scholarly journals Agro-hydrology and multi-temporal high-resolution remote sensing: toward an explicit spatial processes calibration

2014 ◽  
Vol 18 (12) ◽  
pp. 5219-5237 ◽  
Author(s):  
S. Ferrant ◽  
S. Gascoin ◽  
A. Veloso ◽  
J. Salmon-Monviola ◽  
M. Claverie ◽  
...  
Keyword(s):  
High Resolution ◽  
Hydrological Model ◽  
A Priori ◽  
Agricultural Practices ◽  
Crop Growth ◽  
Data Set ◽  
Area Index ◽  
Field Level ◽  
Seeding Date ◽  
Crop Field

Abstract. The growing availability of high-resolution satellite image series offers new opportunities in agro-hydrological research and modeling. We investigated the possibilities offered for improving crop-growth dynamic simulation with the distributed agro-hydrological model: topography-based nitrogen transfer and transformation (TNT2). We used a leaf area index (LAI) map series derived from 105 Formosat-2 (F2) images covering the period 2006–2010. The TNT2 model (Beaujouan et al., 2002), calibrated against discharge and in-stream nitrate fluxes for the period 1985–2001, was tested on the 2005–2010 data set (climate, land use, agricultural practices, and discharge and nitrate fluxes at the outlet). Data from the first year (2005) were used to initialize the hydrological model. A priori agricultural practices obtained from an extensive field survey, such as seeding date, crop cultivar, and amount of fertilizer, were used as input variables. Continuous values of LAI as a function of cumulative daily temperature were obtained at the crop-field level by fitting a double logistic equation against discrete satellite-derived LAI. Model predictions of LAI dynamics using the a priori input parameters displayed temporal shifts from those observed LAI profiles that are irregularly distributed in space (between field crops) and time (between years). By resetting the seeding date at the crop-field level, we have developed an optimization method designed to efficiently minimize this temporal shift and better fit the crop growth against both the spatial observations and crop production. This optimization of simulated LAI has a negligible impact on water budgets at the catchment scale (1 mm yr−1 on average) but a noticeable impact on in-stream nitrogen fluxes (around 12%), which is of interest when considering nitrate stream contamination issues and the objectives of TNT2 modeling. This study demonstrates the potential contribution of the forthcoming high spatial and temporal resolution products from the Sentinel-2 satellite mission for improving agro-hydrological modeling by constraining the spatial representation of crop productivity.

scholarly journals Agro-hydrology and multi temporal high resolution remote sensing: toward an explicit spatial processes calibration

2014 ◽  
Vol 11 (7) ◽  
pp. 7689-7732 ◽  
Author(s):  
S. Ferrant ◽  
S. Gascoin ◽  
A. Veloso ◽  
J. Salmon-Monviola ◽  
M. Claverie ◽  
...  
Keyword(s):  
High Resolution ◽  
Hydrological Modeling ◽  
A Priori ◽  
Agricultural Practices ◽  
Crop Growth ◽  
Nitrogen Transfer ◽  
Temporal Shift ◽  
Field Level ◽  
Seeding Date ◽  
Crop Field

Abstract. The recent and forthcoming availability of high resolution satellite image series offers new opportunities in agro-hydrological research and modeling. We investigated the perspective offered by improving the crop growth dynamic simulation using the distributed agro-hydrological model, Topography based Nitrogen transfer and Transformation (TNT2), using LAI map series derived from 105 Formosat-2 (F2) images during the period 2006–2010. The TNT2 model (Beaujouan et al., 2002), calibrated with discharge and in-stream nitrate fluxes for the period 1985-2001, was tested on the 2006–2010 dataset (climate, land use, agricultural practices, discharge and nitrate fluxes at the outlet). A priori agricultural practices obtained from an extensive field survey such as seeding date, crop cultivar, and fertilizer amount were used as input variables. Continuous values of LAI as a function of cumulative daily temperature were obtained at the crop field level by fitting a double logistic equation against discrete satellite-derived LAI. Model predictions of LAI dynamics with a priori input parameters showed an temporal shift with observed LAI profiles irregularly distributed in space (between field crops) and time (between years). By re-setting seeding date at the crop field level, we proposed an optimization method to minimize efficiently this temporal shift and better fit the crop growth against the spatial observations as well as crop production. This optimization of simulated LAI has a negligible impact on water budget at the catchment scale (1 mm yr−1 in average) but a noticeable impact on in-stream nitrogen fluxes (around 12%) which is of interest considering nitrate stream contamination issues and TNT2 model objectives. This study demonstrates the contribution of forthcoming high spatial and temporal resolution products of Sentinel-2 satellite mission in improving agro-hydrological modeling by constraining the spatial representation of crop productivity.

scholarly journals Improved large-scale hydrological modelling through the assimilation of streamflow and downscaled satellite soil moisture observations

2016 ◽  
Vol 20 (7) ◽  
pp. 3059-3076 ◽  
Author(s):  
Patricia López López ◽  
Niko Wanders ◽  
Jaap Schellekens ◽  
Luigi J. Renzullo ◽  
Edwin H. Sutanudjaja ◽  
...  
Keyword(s):  
Soil Moisture ◽  
High Resolution ◽  
Data Assimilation ◽  
Spatial Resolution ◽  
Hydrological Model ◽  
Meteorological Data ◽  
Observation System ◽  
Data Set ◽  
Coarse Resolution ◽  
The Impact

Abstract. The coarse spatial resolution of global hydrological models (typically  >  0.25°) limits their ability to resolve key water balance processes for many river basins and thus compromises their suitability for water resources management, especially when compared to locally tuned river models. A possible solution to the problem may be to drive the coarse-resolution models with locally available high-spatial-resolution meteorological data as well as to assimilate ground-based and remotely sensed observations of key water cycle variables. While this would improve the resolution of the global model, the impact of prediction accuracy remains largely an open question. In this study, we investigate the impact of assimilating streamflow and satellite soil moisture observations on the accuracy of global hydrological model estimations, when driven by either coarse- or high-resolution meteorological observations in the Murrumbidgee River basin in Australia. To this end, a 0.08° resolution version of the PCR-GLOBWB global hydrological model is forced with downscaled global meteorological data (downscaled from 0.5° to 0.08° resolution) obtained from the WATCH Forcing Data methodology applied to ERA-Interim (WFDEI) and a local high-resolution, gauging-station-based gridded data set (0.05°). Downscaled satellite-derived soil moisture (downscaled from  ∼  0.5° to 0.08° resolution) from the remote observation system AMSR-E and streamflow observations collected from 23 gauging stations are assimilated using an ensemble Kalman filter. Several scenarios are analysed to explore the added value of data assimilation considering both local and global meteorological data. Results show that the assimilation of soil moisture observations results in the largest improvement of the model estimates of streamflow. The joint assimilation of both streamflow and downscaled soil moisture observations leads to further improvement in streamflow simulations (20 % reduction in RMSE). Furthermore, results show that the added contribution of data assimilation, for both soil moisture and streamflow, is more pronounced when the global meteorological data are used to force the models. This is caused by the higher uncertainty and coarser resolution of the global forcing. We conclude that it is possible to improve PCR-GLOBWB simulations forced by coarse-resolution meteorological data with assimilation of downscaled spaceborne soil moisture and streamflow observations. These improved model results are close to the ones from a local model forced with local meteorological data. These findings are important in light of the efforts that are currently made to move to global hyper-resolution modelling and can help to advance this research.

High-resolution wave-equation amplitude-variation-with-ray-parameter (AVP) imaging with sparseness constraints

Geophysics ◽  
2007 ◽  
Vol 72 (1) ◽  
pp. S11-S18 ◽  
Author(s):  
Juefu Wang ◽  
Mauricio D. Sacchi
Keyword(s):  
High Resolution ◽  
Cost Function ◽  
A Priori ◽  
Synthetic Data ◽  
Real Data ◽  
Gradient Algorithm ◽  
Amplitude Variation ◽  
Data Set ◽  
Priori Information ◽  
Ray Parameter

We propose a new scheme for high-resolution amplitude-variation-with-ray-parameter (AVP) imaging that uses nonquadratic regularization. We pose migration as an inverse problem and propose a cost function that uses a priori information about common-image gathers (CIGs). In particular, we introduce two regularization constraints: smoothness along the offset-ray-parameter axis and sparseness in depth. The two-step regularization yields high-resolution CIGs with robust estimates of AVP. We use an iterative reweighted least-squares conjugate gradient algorithm to minimize the cost function of the problem. We test the algorithm with synthetic data (a wedge model and the Marmousi data set) and a real data set (Erskine area, Alberta). Tests show our method helps to enhance the vertical resolution of CIGs and improves amplitude accuracy along the ray-parameter direction.

Algorithms for automated montage synthesis of images from laser-scanning confocal microscopes

1995 ◽  
Vol 53 ◽  
pp. 650-651
Author(s):  
D. E. Becker
Keyword(s):  
Image Analysis ◽  
High Resolution ◽  
Laser Scanning ◽  
Cell Counting ◽  
Wide Area ◽  
Data Set ◽  
Computational Synthesis ◽  
Automated Cell Counting ◽  
Partial View ◽  
The Individual

An efficient, robust, and widely-applicable technique is presented for computational synthesis of high-resolution, wide-area images of a specimen from a series of overlapping partial views. This technique can also be used to combine the results of various forms of image analysis, such as segmentation, automated cell counting, deblurring, and neuron tracing, to generate representations that are equivalent to processing the large wide-area image, rather than the individual partial views. This can be a first step towards quantitation of the higher-level tissue architecture. The computational approach overcomes mechanical limitations, such as hysterisis and backlash, of microscope stages. It also automates a procedure that is currently done manually. One application is the high-resolution visualization and/or quantitation of large batches of specimens that are much wider than the field of view of the microscope.The automated montage synthesis begins by computing a concise set of landmark points for each partial view. The type of landmarks used can vary greatly depending on the images of interest. In many cases, image analysis performed on each data set can provide useful landmarks. Even when no such “natural” landmarks are available, image processing can often provide useful landmarks.

Towards 1-Ångstrom-resolution STEM

1993 ◽  
Vol 51 ◽  
pp. 996-997
Author(s):  
H.S. von Harrach ◽  
D.E. Jesson ◽  
S.J. Pennycook
Keyword(s):  
High Resolution ◽  
Field Emission ◽  
Phase Contrast ◽  
Spherical Aberration ◽  
A Priori ◽  
Dark Field ◽  
Image Resolution ◽  
Objective Lens ◽  
Annular Dark Field ◽  
First Results

Phase contrast TEM has been the leading technique for high resolution imaging of materials for many years, whilst STEM has been the principal method for high-resolution microanalysis. However, it was demonstrated many years ago that low angle dark-field STEM imaging is a priori capable of almost 50% higher point resolution than coherent bright-field imaging (i.e. phase contrast TEM or STEM). This advantage was not exploited until Pennycook developed the high-angle annular dark-field (ADF) technique which can provide an incoherent image showing both high image resolution and atomic number contrast.This paper describes the design and first results of a 300kV field-emission STEM (VG Microscopes HB603U) which has improved ADF STEM image resolution towards the 1 angstrom target. The instrument uses a cold field-emission gun, generating a 300 kV beam of up to 1 μA from an 11-stage accelerator. The beam is focussed on to the specimen by two condensers and a condenser-objective lens with a spherical aberration coefficient of 1.0 mm.

scholarly journals Simulating the Response of Drought–Tolerant Maize Varieties to Nitrogen Application in Contrasting Environments in the Nigeria Savannas Using the APSIM Model

Agronomy ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 76
Author(s):  
Aloysius Beah ◽  
Alpha Y. Kamara ◽  
Jibrin M. Jibrin ◽  
Folorunso M. Akinseye ◽  
Abdullahi I. Tofa ◽  
...  
Keyword(s):  
Grain Yield ◽  
Field Experiments ◽  
Production Systems ◽  
Agricultural Practices ◽  
Net Income ◽  
Nitrogen Application ◽  
N Application ◽  
Area Index ◽  
Support Tool ◽  
Maize Varieties

This paper assessed the application of the Agricultural Production Systems sIMulator (APSIM)–maize module as a decision support tool for optimizing nitrogen application to determine yield and net return of maize production under current agricultural practices in the Nigeria savannas. The model was calibrated for two maize varieties using data from field experiments conducted under optimum conditions in three locations during the 2017 and 2018 cropping seasons. The model was evaluated using an independent dataset from an experiment conducted under different nitrogen (N) levels in two locations within Southern and Northern Guinea savannas. The results show that model accurately predicted days to 50% anthesis and physiological maturity, leaf area index (LAI), grain yield and total dry matter (TDM) of both varieties with low RMSE and RMSEn (%) values within the range of acceptable statistics indices. Based on 31-year seasonal simulation, optimum mean grain yield of 3941 kg ha−1 for Abuja, and 4549 for Kano was simulated at N rate of 120 kg ha–1 for the early maturing variety 2009EVDT. Meanwhile in Zaria, optimum mean yield of 4173 kg ha–1 was simulated at N rate of 90 kg ha−1. For the intermediate maturing variety, IWDC2SYNF2 mean optimum yields of 5152, 5462, and 4849 kg ha−1, were simulated at N application of 120 kg ha−1 for all the locations. The probability of exceeding attainable mean grain yield of 3000 and 4000 kg ha−1 for 2009EVDT and IWDC2SYNF2, respectively would be expected in 95% of the years with application of 90 kg N ha−1 across the three sites. Following the profitability scenarios analysis, the realistic net incomes of US$ 536 ha–1 for Abuja, and US$ 657 ha−1 for Zaria were estimated at N rate of 90 kg ha−1 and at Kano site, realistic net income of US$ 720 ha–1was estimated at N rate of 120 kg ha−1 for 2009EVDT.For IWDC2SYNF2, realistic net incomes of US$ 870, 974, and 818 ha−1 were estimated at N application of 120 kg ha−1 for Abuja, Zaria, and Kano respectively. The result of this study suggests that 90 kg N ha−1 can be recommended for 2009EVDT and 120 kg N ha–1 for IWDC2SYNF2 in Abuja and Zaria while in Kano, 120 kg N ha−1 should be applied to both varieties to attain optimum yield and profit.

scholarly journals A Traveler’s Guide to the Multiverse: Promises, Pitfalls, and a Framework for the Evaluation of Analytic Decisions

2021 ◽  
Vol 4 (1) ◽  
pp. 251524592095492
Author(s):  
Marco Del Giudice ◽  
Steven W. Gangestad
Keyword(s):  
Degrees Of Freedom ◽  
A Priori ◽  
Simulated Data ◽  
Style Analysis ◽  
Data Set ◽  
Scant Attention ◽  
Equivalence Type ◽  
The Impact ◽  
Biased Estimates

Decisions made by researchers while analyzing data (e.g., how to measure variables, how to handle outliers) are sometimes arbitrary, without an objective justification for choosing one alternative over another. Multiverse-style methods (e.g., specification curve, vibration of effects) estimate an effect across an entire set of possible specifications to expose the impact of hidden degrees of freedom and/or obtain robust, less biased estimates of the effect of interest. However, if specifications are not truly arbitrary, multiverse-style analyses can produce misleading results, potentially hiding meaningful effects within a mass of poorly justified alternatives. So far, a key question has received scant attention: How does one decide whether alternatives are arbitrary? We offer a framework and conceptual tools for doing so. We discuss three kinds of a priori nonequivalence among alternatives—measurement nonequivalence, effect nonequivalence, and power/precision nonequivalence. The criteria we review lead to three decision scenarios: Type E decisions (principled equivalence), Type N decisions (principled nonequivalence), and Type U decisions (uncertainty). In uncertain scenarios, multiverse-style analysis should be conducted in a deliberately exploratory fashion. The framework is discussed with reference to published examples and illustrated with the help of a simulated data set. Our framework will help researchers reap the benefits of multiverse-style methods while avoiding their pitfalls.

scholarly journals How Can We Represent Seasonal Land Use Dynamics in SWAT and SWAT+ Models for African Cultivated Catchments?

Water ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1541
Author(s):  
Albert Nkwasa ◽  
Celray James Chawanda ◽  
Anna Msigwa ◽  
Hans C. Komakech ◽  
Boud Verbeiren ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Agricultural Land ◽  
Swat Model ◽  
Agricultural Practices ◽  
Area Index ◽  
Land Use Dynamics ◽  
Cropping Seasons ◽  
Decision Tables ◽  
Land Cover Maps

In SWAT and SWAT+ models, the variations in hydrological processes are represented by Hydrological Response Units (HRUs). In the default models, agricultural land cover is represented by a single growing cycle. However, agricultural land use, especially in African cultivated catchments, typically consists of several cropping seasons, following dry and wet seasonal patterns, and are hence incorrectly represented in SWAT and SWAT+ default models. In this paper, we propose a procedure to incorporate agricultural seasonal land-use dynamics by (1) mapping land-use trajectories instead of static land-cover maps and (2) linking these trajectories to agricultural management settings. This approach was tested in SWAT and SWAT+ models of Usa catchment in Tanzania that is intensively cultivated by implementing dominant dynamic trajectories. Our results were evaluated with remote-sensing observations for Leaf Area Index (LAI), which showed that a single growing cycle did not well represent vegetation dynamics. A better agreement was obtained after implementing seasonal land-use dynamics for cultivated HRUs. It was concluded that the representation of seasonal land-use dynamics through trajectory implementation can lead to improved temporal patterns of LAI in default models. The SWAT+ model had higher flexibility in representing agricultural practices, using decision tables, and by being able to represent mixed cropping cultivations.

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