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ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Articles | Volume X-5-2024
https://doi.org/10.5194/isprs-annals-X-5-2024-205-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/isprs-annals-X-5-2024-205-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
11 Nov 2024
| 11 Nov 2024
Towards Nationwide Mapping of Seagrasses in the Philippines: Empowering Students through Remote Sensing Education
Ayin Tamondong
Department of Geodetic Engineering, University of the Philippines, Quezon City, Philippines
Ariel Blanco
Department of Geodetic Engineering, University of the Philippines, Quezon City, Philippines
Space Information Infrastructure Bureau, Philippine Space Agency, Quezon City, Philippines
Kayziel Martinez
Department of Geodetic Engineering, University of the Philippines, Quezon City, Philippines
Christian Candido
Department of Geodetic Engineering, University of the Philippines, Quezon City, Philippines
Space Information Infrastructure Bureau, Philippine Space Agency, Quezon City, Philippines
Kazuo Nadaoka
School of Environment and Society, Tokyo Institute of Technology, Tokyo, Japan
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Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W8-2023, 9–16, https://doi.org/10.5194/isprs-archives-XLVIII-4-W8-2023-9-2024, https://doi.org/10.5194/isprs-archives-XLVIII-4-W8-2023-9-2024, 2024
P. L. Borrega, Y. A. Felisilda, C. J. Sarmiento, and A. Tamondong
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W8-2023, 69–75, https://doi.org/10.5194/isprs-archives-XLVIII-4-W8-2023-69-2024, https://doi.org/10.5194/isprs-archives-XLVIII-4-W8-2023-69-2024, 2024
D. B. Cabuyadao, C. P. Paladin, A. M. Tamondong, and J. M. Medina
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W8-2023, 85–92, https://doi.org/10.5194/isprs-archives-XLVIII-4-W8-2023-85-2024, https://doi.org/10.5194/isprs-archives-XLVIII-4-W8-2023-85-2024, 2024
C. G. Candido, A. C. Blanco, N. J. B. Borlongan, and R. M. de la Cruz
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W8-2023, 93–99, https://doi.org/10.5194/isprs-archives-XLVIII-4-W8-2023-93-2024, https://doi.org/10.5194/isprs-archives-XLVIII-4-W8-2023-93-2024, 2024
C. G. Candido and J. A. Principe
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W8-2023, 101–106, https://doi.org/10.5194/isprs-archives-XLVIII-4-W8-2023-101-2024, https://doi.org/10.5194/isprs-archives-XLVIII-4-W8-2023-101-2024, 2024
R. M. de la Cruz, D. C. D. M. Vergara, J. I. A. Tabardillo, A. J. C. Sabuito, N. J. B. Borlongan, K. M. Bantay, R. R. Diwa, and A. C. Blanco
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W8-2023, 157–162, https://doi.org/10.5194/isprs-archives-XLVIII-4-W8-2023-157-2024, https://doi.org/10.5194/isprs-archives-XLVIII-4-W8-2023-157-2024, 2024
R. R. Diwa, N. J. B. Borlongan, J. I. A. Tabardillo, A. J. C. Sabuito, C. G. Candido, R. M. de la Cruz, and A. C. Blanco
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W8-2023, 175–181, https://doi.org/10.5194/isprs-archives-XLVIII-4-W8-2023-175-2024, https://doi.org/10.5194/isprs-archives-XLVIII-4-W8-2023-175-2024, 2024
J. B. L. C. Dumalag, A. C. Blanco, and A. M. Tamondong
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W8-2023, 195–202, https://doi.org/10.5194/isprs-archives-XLVIII-4-W8-2023-195-2024, https://doi.org/10.5194/isprs-archives-XLVIII-4-W8-2023-195-2024, 2024
K. A. N. Amaro, L. M. G. Cortez, J. M. Medina, and A. C. Blanco
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W9-2024, 29–36, https://doi.org/10.5194/isprs-archives-XLVIII-4-W9-2024-29-2024, https://doi.org/10.5194/isprs-archives-XLVIII-4-W9-2024-29-2024, 2024
C. D. C. Zablan, A. C. Blanco, Y. H. Primavera-Tirol, and K. Nadaoka
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W2-2023, 1965–1971, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1965-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1965-2023, 2023
A. C. Blanco and C. R. Perez
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-W2-2023, 1331–1336, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1331-2023, https://doi.org/10.5194/isprs-archives-XLVIII-1-W2-2023-1331-2023, 2023
M. B. A. I. Zamora and A. C. Blanco
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-1-W1-2023, 379–386, https://doi.org/10.5194/isprs-annals-X-1-W1-2023-379-2023, https://doi.org/10.5194/isprs-annals-X-1-W1-2023-379-2023, 2023
Masaya Yoshikai, Takashi Nakamura, Eugene C. Herrera, Rempei Suwa, Rene Rollon, Raghab Ray, Keita Furukawa, and Kazuo Nadaoka
Geosci. Model Dev., 16, 5847–5863, https://doi.org/10.5194/gmd-16-5847-2023, https://doi.org/10.5194/gmd-16-5847-2023, 2023
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Due to complex root system structures, representing the impacts of Rhizophora mangroves on flow in hydrodynamic models has been challenging. This study presents a new drag and turbulence model that leverages an empirical model for root systems. The model can be applied without rigorous measurements of root structures and showed high performance in flow simulations; this may provide a better understanding of hydrodynamics and related transport processes in Rhizophora mangrove forests.
Raghab Ray, Rempei Suwa, Toshihiro Miyajima, Jeffrey Munar, Masaya Yoshikai, Maria Lourdes San Diego-McGlone, and Kazuo Nadaoka
Biogeosciences, 20, 911–928, https://doi.org/10.5194/bg-20-911-2023, https://doi.org/10.5194/bg-20-911-2023, 2023
Short summary
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Mangroves are blue carbon ecosystems known to store large amounts of organic carbon in the sediments. This study is a first attempt to apply a chronosequence (or space-for-time substitution) approach to evaluate the distribution and accumulation rate of carbon in a 30-year-old (maximum age) restored mangrove forest. Using this approach, the contribution of restored or planted mangroves to sedimentary organic carbon presents an increasing pattern with mangrove age.
D. C. D. M. Vergara and A. C. Blanco
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W6-2022, 451–456, https://doi.org/10.5194/isprs-archives-XLVIII-4-W6-2022-451-2023, https://doi.org/10.5194/isprs-archives-XLVIII-4-W6-2022-451-2023, 2023
D. C. D. M. Vergara, A. C. Blanco, J. J. S. Marciano Jr., S. F. Meneses III, N. J. B. Borlongan, and A. J. C. Sabuito
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W6-2022, 457–464, https://doi.org/10.5194/isprs-archives-XLVIII-4-W6-2022-457-2023, https://doi.org/10.5194/isprs-archives-XLVIII-4-W6-2022-457-2023, 2023
M. I. D. Mabalot, L. S. Sumera, A. C. Blanco, and B. G. Carcellar
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W6-2022, 201–209, https://doi.org/10.5194/isprs-archives-XLVIII-4-W6-2022-201-2023, https://doi.org/10.5194/isprs-archives-XLVIII-4-W6-2022-201-2023, 2023
A. Manuel and A. C. Blanco
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W6-2022, 217–221, https://doi.org/10.5194/isprs-archives-XLVIII-4-W6-2022-217-2023, https://doi.org/10.5194/isprs-archives-XLVIII-4-W6-2022-217-2023, 2023
J. M. Medina, R. L. Jalbuena, R. A. B. Torres, and A. C. Blanco
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W6-2022, 223–230, https://doi.org/10.5194/isprs-archives-XLVIII-4-W6-2022-223-2023, https://doi.org/10.5194/isprs-archives-XLVIII-4-W6-2022-223-2023, 2023
C. D. C. Zablan, A. C. Blanco, K. Nadaoka, K. P. Martinez, and A. B. Baloloy
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W6-2022, 391–401, https://doi.org/10.5194/isprs-archives-XLVIII-4-W6-2022-391-2023, https://doi.org/10.5194/isprs-archives-XLVIII-4-W6-2022-391-2023, 2023
C. D. C. Zablan, A. A. Nerves, A. C. Blanco, A. B. Baloloy, K. P. Martinez, and M. E. P. Neri
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W6-2022, 403–413, https://doi.org/10.5194/isprs-archives-XLVIII-4-W6-2022-403-2023, https://doi.org/10.5194/isprs-archives-XLVIII-4-W6-2022-403-2023, 2023
A. C. Blanco, B. J. J. Harder, and I. A. R. Teh
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W6-2022, 87–92, https://doi.org/10.5194/isprs-archives-XLVIII-4-W6-2022-87-2023, https://doi.org/10.5194/isprs-archives-XLVIII-4-W6-2022-87-2023, 2023
B. A. B. Recto, R. A. B. Torres, R. V. Ramos, A. M. Tamondong, M. G. Cayetano, and B. J. D. Jiao
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-4-W1-2022, 639–645, https://doi.org/10.5194/isprs-annals-X-4-W1-2022-639-2023, https://doi.org/10.5194/isprs-annals-X-4-W1-2022-639-2023, 2023
R. A. B. Torres, R. V. Ramos, B. A. B. Recto, A. M. Tamondong, B. J. D. Jiao, and M. G. Cayetano
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-4-W1-2022, 729–736, https://doi.org/10.5194/isprs-annals-X-4-W1-2022-729-2023, https://doi.org/10.5194/isprs-annals-X-4-W1-2022-729-2023, 2023
Faisal Amri, Takashi Nakamura, Atsushi Watanabe, Aditiya R. Kartadikaria, and Kazuo Nadaoka
EGUsphere, https://doi.org/10.5194/egusphere-2022-1067, https://doi.org/10.5194/egusphere-2022-1067, 2022
Preprint archived
Short summary
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This study investigates the sea-air CO2 exchange variabilities across the Tropical Maritime Continent between 2010–2019 using numerical model experiment. Model results suggested some periods with higher-than-usual CO2 degassing to the atmosphere related to Indo-Pacific climatic events over the 2010–2019 course. Study conducted here may give insights about sea-air CO2 exchange dynamics in the undersampled area that poorly represented in many climate models and global reconstruction product.
S. F. Meneses III and A. C. Blanco
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 1139–1146, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-1139-2022, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-1139-2022, 2022
A. C. Blanco
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2022, 1077–1082, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-1077-2022, https://doi.org/10.5194/isprs-archives-XLIII-B3-2022-1077-2022, 2022
Masaya Yoshikai, Takashi Nakamura, Rempei Suwa, Sahadev Sharma, Rene Rollon, Jun Yasuoka, Ryohei Egawa, and Kazuo Nadaoka
Biogeosciences, 19, 1813–1832, https://doi.org/10.5194/bg-19-1813-2022, https://doi.org/10.5194/bg-19-1813-2022, 2022
Short summary
Short summary
This study presents a new individual-based vegetation model to investigate salinity control on mangrove productivity. The model incorporates plant hydraulics and tree competition and predicts unique and complex patterns of mangrove forest structures that vary across soil salinity gradients. The presented model does not hold an empirical expression of salinity influence on productivity and thus may provide a better understanding of mangrove forest dynamics in future climate change.
E. R. G. Martinez, R. J. L. Argamosa, R. B. Torres, and A. C. Blanco
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4-W3-2021, 211–214, https://doi.org/10.5194/isprs-archives-XLVI-4-W3-2021-211-2022, https://doi.org/10.5194/isprs-archives-XLVI-4-W3-2021-211-2022, 2022
R. J. L. Argamosa, A. C. Blanco, and R. B. Reyes
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4-W3-2021, 33–38, https://doi.org/10.5194/isprs-archives-XLVI-4-W3-2021-33-2022, https://doi.org/10.5194/isprs-archives-XLVI-4-W3-2021-33-2022, 2022
M. Conopio, A. B. Baloloy, J. Medina, and A. C. Blanco
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4-W6-2021, 103–108, https://doi.org/10.5194/isprs-archives-XLVI-4-W6-2021-103-2021, https://doi.org/10.5194/isprs-archives-XLVI-4-W6-2021-103-2021, 2021
J. E. Escoto, A. C. Blanco, R. J. Argamosa, and J. M. Medina
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4-W6-2021, 161–168, https://doi.org/10.5194/isprs-archives-XLVI-4-W6-2021-161-2021, https://doi.org/10.5194/isprs-archives-XLVI-4-W6-2021-161-2021, 2021
N. B. Gatdula, B. J. D. Jiao, J. A. Laurente, A. C. Blanco, J. M. Medina, D. Fargas, and G. A. Narciso
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4-W6-2021, 169–176, https://doi.org/10.5194/isprs-archives-XLVI-4-W6-2021-169-2021, https://doi.org/10.5194/isprs-archives-XLVI-4-W6-2021-169-2021, 2021
M. L. R. Gonzaga, M. T. S. Wong, A. C. Blanco, and J. A. Principe
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4-W6-2021, 177–184, https://doi.org/10.5194/isprs-archives-XLVI-4-W6-2021-177-2021, https://doi.org/10.5194/isprs-archives-XLVI-4-W6-2021-177-2021, 2021
A. Manuel, A. C. Blanco, O. Cabrera, and M. L. San Diego-McGlone
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4-W6-2021, 207–212, https://doi.org/10.5194/isprs-archives-XLVI-4-W6-2021-207-2021, https://doi.org/10.5194/isprs-archives-XLVI-4-W6-2021-207-2021, 2021
G. A. M. Narciso, D. C. Fargas Jr., C. G. Candido, J. M. Medina, M. L. P. Tinio, and A. C. Blanco
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4-W6-2021, 227–234, https://doi.org/10.5194/isprs-archives-XLVI-4-W6-2021-227-2021, https://doi.org/10.5194/isprs-archives-XLVI-4-W6-2021-227-2021, 2021
M. P. Neri, A. B. Baloloy, and A. C. Blanco
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4-W6-2021, 235–242, https://doi.org/10.5194/isprs-archives-XLVI-4-W6-2021-235-2021, https://doi.org/10.5194/isprs-archives-XLVI-4-W6-2021-235-2021, 2021
R. A. B. Rivera, E. N. B. Idago, A. C. Blanco, and K. A. P. Vergara
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4-W6-2021, 249–256, https://doi.org/10.5194/isprs-archives-XLVI-4-W6-2021-249-2021, https://doi.org/10.5194/isprs-archives-XLVI-4-W6-2021-249-2021, 2021
K. V. Ticman, S. G. Salmo III, K. E. Cabello, M. Q. Germentil, D. M. Burgos, and A. C. Blanco
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4-W6-2021, 295–301, https://doi.org/10.5194/isprs-archives-XLVI-4-W6-2021-295-2021, https://doi.org/10.5194/isprs-archives-XLVI-4-W6-2021-295-2021, 2021
R. B. Torres and A. C. Blanco
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-4-W6-2021, 303–311, https://doi.org/10.5194/isprs-archives-XLVI-4-W6-2021-303-2021, https://doi.org/10.5194/isprs-archives-XLVI-4-W6-2021-303-2021, 2021
A. Tamondong, T. Nakamura, T. E. A. Quiros, and K. Nadaoka
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2021, 109–116, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-109-2021, https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-109-2021, 2021
K. P. Martinez, D. F. M. Burgos, A. C. Blanco, and S. G. Salmo III
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2021, 109–115, https://doi.org/10.5194/isprs-annals-V-3-2021-109-2021, https://doi.org/10.5194/isprs-annals-V-3-2021-109-2021, 2021
D. C. Fargas Jr., G. A. M. Narciso, and A. C. Blanco
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2021, 117–124, https://doi.org/10.5194/isprs-annals-V-3-2021-117-2021, https://doi.org/10.5194/isprs-annals-V-3-2021-117-2021, 2021
K. E. Cabello, M. Q. Germentil, A. C. Blanco, E. G. Macatulad, and S. G. Salmo III
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2021, 243–250, https://doi.org/10.5194/isprs-annals-V-3-2021-243-2021, https://doi.org/10.5194/isprs-annals-V-3-2021-243-2021, 2021
The International Society for Photogrammetry and Remote Sensing is a non-governmental organization devoted to the development of international cooperation for the advancement of photogrammetry and remote sensing and their applications. The Society operates without any discrimination on grounds of race, religion, nationality, or political philosophy.
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