Toshihiro Sakamoto

Ecology · 2010–2020

A researcher in the Science corpus: 3 papers; trusts 1 researcher and is trusted by 13 researchers here, as inferred from the citation graph.

Subfields

• Ecology — 14 citations into it; #1,973 of 10,717 by trust here, #7,367 by citations
• Environmental Engineering — 7 citations into it; #1,233 of 5,479 by trust here, #2,998 by citations
• Plant Science — 7 citations into it

Whom Toshihiro Sakamoto trusts overall

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

1. Anatoly A. Gitelson

Who trusts Toshihiro Sakamoto overall

1. Xiuliang Jin
2. Pablo J. Zarco-Tejada
3. Urs Schmidhalter
4. Matthew P Reynolds
5. Malcolm J. Hawkesford
6. Rajeev K. Varshney

Papers from Toshihiro Sakamoto's perspective

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

1. Crop identification using harmonic analysis of time-series AVHRR NDVI data
2. Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture
3. Wide Dynamic Range Vegetation Index for remote quantification of biophysical characteristics of vegetation. (Journal of plant physiology)
4. A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection
5. Leaf optical properties in higher plants: linking spectral characteristics to stress and chlorophyll concentration. (American-Eurasian journal of botany)
6. Remote estimation of nitrogen and chlorophyll contents in maize at leaf and canopy levels (International Journal of Applied Earth Observation and Geoinformation)
7. Calibration and validation of hyperspectral indices for the estimation of broadleaved forest leaf chlorophyll content, leaf mass per area, leaf area index and leaf canopy biomass
8. Towards universal broad leaf chlorophyll indices using PROSPECT simulated database and hyperspectral reflectance measurements
9. Combined Spectral Index to Improve Ground‐Based Estimates of Nitrogen Status in Dryland Wheat
10. A new technique for extracting the red edge position from hyperspectral data: The linear extrapolation method

Their papers

• Incorporating environmental variables into a MODIS-based crop yield estimation method for United States corn and soybeans through the use of a random forest regression algorithm (2020) — 138 citations
• Refined shape model fitting methods for detecting various types of phenological information on major U.S. crops (2018) — 81 citations
• A Two-Step Filtering approach for detecting maize and soybean phenology with time-series MODIS data (2010) — 322 citations