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We present an atlas and follow-up spectroscopic observations of 87 thin stream-like structures detected with the STREAMFINDER algorithm in Gaia DR3, of which 28 are new discoveries. Here, we focus on using these streams to refine mass models of the Galaxy. Fits with a double-power-law halo with the outer power-law slope set to − β _h = −3 yield an inner power-law slope of $-{\gamma }_{h}=-({0.97}_{-0.21}^{+0.17}\,)$ , a scale radius of ${r}_{0,h}={14.7}_{-1.0}^{+4.7}\,\mathrm{kpc}$ , a halo density flattening q _m _, _h = 0.75 ± 0.03, and a local dark matter density of ρ _h _,⊙ = 0.0114 ± 0.0007 M _⊙ pc ^−3 . Freeing β yields $\beta ={2.53}_{-0.16}^{+0.42}$ , but this value is heavily influenced by our chosen virial mass limit. The stellar disks are found to have a combined mass of ${4.20}_{-0.53}^{+0.44}\times {10}^{10}\,{M}_{\odot }$ , with the thick disk contributing 12.4% ± 0.7% to the local stellar surface density. The scale lengths of the thin and thick disks are ${2.17}_{-0.08}^{+0.18}$ and ${1.62}_{-0.13}^{+0.72}\,\mathrm{kpc}$ , respectively, while their scale heights are ${0.347}_{-0.010}^{+0.007}$ and ${0.86}_{-0.02}^{+0.03}\,\mathrm{kpc}$ , respectively. The virial mass of the favored model is ${M}_{200}={1.09}_{-0.14}^{+0.19}\times {10}^{12}\,{M}_{\odot }$ , while the mass inside of 50 kpc is M _R _

One challenge in predicting soil parameters using in situ visible and near infrared spectroscopy is the distortion of the spectra due to soil moisture. External parameter orthogonalization (EPO) is a mathematical method to remove unwanted variability from spectra. We created two different EPO correction matrices based on the difference between spectra collected in situ and, respectively, spectra collected from the same soil samples after drying and sieving and after drying, sieving and finely grinding. Spectra from 134 soil samples recorded with two different spectrometers were split into calibration and validation sets and the two EPO corrections were applied. Clay, organic carbon and total nitrogen content were predicted by partial least squares regression for uncorrected and EPO-corrected spectra using models based on the same type of spectra ("within domain") as well as using laboratory-based models to predict in situ collected spectra ("cross-domain"). Our results show that the within-domain prediction of clay is improved with EPO corrections only for the research grade spectrometer, with no improvement for the other parameters. For the cross-domain predictions, there was a positive effect from both EPO corrections on all parameters. Overall, we also found that in situ collected spectra provided an equally successful prediction as laboratory-based spectra. [ABSTRACT FROM AUTHOR]

The application of visible and near-infrared (vis–NIR) spectroscopy to characterize soil samples has gained growing interest as a fast and cost-effective methodology forsoil fertility assessment.In orderto profit from the full potential of vis–NIR spectroscopy, the acquisition of soil spectra directly in-situ would increase the possibility to obtain data rapidly and at a high spatial and temporal resolution. In the present study, we test and propose the best practice to characterize a set of fertility-related parameters (i.e. texture, organic carbon, pH, cation exchange capacity and major nutrients) of agricultural soils by measuring vis–NIR spectra in the field. To reach this goal, we compare the spectra obtained from different scanning positions with two portable spectrometers, that is, a micro-electromechanical systems (MEMS)-based spectrometer and a research-grade vis–NIR spectrometer. On the basis of 134 soil sampling points, vis–NIR spectra were recorded from: (1) the cutaway side of a soil sample collected with an Edelman auger to a depth of 20 cm, (2) the raw soil surface, as well as (3) the cleaned and smoothed soil surface. Partial least squares regression (PLSR) calibration models were built for the selected soil parameters, scanning positions and different spectral pretreatments for both spectrometers. The model performance was evaluated based on the ratio of performance to interquartile range (RPIQ), the R2 , the root mean squared error (RMSE) and Lin's concordance correlation coefficient (CCC). Overall, the following soil parameters were successfully predicted: clay, sand, pH, organic carbon, cation exchange capacity, total nitrogen and exchangeable magnesium. In contrast, total and exchangeable Ca, K and P, as well as total Mg could not be predicted at a satisfactory level for both the spectrometers. The best scanning position for the successfully calibrated models was along the cutaway sides of the Edelman auger. Although the research-grade spectrometer gave better performance indicators for most of the parameters, the calibrations with the MEMS-based spectrometer still resulted in satisfactory predictions. Based on these findings, the proposed best practice for obtaining in-situ soil vis–NIR scans is to scan along the cutaway sides of a soil core using at least five replicate scans. [ABSTRACT FROM AUTHOR]