2011 to 2019 using satellite imagery, and examined the relationship between elephant movement and bomas using GPS data. The results showed that elephants adjusted their behavior to avoid human activity around bomas, particularly during the dry season. Understanding the consequences of these behavioral adjustments is critical for the long-term population viability of elephants.
REMOTE SENSING IN ECOLOGY AND CONSERVATION
(2022)
Article
Microbiology
Haili Yu, Tiejun Wang, Andrew Skidmore, Marco Heurich, Claus Bassler
Summary: This study used 50 years of macrofungal occurrence records from GBIF to analyze macrofungal diversity and distribution patterns in Norway and Sweden. The results showed that the cumulative number of macrofungal species stabilizes into localized hotspots of predicted macrofungal diversity with sampling efforts greater than approximately 30 years.
Article
Ecology
Xin Zong, Tiejun Wang, Andrew K. Skidmore, Marco Heurich
Summary: This study demonstrates the use of three-dimensional cumulative viewshed in studying animal spatial behavior at a landscape level. The researchers utilized a combined terrestrial and airborne LiDAR technique to measure fine-scale habitat visibility in forested landscapes. The findings reveal the red deer's preference for intermediate habitat visibility and their adaptation of movement rate to fine-scale visibility. This research provides valuable insights into the influence of visibility on animal behavior and highlights the potential of LiDAR in animal ecology and behavior studies.
JOURNAL OF ANIMAL ECOLOGY
(2023)
Article
Environmental Sciences
Yicen Zhang, Junjie Wang, Zhifeng Wu, Juyu Lian, Wanhui Ye, Fangyuan Yu
Summary: This study explores the feasibility and effectiveness of using leaf traits for tree species classification, as well as the impact of vertical canopy positions on classification accuracy. The results show that combining leaf functional traits and leaf hyperspectral reflectance data achieves the highest accuracy, and the vertical canopy position plays a significant role in classification.
Article
Biodiversity Conservation
Haili Yu, Tiejun Wang, Andrew Skidmore, Marco Heurich, Claus Baessler
Summary: This study used occurrence data from eight European countries to build species distribution models and predict the response of macrofungi to climate change. The results showed that considering climate change alone, 77% of macrofungal species will expand their distribution range and 57% of the area will have an increase in macrofungal species richness. However, when considering the combined climate and tree species distribution change, only 50% of the species are predicted to expand their distribution range and 49% of the area will experience an increase in macrofungal species richness.
DIVERSITY AND DISTRIBUTIONS
(2023)
Article
Multidisciplinary Sciences
Zijing Wu, Ce Zhang, Xiaowei Gu, Isla Duporge, Lacey F. Hughey, Jared A. Stabach, Andrew K. Skidmore, J. Grant C. Hopcraft, Stephen J. J. Lee, Peter M. Atkinson, Douglas J. McCauley, Richard Lamprey, Shadrack Ngene, Tiejun Wang
Summary: This study presents a deep learning pipeline that can automatically locate and count large herds of migratory ungulates in the Serengeti-Mara ecosystem using high-resolution satellite imagery. The results achieve accurate detection of nearly 500,000 individuals across thousands of square kilometers and multiple habitat types. This research demonstrates the capability of satellite remote sensing and machine learning techniques to automate the counting of large populations of terrestrial mammals and improve our understanding of animal behavior and ecology.
NATURE COMMUNICATIONS
(2023)
Article
Biodiversity Conservation
Zhongwen Hu, Jinjing Wu, Jingzhe Wang, Yinghui Zhang, Haichao Zhou, Changjun Gao, Junjie Wang, Guofeng Wu
Summary: The study aims to investigate the impact of exotic mangrove species on the spatial dynamics of mangroves in Shenzhen Bay, China. It was found that the mangrove area in the study area increased from 2000 to 2022, with a growth rate of 5.14% in Shenzhen and 2.38% in Hong Kong. The rapid spread of Sonneratia species was identified as one of the main contributors to the growth of mangrove hotspots, mainly concentrated in the estuary delta. The results provide valuable insights for accurate mangrove mapping and emphasize the importance of addressing the spread and invasive potential of exotic mangrove species in the study area, as well as cooperation with adjacent reserves.
ECOLOGICAL INDICATORS
(2023)
Article
Environmental Sciences
Yi Xu, Tiejun Wang, Andrew K. Skidmore, Tawanda W. Gara
Summary: This study proposes a novel approach to match individual trees between aerial photographs and airborne LiDAR data. By leveraging the maximum overlap of tree crowns in a local area, the correct and optimal offset vector is determined, and the mismatch in individual tree positions is rectified using this vector. Compared to a conventional method, the proposed approach significantly improves the accuracy of matching individual trees between aerial photographs and airborne LiDAR data.
Article
Geochemistry & Geophysics
Xu Ma, Jianli Ding, Tiejun Wang, Lei Lu, Hui Sun, Fei Zhang, Xiao Cheng, Ilyas Nurmemet
Summary: This study proposed a new method to estimate vegetation fractional vegetation cover (FVC) in arid areas using high-spatial-resolution (HSR) images. The method addressed the issue of estimating FVC from nadir-mode HSR images by modifying the radiation influence and developing a new pixel dichotomy coupled linear kernel-driven model. The results showed high consistency with true data and provided a useful algorithm for producing HSR FVCs in arid areas.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2023)
Article
Forestry
Zhengnan Zhang, Tiejun Wang, Andrew K. Skidmore, Fuliang Cao, Guanghui She, Lin Cao
Summary: The diameter at breast height (DBH) is an important trait for studying plant ecology and biodiversity, as well as managing forests. Traditional ground-based approaches for measuring individual tree DBH over large areas are time-consuming and expensive. In this study, we propose an improved area-based approach using airborne LiDAR data to estimate plot-level DBH by utilizing the relationship between tree height and DBH. The results demonstrate the potential of using height-DBH relationships to improve the accuracy of estimating plot-level DBH from airborne LiDAR data.
Article
Geography
Hunggul Y. S. H. Nugroho, Andrew Skidmore, Yousif A. Hussin
Summary: The decision of the Indonesian constitutional court to review forestry laws in 2013 marked a significant step forward in recognizing the rights of Indigenous people to forest. However, special measures are required to verify Indigenous status. This paper conducted a case study in a protected forest, evaluating the capacity of Indigenous communities to manage the forest and suggesting holistic approaches to ensure sustainable management for the benefit of the community and the environment.