The impact of Mânuka-dominated riparian on lake's water quality - a multi-source remote sensing approach

Simna Rassak; Alvaro Orsi; Albert Bifet; Maria Jesus Gutierrez Gines; Kristin Bohm; Kevin I.Kai Wang; Akshat Bisht

doi:10.1109/MIGARS61408.2024.10544620

The impact of Mânuka-dominated riparian on lake's water quality - a multi-source remote sensing approach

Simna Rassak
, Alvaro Orsi
, Albert Bifet
, Maria Jesus Gutierrez Gines
, Kristin Bohm
, Kevin I.Kai Wang
, Akshat Bisht

University of Waikato
Institute of Environmental Science And Research(ESR)
University of Auckland

Résultats de recherche: Le chapitre dans un livre, un rapport, une anthologie ou une collection › Contribution à une conférence › Revue par des pairs

Résumé

Mânuka trees in riparian plantings on lake banks can improve water quality and its ecosystem. In this study, we used multisource remote sensing data analysis on a mânuka experiment plot in Lake Waikare catchment to understand the role of Mânuka trees in mitigating pollution and climate change effects. We evaluate experiment plots with and without Mânuka trees. We compare soil moisture sensors in both these areas and calculate soil water retention and soil loss.

langue originale	Anglais
titre	2024 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2024
Editeur	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronique)	9798350389678
Les DOIs	https://doi.org/10.1109/MIGARS61408.2024.10544620
état	Publié - 1 janv. 2024
Modification externe	Oui
Evénement	2024 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2024 - Wellington, Nouvelle-Zélande Durée: 8 avr. 2024 → 10 avr. 2024

Série de publications

Nom	2024 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2024

Une conférence

Une conférence	2024 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2024
Pays/Territoire	Nouvelle-Zélande
La ville	Wellington
période	8/04/24 → 10/04/24

SDG des Nations Unies

Ce résultat contribue à ou aux Objectifs de développement durable suivants

SDG 13 Action climatique

Accès au document

10.1109/MIGARS61408.2024.10544620

Contient cette citation

Rassak, S., Orsi, A., Bifet, A., Gines, M. J. G., Bohm, K., Wang, K. I. K., & Bisht, A. (2024). The impact of Mânuka-dominated riparian on lake's water quality - a multi-source remote sensing approach. Dans 2024 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2024 (2024 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2024). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MIGARS61408.2024.10544620

Rassak, Simna ; Orsi, Alvaro ; Bifet, Albert et al. / The impact of Mânuka-dominated riparian on lake's water quality - a multi-source remote sensing approach. 2024 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2024. Institute of Electrical and Electronics Engineers Inc., 2024. (2024 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2024).

@inproceedings{806cde6ba96d44768de75aa746c3684f,

title = "The impact of M{\^a}nuka-dominated riparian on lake's water quality - a multi-source remote sensing approach",

abstract = "M{\^a}nuka trees in riparian plantings on lake banks can improve water quality and its ecosystem. In this study, we used multisource remote sensing data analysis on a m{\^a}nuka experiment plot in Lake Waikare catchment to understand the role of M{\^a}nuka trees in mitigating pollution and climate change effects. We evaluate experiment plots with and without M{\^a}nuka trees. We compare soil moisture sensors in both these areas and calculate soil water retention and soil loss.",

keywords = "remote sensing, soil loss, soil water retention, vegetation indices",

author = "Simna Rassak and Alvaro Orsi and Albert Bifet and Gines, \{Maria Jesus Gutierrez\} and Kristin Bohm and Wang, \{Kevin I.Kai\} and Akshat Bisht",

note = "Publisher Copyright: {\textcopyright} 2024 IEEE.; 2024 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2024 ; Conference date: 08-04-2024 Through 10-04-2024",

year = "2024",

month = jan,

day = "1",

doi = "10.1109/MIGARS61408.2024.10544620",

language = "English",

series = "2024 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2024",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2024 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2024",

}

Rassak, S, Orsi, A, Bifet, A, Gines, MJG, Bohm, K, Wang, KIK & Bisht, A 2024, The impact of Mânuka-dominated riparian on lake's water quality - a multi-source remote sensing approach. Dans 2024 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2024. 2024 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2024, Institute of Electrical and Electronics Engineers Inc., 2024 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2024, Wellington, Nouvelle-Zélande, 8/04/24. https://doi.org/10.1109/MIGARS61408.2024.10544620

The impact of Mânuka-dominated riparian on lake's water quality - a multi-source remote sensing approach. / Rassak, Simna; Orsi, Alvaro; Bifet, Albert et al.
2024 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2024. Institute of Electrical and Electronics Engineers Inc., 2024. (2024 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2024).

Résultats de recherche: Le chapitre dans un livre, un rapport, une anthologie ou une collection › Contribution à une conférence › Revue par des pairs

TY - GEN

T1 - The impact of Mânuka-dominated riparian on lake's water quality - a multi-source remote sensing approach

AU - Rassak, Simna

AU - Orsi, Alvaro

AU - Bifet, Albert

AU - Gines, Maria Jesus Gutierrez

AU - Bohm, Kristin

AU - Wang, Kevin I.Kai

AU - Bisht, Akshat

PY - 2024/1/1

Y1 - 2024/1/1

N2 - Mânuka trees in riparian plantings on lake banks can improve water quality and its ecosystem. In this study, we used multisource remote sensing data analysis on a mânuka experiment plot in Lake Waikare catchment to understand the role of Mânuka trees in mitigating pollution and climate change effects. We evaluate experiment plots with and without Mânuka trees. We compare soil moisture sensors in both these areas and calculate soil water retention and soil loss.

AB - Mânuka trees in riparian plantings on lake banks can improve water quality and its ecosystem. In this study, we used multisource remote sensing data analysis on a mânuka experiment plot in Lake Waikare catchment to understand the role of Mânuka trees in mitigating pollution and climate change effects. We evaluate experiment plots with and without Mânuka trees. We compare soil moisture sensors in both these areas and calculate soil water retention and soil loss.

KW - remote sensing

KW - soil loss

KW - soil water retention

KW - vegetation indices

U2 - 10.1109/MIGARS61408.2024.10544620

DO - 10.1109/MIGARS61408.2024.10544620

M3 - Conference contribution

AN - SCOPUS:85196085886

T3 - 2024 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2024

BT - 2024 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2024

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2024 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2024

Y2 - 8 April 2024 through 10 April 2024

ER -

Rassak S, Orsi A, Bifet A, Gines MJG, Bohm K, Wang KIK et al. The impact of Mânuka-dominated riparian on lake's water quality - a multi-source remote sensing approach. Dans 2024 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2024. Institute of Electrical and Electronics Engineers Inc. 2024. (2024 International Conference on Machine Intelligence for GeoAnalytics and Remote Sensing, MIGARS 2024). doi: 10.1109/MIGARS61408.2024.10544620

The impact of Mânuka-dominated riparian on lake's water quality - a multi-source remote sensing approach

Résumé

Série de publications

Une conférence

SDG des Nations Unies

Accès au document

Empreinte digitale

Contient cette citation