173 research outputs found

    Copernicus Cal/Val Solution - D3.3 - Copernicus operational FRM network and supersites

    Get PDF
    - Identify measurement gaps, considering the existing ground-based Cal/Val measurement campaigns and networks (as outcome from Tasks 2.4 and 2.5) - Identify rationalization and optimization pathways: e.g., use of common instrumentation, protocols, and standards across sites; cross-Sentinel use of generic measurements; “supersite” approaches to minimize maintenance costs, as well as possible synergies with other European or international programs - Define a minimum set of requirements for a “Copernicus” label for measurement sites, addressing measurement protocols, documentation, availability, data policy; define a certification process - Principles and need to evaluate degree of equivalence between individual networks and sites (inter-comparisons) and for other comparison measurement

    Evaluation of low-cost Earth observations to scale-up national forest monitoring in Miombo Woodlands of Malawi

    Get PDF
    This study explored the extent that low-cost Earth Observations (EO) data could effectively be combined with in-situ tree-level measurements to support national estimates of Above Ground Biomass (AGB) and Carbon (C) in Malawi’s Miombo Woodlands. The specific objectives were to; (i) investigate the effectiveness of low-cost optical UAV orthomosaics in geo-locating individual trees and estimating AGB and C, (ii) scale-up the AGB estimates using the canopy height model derived from the UAV imagery, and crown diameter measurements; and (iii) compare results from (ii), ALOS-PALSAR-2, Sentinel1, ESA CCI Biomass Map datasets, and Sentinel 2 vis/NIR/SWIR band combination datasets in mapping biomass. Data were acquired in 2019 from 13 plots over Ntchisi Forest in 3-fold, vis-a-vis; (i) individual tree measurements from 0.1ha ground-based (gb) plots, (ii) 3-7cm pixel resolution optical airborne imagery from 50ha plots, and (iii) SAR backscatter and Vis/NIR/SWIR bands imagery. Results demonstrate a strong correlational relationship (R2 = 0.7, RMSE = 11tCha-1) between gb AGB and gb fractional cover percent (FC %), more importantly (R2 = 0.7) between gb AGB and UAV-based FC. Similarly, another set of high correlation (R2 = 0.9, RMSE = 7tCha-1; R2 = 0.8, RMSE = 8tCha-1; and R2 = 0.7) was observed between the gb AGB and EO-based AGB from; (i) ALOS-PALSAR-2, (ii) ESA-CCI-Biomass Map, and (iii) S1-C-band, respectively. Under the measurement conditions, these findings reveal that; (i) FC is more indicative of AGB and C pattern than CHM, (ii) the UAV can collect optical data of very high resolution (3-7cm resolution with ±13m horizontal geolocation error), and (iii) provides the cost-effective means of bridging the ground datasets to the wall-to-wall satellite EO data (ÂŁ7 ha-1 compared to ÂŁ30 ha-1, per person, provided by the gb system). The overall better performance of the SAR backscatter (R2 = 0.7 to 0.9) establishes the suitability of the SAR backscatter to infer the Miombo AGB and fractional cover with high accuracy. However, the following factors compromised the accuracy for both the SAR and optical measurements; leaf-off and seasonality (fire, aridness), topography (steep slopes of 18-74%), and sensing angle. Inversely, the weak to moderate correlation observed between the gb height and UAV FC % measurements (R2 = 0.4 to 0.7) are attributable to the underestimation systematic error that UAV height datasets are associated with. The visual lacunarity analysis on S2-Vis/NIR/SWIR composite band and SAR backscatter measurements demonstrated robust, consistent and homogenous spatial crown patterns exhibited particularly by the leaf-on tree canopies along riverine tree belts and cohorts. These results reveal the potential of vis/NIR/SWIR band combination in determining the effect of fire, rock outcrops and bare land/soil common in these woodlands. Coarsening the EO imagery to ≄50m pixel resolution compromised the accuracy of the estimations, hence <50m resolution is the ideal scale for these Miombo. Careful consideration of the aforementioned factors and incorporation of FC parameter in during estimation of AGB and C will go a long way in not only enhancing the accuracy of the measurements, but also in bolstering Malawi’s NFMS standards to yield carbon off-set payments under the global REDD+ mechanism

    Exploring bistatic scattering modeling for land surface applications using radio spectrum recycling in the Signal of Opportunity Coherent Bistatic Simulator

    Get PDF
    The potential for high spatio-temporal resolution microwave measurements has urged the adoption of the signals of opportunity (SoOp) passive radar technique for use in remote sensing. Recent trends in particular target highly complex remote sensing problems such as root-zone soil moisture and snow water equivalent. This dissertation explores the continued open-sourcing of the SoOp coherent bistatic scattering model (SCoBi) and its use in soil moisture sensing applications. Starting from ground-based applications, the feasibility of root-zone soil moisture remote sensing is assessed using available SoOp resources below L-band. A modularized, spaceborne model is then developed to simulate land-surface scattering and delay-Doppler maps over the available spectrum of SoOp resources. The simulation tools are intended to provide insights for future spaceborne modeling pursuits

    ALOS-2/PALSAR-2 Calibration, Validation, Science and Applications

    Get PDF
    Twelve edited original papers on the latest and state-of-art results of topics ranging from calibration, validation, and science to a wide range of applications using ALOS-2/PALSAR-2. We hope you will find them useful for your future research

    Development of high-precision snow mapping tools for Arctic environments

    Get PDF
    Le manteau neigeux varie grandement dans le temps et l’espace, il faut donc de nombreux points d’observation pour le dĂ©crire prĂ©cisĂ©ment et ponctuellement, ce qui permet de valider et d’amĂ©liorer la modĂ©lisation de la neige et les applications en tĂ©lĂ©dĂ©tection. L’analyse traditionnelle par des coupes de neige dĂ©voile des dĂ©tails pointus sur l’état de la neige Ă  un endroit et un moment prĂ©cis, mais est une mĂ©thode chronophage Ă  laquelle la distribution dans le temps et l’espace font dĂ©faut. À l’opposĂ© sur la fourchette de la prĂ©cision, on retrouve les solutions orbitales qui couvrent la surface de la Terre Ă  intervalles rĂ©guliers, mais Ă  plus faible rĂ©solution. Dans l’optique de recueillir efficacement des donnĂ©es spatiales sur la neige durant les campagnes de terrain, nous avons dĂ©veloppĂ© sur mesure un systĂšme d’aĂ©ronef tĂ©lĂ©pilotĂ© (RPAS) qui fournit des cartes d’épaisseur de neige pour quelques centaines de mĂštres carrĂ©s, selon la mĂ©thode Structure from motion (SfM). Notre RPAS peut voler dans des tempĂ©ratures extrĂȘmement froides, au contraire des autres systĂšmes sur le marchĂ©. Il atteint une rĂ©solution horizontale de 6 cm et un Ă©cart-type d’épaisseur de neige de 39 % sans vĂ©gĂ©tation (48,5 % avec vĂ©gĂ©tation). Comme la mĂ©thode SfM ne permet pas de distinguer les diffĂ©rentes couches de neige, j’ai dĂ©veloppĂ© un algorithme pour un radar Ă  onde continue Ă  modulation de frĂ©quence (FM-CW) qui permet de distinguer les deux couches principales de neige que l’on retrouve rĂ©guliĂšrement en Arctique : le givre de profondeur et la plaque Ă  vent. Les distinguer est crucial puisque les caractĂ©ristiques diffĂ©rentes des couches de neige font varier la quantitĂ© d’eau disponible pour l’écosystĂšme lors de la fonte. Selon les conditions sur place, le radar arrive Ă  estimer l’épaisseur de neige selon un Ă©cart-type entre 13 et 39 %. vii Finalement, j’ai Ă©quipĂ© le radar d’un systĂšme de gĂ©olocalisation Ă  haute prĂ©cision. Ainsi Ă©quipĂ©, le radar a une marge d’erreur de gĂ©olocalisation d’en moyenne <5 cm. À partir de la mesure radar, on peut dĂ©duire la distance entre le haut et le bas du manteau neigeux. En plus de l’épaisseur de neige, on obtient Ă©galement des points de donnĂ©es qui permettent d’interpoler un modĂšle d’élĂ©vation de la surface solide sous-jacente. J’ai utilisĂ© la mĂ©thode de structure triangulaire (TIN) pour toutes les interpolations. Le systĂšme offre beaucoup de flexibilitĂ© puisqu’il peut ĂȘtre installĂ© sur un RPAS ou une motoneige. Ces outils Ă©paulent la modĂ©lisation du couvert neigeux en fournissant des donnĂ©es sur un secteur, plutĂŽt que sur un seul point. Les donnĂ©es peuvent servir Ă  entraĂźner et Ă  valider les modĂšles. Ainsi amĂ©liorĂ©s, ils peuvent, par exemple, permettre de prĂ©dire la taille, le niveau de santĂ© et les dĂ©placements de populations d’ongulĂ©s, dont la survie dĂ©pend de la qualitĂ© de la neige. (Langlois et coll., 2017.) Au mĂȘme titre que la validation de modĂšles de neige, les outils prĂ©sentĂ©s permettent de comparer et de valider d’autres donnĂ©es de tĂ©lĂ©dĂ©tection (par ex. satellites) et d’élargir notre champ de comprĂ©hension. Finalement, les cartes ainsi crĂ©Ă©es peuvent aider les Ă©cologistes Ă  Ă©valuer l’état d’un Ă©cosystĂšme en leur donnant accĂšs Ă  une plus grande quantitĂ© d’information sur le manteau neigeux qu’avec les coupes de neige traditionnelles.Abstract: Snow is highly variable in time and space and thus many observation points are needed to describe the present state of the snowpack accurately. This description of the state of the snowpack is necessary to validate and improve snow modeling efforts and remote sensing applications. The traditional snowpit analysis delivers a highly detailed picture of the present state of the snow in a particular location but lacks the distribution in space and time as it is a time-consuming method. On the opposite end of the spatial scale are orbital solutions covering the surface of the Earth in regular intervals, but at the cost of a much lower resolution. To improve the ability to collect spatial snow data efficiently during a field campaign, we developed a custom-made, remotely piloted aircraft system (RPAS) to deliver snow depth maps over a few hundred square meters by using Structure-from-Motion (SfM). The RPAS is capable of flying in extremely low temperatures where no commercial solutions are available. The system achieves a horizontal resolution of 6 cm with snow depth RMSE of 39% without vegetation (48.5% with vegetation) As the SfM method does not distinguish between different snow layers, I developed an algorithm for a frequency modulated continuous wave (FMCW) radar that distinguishes between the two main snow layers that are found regularly in the Arctic: “Depth Hoar” and “Wind Slab”. The distinction is important as these characteristics allow to determine the amount of water stored in the snow that will be available for the ecosystem during the melt season. Depending on site conditions, the radar estimates the snow depth with an RMSE between 13% and 39%. v Finally, I equipped the radar with a high precision geolocation system. With this setup, the geolocation uncertainty of the radar on average < 5 cm. From the radar measurement, the distance to the top and the bottom of the snowpack can be extracted. In addition to snow depth, it also delivers data points to interpolate an elevation model of the underlying solid surface. I used the Triangular Irregular Network (TIN) method for any interpolation. The system can be mounted on RPAS and snowmobiles and thus delivers a lot of flexibility. These tools will assist snow modeling as they provide data from an area instead of a single point. The data can be used to force or validate the models. Improved models will help to predict the size, health, and movements of ungulate populations, as their survival depends on it (Langlois et al., 2017). Similar to the validation of snow models, the presented tools allow a comparison and validation of other remote sensing data (e.g. satellite) and improve the understanding limitations. Finally, the resulting maps can be used by ecologist to better asses the state of the ecosystem as they have a more complete picture of the snow cover on a larger scale that it could be achieved with traditional snowpits

    Examining Ecosystem Drought Responses Using Remote Sensing and Flux Tower Observations

    Get PDF
    Indiana University-Purdue University Indianapolis (IUPUI)Water is fundamental for plant growth, and vegetation response to water availability influences water, carbon, and energy exchanges between land and atmosphere. Vegetation plays the most active role in water and carbon cycle of various ecosystems. Therefore, comprehensive evaluation of drought impact on vegetation productivity will play a critical role for better understanding the global water cycle under future climate conditions. In-situ meteorological measurements and the eddy covariance flux tower network, which provide meteorological data, and estimates of ecosystem productivity and respiration are remarkable tools to assess the impacts of drought on ecosystem carbon and water cycles. In regions with limited in-situ observations, remote sensing can be a very useful tool to monitor ecosystem drought status since it provides continuous observations of relevant variables linked to ecosystem function and the hydrologic cycle. However, the detailed understanding of ecosystem responses to drought is still lacking and it is challenging to quantify the impacts of drought on ecosystem carbon balance and several factors hinder our explicit understanding of the complex drought impacts. This dissertation addressed drought monitoring, ecosystem drought responses, trends of vegetation water constraint based on in-situ metrological observations, flux tower and multi-sensor remote sensing observations. This dissertation first developed a new integrated drought index applicable across diverse climate regions based on in-situ meteorological observations and multi-sensor remote sensing data, and another integrated drought index applicable across diverse climate regions only based on multi-sensor remote sensing data. The dissertation also evaluated the applicability of new satellite dataset (e.g., solar induced fluorescence, SIF) for responding to meteorological drought. Results show that satellite SIF data could have the potential to reflect meteorological drought, but the application should be limited to dry regions. The work in this dissertation also accessed changes in water constraint on global vegetation productivity, and quantified different drought dimensions on ecosystem productivity and respiration. Results indicate that a significant increase in vegetation water constraint over the last 30 years. The results highlighted the need for a more explicit consideration of the influence of water constraints on regional and global vegetation under a warming climate

    Remote Sensing of Savannas and Woodlands

    Get PDF
    Savannas and woodlands are one of the most challenging targets for remote sensing. This book provides a current snapshot of the geographical focus and application of the latest sensors and sensor combinations in savannas and woodlands. It includes feature articles on terrestrial laser scanning and on the application of remote sensing to characterization of vegetation dynamics in the Mato Grosso, Cerrado and Caatinga of Brazil. It also contains studies focussed on savannas in Europe, North America, Africa and Australia. It should be important reading for environmental practitioners and scientists globally who are concerned with the sustainability of the global savanna and woodland biome

    The data concept behind the data: From metadata models and labelling schemes towards a generic spectral library

    Get PDF
    Spectral libraries play a major role in imaging spectroscopy. They are commonly used to store end-member and spectrally pure material spectra, which are primarily used for mapping or unmixing purposes. However, the development of spectral libraries is time consuming and usually sensor and site dependent. Spectral libraries are therefore often developed, used and tailored only for a specific case study and only for one sensor. Multi-sensor and multi-site use of spectral libraries is difficult and requires technical effort for adaptation, transformation, and data harmonization steps. Especially the huge amount of urban material specifications and its spectral variations hamper the setup of a complete spectral library consisting of all available urban material spectra. By a combined use of different urban spectral libraries, besides the improvement of spectral inter- and intra-class variability, missing material spectra could be considered with respect to a multi-sensor/ -site use. Publicly available spectral libraries mostly lack the metadata information that is essential for describing spectra acquisition and sampling background, and can serve to some extent as a measure of quality and reliability of the spectra and the entire library itself. In the GenLib project, a concept for a generic, multi-site and multi-sensor usable spectral library for image spectra on the urban focus was developed. This presentation will introduce a 1) unified, easy-to-understand hierarchical labeling scheme combined with 2) a comprehensive metadata concept that is 3) implemented in the SPECCHIO spectral information system to promote the setup and usability of a generic urban spectral library (GUSL). The labelling scheme was developed to ensure the translation of individual spectral libraries with their own labelling schemes and their usually varying level of details into the GUSL framework. It is based on a modified version of the EAGLE classification concept by combining land use, land cover, land characteristics and spectral characteristics. The metadata concept consists of 59 mandatory and optional attributes that are intended to specify the spatial context, spectral library information, references, accessibility, calibration, preprocessing steps, and spectra specific information describing library spectra implemented in the GUSL. It was developed on the basis of existing metadata concepts and was subject of an expert survey. The metadata concept and the labelling scheme are implemented in the spectral information system SPECCHIO, which is used for sharing and holding GUSL spectra. It allows easy implementation of spectra as well as their specification with the proposed metadata information to extend the GUSL. Therefore, the proposed data model represents a first fundamental step towards a generic usable and continuously expandable spectral library for urban areas. The metadata concept and the labelling scheme also build the basis for the necessary adaptation and transformation steps of the GUSL in order to use it entirely or in excerpts for further multi-site and multi-sensor applications

    Remote Sensing of the Aquatic Environments

    Get PDF
    The book highlights recent research efforts in the monitoring of aquatic districts with remote sensing observations and proximal sensing technology integrated with laboratory measurements. Optical satellite imagery gathered at spatial resolutions down to few meters has been used for quantitative estimations of harmful algal bloom extent and Chl-a mapping, as well as winds and currents from SAR acquisitions. The knowledge and understanding gained from this book can be used for the sustainable management of bodies of water across our planet
    • 

    corecore