Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Evaluating the VIIRS Imagery for Developing Near Real-Time Nationwide Vegetation Cover Monitoring in Indonesia

Yudi Setiawan
* ORCID logo ,
Kustiyo Kustiyo
,
Sahid Agustian Hudjimartsu
ORCID logo ,
Judin Purwanto
,
Riva Rovani
,
Anna Tosiani
,
Basyiruddin Usman
,
Tatik Kartika
ORCID logo ,
Novie Indriasari
,
Lilik Budi Prasetyo
ORCID logo ,
Belinda Arunarwati Margono
Version 1 : Received: 17 April 2024 / Approved: 18 April 2024 / Online: 18 April 2024 (10:57:27 CEST)

How to cite: Setiawan, Y.; Kustiyo, K.; Hudjimartsu, S.A.; Purwanto, J.; Rovani, R.; Tosiani, A.; Usman, B.; Kartika, T.; Indriasari, N.; Prasetyo, L.B.; Margono, B.A. Evaluating the VIIRS Imagery for Developing Near Real-Time Nationwide Vegetation Cover Monitoring in Indonesia. Preprints 2024, 2024041215. https://doi.org/10.20944/preprints202404.1215.v1 Setiawan, Y.; Kustiyo, K.; Hudjimartsu, S.A.; Purwanto, J.; Rovani, R.; Tosiani, A.; Usman, B.; Kartika, T.; Indriasari, N.; Prasetyo, L.B.; Margono, B.A. Evaluating the VIIRS Imagery for Developing Near Real-Time Nationwide Vegetation Cover Monitoring in Indonesia. Preprints 2024, 2024041215. https://doi.org/10.20944/preprints202404.1215.v1

Abstract

The necessity for precise and current data concerning the dynamics of land cover change in Indonesia is crucial for efforts to reduce natural vegetation cover due to agricultural expansion. The functionality of monitoring systems that incorporate Terra-MODIS is currently compromised by the limited availability of data for the immediate future. This study seeks to assess the potential of VIIRS satellite imagery in developing an early warning system for monitoring vegetation cover change in Indonesia. The Normalized Differential Open Area Index (NDOAI) computed from the 8-day’ VIIRS data was employed to detect changes in vegetation cover based on pixel-by-pixel subtraction in the NDOAI data time series. Evaluating the pixel-level accuracy of change detection is complicated due to the fact that we evaluate a change map at a coarser resolution than the Landsat-based reference map. The results revealed that increasing the threshold percentage is associated with improved accuracy. In change detection, there is often a trade-off between accuracy and sensitivity. A threshold that is too low may result in false positives, while a threshold that is too high may lead to missed changes. This study demonstrates that when a threshold value of less than 20% is applied, Landsat can identify vegetation cover changes at an earlier stage. Conversely, when a threshold value greater than 20% is employed, VIIRS will detect the change 4.5 days earlier than Landsat. Additionally, VIIRS is capable of detecting changes 25.4 days and 54.8 days faster than Landsat, respectively, when using thresholds of 40% and 75%.

Keywords

change detection; temporal vegetation dynamics; open area index; multi temporal VIIRS

Subject

Environmental and Earth Sciences, Remote Sensing

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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