scholarly journals Plant ecophysiological processes in spectral profiles: perspective from a deciduous broadleaf forest

2021 ◽  
Author(s):  
Hibiki M. Noda ◽  
Hiroyuki Muraoka ◽  
Kenlo Nishida Nasahara
Keyword(s):  
Remote Sensing ◽  
Optical Properties ◽  
Spectral Reflectance ◽  
Canopy Structure ◽  
Terrestrial Ecosystems ◽  
Optical Remote Sensing ◽  
Canopy Reflectance ◽  
Broadleaf Forest ◽  
Leaf Optical Properties ◽  
Deciduous Broadleaf Forest

AbstractThe need for progress in satellite remote sensing of terrestrial ecosystems is intensifying under climate change. Further progress in Earth observations of photosynthetic activity and primary production from local to global scales is fundamental to the analysis of the current status and changes in the photosynthetic productivity of terrestrial ecosystems. In this paper, we review plant ecophysiological processes affecting optical properties of the forest canopy which can be measured with optical remote sensing by Earth-observation satellites. Spectral reflectance measured by optical remote sensing is utilized to estimate the temporal and spatial variations in the canopy structure and primary productivity. Optical information reflects the physical characteristics of the targeted vegetation; to use this information efficiently, mechanistic understanding of the basic consequences of plant ecophysiological and optical properties is essential over broad scales, from single leaf to canopy and landscape. In theory, canopy spectral reflectance is regulated by leaf optical properties (reflectance and transmittance spectra) and canopy structure (geometrical distributions of leaf area and angle). In a deciduous broadleaf forest, our measurements and modeling analysis of leaf-level characteristics showed that seasonal changes in chlorophyll content and mesophyll structure of deciduous tree species lead to a seasonal change in leaf optical properties. The canopy reflectance spectrum of the deciduous forest also changes with season. In particular, canopy reflectance in the green region showed a unique pattern in the early growing season: green reflectance increased rapidly after leaf emergence and decreased rapidly after canopy closure. Our model simulation showed that the seasonal change in the leaf optical properties and leaf area index caused this pattern. Based on this understanding we discuss how we can gain ecophysiological information from satellite images at the landscape level. Finally, we discuss the challenges and opportunities of ecophysiological remote sensing by satellites.

scholarly journals Decoupling Canopy Structure and Leaf Biochemistry: Testing the Utility of Directional Area Scattering Factor (DASF)

2018 ◽  
Vol 10 (12) ◽  
pp. 1911
Author(s):  
Jennifer Adams ◽  
Philip Lewis ◽  
Mathias Disney
Keyword(s):  
Remote Sensing ◽  
Optical Properties ◽  
Prior Knowledge ◽  
Canopy Structure ◽  
Remote Sensing Data ◽  
Sensing Data ◽  
Leaf Optical Properties ◽  
Soil Effects ◽  
Scattering Factor ◽  
Directional Reflectance

Biochemical properties retrieved from remote sensing data are crucial sources of information for many applications. However, leaf and canopy scattering processes must be accounted for to reliably estimate information on canopy biochemistry, carbon-cycle processes and energy exchange. A coupled leaf-canopy model based on spectral invariants theory has been proposed, that uses the so-called Directional Area Scattering Factor (DASF) to correct hyperspectral remote sensing data for canopy structural effects. In this study, the reliability of DASF to decouple canopy structure and biochemistry was empirically tested using simulated reflectance spectra modelled using a Monte Carlo Ray Tracing (MCRT) radiative transfer model. This approach allows all canopy and radiative properties to be specified a priori. Simulations were performed under idealised conditions of directional-hemispherical reflectance, isotropic Lambertian leaf reflectance and transmittance and sufficiently dense (high LAI) canopies with black soil where the impact of canopy background is negligible, and also departures from these conditions. It was shown that both DASF and total canopy scattering could be accurately extracted under idealised conditions using information from both the full 400–2500 nm spectral interval and the 710–790 nm interval alone, even given no prior knowledge of leaf optical properties. Departures from these idealised conditions: varying view geometry, bi-directional reflectance, LAI and soil effects, were tested. We demonstrate that total canopy scattering could be retrieved under conditions of varying view geometry and bi-directional reflectance, but LAI and soil effects were shown to reduce the accuracy with which the scattering can be modelled using the DASF approach. We show that canopy architecture, either homogeneous or heterogeneous 3D arrangements of canopy scattering elements, has important influences over DASF and consequently the accuracy of retrieval of total canopy scattering. Finally, although DASF and total canopy scattering could be retrieved to within 2.4% of the modelled total canopy scattering signal given no prior knowledge of leaf optical properties, spectral invariant parameters were not accurately retrieved from the simulated signal. This has important consequences since these parameters are quite widely used in canopy reflectance modelling and have the potential to help derive new, more accurate canopy biophysical information. Understanding and quantifying the limitations of the DASF approach as we have done here, is an important step in allowing the wider use of these methods for decoupling canopy structure and biochemistry.

scholarly journals Some Peculiarities of Arable Soil Organic Matter Detection Using Optical Remote Sensing Data

2021 ◽  
Vol 13 (12) ◽  
pp. 2313
Author(s):  
Elena Prudnikova ◽  
Igor Savin
Keyword(s):  
Remote Sensing ◽  
Organic Matter ◽  
Soil Organic Matter ◽  
Spectral Reflectance ◽  
Remote Sensing Data ◽  
Soil Surface ◽  
Optical Remote Sensing ◽  
Test Field ◽  
Sensing Data ◽  
Sentinel 2

Optical remote sensing only provides information about the very thin surface layer of soil. Rainfall splash alters soil surface properties and its spectral reflectance. We analyzed the impact of rainfall on the success of soil organic matter (SOM) content (% by mass) detection and mapping based on optical remote sensing data. The subject of the study was the arable soils of a test field located in the Tula region (Russia), their spectral reflectance, and Sentinel-2 data. Our research demonstrated that rainfall negatively affects the accuracy of SOM predictions based on Sentinel-2 data. Depending on the average precipitation per day, the R2cv of models varied from 0.67 to 0.72, RMSEcv from 0.64 to 1.1% and RPIQ from 1.4 to 2.3. The incorporation of information on the soil surface state in the model resulted in an increase in accuracy of SOM content detection based on Sentinel-2 data: the R2cv of the models increased up to 0.78 to 0.84, the RMSEcv decreased to 0.61 to 0.71%, and the RPIQ increased to 2.1 to 2.4. Further studies are necessary to identify how the SOM content and composition of the soil surface change under the influence of rainfall for other soils, and to determine the relationships between rainfall-induced SOM changes and soil surface spectral reflectance.

LAI Retrieval Based on PROSPECT-SAILH Model from Multi-Angular Data of WiDAS Imaging System

2012 ◽  
Vol 518-523 ◽  
pp. 5697-5703
Author(s):  
Zhao Yan Liu ◽  
Ling Ling Ma ◽  
Ling Li Tang ◽  
Yong Gang Qian
Keyword(s):  
Remote Sensing ◽  
Imaging System ◽  
Remote Sensing Data ◽  
Canopy Reflectance ◽  
Area Index ◽  
Sensing Data ◽  
Spectral Bands ◽  
Sensing Technology ◽  
Leaf Optical Properties ◽  
Angular Data

The aim of this study is to assess the capability of estimating Leaf Area Index (LAI) from high spatial resolution multi-angular Vis-NIR remote sensing data of WiDAS (Wide-Angle Infrared Dual-mode Line/Area Array Scanner) imaging system by inverting the coupled radiative transfer models PROSPECT-SAILH. Based on simulations from SAILH canopy reflectance model and PROSPECT leaf optical properties model, a Look-up Table (LUT) which describes the relationship between multi-angular canopy reflectance and LAI has been produced. Then the LAI can be retrieved from LUT by directly matching canopy reflectance of six view directions and four spectral bands with LAI. The inversion results are validated by field data, and by comparing the retrieval results of single-angular remote sensing data with multi-angular remote sensing data, we can found that the view angle takes the obvious impact on the LAI retrieval of single-angular data and that high accurate LAI can be obtained from the high resolution multi-angular remote sensing technology.

Canopy structure and imaging geometry may create unique problems during spectral reflectance measurements of crop canopies in bioregenerative advanced life support systems

2007 ◽  
Vol 6 (2) ◽  
pp. 109-121
Author(s):  
Andrew C. Schuerger ◽  
Kenneth L. Copenhaver ◽  
David Lewis ◽  
Russell Kincaid ◽  
George May
Keyword(s):  
Remote Sensing ◽  
Plant Growth ◽  
Spectral Reflectance ◽  
Life Support ◽  
Support Systems ◽  
Canopy Structure ◽  
Advanced Life Support ◽  
Sensing System ◽  
Plant Canopies ◽  
Reflectance Measurements

AbstractHuman exploration missions to the Moon or Mars might be helped by the development of a bioregenerative advanced life-support (ALS) system that utilizes higher plants to regenerate water, oxygen and food. In order to make bioregenerative ALS systems competitive to physiochemical life-support systems, the ‘equivalent system mass’ (ESM) must be reduced by as much as possible. One method to reduce the ESM of a bioregenerative ALS system would be to deploy an automated remote sensing system within plant production modules to monitor crop productivity and disease outbreaks. The current study investigated the effects of canopy structure and imaging geometries on the efficiency of measuring the spectral reflectance of individual plants and crop canopies in a simulated ALS system. Results indicate that canopy structure, shading artefacts and imaging geometries are likely to create unique challenges in developing an automated remote sensing system for ALS modules. The cramped quarters within ALS plant growth units will create problems in collecting spectral reflectance measurements from the nadir position (i.e. directly above plant canopies) and, thus, crop canopies likely will be imaged from a diversity of orientations relative to the primary illumination source. In general, highly reflective white or polished surfaces will be used within an ALS plant growth module to maximize the stray light that is reflected onto plant canopies. Initial work suggested that these highly reflective surfaces might interfere with the collection of spectral reflectance measurements of plants, but the use of simple remote sensing algorithms such as 760/685 band ratios or normalized difference vegetation index (NDVI) images greatly reduced the effects of the reflective backgrounds. A direct comparison of 760/685 and NDVI images from canopies of lettuce, pepper and tomato plants indicated that unique models of individual plants are going to be required to properly assess the health conditions of canopies. A mixed model of all three plant species was not effective in predicting plant stress using either the 760/685 or NDVI remote sensing algorithms.

Linking near-surface and satellite remote sensing measurements of deciduous broadleaf forest phenology

2012 ◽  
Vol 117 ◽  
pp. 307-321 ◽  
Author(s):  
Koen Hufkens ◽  
Mark Friedl ◽  
Oliver Sonnentag ◽  
Bobby H. Braswell ◽  
Thomas Milliman ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Satellite Remote Sensing ◽  
Broadleaf Forest ◽  
Near Surface ◽  
Deciduous Broadleaf Forest

scholarly journals Seagrass Mapping and Monitoring Along the Coasts of Crete, Greece

2019 ◽  
Author(s):  
Polina Lemenkova
Keyword(s):  
Remote Sensing ◽  
Optical Properties ◽  
Environmental Factors ◽  
Spectral Reflectance ◽  
Mediterranean Region ◽  
The World ◽  
Seagrass Mapping ◽  
Resolution Imaging ◽  
The Mediterranean ◽  
Remote Sensing Techniques

Type: Master's Thesis (M.Sc.).School: University of Twente, Faculty of Geo-Information Science and Earth Observation (ITC).Supervisors: Albertus G. (Bert) Toxopeus, Valentijn Venus. Location: Netherlands, Enschede (Overijssel Province).The seagrasses, a unique group of aquatic plants, create complex, extremely diversified and productive ecological systems in the littoral coastal zones. The only flowering plant in the world that is able to live completely submerged, seagrasses play vital role in the marine ecosystems of the World Ocean. Seagrasses are the most important component in the environmental food chain of the coastal ecosystems, being a vital food source for various marine species (e.g. fish, dugongs, turtles, swans), and a producer of organic matter, which is the very basis of the food web. The P.oceanica seagrass is an endemic for the Mediterranean region, and a main species in the marine coastal environment of Greece. Meadows of P.oceanica are subjected to the human activities, because they occur in coastal areas, where they are affected both by anthropogenic and by climatic and environmental factors. Nowadays P.oceanica is in the alarming state of regression, because of the deterioration of the environment in the Mediterranean Sea. Due to these reasons, P.oceanica is a protected species since 1988 in some European countries (France). Monitoring P.oceanica is therefore an important contribution to the saving and protecting the environment of Mediterranean region. The current MSc thesis focuses on the monitoring of seagrass P.oceanica along the northern coasts of Crete Island, Greece, and investigates the application of the remote sensing techniques for the seagrass mapping. This research was articulated in two parts, where the first one involves an ecological approach to the seagrass distribution in various regions around the globe and the experience of seagrass monitoring nowadays. The second part of this work has technical character and investigates the application of the remote sensing techniques towards seagrass mapping. It, furthermore, focuses on the optical properties of the P.oceanica and other seafloor cover types, and studies distinguishability of various seafloor cover types. Studies of the optical characteristics of separate seafloor cover types were made with purpose to clarify, whether their spectral properties change with varying environmental conditions.Special attention has been drawn on the role of environmental factors on the distribution of P.oceanica along the coasts of Crete, and in particular, how the optical properties of the seafloor cover types, i.e. spectral reflectance, are being changed under varying external conditions, e.g. water column, amount of suspended particles and sediments in the seawater, and water temperature. For this purpose we studied differences in the spectral reflectance of P.oceanica and other bottom cover types at three distinct depths. The diverse spectral values entail variations in optical properties of the seafloor cover types at changing environmental conditions. We applied WASI Water Color Simulator (WASI) simulation techniques for the modelling of the optical parameters of various seafloor cover types by various spaceborne imaging spectrometers (MEdium Resolution Imaging Spectrometer (MERIS), Sea-viewing Wide Field-of-view Sensor (SeaWiFS), Coastal Zone Color Scanner (CZCS) and MODerate resolution Imaging Spectroradiometer (MODIS)), in order to understand their suitability and possible limitations for the seagrass mapping. Fieldwork research sites were presented by separate locations on the northern coast of Crete region (Ligaria, Agia Pelagia, Xerocampos). The additional measurements of the reflectance spectra of the seawater with and without sediments have been made in aquarium tank in 2009 by means of Trios-RAMSES spectroradiometer. Parallel to the collection of spectra signatures, we captured the imagery for the seagrass mapping, which consists of the aerial images from the Google Earth website and the satellite Landsat TM and ETM+ scenes.

scholarly journals Recent advances in space-borne optical remote sensing systems for monitoring global terrestrial ecosystems

2016 ◽  
Vol 40 (2) ◽  
pp. 322-351 ◽  
Author(s):  
Jadunandan Dash ◽  
Booker O. Ogutu
Keyword(s):  
Remote Sensing ◽  
Terrestrial Ecosystem ◽  
Remote Sensing Data ◽  
Terrestrial Ecosystems ◽  
Global Scale ◽  
Data Availability ◽  
Landsat 8 ◽  
Optical Remote Sensing ◽  
Ecosystem Monitoring ◽  
Sensing Data

Since the launch of the first Landsat satellite in the early 1970s, the field of space-borne optical remote sensing has made significant progress. Advances have been made in all aspects of optical remote sensing data, including improved spatial, temporal, spectral and radiometric resolutions, which have increased the uptake of these data by wider scientific communities. Flagship satellite missions such as NASA’s Terra and Aqua and ESA’s Envisat with their high temporal (<3days) and spectral (15–36 bands) resolutions opened new opportunities for routine monitoring of various aspects of terrestrial ecosystems at the global scale and have provided greater understanding of critical biophysical processes in the terrestrial ecosystem. The launch of new satellite sensors such as Landsat 8 and the European Space Agency’s Copernicus Sentinel missions (e.g. Sentinel 2 with improved spatial resolution (10–60 m) and potential revisit time of five days) is set to revolutionise the availability and use of remote sensing data in global terrestrial ecosystem monitoring. Furthermore, the recent move towards use of constellations of nanosatellites (e.g. the Flock missions by Planet Labs) to collect on-demand high spatial and temporal resolution optical remote sensing data would enable uptake of these data for operational monitoring. As a result of increase in data availability, optical remote sensing data are now increasingly used to support a number of operational services (e.g. land monitoring, atmosphere monitoring and climate change studies). However, many challenges still remain in exploiting the growing volume of optical remote sensing data to monitor global terrestrial ecosystems. These challenges include ensuring the highest data quality both in terms of the sensitivity of sensors and the derived biophysical products, affordability and availability of the data and continuity of data acquisition. This review provides an overview of the developments in space-borne optical remote sensing in the past decade and discusses a selection of aspects of global terrestrial ecosystems where the data are currently used. It concludes by highlighting some of the challenges and opportunities of using optical remote sensing data in monitoring global terrestrial ecosystems.

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