Data · dataset · 2018
Mapping spatial-temporal sediment dynamics of river-floodplains in the Amazon
Listed in Teesside University Research Data Repository
This directory contains the following maps in GeoTIFF format: open-water frequency, time-series of reflectance for each band (Red and NIR), and frequency of SSSC classes.
Description
Fassoni-Andrade, A. C., & Paiva, R. C. D. (2019). Mapping spatial-temporal sediment dynamics of river-floodplains in the Amazon.
Remote Sensing of Environment, 221, 94-107. sciencedirect.com/science/article/abs/pii/S0034425718305005 Corresponding autor: alice.fassoni@ufrgs.br 1) Data Description: 1.1) Spatial Representation Type: Raster Format: TIFF Columns and rows: 7661, 2405 Cell Size (X,Y): 0.002245, 0.002245 (~250m) 1.2) Extent (coordinate system): Top: -0.025 Left: -67.28 Right: -50.081055 Botton: -5.424225 1.3) Spatial Reference Properties (GCS_WGS_1984.prj file): Type: Geographic Geographic Coordinate Reference: WGS 1984 Open Geospatial Consortium (OGC) Well Known Text (WKT): GEOGCS["GCS_WGS_1984", DATUM["D_WGS_1984", SPHEROID["WGS_1984",6378137.0,298.257223563]], PRIMEM["Greenwich",0.0], UNIT["Degree",0.0174532925199433], AUTHORITY["EPSG",4326]] 2) Data description for individual files: 2.1) File: open_water_frequency.tif This map indicates for how long, during 15 years (2003-2017), each pixel in rivers and lakes of central Amazon basin remained as open-water at every four days.
Read the rest (4 more)
Number of Bands: 1 Values between 0 and 100. Pixel Type: floating point Pixel Depth: 32 bit No Data Value: 0 2.2) File: class_SSC_frequency.tif This map represents a 15-year frequency (2003-2017) at which each pixel in rivers and lakes of central Amazon basin remains in one of the surface suspended sediments concentration classes (SSSC): high, moderate, and low. The open-water frequency map must be considered to interpret the sediments temporal dynamics in the class frequency map.
For example, a pixel in the floodplain lake with frequency of 10, 30, and 20% in SSSC classes low, medium and high respectively, remains 40% of the time as no open-water. Number of Bands: 3 band 1: low SSSC class; band 2: Moderate SSSC class; band 3: High SSSC class Composition of bands for best visualization: R(3)G(2)B(1) without contrast Values between 0 and 100. Pixel Type: double precision Pixel Depth: 64 bit No Data Value: 0 2.3) File: time_series_nir.tif This map represents the climatology time series of infrared (nir) reflectance in period of four-days in rivers and lakes of central Amazon basin between 2003 and 2017 (15 years).
Number of Bands: 92 (each band represent a date that is identified in dates.txt file) Values between 0 and 10000. Pixel Type: floating point Pixel Depth: 32 bit No Data Value: 0 2.4) File: time_series_red.tif This map represents the climatology time series of red reflectance in period of four-days in rivers and lakes of central Amazon basin between 2003 and 2017 (15 years). Number of Bands: 92 (each band represent a date that is identified in dates.txt file) Values between 0 and 10000.
Pixel Type: floating point Pixel Depth: 32 bit No Data Value: 0
Links
Where it is published
- DOI doi.org/10.17632/wy2mz3nm7p.1 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Photogrammetry and remote sensing · Satellite remote sensing · Social Science
- Inferred from text
- Genome sequencing 65% · Text 75%
Provenance · 1 source records, 14 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/wy2mz3nm7p.1 | 9 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].anzsrc:field:401304 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Remote Sensing'] |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:engineering | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:humanities | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:social-science | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[modality].local:modality:genome-sequencing | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (65%) |
| concepts[modality].local:modality:remote-sensing | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Remote Sensing'] |
| concepts[modality].local:modality:text | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (75%) |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |