Onisimo Mutanga

Ecology · 2003–2019

A researcher in the Science corpus: 13 papers; trusts 28 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Ecology — 69 citations into it; #2,676 of 10,717 by trust here, #3,102 by citations
• Artificial Intelligence — 26 citations into it
• Plant Science — 26 citations into it
• Global and Planetary Change — 24 citations into it
• Media Technology — 24 citations into it; #3,059 of 3,621 by trust here, #3,192 by citations
• Environmental Engineering — 23 citations into it; #4,049 of 5,479 by trust here, #2,092 by citations
• Analytical Chemistry — 21 citations into it; #958 of 1,254 by trust here, #1,084 by citations
• Statistics and Probability — 17 citations into it

Whom Onisimo Mutanga trusts overall

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

1. Trevor J. Hastie
2. Mahesh Pal
3. Giles M. Foody
4. Prasad S. Thenkabail
5. Leo Breiman
6. Moses Azong Cho
7. Jerome H. Friedman
8. Jun Xiong
9. Robert E. Schapire
10. Vladimir Naumovich Vapni

Who trusts Onisimo Mutanga overall

1. Chaichoke Vaiphasa
2. Dehua Zhao
3. Jochem Verrelst
4. Andrew K. Skidmore
5. Yumiko Kanke
6. Ittai Herrmann
7. Helmi Zulhaidi Mohd Shafri
8. Abel Ramoelo
9. Elhadi Adam
10. Edwin Raczko

Papers from Onisimo Mutanga's perspective

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

1. Random Forests
2. The Nature of Statistical Learning Theory
3. Support-Vector Networks
4. Bagging Predictors
5. Random Forests for land cover classification (Pattern Recognition Letters)
6. A decision-theoretic generalization of on-line learning and an application to boosting
7. Stochastic gradient boosting
8. Status of land cover classification accuracy assessment
9. Google Earth Engine: Planetary-scale geospatial analysis for everyone
10. Automated cropland mapping of continental Africa using Google Earth Engine cloud computing

Their papers

• Google Earth Engine Applications (2019) — 500 citations
• Mapping spatial variability of foliar nitrogen in coffee (Coffea arabica L.) plantations with multispectral Sentinel-2 MSI data (2018) — 70 citations
• Google Earth Engine Applications Since Inception: Usage, Trends, and Potential (2018) — 609 citations
• Remote sensing of species diversity using Landsat 8 spectral variables (2017) — 105 citations
• Testing the reliability and stability of the internal accuracy assessment of random forest for classifying tree defoliation levels using different validation methods (2015) — 70 citations
• Predicting Eucalyptus spp. stand volume in Zululand, South Africa: an analysis using a stochastic gradient boosting regression ensemble with multi-source data sets (2015) — 59 citations
• Evaluating the impact of red-edge band from Rapideye image for classifying insect defoliation levels (2014) — 113 citations
• A comparison of partial least squares (PLS) and sparse PLS regressions for predicting yield of Swiss chard grown under different irrigation water sources using hyperspectral data (2014) — 94 citations
• Land-use/cover classification in a heterogeneous coastal landscape using RapidEye imagery: evaluating the performance of random forest and support vector machines classifiers (2014) — 421 citations
• Commercial tree species discrimination using airborne AISA Eagle hyperspectral imagery and partial least squares discriminant analysis (PLS-DA) in KwaZulu-Natal, South Africa (2013) — 147 citations
• High density biomass estimation for wetland vegetation using WorldView-2 imagery and random forest regression algorithm (2012) — 851 citations
• Red edge shift and biochemical content in grass canopies (2007) — 276 citations
• Discriminating tropical grass (Cenchrus ciliaris) canopies grown under different nitrogen treatments using spectroradiometry (2003) — 152 citations