- 标题
- 摘要
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- 实验方案
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Terrestrial Remote Sensing of Snowmelt in a Diverse High-Arctic Tundra Environment Using Time-Lapse Imagery
摘要： Snow cover is one of the crucial factors influencing the plant distribution in harsh Arctic regions. In tundra environments, wind redistribution of snow leads to a very heterogeneous spatial distribution which influences growth conditions for plants. Therefore, relationships between snow cover and vegetation should be analyzed spatially. In this study, we correlate spatial data sets on tundra vegetation types with snow cover information obtained from orthorectification and classification of images collected from a time-lapse camera installed on a mountain summit. The spatial analysis was performed over an area of 0.72 km2, representing a coastal tundra environment in southern Svalbard. The three-year monitoring is supplemented by manual measurements of snow depth, which show a statistically significant relationship between snow abundance and the occurrence of some of the analyzed land cover types. The longest snow cover duration was found on 'rock debris' type and the shortest on 'lichen-herb-heath tundra', resulting in melt-out time-lag of almost two weeks between this two land cover types. The snow distribution proved to be consistent over the different years with a similar melt-out pattern occurring in every analyzed season, despite changing melt-out dates related to different weather conditions. The data set of 203 high resolution processed images used in this work is available for download in the supplementary materials.
关键词： tundra vegetation,arctic,snow cover dynamics,snowmelt,orthorectification,time-lapse photography,ground based camera,Svalbard,tundra environment
更新于2025-09-23 15:23:52
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An Interplay between Photons, Canopy Structure, and Recollision Probability: A Review of the Spectral Invariants Theory of 3D Canopy Radiative Transfer Processes
摘要： Earth observations collected by remote sensors provide unique information to our ever-growing knowledge of the terrestrial biosphere. Yet, retrieving information from remote sensing data requires sophisticated processing and demands a better understanding of the underlying physics. This paper reviews research efforts that lead to the developments of the stochastic radiative transfer equation (RTE) and the spectral invariants theory. The former simplifies the characteristics of canopy structures with a pair-correlation function so that the 3D information can be succinctly packed into a 1D equation. The latter indicates that the interactions between photons and canopy elements converge to certain invariant patterns quantifiable by a few wavelength independent parameters, which satisfy the law of energy conservation. By revealing the connections between plant structural characteristics and photon recollision probability, these developments significantly advance our understanding of the transportation of radiation within vegetation canopies. They enable a novel physically-based algorithm to simulate the 'hot-spot' phenomenon of canopy bidirectional reflectance while conserving energy, a challenge known to the classic radiative transfer models. Therefore, these theoretical developments have a far-reaching influence in optical remote sensing of the biosphere.
关键词： vegetation remote sensing,stochastic radiative transfer equation,spectral invariants theory
更新于2025-09-23 15:23:52
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Use of Hyperspectral Image Data Outperforms Vegetation Indices in Prediction of Maize Yield
摘要： Hyperspectral cameras can provide reflectance data at hundreds of wavelengths. This information can be used to derive vegetation indices (VIs) that are correlated with agronomic and physiological traits. However, the data generated by hyperspectral cameras are richer than what can be summarized in a VI. Therefore, in this study, we examined whether prediction equations using hyperspectral image data can lead to better predictive performance for grain yield than what can be achieved using VIs. For hyperspectral prediction equations, we considered three estimation methods: ordinary least squares, partial least squares (a dimension reduction method), and a Bayesian shrinkage and variable selection procedure. We also examined the benefits of combining reflectance data collected at different time points. Data were generated by CIMMYT in 11 maize (Zea mays L.) yield trials conducted in 2014 under heat and drought stress. Our results indicate that using data from 62 bands leads to higher prediction accuracy than what can be achieved using individual VIs. Overall, the shrinkage and variable selection method was the best-performing one. Among the models using data from a single time point, the one using reflectance collected at 28 d after flowering gave the highest prediction accuracy. Combining image data collected at multiple time points led to an increase in prediction accuracy compared with using single-time-point data.
关键词： maize yield,hyperspectral imaging,prediction accuracy,vegetation indices,Bayesian methods
更新于2025-09-23 15:23:52
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - The Effect of Trunks on Directional Brightness Temperatures of a Leafless Forest Using a Geometrical Optical Model
摘要： In the paper, a geometric optical model is proposed for a vegetation-trunk-soil scene. The effect of tree trunks was analyzed by comparing directional brightness temperatures (BTs) between vegetation-soil and vegetation-trunk-soil scenes. The comparison result reveals the tree trunk can cause directional BTs as a whole lower because of its shadow and shaded area. Therefore, the tree trunk should be considered when retrieving temperatures from thermal infrared observations over a leafless forest. Efforts using measured TIR data requires to be done in the future.
关键词： vegetation-trunk-soil canopy,directional anisotropy,brightness temperature
更新于2025-09-23 15:23:52
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Heat Response of Global Vegetation Biomes to Ongoing Climate Warming Based on Remote Sensing
摘要： Research is needed by global change scientists on how global vegetation biomes respond to ongoing climate warming. To address this issue, we selected study sites with significant climate warming for diverse vegetation biomes, and used global gridded temperature and remote sensing data over the past 32 years (1982–2013). The results suggested that climate warming in areas above approximately 60° N is relaxing the heat-constraints on vegetation activity, thus promoting plant growth; whereas, in mid to low latitude areas, ongoing climate warming probably imposes negative impacts on vegetation biomes through drought and heat stress. Understanding these potential effects is important for planning adaptation strategies to mitigate the impacts of climate warming, particularly for agro-ecosystems.
关键词： climate warming,heat responses,remote sensing,global vegetation biomes
更新于2025-09-23 15:23:52
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Advancing the PROSPECT-5 Model to Simulate the Spectral Reflectance of Copper-Stressed Leaves
摘要： This paper proposes a modified model based on the PROSPECT-5 model to simulate the spectral reflectance of copper-stressed leaves. Compared with PROSPECT-5, the modified model adds the copper content of leaves as one of input variables, and the specific absorption coefficient related to copper (Kcu) was estimated and fixed in the modified model. The specific absorption coefficients of other biochemical components (chlorophyll, carotenoid, water, dry matter) were the same as those in PROSPECT-5. Firstly, based on PROSPECT-5, we estimated the leaf structure parameters (N), using biochemical contents (chlorophyll, carotenoid, water, and dry matter) and the spectra of all the copper-stressed leaves (samples). Secondly, the specific absorption coefficient related to copper (Kcu) was estimated by fitting the simulated spectra to the measured spectra using 22 samples. Thirdly, other samples were used to verify the effectiveness of the modified model. The spectra with the new model are closer to the measured spectra when compared to that with PROSPECT-5. Moreover, for all the datasets used for validation and calibration, the root mean square errors (RMSEs) from the new model are less than that from PROSPECT-5. The differences between simulated reflectance and measured reflectance at key wavelengths with the new model are nearer to zero than those with the PROSPECT-5 model. This study demonstrated that the modified model could get more accurate spectral reflectance from copper-stressed leaves when compared with PROSPECT-5, and would provide theoretical support for monitoring the vegetation stressed by copper using remote sensing.
关键词： vegetation remote sensing,leaf,PROSPECT,reflectance model,copper,spectra
更新于2025-09-23 15:23:52
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Detection of peanut leaf spots disease using canopy hyperspectral reflectance
摘要： Leaf spot is one of the most destructive diseases, which has a significant impact on the peanut production. Detecting leaf spot via spectral measurement and analysis is a possible alternative to traditional methods in detecting the spatial distribution of this disease. In this study, we identified sensitive bands and derived hyperspectral vegetation index specific to leaf spot detection. Hyperspectral canopy reflectance spectra of peanut cultivars susceptibilities to leaf spot were measured at two experimental sites in 2017. The normalized difference spectral index (NDSI) was derived based on their correlation with disease index (DI) in the leaf spectrum between 325 nm and 1075 nm. The results showed that canopy spectral reflectance decreased significantly in the near-infrared regions (NIR) as DI increased (r < -0.90). The spectral index for detecting leaf spot in peanut were LSI: (NDSI (R938, R761)) with R2 values of up to 0.68 for the regression model. The high fit between the observed and estimated values indicates that the DI detecting model based on the index could be used in peanut leaf spot detection in the absence of other stresses causing unhealthy symptoms. The results of this study show that it will provide a reliable, effective and accurate method for detecting leaf spot diseases in peanut through the analysis of hyperspectral data in the future.
关键词： Vegetation index,Disease index,Arachis hypogaea L.,Canopy hyperspectral reflectance
更新于2025-09-23 15:23:52
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Landsat-8 and Worldview-3 Data for Assessing Crop Residue Cover
摘要： Crop residues on the soil surface provide defense against erosive forces of water and wind. Quantifying crop residue cover is crucial for monitoring extent of conservation tillage practices. Current multispectral satellite sensors either lack appropriate spectral bands to reliably distinguish crop residue from soil or cannot provide global coverage. Our objective was to estimate crop residue cover in corn and soybean fields in central Iowa by combining data from two multispectral satellites - Landsat-8 and WorldView-3. Shortly after planting in 2016, we measured crop residue cover in >45 fields using the line-point transect method. Landsat Normalized Difference Tillage Index (NDTI) required local calibrations to account for variations in soils, crops, and moisture conditions. In contrast, WorldView-3 Shortwave Infrared Normalized Difference Residue Index (SINDRI) reliably estimated crop residue cover with minimal ground truth data. Although WorldView-3 images cannot provide global coverage, they can augment and extend ground truth observations for calibrating Landsat indices.
关键词： Soils,Crops,Conservation tillage,Non-photosynthetic vegetation,Agriculture
更新于2025-09-23 15:23:52
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Performance of a modified solar chimney power plant for power generation and vegetation
摘要： This paper develops a mathematical model to investigate the performance of a modified solar chimney power plant (MSCPP) for purposes of both power generation and vegetation. It then estimates the net added benefit. Results show that with the vegetation area enlarging, the MFR of the vapor increases, and more heat is used as the latent heat for water evaporation, leading to considerable reduction of the power. Condensation from the saturated air occurs only for very large vegetation area. On a cooler day, the plant produces less power and the condensation occurs for smaller vegetation area. Higher relative humidity of ambient air results in clear reduction of the MFR of the vapor evaporating from the vegetation area, and accordingly the great enhancement of the power. The benefit from agricultural products is larger than the benefit loss caused by the electricity loss, and the benefit of fresh water condensed from the saturated air is negligible. This leads to net added benefit for the MSCPP compared to the conventional plant. The net added benefit becomes greater with larger vegetation area. When the chimney is heightened from 1000 m to 1500 m, the power is enhanced greatly; however, the net added benefit becomes smaller.
关键词： Vegetation,Solar collector,Latent heat,Fresh water,Solar chimney,Power generation
更新于2025-09-23 15:23:52
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Assessment of red-edge vegetation indices for crop leaf area index estimation
摘要： This study explores the potential of vegetation indices (VIs) for crop leaf area index (LAI) estimation, with a focus on comparing red-edge reflectance based (RE-based) and the visible reflectance based (VIS-based) VIs. Seven VIs were derived from multi-temporal RapidEye images to correlate with LAI of two crop species having contrasting leaf structures and canopy architectures: spring wheat (a monocot) and canola (a dicot) in northern Ontario, Canada. The relationship between LAI and the selected VIs (LAI-VI) was characterized using a semi-empirical model. The Markov Chain Monte Carlo (MCMC) sampling method was used to estimate the model parameters, including the extinction coefficient (KVI) and VI value for dense green canopy (VI∞). Results showed that crop-specific regression models were much closer to a generic regression model using the RE-based VIs than using the VIS-based VIs. Furthermore, the joint posterior probability distribution of the KVI and VI∞ of the RE-based VIs tended to converge for the two crops. This suggests that the RE-based VIs are not as sensitive to canopy structure, e.g., the average leaf angle (ALA), as the VIS-based VIs. This is also demonstrated by the sensitivity analyses using both PROSAIL simulations and field measurements. Hence, the RE-based VIs can be used to develop a more generic LAI estimation algorithm for different crops. Further studies are required to assess the impact of soil reflectance and other factors, such as illumination-target-viewing geometries and atmospheric conditions, on LAI retrieval.
关键词： Sensitivity analysis,Crops,RapidEye,Leaf area index,red-edge,Vegetation index
更新于2025-09-23 15:23:52