The remote sensing community puts major efforts into calibration and validation of sensors, measurements, and derived products to quantify and reduce uncertainties. Given recent advances in ...instrument design, radiometric calibration, atmospheric correction, algorithm development, product development, validation, and delivery, the lack of standardization of reflectance terminology and products becomes a considerable source of error. This article provides full access to the basic concept and definitions of reflectance quantities, as given by Nicodemus et al. Nicodemus, F.E., Richmond, J.C., Hsia, J.J., Ginsberg, I.W., and Limperis, T. (1977). Geometrical Considerations and Nomenclature for Reflectance. In: National Bureau of Standards, US Department of Commerce, Washington, D.C. URL:
http://physics.nist.gov/Divisions/Div844/facilities/specphoto/pdf/geoConsid.pdf. and Martonchik et al. Martonchik, J.V., Bruegge, C.J., and Strahler, A. (2000). A review of reflectance nomenclature used in remote sensing. Remote Sensing Reviews, 19, 9–20.. Reflectance terms such as BRDF, HDRF, BRF, BHR, DHR, black-sky albedo, white-sky albedo, and blue-sky albedo are defined, explained, and exemplified, while separating conceptual from measurable quantities. We use selected examples from the peer-reviewed literature to demonstrate that very often the current use of reflectance terminology does not fulfill physical standards and can lead to systematic errors. Secondly, the paper highlights the importance of a proper usage of definitions through quantitative comparison of different reflectance products with special emphasis on wavelength dependent effects. Reflectance quantities acquired under hemispherical illumination conditions (i.e., all outdoor measurements) depend not only on the scattering properties of the observed surface, but as well on atmospheric conditions, the object's surroundings, and the topography, with distinct expression of these effects in different wavelengths. We exemplify differences between the hemispherical and directional illumination quantities, based on observations (i.e., MISR), and on reflectance simulations of natural surfaces (i.e., vegetation canopy and snow cover). In order to improve the current situation of frequent ambiguous usage of reflectance terms and quantities, we suggest standardizing the terminology in reflectance product descriptions and that the community carefully utilizes the proposed reflectance terminology in scientific publications.
This article reviews the use of optical and microwave remote sensing data for soil and terrain mapping with emphasis on applications at regional and coarser scales. Remote sensing is expected to ...offer possibilities for improving incomplete spatial and thematic coverage of current regional and global soil databases. Traditionally, remotely sensed imagery have been used to support segmentation of the landscape into rather homogeneous soil–landscape units for which soil composition can be established by sampling. Soil properties have also been inferred from optical and microwave data using physically-based and empirical methods. Used as a secondary data source, remotely sensed imagery may support spatial interpolation of sparsely sampled soil property data. Soil properties that have been measured using remote or proximal sensing approaches include mineralogy, texture, soil iron, soil moisture, soil organic carbon, soil salinity and carbonate content. In sparsely vegetated areas, successful use of space borne, airborne, and in situ measurements using optical, passive and active microwave instruments has been reported. On the other hand, in densely vegetated areas, soil data acquisition typically relied on indirect retrievals using soil indicators, such as plant functional groups, productivity changes, and Ellenberg indicator values. Several forms of kriging, classification and regression tree analyses have been used jointly with remotely sensed data to predict soil properties at unvisited locations aiming at obtaining continuous area coverage. We expect that remotely sensed data from existing platforms and planned missions can provide an important data source supporting digital soil mapping. Yet, most studies so far have been performed on a local scale and only few on regional or smaller map scale. Although progress has been made, current methods and techniques still bear potential to further explore the full range of spectral, spatial and temporal properties of existing data sources. For example, space borne spectroscopy has been of limited use in retrieving soil data when compared to laboratory or field spectroscopy. To date, there is no coherent methodology established, where approaches of spatial segmentation, measurements of soil properties and interpolation using remotely sensed data are integrated in a holistic fashion to achieve complete area coverage. Such approaches will enhance the perspectives of using remotely sensed data for digital soil mapping.
► Remote sensing offers possibilities for improving current soil databases. ► Soil attribute retrievals from remote sensing should be used as covariates in DSM. ► The gap between proximal and remote sensing has to be bridged. ► We will be seeing future instruments launched soon enhancing the perspectives of DSM. ► A coherent multidisciplinary method for soil and terrain mapping should be developed.
Monitoring vegetation dynamics is fundamental for improving Earth system models and for increasing our understanding of the terrestrial carbon cycle and the interactions between biosphere and ...climate. Medium spatial resolution sensors, like MERIS, exhibit a significant potential to study these dynamics over large areas because of their spatial, spectral and temporal resolution. However, the spatial resolution provided by MERIS (300 m in full resolution mode) is not appropriate to monitor heterogeneous landscapes, where typical length scales of these dynamics rarely reach 300 m. We, therefore, motivate the use of data fusion techniques to downscale medium spatial resolution data (MERIS full resolution, FR) to a Landsat-like spatial resolution (25 m). An unmixing-based data fusion approach was applied to a time series of MERIS FR images acquired over The Netherlands. The selected data fusion approach is based on the linear mixing model and uses a high spatial resolution land use database to produce images having the spectral and temporal resolution as provided by MERIS, but a Landsat-like spatial resolution. A quantitative assessment of the quality of the fused images was done in order to test the validity of the proposed method and to evaluate the radiometric characteristics of the MERIS fused images. The resulting series of fused images was subsequently used to compute two vegetation indices specifically designed for MERIS: the MERIS terrestrial chlorophyll index (MTCI) and the MERIS global vegetation index (MGVI). These indices represent continuous fields of canopy chlorophyll (MTCI) and of the fraction of photosynthetically active radiation absorbed by the canopy (MGVI). Results indicate that the selected data fusion approach can be successfully used to downscale MERIS data and, therefore, to monitor vegetation dynamics at Landsat-like spatial, and MERIS-like spectral and temporal resolution.
Sun-induced chlorophyll fluorescence (SIF) is a radiation flux emitted from chlorophyll molecules and is considered an indicator of the actual functional state of plant photosynthesis. The remote ...measurement of SIF opens a new perspective to assess actual photosynthesis at larger, ecologically relevant scales and provides an alternative approach to study the terrestrial carbon cycle. Recent studies demonstrated the reliability of measured SIF signals and showed significant relationships between SIF and gross primary production (GPP) at ecosystem and global scales. Despite these encouraging results, understanding the complex mechanisms between SIF and GPP remains challenging before SIF can be finally utilized to constrain estimates of GPP. In this study, we present a comprehensive assessment of the relationship between far-red SIF retrieved at 760nm (SIF760) and GPP, and its transferability across three structurally and physiologically contrasting ecosystems: perennial grassland, cropland and mixed temperate forest. We use multi-temporal imaging spectroscopy (IS) data acquired with the Airborne Prism EXperiment (APEX) sensor as well as eddy covariance (EC) flux tower data to evaluate the relationship between SIF760 and GPPEC. We use simulations performed with the coupled photosynthesis–fluorescence model SCOPE to prove trends obtained from our observational data and to assess apparent confounding factors such as physiological and structural interferences or temporal scaling effects. Observed relationships between SIF760 and GPPEC were asymptotic and ecosystem-specific, i.e., perennial grassland (R2=0.59, rRMSE=27.1%), cropland (R2=0.88, rRMSE=3.5%) and mixed temperate forest (R2=0.48, rRMSE=15.88%). We demonstrate that asymptotic leaf level relationships between SIF760 and GPPEC became more linear at canopy level and scaled with temporal aggregation. We conclude that remote sensing of SIF provides a new observational approach to decrease uncertainties in estimating GPP across ecosystems but requires dedicated strategies to compensate for the various confounding factors impacting SIF–GPP relationships. Our findings help in bridging the gap between mechanistic understanding at leaf level and ecosystem-specific observations of the relationships between SIF and GPP.
•SIF760 shows ecosystem-specific and asymptotic relationships to GPP.•Compared to greenness based indices, SIF760 is more consistently related to GPP.•Canopy structure and competing energy pathways confound SIF760–GPP relationships.•SIF760–GPP relationships scale with temporal aggregation.•Complementary environmental and vegetation information is needed to use SIF760.
View angle effects present in spectral vegetation indices can either be regarded as an added source of uncertainty for variable retrieval or as a source of additional information, enhancing the ...variable retrieval; however, the magnitude of these angular effects remains for most indices unknown or unquantified. We use the ESA-mission CHRIS-PROBA (Compact High Resolution Imaging Spectrometer onboard the Project for On-board Autonomy) providing spaceborne imaging spectrometer and multiangular data to assess the reflectance anisotropy of broadband as well as recently developed narrowband indices. Multiangular variability of Hemispherical Directional Reflectance Factor (HDRF) is a prime factor determining the indices´ angular response. Two contrasting structural vegetation types, pine forest and meadow, were selected to study the effect of reflectance anisotropy on the angular response. Calculated indices were standardized and statistically evaluated for their varying HDRF. Additionally we employ a coupled radiative transfer model (PROSPECT/FLIGHT) to quantify and substantiate the findings beyond an incidental case study. Nearly all tested indices manifested a prominent anisotropic behaviour. Apart from the conventional broadband greenness indices e.g. Simple Ratio Index (SRI), Normalized Difference Vegetation Index (NDVI), light use efficiency and leaf pigment indices e.g. Structure Insensitive Pigment Index (SIPI), Photochemical Reflectance Index (PRI) and Anthocyanin Reflectance Index (ARI) did express significant different angular responses depending on the vegetation type. Following the quantification of the impact, we conclude that the angular-dependent fraction of non-photosynthetic material is of critical importance shaping the angular signature of these VIs. This work highlights the influence of viewing geometry and surface reflectance anisotropy, particularly when using light use efficiency and leaf pigment indices.
Land degradation is always with us but its causes, extent and severity are contested. We define land degradation as a long-term decline in ecosystem function and productivity, which may be assessed ...using long-term, remotely sensed normalized difference vegetation index (NDVI) data. Deviation from the norm may serve as a proxy assessment of land degradation and improvement - if other factors that may be responsible are taken into account. These other factors include rainfall effects which may be assessed by rain-use efficiency, calculated from NDVI and rainfall. Results from the analysis of the 23-year Global Inventory Modeling and Mapping Studies (GIMMS) NDVI data indicate declining rain-use efficiency-adjusted NDVI on ca. 24% of the global land area with degrading areas mainly in Africa south of the equator, South-East Asia and south China, north-central Australia, the Pampas and swaths of the Siberian and north American taiga; 1.5 billion people live in these areas. The results are very different from previous assessments which compounded what is happening now with historical land degradation. Economic appraisal can be undertaken when land degradation is expressed in terms of net primary productivity and the resultant data allow statistical comparison with other variables to reveal possible drivers.
Progress in field spectroscopy Milton, Edward J.; Schaepman, Michael E.; Anderson, Karen ...
Remote sensing of environment,
09/2009, Letnik:
113
Journal Article
Recenzirano
Odprti dostop
This paper reviews developments in the science of field spectroscopy, focusing on the last twenty years in particular. During this period field spectroscopy has become established as an important ...technique for characterising the reflectance of natural surfaces in situ, for supporting the vicarious calibration of airborne and satellite sensors, and for providing a means of scaling-up measurements from small areas (e.g. leaves, rocks) to composite scenes (e.g. vegetation canopies), and ultimately to pixels. This paper describes the physical basis of the subject and evaluates the different methods and instruments which have been employed across a range of studies. The development and use of field goniometers is described, and related to methods for estimating the bidirectional reflectance distribution function (BRDF) from directional reflectance measurements in the field. The paper also considers the practical aspects of field spectroscopy, and identifies a number of factors affecting the useability of field spectroradiometers, including the weight and cost of the instruments, limitations of some commonly used methodologies and practical issues such as the legibility of displays and limited battery life. The prospects for the future of field spectroscopy are considered in relation to the increasingly important contribution that field spectral data will make to EO-based global measurement and monitoring systems, specifically through their assimilation into numerical models. However, for this to be achieved it is essential that the data are of high quality, with stated levels of accuracy and uncertainty, and that common protocols are developed and maintained to ensure the long-term value of field spectroscopic data. The importance of employing a precise terminology for describing the geometric configuration of measurements is highlighted in relation to issues of repeatability and reproducibility. Through such refinements in methodology, field spectroscopy will establish its credentials as a reliable method of environmental measurement, underpinning quantitative Earth observation and its applications in the environmental and Earth sciences.
The science of spectroscopy has existed for more than three centuries, and imaging spectroscopy for the Earth system for three decades. We first discuss the historical background of spectroscopy, ...followed by imaging spectroscopy, introducing a common definition for the latter. The relevance of imaging spectroscopy is then assessed using a comprehensive review of the cited literature. Instruments, technological advancements and (pre-)processing approaches are discussed to set the scene for application related advancements. We demonstrate these efforts using four examples that represent progress due to imaging spectroscopy, namely (i) bridging scaling gaps from molecules to ecosystems using coupled radiative transfer models (ii) assessing surface heterogeneity including clumping, (iii) physical based (inversion) modeling, and iv) assessing interaction of light with the Earth surface. Recent advances of imaging spectroscopy contributions to the Earth system sciences are discussed. We conclude by summarizing the achievements of thirty years of imaging spectroscopy and strongly recommend this community to increase its efforts to convince relevant stakeholders of the urgency to acquire the highest quality imaging spectrometer data for Earth observation from operational satellites capable of collecting consistent data for climatically-relevant periods of time.
Imaging spectroscopy (IS) provides an efficient tool to assess vegetation status and functioning at ecologically relevant scales. Reliable extraction of vegetation information from spatial and ...spectral high resolution spectroscopy data requires accurate retrieval schemes to account for the complex radiative transfer in the coupled vegetation-atmosphere system. Particularly the coupling of the atmosphere and vegetation considering combined effects of anisotropy, absorption and scattering typically relies on many assumptions, rendering estimates of direct (Edir) and diffuse (Edif) surface irradiance error prone. This impacts the reliability of retrieved vegetation properties.
In this study we discuss and quantify the retrieval sensitivity of vegetation information using high resolution IS data to inaccurate assumptions of direct and diffuse surface irradiance. We use observations and simulations and focus on the two vegetation indices normalized difference vegetation index (NDVI) and the photochemical reflectance index (PRI), and on sun-induced chlorophyll fluorescence (Fs). Our results indicate that, even if the irradiance field (E) is exactly known, reflectance based vegetation indices show an inherent variation of 9% (NDVI) and 12% (PRI) respectively. These variations are caused by complex interactions of surface irradiance and reflectance anisotropy. The emitted Fs signal was found to be almost unaffected by those variations, if the retrieval considers surface anisotropy. Further, estimation of vegetation properties is subject to large uncertainties if instantaneous E fields are unknown. In that case, they range up to 13% for the NDVI, up to 32% for the PRI, and up to 58% for Fs. We conclude that retrieval sensitivities of vegetation indices and Fs to illumination effects must be carefully considered in data interpretation and suggest using coupled surface-atmosphere models to exploit the full information content of IS data.
•Effects of surface irradiance E are intrinsically coupled to reflectance anisotropy.•Increasing spatial resolution complicates the estimation of surface E.•Retrieved vegetation information differs in sunlit and shaded canopies.•NDVI, PRI and Fs retrievals are sensitive to changing direct and diffuse surface E.•Coupled vegetation-atmosphere models allow reducing illumination effects.
Sun-induced chlorophyll fluorescence (Fs) is the radiation flux emitted from chlorophyll molecules and can be used as a remote sensing (RS) observable to be linked to plant photosynthesis. Recently, ...significant progress has been made to quantify Fs from RS data, but both retrieval and interpretation of Fs remain challenging. In the case of airborne sensors with a medium spectral resolution (<2–4nm), Fs is typically estimated using the Fraunhofer Line Depth (FLD) approach focusing on atmospheric O2 absorption bands. Most critical for accurate Fs retrievals based on such methods is the characterization of atmospheric scattering and absorption processes during data acquisition. So far, detailed experimental evidence on the retrieval accuracy of airborne measured Fs is lacking. We performed an experiment using a low-flying aircraft equipped with a non-imaging spectrometer acquiring medium spectral resolution data during the course of one day, using a repeat-track approach with changing flight altitudes. Fs in the near infrared was retrieved using a semi-empirical approach constraining the FLD based Fs retrieval from the O2-A absorption band at 760nm by using non-fluorescent surfaces. We used a local sensitivity analysis to assess Fs retrieval biases related to observational and atmospheric parameters. Our results demonstrate a reliable Fs retrieval from airborne data using reference surfaces and indicate the need for accurate knowledge of atmospheric scattering and absorption processes. This study contributes to an estimation of the total error budget of Fs retrievals and will serve as a practical guideline for Fs retrieval schemes to be applied to medium resolution airborne spectroscopy data.
•A semi-empirical approach was used to retrieve Fs from airborne spectroscopy data.•Atmospheric effects potentially impacting Fs retrievals could be minimized.•We provide experimental evidence that Fs is retrievable in oxygen absorption lines.•Retrieval errors caused by observational & atmospheric parameters were quantified.•Results contribute to the total uncertainty budget of Fs retrievals.
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