MODELING AND FORECASTING CUMULATIVE EVI ANOMALIES USING SARIMA FOR BIOPHYSICAL MONITORING: A CASE STUDY IN THE PHILIPPINES

Understanding changes in vegetation cover that affect the biophysical conditions of a region can help in formulating policies to address current and future problems of terrestrial ecosystems such as deforestation and environmental degradation. This study focuses on developing a model that forecasts...

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Autores principales:	A. J. L. Diccion, J. Z. Duran
Formato:	article
Lenguaje:	EN
Publicado:	Copernicus Publications 2021
Materias:	Technology T Engineering (General). Civil engineering (General) TA1-2040 Applied optics. Photonics TA1501-1820
Acceso en línea:	https://doaj.org/article/fcaf3c3f6f3449b8a8f7b4436b802048
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spelling	oai:doaj.org-article:fcaf3c3f6f3449b8a8f7b4436b8020482021-11-19T00:17:13ZMODELING AND FORECASTING CUMULATIVE EVI ANOMALIES USING SARIMA FOR BIOPHYSICAL MONITORING: A CASE STUDY IN THE PHILIPPINES10.5194/isprs-archives-XLVI-4-W6-2021-141-20211682-17502194-9034https://doaj.org/article/fcaf3c3f6f3449b8a8f7b4436b8020482021-11-01T00:00:00Zhttps://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLVI-4-W6-2021/141/2021/isprs-archives-XLVI-4-W6-2021-141-2021.pdfhttps://doaj.org/toc/1682-1750https://doaj.org/toc/2194-9034Understanding changes in vegetation cover that affect the biophysical conditions of a region can help in formulating policies to address current and future problems of terrestrial ecosystems such as deforestation and environmental degradation. This study focuses on developing a model that forecasts the cumulative Enhanced Vegetation Index (EVI) anomalies as a tool for biophysical conditions monitoring in the Philippines. Satellite data from MODIS MYD13Q1 V6, which contains vegetation index per pixel at 16-day intervals with a resolution of 250 meters, were utilized. The cumulative EVI anomalies per instant were calculated in Google Earth Engine by aggregating the difference of a specific data point in 2011–2020 to a reference EVI mean computed from 2001–2010. The Error-Trend-Seasonality model shows that the cumulative EVI anomalies graph is non-stationary with an upward trend and seasonality. The upward trend of the cumulative EVI anomalies indicates the improvement of vegetation in the Philippines. To check the stationarity of the cumulative EVI anomalies data, the Augmented Dickey-Fuller test was utilized and the model was generated using Seasonal Autoregressive Integrated Moving Average model. Based on the analysis, the best-fit model for the cumulative EVI anomalies is SARIMA (1,1,0)(1,1,1)12 with a mean absolute percentage error (MAPE) of 13.26%. Thus, the proposed model can be used as a tool for biophysical assessment by monitoring and forecasting changes in vegetation and contribute to attaining the UN Sustainable Development Goals 2 and 15 – ‘Eliminating Hunger’ and ‘Life on Land’.A. J. L. DiccionJ. Z. DuranCopernicus PublicationsarticleTechnologyTEngineering (General). Civil engineering (General)TA1-2040Applied optics. PhotonicsTA1501-1820ENThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLVI-4-W6-2021, Pp 141-146 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Technology T Engineering (General). Civil engineering (General) TA1-2040 Applied optics. Photonics TA1501-1820
spellingShingle	Technology T Engineering (General). Civil engineering (General) TA1-2040 Applied optics. Photonics TA1501-1820 A. J. L. Diccion J. Z. Duran MODELING AND FORECASTING CUMULATIVE EVI ANOMALIES USING SARIMA FOR BIOPHYSICAL MONITORING: A CASE STUDY IN THE PHILIPPINES
description	Understanding changes in vegetation cover that affect the biophysical conditions of a region can help in formulating policies to address current and future problems of terrestrial ecosystems such as deforestation and environmental degradation. This study focuses on developing a model that forecasts the cumulative Enhanced Vegetation Index (EVI) anomalies as a tool for biophysical conditions monitoring in the Philippines. Satellite data from MODIS MYD13Q1 V6, which contains vegetation index per pixel at 16-day intervals with a resolution of 250 meters, were utilized. The cumulative EVI anomalies per instant were calculated in Google Earth Engine by aggregating the difference of a specific data point in 2011–2020 to a reference EVI mean computed from 2001–2010. The Error-Trend-Seasonality model shows that the cumulative EVI anomalies graph is non-stationary with an upward trend and seasonality. The upward trend of the cumulative EVI anomalies indicates the improvement of vegetation in the Philippines. To check the stationarity of the cumulative EVI anomalies data, the Augmented Dickey-Fuller test was utilized and the model was generated using Seasonal Autoregressive Integrated Moving Average model. Based on the analysis, the best-fit model for the cumulative EVI anomalies is SARIMA (1,1,0)(1,1,1)12 with a mean absolute percentage error (MAPE) of 13.26%. Thus, the proposed model can be used as a tool for biophysical assessment by monitoring and forecasting changes in vegetation and contribute to attaining the UN Sustainable Development Goals 2 and 15 – ‘Eliminating Hunger’ and ‘Life on Land’.
format	article
author	A. J. L. Diccion J. Z. Duran
author_facet	A. J. L. Diccion J. Z. Duran
author_sort	A. J. L. Diccion
title	MODELING AND FORECASTING CUMULATIVE EVI ANOMALIES USING SARIMA FOR BIOPHYSICAL MONITORING: A CASE STUDY IN THE PHILIPPINES
title_short	MODELING AND FORECASTING CUMULATIVE EVI ANOMALIES USING SARIMA FOR BIOPHYSICAL MONITORING: A CASE STUDY IN THE PHILIPPINES
title_full	MODELING AND FORECASTING CUMULATIVE EVI ANOMALIES USING SARIMA FOR BIOPHYSICAL MONITORING: A CASE STUDY IN THE PHILIPPINES
title_fullStr	MODELING AND FORECASTING CUMULATIVE EVI ANOMALIES USING SARIMA FOR BIOPHYSICAL MONITORING: A CASE STUDY IN THE PHILIPPINES
title_full_unstemmed	MODELING AND FORECASTING CUMULATIVE EVI ANOMALIES USING SARIMA FOR BIOPHYSICAL MONITORING: A CASE STUDY IN THE PHILIPPINES
title_sort	modeling and forecasting cumulative evi anomalies using sarima for biophysical monitoring: a case study in the philippines
publisher	Copernicus Publications
publishDate	2021
url	https://doaj.org/article/fcaf3c3f6f3449b8a8f7b4436b802048
work_keys_str_mv	AT ajldiccion modelingandforecastingcumulativeevianomaliesusingsarimaforbiophysicalmonitoringacasestudyinthephilippines AT jzduran modelingandforecastingcumulativeevianomaliesusingsarimaforbiophysicalmonitoringacasestudyinthephilippines
_version_	1718420646076088320

MODELING AND FORECASTING CUMULATIVE EVI ANOMALIES USING SARIMA FOR BIOPHYSICAL MONITORING: A CASE STUDY IN THE PHILIPPINES

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