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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Vegetation structural complexity and biodiversity in the Great Smoky Mountains

Vegetation structural complexity and biodiversity tend to be positively correlated, but understanding of this relationship is limited in part by structural metrics tending to quantify only horizontal or vertical variation, and that do not reflect internal structure. We developed new metrics for quantifying internal vegetation structural complexity using terrestrial LiDAR scanning and applied them to 12 NEON forest plots across an elevational gradient in Great Smoky Mountains National Park, USA. We asked (1) How do our newly developed structure metrics compare to traditional metrics? (2) How does forest structure vary with elevation in a high-biodiversity, high topographic complexity region? (3) How do forest structural metrics vary in the strength of their relationships with vascular plant biodiversity? Our new measures of canopy density (Depth) and structural complexity (σDepth), and their canopy height-normalized counterparts, were sensitive to structural variations and effectively summarized horizontal and vertical dimensions of structural complexity. Forest structure varied widely across plots spanning the elevational range of GRSM, with taller, more structurally complex forests at lower elevation. Vascular plant biodiversity was negatively correlated with elevation and more strongly positively correlated with vegetation structure variables. The strong correlations we observed between canopy structural complexity and biodiversity suggest that structural complexity metrics could be used to assay plant biodiversity over large areas in concert with airborne and spaceborne platforms.

Jonathan A. Walter↗
NASA NTRS2012

How Did I Get Here?

What country was responsible for much of the early work in laser altimetry, who was the first scientist to look at a vegetation profile generated by a laser, who first related laser ranges to forest structure? The purpose of this paper is to look back 3+ decades ago when forestry lidar was in its formative years and to give credit to those who first thought to employ a laser to measure the Earth's surface. As with much scientific research, advances were often made independently and concurrently in a number of countries. Functioning lasers were first demonstrated in 1960 in the USA and in 1961 in the USSR, but research into the use of lasers as forest measurement tools did not begin for another IS years. Initially, with respect to Earth resources, lasers were employed to measure sea ice surface roughness, to make near-shore bathymetric measurements, to penetrate forests to make detailed topographic measurements, and to fluoresce oceanic phytoplankton for surface current studies. Some of these early studies noted that forest profiles were evident but in fact added noise to topographic retrievals. Trees became the signal rather than noise in 1976 when researchers in the Canadian Forest Service went to an IUFRO conference in Oslo and reported on efforts to better estimate timber volume in tropical forests. They employed large-scale airphotos (1:500 up to 1:4000) to measure the top of the tropical canopy, an avionic radar to measure the location of the ground beneath the canopy, and a barometric sensor to record aircraft/radar height above a datum (e.g., sea level). Their radar did not work well in dense vegetation and mentioned in passing that a laser altimeter had worked well in Canadian forests. But in a report 2 years later they reported that, on a study area in Costa Rica, the radar ground line was much improved and no mention is made of a lidar altimeter. In the USSR in 1977, Russian researchers felled a birch and a spruce, aimed a helium-neon, 0.63 micron laser with a spot size of approx 25mm, at the horizontal trees, produced a profilograph, compared it to tape measurements, and concluded that, with increased power, such a laser could be mounted on an aircraft to remotely measure forest canopies. In 1979, they mounted their He-Ne laser on an AN-2 biplane and acquired their fIrSt airborne profiles. Scientists with TRANARG, a mapping/surveying company in Caracas, Venezuela, reported on 1976 flights employing a helium-neon lidar to collect over 11,000 km of lidar profiles spaced 1.5 km apart in order to construct a topographic map to help site a new reservoir. They noted 35-40 m median canopy heights with emergents up to 55 m in their profiles. These studies and others that utilize these height and canopy density metrics for forest mensuration are reviewed in this glance backwards at the history of forestry lidar.

Nelson, Ross↗
NASA NTRSDate not supplied

Assessing Alaskan boreal forest landcover affected by climate-wildfire interactions from ground truth surveys and NASA airborne remote sensing

Alaska’s boreal forest is facing unprecedented challenges under rapid climate warming (increasingly severe fires, droughts, pest/disease outbreaks) that may destabilize its function as a global carbon sink. Forests near Fairbanks may be especially vulnerable, impacting air quality and ecosystem services. We combined GT (ground truthing) with Airborne Visible InfraRed Imaging Spectrometer (AVIRIS-NG) images collected by the NASA Arctic-Boreal Vulnerability Experiment (ABoVE) program (2017-2019) to assess landcover change at five recently burned sites (2001-2019) of different fire severities and moisture regimes within 30 miles of Fairbanks. GT included tree seedling counts, understory % cover and >50% leaf canopy color assessment. 36 circular plots (1/30 ha radius) including 6 moderate to severely burned plots were selected across sites. 31 additional sites including 12 burned sites were geotagged in photos. AVIRIS images were processed from 29 spectral bands selected to identify changes in chlorophyll and water content. Images were segmented into natural boundaries (polygons) using ENVI 5.5 software. A spectral library of 8 AVIRIS bands with high between-class/low within-class variation was used in two random forest models to predict vegetation classes (model 1: 12 classes, model 2: 14 classes) in each AVIRIS scene, using 20% of the data as training data. Model 2 classified 20% more polygons overall, but only 42% of GT/geotagged polygons were correctly classified by both models. More forest sites were correctly classified (63%) than open vegetation (32%) or post-fire sites (46%). 50% of aspen forest and post-fire polygons were misclassified as shrubland. GT revealed that post-fire plots supported 134,000 (± 48,000) tree seedlings and saplings ha-1 (0.2 - 4 m height, 64% deciduous) versus 2500 (± 2100) shrubs ha-1 (1-6 m height). > 50% canopy browning was observed in conifer forest (8 plots) with no signs of insect infestation. Canopy herbivory > 50% (leaf miner, leaf beetle) and moose herbivory of tree bark was seen across aspen sites. Our study suggests: 1) low canopy vegetation presents challenges for improved landcover classification, and 2) aspen forest should be differentiated in vegetation maps which would aid in tracking herbivory.

Alaska↗
DOE OSTI2024

NGEE Arctic 2019 Alder Ground Truth Survey, Seward Peninsula AK

In July 2019 we made traveled the road system outside of Nome, AK and detailed the GPS coordinates of alder shrublands for the purpose of ground-truthing alder maps of the region. Both visual and ground-based observations were made for patches of alder shrublands greater 5x5m and larger, ideally 10x10m. Visual observations were made from the car and GPS coordinates are approximate, placed by dropping pins on georeferenced pdfs using the Avenza app. Visual observations included positive identified alder shrublands as well as thickets of non-alder shrubs. Ground Observations were made at a subset of locations where we were able to hike to alders shrubland areas. Ground observations include GPS points (made with Garmin InReach) as well as relevant features of a centrally located, representative alder shrub in the patch (max height, basal diameter of all ramets, soil depth). Aboveground biomass (weight dry mass) of the surveyed shrub was calculated based on alder-specific allometric equations in Berner et al 2015 which our team checked for accuracy for the Seward Peninsula as part of Salmon et al 2019. This dataset contains three data files, three data dictionaries, and one file-level metadata file all in*.csv format plus one *.txt README file. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1999

Lidar Altimeter Measurements of Canopy Structure: Methods and Validation for Closed Canopy, Broadleaf Forests

Lidar altimeter observations of vegetated landscapes provide a time-resolved measure of laser pulse backscatter energy from canopy surfaces and the underlying ground. Airborne lidar altimeter data was acquired using the Scanning Lidar Imager of Canopies by Echo Recovery (SLICER) for a successional sequence of four, closed-canopy, deciduous forest stands in eastern Maryland. The four stands were selected so as to include a range of canopy structures of importance to forest ecosystem function, including variation in the height and roughness of the outer-most canopy surface and the vertical organization of canopy stories and gaps. The character of the SLICER backscatter signal is described and a method is developed that accounts for occlusion of the laser energy by canopy surfaces, transforming the backscatter signal to a canopy height profile (CHP) that quantitatively represents the relative vertical distribution of canopy surface area. The transformation applies an increased weighting to the backscatter amplitude as a function of closure through the canopy and assumes a horizontally random distribution of the canopy components. SLICER CHPs, averaged over areas of overlap where lidar ground tracks intersect, are shown to be highly reproducible. CHP transects across the four stands reveal spatial variations in vegetation, at the scale of the individual 10 m diameter laser footprints, within and between stands. Averaged SLICER CHPs are compared to analogous height profile results derived from ground-based sightings to plant intercepts measured on plots within the four stands. Tbe plots were located on the segments of the lidar ground tracks from which averaged SLICER CHPs were derived, and the ground observations were acquired within two weeks of the SLICER data acquisition to minimize temporal change. The differences in canopy structure between the four stands is similarly described by the SLICER and ground-based CHP results, however a Chi-square test of similarity documents differences that are statistically significant. The differences are discussed in terms of measurement properties that define the smoothness of the resulting CHPs and Lidar Altimeter Measurements of Canopy Structure - Harding et al. canopy properties that may vertically bias the CHP representations of canopy structure. The statistical differences are most likely due to the more noisy character of the ground-based CHPs, especially high in the canopy where ground-based sightings are rare resulting in an underestimate of canopy surface area and height, and to departures from the assumption of horizontal randomness which bias the CHPs toward the observer (upward for SLICER and downward for ground-based CHPs). The results demonstrate that the SLICER observations reliably provide a measure of canopy structure that reveals ecologically interesting structural variations such as those characterizing a successional sequence of closed-canopy, broadleaf forest stands.

Harding, D. J.↗
DOE OSTI2024

Integrating State Data Assimilation and Innovative Model Parameterization Reduces Simulated Carbon Uptake in the Arctic and Boreal Region

Model representation of carbon uptake and storage is essential for accurate projection of the response of the arctic-boreal zone to a rapidly changing climate. Land model estimates of LAI and aboveground biomass that can have a marked influence on model projections of carbon uptake and storage vary substantially in the arctic and boreal zone, making it challenging to correctly evaluate model estimates of Gross Primary Productivity (GPP). To understand and correct bias of LAI and aboveground biomass in the Community Land Model (CLM), we assimilated the 8-day Moderate Resolution Imaging Spectroradiometer (MODIS) LAI observation and a machine learning product of annual aboveground biomass into CLM using an Ensemble Adjustment Kalman Filter (EAKF) in an experimental region including Alaska and Western Canada. Assimilating LAI and aboveground biomass reduced these model estimates by 58% and 72%, respectively. The change of aboveground biomass was consistent with independent estimates of canopy top height at both regional and site levels. The International Land Model Benchmarking system assessment showed that data assimilation significantly improved CLM's performance in simulating the carbon and hydrological cycles, as well as in representing the functional relationships between LAI and other variables. Here, to further reduce the remaining bias in GPP after LAI bias correction, we re-parameterized CLM to account for low temperature suppression of photosynthesis. The LAI bias corrected model that included the new parameterization showed the best agreement with model benchmarks. Combining data assimilation with model parameterization provides a useful framework to assess photosynthetic processes in LSMs.

58 GEOSCIENCES↗
NASA NTRS2019

Measuring Mangrove Carbon Loss and Gain in Deltas

Demand for mangrove forest resources has led to a steady decline in mangrove area over the past century. Land conversions in the form of agriculture, aquaculture and urbanization account for much of the deforestation of mangrove wetlands. However, natural processes at the transition zone between land and ocean can also rapidly change mangrove spread. In this study, we applied a robust field-based carbon inventory and new structural and temporal remote sensing techniques to quantify the magnitude and change of mangrove carbon stocks in major deltas across Africa and Asia. From 2000–2016, approximately 1.6% (12 270 ha) of the total mangrove area within these deltas disappeared, primarily through erosion and conversion to agriculture. However, the rapid expansion of mangroves in some regions during this same period resulted in new forests that were taller and more carbon-dense than the deforested areas. Because of the rapid vertical growth rates and horizontal expansion, new mangrove forests were able to offset the total carbon losses of 5 332 843 Mg C by 44%. Each hectare of new mangrove forest accounted for ∼84% to ∼160% of the aboveground carbon for each hectare of mangrove forest lost, regardless of the net change in mangrove area. Our study highlights the significance of the natural dynamics of erosion and sedimentation on carbon loss and sequestration potential for mangroves over time. Areas of naturally regenerating mangroves will have a much larger carbon sequestration potential if the rate of mangrove deforestation of taller forests is curbed.

canopy height↗
NASA NTRS2019

Optical System Design and Integration of the Global Ecosystem Dynamics Investigation Lidar

The Global Ecosystem Dynamics Investigation (GEDI) instrument was designed, built, and tested in-house at NASA’s Goddard Space Flight Center and launched to the International Space Station (ISS) on December 5, 2018. GEDI is a multi-beam waveform LiDAR (light detection and ranging) designed to measure the Earth’s global tree height and canopy density using 8 laser beam ground tracks separated by roughly 600 meters. Given the ground coverage required and the 2 year mission duration, a unique optical design solution was developed. GEDI generates 8 ground sampling tracks from 3 transmitter systems viewed by a single receiver telescope, all while maximizing system optical efficiency and transmitter to receiver boresight alignment margin. The GEDI optical design, key optical components, and system level integration and testing are presented here. GEDI began 2 years of science operations in March 2019 and so far, it is meeting all of its key optical performance requirements and is returning outstanding science.

Integration↗
NASA NTRSDate not supplied

The Global Water Monitor: Wetland surface height dynamics for Ecology, Conservation, and Resource Management

The Global Water Monitor (GWM) offers surface water-related products for lakes, river reaches and wetland zones. The surface elevation change products are derived from satellite radar altimeters, such as the Jason/Sentinel series, and can span multiple decades. While the current instruments are profiling, they offer surface water height at specific locations, thus contributing to parallel observation of wetland surface water extent. GWM wetland products are “operational” with routine updates within 1-2days of satellite overpass. There is also assurance of product continuity to at least the end of 2030. Currently, the GWM holds products for a small selection (~40) of diverse wetlands for objectives that focus on conservation and water/fisheries resource monitoring. These sites have been requested by various organizations also looking to the effects of climate change and anthropogenic influences. Many of the current GWM wetland regions are in National Parks such as the Everglades (USA), the Wasur (Rep. Indonesia), and the Kakadu marshes (Australia). They also include coastal river deltas of the Danube, Mekong, Amazon, Orinoco and Ganges Rivers, and the internal Okavango Delta in Botswana. The preliminary set also ensures a diverse range of wetlands e.g., the shallow pot-hole lake region of the Sand Hills and the coastal Black Swamp of the USA, the peat fields of Malaysia and rice growing fields of Yilinzhen in China. Extensive wetlands in Brazil (the Pantanal), South Sudan (the Sudd Marshes) and Belarus (the Pinsk) are also featured, as are the mangrove regions of the Sundarbans (India) and the Laguna Terminos (Mexico). The Usangu wetland (Tanzania) is also included, a focus region where wetland ecology strongly competes with demands from irrigation, livestock, and the needs of downstream hydro-electric power. The nadir-pointing altimeter instruments record height variations regardless of vegetation or canopy cover, and height dynamics at 10-day or monthly resolution reveal seasonal and inter-annual variations as well as longer-term declining or re-charging trends. These products provide a unique, multi-decadal data set that can stand-alone or serve with cross-validation or image-fusion efforts.

Charon Birkett↗
NASA NTRS2024

Integrating State Data Assimilation and Innovative Model Parameterization Reduces Simulated Carbon Uptake in the Arctic and Boreal Region

Model representation of carbon uptake and storage is essential for accurate projection of the response of the arctic‐boreal zone to a rapidly changing climate. Land model estimates of LAI and aboveground biomass that can have a marked influence on model projections of carbon uptake and storage vary substantially in the arctic and boreal zone, making it challenging to correctly evaluate model estimates of Gross Primary Productivity (GPP). To understand and correct bias of LAI and aboveground biomass in the Community Land Model (CLM), we assimilated the 8‐day Moderate Resolution Imaging Spectroradiometer (MODIS) LAI observation and a machine learning product of annual aboveground biomass into CLM using an Ensemble Adjustment Kalman Filter (EAKF) in an experimental region including Alaska and Western Canada. Assimilating LAI and aboveground biomass reduced these model estimates by 58% and 72%, respectively. The change of aboveground biomass was consistent with independent estimates of canopy top height at both regional and site levels. The International Land Model Benchmarking system assessment showed that data assimilation significantly improved CLM's performance in simulating the carbon and hydrological cycles, as well as in representing the functional relationships between LAI and other variables. To further reduce the remaining bias in GPP after LAI bias correction, we re‐parameterized CLM to account for low temperature suppression of photosynthesis. The LAI bias corrected model that included the new parameterization showed the best agreement with model benchmarks. Combining data assimilation with model parameterization provides a useful framework to assess photosynthetic processes in LSMs.

land data assimilation↗
NASA NTRS2000

Primary and Secondary Controls on Measurements of Forest Height Using Large-Footprint Lidar at the Hubbard Brook LTER

On September 26, 1999, we mapped canopy structure over 90% of the Hubbard Brook Experimental Forest in White Mountain National Forest, New Hampshire, using the Laser Vegetation Imaging Sensor (LVIS). This airborne instrument was configured to emulate data expected from the Vegetation Canopy Lidar (VCL) space mission. We compared above ground heights of the tallest surfaces detected by lidar with average forest canopy heights estimated from tree-based measurements in or near 346 0.05 ha plots (made in autumn of 1997 and 1998). Vegetation heights had by far the predominant influence on lidar top heights, but with this large data set we were able to measure two significant secondary effects: those of steepness or slope of the underlying terrain and of tree crown form. The size of the slope effect was intermediate between that expected from models of homogeneous canopy layers and for solitary tree crowns. The first detected surfaces were also proportionately taller for plots with more basal area in broad leaved northern hardwoods than for mostly coniferous plots. We expected this because of the contrast between the shapes of cumulative distributions of surface area for elliptical or hemi-elliptical tree crowns and those for conical crowns. Correcting for these secondary effects, when appropriate data are available for calibration, may improve vegetation structure estimates in regional studies using VCL or similar lidar data sources.

Knox, Robert G.↗
DOE OSTI2026

Data for Nitrogen Dynamics and Physiological N Use Efficiency in High-biomass Sorghum

Improving nitrogen (N) efficiency is essential for sustainable high-biomass sorghum ( Sorghum bicolor L. Moench ) production. This study evaluated leaf and stem N dynamics, canopy N remobilization, and physiological nitrogen use efficiency (pNUE) in two photoperiod-sensitive sorghum hybrids under two N rates (0 and 168 kg-N ha−1) across multiple environments in Texas and Illinois. Leaf N concentrations increased with plant height in the canopy with steeper gradients under low-N conditions, indicating enhanced N remobilization when N is limited. Stem tissue showed less variation in N concentration across canopy nodal positions, with within-plant differences ranging from 1.2 to 7.6 g kg−1, compared to 3.1 to 16.3 g kg−1 in leaves. While pNUE was generally higher under unfertilized conditions, it varied largely by site; however, genotypic differences were minimal within the given year. These results highlight the importance of integrating environmental and management factors into breeding and fertilization strategies to enhance N efficiency in high-biomass sorghum.

Nitrogen↗
NASA NTRS1984

Determining forest canopy characteristics using airborne laser data

A study is reported in which a profiling laser system flown at relatively low altitudes over a forested area was used to measure various forest canopy attributes, including tree heights. An analysis of the data obtained indicates that canopy closure is most strongly related to the penetration capability of the laser pulse, with the pulses attenuated more quickly in a dense canopy. Laser estimates of the average tree heights differ by less than 1 m from the photogrammetrically acquired values. It is concluded that the laser system is suitable for remotely sensing the vertical forest canopy profile. Elements of this profile are linearly related to crown closure and can be used to assess tree height.

Nelson, R.↗
NASA NTRS1989

The use of aircraft laser ranging data for forest mensuration

Laser studies dealing with various aspects of forest canopy measurement are reviewed. Aircraft LIDAR data have been used to estimate canopy density, tree heights, forest volume and biomass, to discriminate terrain units, and to add a height component to multispectral forest cover classifications. Linear comparisons between photogrammetrically-estimated canopy density and laser metrics indicate that the laser explains 45-65 percent of the variation noted in the photo estimates.

Nelson, Ross F.↗
NASA NTRS1983

Magnetic canopies in unipolar regions

Base-height statistics are presented for magnetic canopies in six unipolar magnetic regions which were observed near the limb with the Kitt Peak Vacuum Telescope and Diode Array Magnetograph during the period 25 April-3 July, 1980. As in earlier studies, extensive areas are found to be covered by low-lying canopies.

Jones, H. P.↗
NASA NTRS1982

Magnetograph response to canopy-type fields

The response of longitudinal-field magnetographs to magnetic fields which are semi-infinite or confined to a horizontal layer is discussed with respect to the interpretation of solar diffuse fields, observed towards the limb, in terms of magnetic canopy models. Numerical results are presented for several reference solar models and typical 'calibration' curves are shown for the CI 9111 A, Fe I 8688 A, and Ca II 8542 A lines in magnetostatic atmospheres derived from a mean model. A procedure is developed for determining the base heights of magnetic canopies from observations with an uncertainty not exceeding the order of a pressure scale height. Until definitive information regarding atmospheric structure inside flux tubes can be developed from theory or observation, reliable field strengths cannot be derived from the data.

Jones, H. P.↗
NASA NTRS1999

The Laser Vegetation Imaging Sensor (LVIS): A Medium-Altitude, Digitization-Only, Airborne Laser Altimeter for Mapping Vegetation and Topography

The Laser Vegetation Imaging Sensor (LVIS) is an airborne, scanning laser altimeter designed and developed at NASA's Goddard Space Flight Center. LVIS operates at altitudes up to 10 km above ground, and is capable of producing a data swath up to 1000 m wide nominally with 25 m wide footprints. The entire time history of the outgoing and return pulses is digitized, allowing unambiguous determination of range and return pulse structure. Combined with aircraft position and attitude knowledge, this instrument produces topographic maps with decimeter accuracy and vertical height and structure measurements of vegetation. The laser transmitter is a diode-pumped Nd:YAG oscillator producing 1064 nm, 10 nsec, 5 mJ pulses at repetition rates up to 500 Hz. LVIS has recently demonstrated its ability to determine topography (including sub-canopy) and vegetation height and structure on flight missions to various forested regions in the U.S. and Central America. The LVIS system is the airborne simulator for the Vegetation Canopy Lidar (VCL) mission (a NASA Earth remote sensing satellite due for launch in 2000), providing simulated data sets and a platform for instrument proof-of-concept studies. The topography maps and return waveforms produced by LVIS provide Earth scientists with a unique data set allowing studies of topography, hydrology, and vegetation with unmatched accuracy and coverage.

Blair, J. Bryan↗
DOE OSTI2026

Nitrogen dynamics and physiological N use efficiency in high‐biomass sorghum

Improving nitrogen (N) efficiency is essential for sustainable high-biomass sorghum ( Sorghum bicolor L. Moench) production. This study evaluated leaf and stem N dynamics, canopy N remobilization, and physiological nitrogen use efficiency (pNUE) in two photoperiod-sensitive sorghum hybrids under two N rates (0 and 168 kg-N ha −1 ) across multiple environments in Texas and Illinois. Leaf N concentrations increased with plant height in the canopy with steeper gradients under low-N conditions, indicating enhanced N remobilization when N is limited. Stem tissue showed less variation in N concentration across canopy nodal positions, with within-plant differences ranging from 1.2 to 7.6 g kg −1 , compared to 3.1 to 16.3 g kg −1 in leaves. While pNUE was generally higher under unfertilized conditions, it varied largely by site; however, genotypic differences were minimal within the given year. These results highlight the importance of integrating environmental and management factors into breeding and fertilization strategies to enhance N efficiency in high-biomass sorghum.

60 APPLIED LIFE SCIENCES↗