Výsledky vyhledávání - "Motomasa Daigo"

A STUDY ON PRODUCING HIGHLY RELIABILE REFERENCE DATA SETS FOR GLOBAL LAND COVER VALIDATION

Autor: F. Ochiai, Noboru Fujiwara, Noriko Soyama, Motomasa Daigo, Kanako Muramatsu

Publikováno v: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLI-B8, Pp 1207-1211 (2016)

Validating the accuracy of land cover products using a reliable reference dataset is an important task. A reliable reference dataset is produced with information derived from ground truth data. Recently, the amount of ground truth data derived from i

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::317b27d9b7366a4e24d1f9533fa06855
https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B8/1207/2016/isprs-archives-XLI-B8-1207-2016.pdf

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A Vegetation Index to Estimate Terrestrial Gross Primary Production Capacity for the Global Change Observation Mission-Climate (GCOM-C)/Second-Generation Global Imager (SGLI) Satellite Sensor

Autor: Shin Nagai, Juthasinee Thanyapraneedkul, Kanako Muramatsu, Kenlo Nishida Nasahara, Noriko Soyama, Hiroyuki Muraoka, Shinobu Furumi, Hibiki M Noda, Yasuko Mizoguchi, Motomasa Daigo, Takahisa Maeda, Masayoshi Mano

Publikováno v: Remote Sensing, Vol 4, Iss 12, Pp 3689-3720 (2012)
Remote Sensing
Volume 4
Issue 12
Pages: 3689-3720

To estimate global gross primary production (GPP), which is an important parameter for studies of vegetation productivity and the carbon cycle, satellite data are useful. In 2014, the Japan Aerospace Exploration Agency (JAXA) plans to launch the Glob

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::07839079d48ff0f94003833d93f3a4e7
https://doi.org/10.3390/rs4123689

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Topographic effects on estimating net primary productivity of green coniferous forest in complex terrain using Landsat data: a case study of Yoshino Mountain, Japan

Autor: Motomasa Daigo, Wei Huang, Liangpei Zhang, Kanako Muramatsu, Pingxiang Li, Shinobu Furumi

Publikováno v: International Journal of Remote Sensing. 31:2941-2957

In mountainous areas, irregular terrain significantly affects spatial variations of climatic variables and the reflectance of pixels in remote sensing imagery. Consequently, the variations may affect the estimation of net primary productivity (NPP).

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::72093d016e3222bb9689ac7650c1191b
https://doi.org/10.1080/01431160903140829

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A new vegetation index derived from the pattern decomposition method applied to Landsat‐7/ETM+ images in Mongolia

Autor: F. Ochiai, Ichirow Kaihotsu, Yan Xiong, S. Nakayama, D. Oyunbaatar, Motomasa Daigo, B. Bolortsetseg, Masahiro Hirata, Kanako Muramatsu, Kazato Oishi

Publikováno v: International Journal of Remote Sensing. 28:3493-3511

The goal of this study was to estimate vegetation coverage and map the land-cover in an experimental field (60×60 km) near Mandalgobi, Mongolia using Landsat-7/ETM+ data for ground truthing in the Advanced Earth Observing Satellite II (ADEOS-II) Mon

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::41c1ed4a765589fb84ca8c8f6598f718
https://doi.org/10.1080/01431160601024200

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Hyperspectral Data Transformation and Vegetation Index Performance Based on the Universal Pattern Decomposition Method

Autor: Lifu Zhang, Liangpei Zhang, Motomasa Daigo, Lei Yan, Kanako Muramatsu, Noboru Fujiwara

Publikováno v: Journal of Imaging Science and Technology. 51:141-147

Traditional vegetation indices are based on only a few spectral bands. However, hyperspectral spectrometers, such as the airborne visible infrared imaging spectrometer (AVIRIS), collect data with 224 contiguous spectral bands. Traditional vegetation

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::5dead40feb122b05440de5e38e632e30
https://doi.org/10.2352/j.imagingsci.technol.(2007)51:2(141)

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A new vegetation index based on the universal pattern decomposition method

Autor: Motomasa Daigo, Noboru Fujiwara, Shinobu Furumi, Liangpei Zhang, Kanako Muramatsu, Lifu Zhang

Publikováno v: International Journal of Remote Sensing. 28:107-124

This study examined a new vegetation index, based on the universal pattern decomposition method (VIUPD). The universal pattern decomposition method (UPDM) allows for sensor-independent spectral analysis. Each pixel is expressed as the linear sum of s

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::ffe16a86afb2a27e878fefc39e9313c8
https://doi.org/10.1080/01431160600857402

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Assessment of the universal pattern decomposition method using MODIS and ETM+ data

Autor: Liangpei Zhang, Shinobu Furumi, Kanako Muramatsu, Motomasa Daigo, N. Fujiwara, Lifu Zhang

Publikováno v: International Journal of Remote Sensing. 28:125-142

The universal pattern decomposition method (UPDM) is a sensor-independent method in which each satellite pixel is expressed as the linear sum of fixed, standard spectral patterns for water, vegetation and soil. The same normalized spectral patterns c

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b8accb7a49e997d3140b683a91aa5f9c
https://doi.org/10.1080/01431160600617228

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A scale-up method for reference data for validation of global land cover maps using ALOS/AVNIR-2 satellite data

Autor: F. Ochiai, Noriko Soyama, Kenlo Nishida Nasahara, Takeo Tadono, Motomasa Daigo, Kanako Muramatsu, Itsuko Ohashi

Publikováno v: SPIE Proceedings.

Validating the accuracy of land cover products using a reliable reference dataset is an important task. Recently, the amount of ground truth data provided by volunteers has increased. Although ground truth data can provide information that can produc

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::ddb62a5aa980ece6074f2d2aba4b9454
https://doi.org/10.1117/12.2192533

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Algorithm developing of gross primary production from its capacity and a canopy conductance index using flux and global observing satellite data

Autor: Motomasa Daigo, Shinobu Furumi, Kanako Muramatsu

Publikováno v: SPIE Proceedings.

We plan to estimate gross primary production (GPP) using the SGLI sensor on-board the GCOM-C1 satellite after it is launched in 2017 by the Japan Aerospace Exploration Agency, as we have developed a GPP estimation algorithm that uses SGLI sensor data

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::1b015b0d082cda0d84cd04eae5d97a57
https://doi.org/10.1117/12.2195026

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