scholarly journals A High-Resolution Map of Singapore’s Terrestrial Ecosystems

Data ◽  
2019 ◽  
Vol 4 (3) ◽  
pp. 116 ◽  
Author(s):  
Gaw ◽  
Yee ◽  
Richards
Keyword(s):  
High Resolution ◽  
Land Cover ◽  
Natural Capital ◽  
Urban Ecosystems ◽  
Terrestrial Ecosystems ◽  
Tropical Regions ◽  
High Resolution Satellite Images ◽  
High Resolution Map ◽  
City State ◽  
Resolution Map

The natural and semi-natural areas within cities provide important refuges for biodiversity, as well as many benefits to people. To study urban ecology and quantify the benefits of urban ecosystems, we need to understand the spatial extent and configuration of different types of vegetated cover within a city. It is challenging to map urban ecosystems because they are typically small and highly fragmented; thus requiring high resolution satellite images. This article describes a new high-resolution map of land cover for the tropical city-state of Singapore. We used images from WorldView and QuickBird satellites, and classified these images using random forest machine learning and supplementary datasets into 12 terrestrial land classes. Close to 50 % of Singapore’s land cover is vegetated while freshwater fills about 6 %, and the rest is bare or built up. The overall accuracy of the map was 79 % and the class-specific errors are described in detail. Tropical regions such as Singapore have a lot of cloud cover year-round, complicating the process of mapping using satellite imagery. The land cover map provided here will have applications for urban biodiversity studies, ecosystem service quantification, and natural capital assessment.

Tomato chromosome 6: a high resolution map of the long arm and construction of a composite integrated marker-order map

1996 ◽  
Vol 92 (8) ◽  
pp. 1065-1072 ◽  
Author(s):  
M. F. van Wordragen ◽  
R. L. Weide ◽  
E. Coppoolse ◽  
P. Zabel ◽  
M. Koornneef
Keyword(s):  
High Resolution ◽  
Marker Order ◽  
Chromosome 6 ◽  
Tomato Chromosome ◽  
High Resolution Map ◽  
Resolution Map

scholarly journals A high-resolution map of bacteriophage ϕX174 transcription

Virology ◽  
2020 ◽  
Vol 547 ◽  
pp. 47-56 ◽  
Author(s):  
Dominic Y. Logel ◽  
Paul R. Jaschke
Keyword(s):  
High Resolution ◽  
High Resolution Map ◽  
Resolution Map

scholarly journals A Comprehensive, High-Resolution Map of a Gene’s Fitness Landscape

2016 ◽  
Vol 33 (5) ◽  
pp. 1378-1378 ◽  
Author(s):  
Elad Firnberg ◽  
Jason W. Labonte ◽  
Jeffrey J. Gray ◽  
Marc Ostermeier
Keyword(s):  
High Resolution ◽  
Fitness Landscape ◽  
High Resolution Map ◽  
Resolution Map

A high-resolution map of the chromosomal region surrounding the nude gene

Genomics ◽  
1995 ◽  
Vol 26 (2) ◽  
pp. 308-317 ◽  
Author(s):  
C.C. Blackburn ◽  
J. Griffith ◽  
G. Morahan
Keyword(s):  
High Resolution ◽  
Chromosomal Region ◽  
High Resolution Map ◽  
Resolution Map

scholarly journals A New High-Resolution Map of World Mountains and an Online Tool for Visualizing and Comparing Characterizations of Global Mountain Distributions

2018 ◽  
Vol 38 (3) ◽  
pp. 240-249 ◽  
Author(s):  
Roger Sayre ◽  
Charlie Frye ◽  
Deniz Karagulle ◽  
Jürg Krauer ◽  
Sean Breyer ◽  
...  
Keyword(s):  
High Resolution ◽  
Online Tool ◽  
High Resolution Map ◽  
Resolution Map

scholarly journals GRANULOMETRIC MAPS FROM HIGH RESOLUTION SATELLITE IMAGES

2011 ◽  
Vol 21 (1) ◽  
pp. 19 ◽  
Author(s):  
Catherine Mering ◽  
Franck Chopin
Keyword(s):  
High Resolution ◽  
Land Cover ◽  
Arid Regions ◽  
Satellite Images ◽  
Distribution Analysis ◽  
Granulometric Analysis ◽  
High Resolution Satellite Images ◽  
Thematic Mapping ◽  
Urban Settlements

A new method of land cover mapping from satellite images using granulometric analysis is presented here. Discontinuous landscapes such as steppian bushes of semi arid regions and recently growing urban settlements are especially concerned by this study. Spatial organisations of the land cover are quantified by means of the size distribution analysis of the land cover units extracted from high resolution remotely sensed images. A granulometric map is built by automatic classification of every pixel of the image according to the granulometric density inside a sliding neighbourhood. Granulometric mapping brings some advantages over traditional thematic mapping by remote sensing by focusing on fine spatial events and small changes in one peculiar category of the landscape.

scholarly journals The architecture of SARS-CoV-2 transcriptome

2020 ◽  
Author(s):  
Dongwan Kim ◽  
Joo-Yeon Lee ◽  
Jeong-Sun Yang ◽  
Jun Won Kim ◽  
V. Narry Kim ◽  
...  
Keyword(s):  
High Resolution ◽  
Rna Sequencing ◽  
Rna Modification ◽  
List Type ◽  
Rna Modifications ◽  
Subgenomic Rnas ◽  
Frequent Motif ◽  
High Resolution Map ◽  
Functional Investigation ◽  
Resolution Map

AbstractSARS-CoV-2 is a betacoronavirus that is responsible for the COVID-19 pandemic. The genome of SARS-CoV-2 was reported recently, but its transcriptomic architecture is unknown. Utilizing two complementary sequencing techniques, we here present a high-resolution map of the SARS-CoV-2 transcriptome and epitranscriptome. DNA nanoball sequencing shows that the transcriptome is highly complex owing to numerous recombination events, both canonical and noncanonical. In addition to the genomic RNA and subgenomic RNAs common in all coronaviruses, SARS-CoV-2 produces a large number of transcripts encoding unknown ORFs with fusion, deletion, and/or frameshift. Using nanopore direct RNA sequencing, we further find at least 41 RNA modification sites on viral transcripts, with the most frequent motif being AAGAA. Modified RNAs have shorter poly(A) tails than unmodified RNAs, suggesting a link between the internal modification and the 3′ tail. Functional investigation of the unknown ORFs and RNA modifications discovered in this study will open new directions to our understanding of the life cycle and pathogenicity of SARS-CoV-2.HighlightsWe provide a high-resolution map of SARS-CoV-2 transcriptome and epitranscriptome using nanopore direct RNA sequencing and DNA nanoball sequencing.The transcriptome is highly complex owing to numerous recombination events, both canonical and noncanonical.In addition to the genomic and subgenomic RNAs common in all coronaviruses, SARS-CoV-2 produces transcripts encoding unknown ORFs.We discover at least 41 potential RNA modification sites with an AAGAA motif.

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