Wai‐Tim Ng

961 citations
16 papers · 705 indexed · 1 hit paper · h-index 13

Wai‐Tim Ng

15 papers receiving 687 citations

Hit Papers

How much does multi-temporal Sentinel-2 data improve crop...247201820262020202350100150200

Peers

Wai‐Tim Ng
Comparison fields: 5 of 73
  • Ecological Modeling 143
  • Ecology 462
  • Environmental Engineering 185
  • Media Technology 101
  • Forestry 44
Replace David Sheeren with:
David Sheeren France
Benjamin Mack Germany
Toon Spanhove Belgium
Cibele Hummel do Amaral Brazil
Philippe Rufin Germany
Loris Vescovo Italy
Fábio Marcelo Breunig Brazil
Tatjana Koukal Austria
Sabelo Madonsela South Africa
A. C. Coutinho Brazil
Wai‐Tim Ng relative to David Sheeren France David Sheeren's profile →
Citations per field
00.5×1.5×2.1×
David Sheeren · 1×
Citations per year

Countries citing papers authored by Wai‐Tim Ng

Since Specialization
Citations

This map shows the geographic impact of Wai‐Tim Ng's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Wai‐Tim Ng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wai‐Tim Ng more than expected).

Fields of papers citing papers by Wai‐Tim Ng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wai‐Tim Ng. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Wai‐Tim Ng. The network helps show where Wai‐Tim Ng may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Wai‐Tim Ng, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Wai‐Tim Ng Line = papers co-authored together Wai‐Tim Ng links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 202029
2 202065
3 202018
4 201952
5 201822
6 201823
7
How much does multi-temporal Sentinel-2 data improve crop type classification?breakdown →
2018247
8
Survey of the avifauna of Giang Man proposed nature reserve, Quang Binh province, Vietnam
20170
9 201787
10 201764
11 201623
12 20165
13 201630
14 201520
15 201414
16
THE VASCULAR PLANT FLORA OF BUKIT BATOK, SINGAPORE
20136

About Wai‐Tim Ng

Wai‐Tim Ng is a scholar working on Ecological Modeling, Ecology, Nature and Landscape Conservation, Environmental Engineering and Management, Monitoring, Policy and Law, having authored 16 papers that have together received 705 indexed citations. Recurring topics across this work include Remote Sensing in Agriculture (7 papers), Species Distribution and Climate Change (5 papers), Ecology and Vegetation Dynamics Studies (4 papers), Rangeland Management and Livestock Ecology (3 papers), Remote Sensing and LiDAR Applications (3 papers), Wildlife Ecology and Conservation (3 papers), Forest Insect Ecology and Management (2 papers) and Plant Diversity and Evolution (1 paper). The work is most often cited by research in Ecological Modeling (143 citations), Ecology (462 citations), Environmental Engineering (185 citations), Media Technology (101 citations) and Forestry (44 citations). Wai‐Tim Ng has collaborated with scholars based in Austria, Kenya and Switzerland. Frequent co-authors include Clement Atzberger, Markus Immitzer, Francesco Vuolo, Sandra Eckert, Hussein Gadain, Purity Rima Mbaabu, Felix Rembold, Michele Meroni, Urs Schaffner and Simon Choge. Their work appears in journals such as International Journal of Applied Earth Observation and Geoinformation, Remote Sensing, Land Degradation and Development, Ecology and Evolution and Tropical Animal Health and Production.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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