Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
4
datasets available to search
ShareScore release 0.9.0
Dataset results
4 results for “Terrestrial remote sensing”
Remote sensing and field information aid in predicting the presence of the terrestrial orchid Cyclopogon lute-albus
<p>Tropical montane cloud forest is one of the most threatened ecosystems, in central Veracruz, Mexico. Within this ecosystem, terrestrial orchids are strongly dependent on forest conditions and may be sensitive to environmental change. We applied field surveys of abiotic and biotic factors associated with the presence of the terrestrial orchid <em>Cyclopogon luteo-albus</em> and combined this with correlative niche modeling approaches to evaluate its potential distribution under two different environmental sets and two different extents. Layers of environmental information were obtained from Landsat imagery and interpolated bioclimatic and soil property layers. Existing species records were used as training data by sampling five forest fragments in central Veracruz, utilizing herbarium and global biodiversity information facility databases. The resulting predictions were tested by sampling at 15 sites of potential distribution. The model predicted the presence of <em>C. luteo-albus</em> with a reliability of 80%. The most important variables of models derived from interpolated layers coincide with site-relevant parameters suggesting the utility of these tools to further explore species suitabilities at larger geographic extents. Potential distribution mapping is an important tool to identify key areas for conservation and priority areas for future studies of species and partially resolves the lack of records of many orchid species.</p>
Remote sensing and field information aid in predicting the presence of the terrestrial orchid Cyclopogon lute-albus
Open the record for dataset details and reuse information.
Drought risk of global terrestrial gross primary productivity in recent 40 years detected by a remote sensing-driven process model
<p class="Abstract"><span>Gross primary productivity (GPP) is the largest flux in the global terrestrial carbon cycle and affected by multiple factors. In recent decades, drought has significantly impacted global terrestrial GPP and been projected to occur with increasing frequency and intensity. However, the drought risk of global terrestrial GPP has not been well investigated. In this study, global terrestrial GPP over the period from 1981 to 2016 was simulated with the process-based Boreal Ecosystem Productivity Simulator (BEPS) model. Then, the drought risk of terrestrial GPP was quantified as the product of frequency of drought and reduction of GPP caused by drought, which were determined using the standardized precipitation evapotranspiration index (SPEI). During the study period, the drought risk of terrestrial GPP exhibited detectable spatial heterogeneity, high in southeastern United States, most of South America, southern Europe, central and eastern Africa, eastern and southeastern Asia, and eastern Australia. In these regions, the maximum reduction of GPP might be above 30% in drought years relative to that in normal years. The drought risk of GPP was low at high latitudes of the Northern Hemisphere, in which terrestrial GPP increased slightly in drought years. The spatial pattern of the drought risk of GPP simulated by the BEPS model was close to that of FLUXCOM GPP, which was scaled from tower observations with a machine learning algorithm forced by remote sensing and meteorological data. This study advances our understanding on the impact of drought on terrestrial GPP over the globe.</span></p>
Drought risk of global terrestrial gross primary productivity in recent 40 years detected by a remote sensing-driven process model
Open the record for dataset details and reuse information.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.