Prasad S. Thenkabail

Ecology · 2000–2018

A researcher in the Science corpus: 7 papers; trusts 3 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Ecology — 54 citations into it; #3,238 of 10,717 by trust here, #1,697 by citations
• Media Technology — 33 citations into it; #3,069 of 3,621 by trust here, #2,033 by citations
• Atmospheric Science — 14 citations into it

Whom Prasad S. Thenkabail trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Yang Shao
2. Noel Gorelick
3. Jun Xiong
4. Ross S. Lunetta
5. Martin Herold
6. Steffen Fritz
7. Matthew C. Hansen
8. José Manuel Peñá-Barragán
9. A. Chapagain
10. Giorgos Mountrakis

Who trusts Prasad S. Thenkabail overall

1. Onisimo Mutanga
2. Clement Atzberger
3. T. Almeida
4. Saleem Ullah
5. Fei Li
6. Kun Jia
7. Jochem Verrelst
8. Chuanwen Wei
9. Martin Schlerf
10. Michel Eustáquio Dantas Chaves

Papers from Prasad S. Thenkabail's perspective

Ordered by how strongly the researchers Prasad S. Thenkabail trusts endorse each paper. Same corpus, a different order for every researcher.

1. Global land cover mapping from MODIS: algorithms and early results
2. Random Forests
3. Some challenges in global land cover mapping : An assessment of agreement and accuracy in existing 1 km datasets
4. Highlighting continued uncertainty in global land cover maps for the user community
5. A review of large area monitoring of land cover change using Landsat data
6. Google Earth Engine: Planetary-scale geospatial analysis for everyone
7. Sentinel-2: ESA's Optical High-Resolution Mission for GMES Operational Services
8. Assessing the accuracy of land cover change with imperfect ground reference data
9. World population stabilization unlikely this century (Science)
10. The global component of freshwater demand and supply: an assessment of virtual water flows between nations as a result of trade in agricultural and industrial products

Their papers

• A 30-m landsat-derived cropland extent product of Australia and China using random forest machine learning algorithm on Google Earth Engine cloud computing platform (2018) — 460 citations
• Automated cropland mapping of continental Africa using Google Earth Engine cloud computing (2017) — 434 citations
• Nominal 30-m Cropland Extent Map of Continental Africa by Integrating Pixel-Based and Object-Based Algorithms Using Sentinel-2 and Landsat-8 Data on Google Earth Engine (2017) — 347 citations
• A support vector machine to identify irrigated crop types using time-series Landsat NDVI data (2015) — 340 citations
• Global Land Cover Mapping: A Review and Uncertainty Analysis (2014) — 321 citations
• Free Access to Landsat Imagery (2008) — 927 citations
• Hyperspectral Vegetation Indices and Their Relationships with Agricultural Crop Characteristics (2000) — 1,325 citations