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The Use of Vegetation Indices on Temporal Mangrove Condition: A Case Study on Timbulsloko and Bedono, Demak
Corresponding Author(s) : Zahra Safira Aulia
Jurnal Ilmiah Perikanan dan Kelautan,
Vol. 16 No. 1 (2024): JURNAL ILMIAH PERIKANAN DAN KELAUTAN
Abstract
Abstract
Mangrove forests in Timbulsloko and Bedono have very dynamic conditions, due to tidal flooding and land subsidence that occur in these areas. Meanwhile, mangrove forests in the Timbulsloko and Bedono Village play an important role in preventing abrasion which often occurs in these areas. The importance of the mangroves function in this area makes it crucial to monitor their condition. Monitoring the condition of mangroves can be done by looking at their density through the vegetation index. Therefore, this study aimed to determine the best vegetation index to be used in the Timbulsloko and Bedono villages to monitor mangroves in 2016-2018, 2020, and 2022. The method in this research consisted of two stages, namely sentinel 2 image processing and the field survey. Image processing was used to determine the condition of mangroves based on several vegetation indices. Meanwhile, data collection in the field was utilized to validate several vegetation indices used in this study and conducted with the hemispherical photography method. Linear regression analysis was used to determine the most suitable vegetation index to be applied in the study area. The study found that NDVI vegetation index had the highest accuracy value, followed by SAVI, EVI, and MVI. The use of NDVI to see the changes in mangrove conditions showed an increase in the total area in each category. So, it can be concluded that the area and density of mangrove forests in the Bedono and Timbulsloko villages increased every year.
Highlight Research
- Mangroves in each region have different canopy density values.
- The use of the mangrove vegetation index will produce different accuracy values in different areas.
- LAI has a very strong relationship with the NDVI.
- The addition of area in the sparse mangrove category can be an indication of mangrove planting at the most recent time.
- In general, the research outcome will be valuable recommendation for mangrove rehabilitation in current target area.
Keywords
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- Aulia, Z. S., Hidayat, R. R., & Amron, A. (2022). Carbon sink estimation of mangrove vegetation using remote sensing in Segara Anakan, Cilacap. Jurnal Ilmiah Perikanan dan Kelautan, 14(1):130-141.
- Baloloy, A. B., Blanco, A. C., Ana, R. R. C. S., & Nadaoka, K. (2020). Development and application of a new mangrove vegetation index (MVI) for rapid and accurate mangrove mapping. ISPRS Journal of Photogrammetry and Remote Sensing, 166:95-117.
- Cahyaningsih, A. P., Deanova, A. K., Pristiawati, C. M., Ulumuddin, Y. I., Kusumawati, L., & Setyawan, A. D. (2022). Review: Causes and impacts of anthropogenic activities on mangrove deforestation and degradation in Indonesia. International Journal of Bonorowo Wetlands, 12(1):12-22.
- Conopio, M., Baloloy, A. B., Medina, J., & Blanco, A. C. (2021). Spatio-Temporal mapping and analysis of mangrove extents around manila bay using landsat satellite imagery and mangrove vegetation index (MVI). The International Society for Photogrammetry and Remote Sensing, 46(4/W6-2021):103-108.
- Damastuti, E., & de Groot, R. (2019). Participatory ecosystem service mapping to enhance community-based mangrove rehabilitation and management in Demak, Indonesia. Regional Environmental Change, 19(1):65-78.
- Damastuti, E., de Groot, R., Debrot, A. O., & Silvius, M. J. (2022). Effectiveness of community-based mangrove management for biodiversity conservation: A case study from Central Java, Indonesia. Trees, Forests and People, 7:1-13.
- Evangelides, C., & Nobajas, A. (2020). Red-Edge Normalised Difference Vegetation Index (NDVI705) from Sentinel-2 imagery to assess post-fire regeneration. Remote Sensing Applications: Society and Environment, 17:1-9.
- Handayani, S., Bengen, D. G., Nurjaya, I. W., Adrianto, L., & Wardiatno, Y. (2020). The sustainability status of mangrove ecosystem management in the rehabilitation area of Sayung Coastal Zone, Demak Regency, Central Java Indonesia. AACL Bioflux, 13(2):865-884.
- Harini, R., Ariani, R. D., Fistiningrum, W., & Ariestantya, D. (2019). Economic Valuation of Mangrove Management in Kulon Progo Regency. IOP Conference Series: Earth and Environmental Science, 256(1):1-11.
- Helmi, M., Satriadi, A., Suryoputro, A. A. D., Marwoto, J., Setiyono, H., & Hariyadi. (2018). Rehabilitation priority area assessment on death coral using cell based modeling approach at Parang Island, Karimunjawa National Park, Indonesia. International Journal of Civil Engineering and Technology, 9(11):2949-2961.
- Juniansah, A., Tama, G. C., Febriani, K. R., Baharain, M. N., Kanekaputra, T., Wulandari, Y. S., & Kamal, M. (2018). Mangrove Leaf Area Index Estimation Using Sentinel 2A Imagery in Teluk Ratai, Pesawaran Lampung. IOP Conference Series: Earth and Environmental Science, 165(1):1-8.
- Khatami, R., Mountrakis, G., & Stehman, S. V. (2016). A meta-analysis of remote sensing research on supervised pixel-based land-cover image classification processes: General guidelines for practitioners and future research. Remote Sensing of Environment, 177:89-100.
- Kuenzer, C., Bluemel, A., Gebhardt, S., Quoc, T. V., & Dech, S. (2011). Remote sensing of mangrove ecosystems: A review. Remote Sensing, 3(5):878-928.
- Li, K., Huang, X., Zhang, J., Sun, Z., Huang, J., Sun, C., Xie, Q., & Song, W. (2020). A new method for forest canopy hemispherical photography segmentation based on deep learning. Forests, 11(12):1-16.
- Marfai, M.A. (2014). Impact of sea level rise to coastal ecology: a case study on the northern part of Java Island, Indonesia. Quaestiones Geographicae, 33(1):107-114.
- Muhsoni, F. F., Sambah, A. B., Mahmudi, M., & Wiadnya, D. G. R. (2018). Comparison of different vegetation indices for assessing mangrove density using sentinel-2 imagery. International Journal of Geomate, 14(45):42-51.
- Muskananfola, M.R., Supriharyono, & Febrianto, S. (2020). Spatio-temporal analysis of shoreline change along the coast of Sayung Demak, Indonesia using Digital Shoreline Analysis System. Regional Studies in Marine Science, 34:1-9.
- Neri, M. P., Baloloy, A. B., & Blanco, A. C. (2021). Limitation assessment and workflow refinement of the Mangrove Vegetation Index (MVI)-based mapping methodology using Sentinel-2 Imagery. The International Society for Photogrammetry and Remote Sensing, 235-242,
- Onyena, A. P., & Sam, K. (2020). A review of the threat of oil exploitation to mangrove ecosystem: Insights from Niger Delta, Nigeria. In Global Ecology and Conservation, 22:1-11.
- Pamungkas, S. (2022). Analysis of vegetation index for NDVI, EVI-2, and SAVI for mangrove forest density using Google Earth Engine in Lembar Bay, Lombok Island. Geomatics International Conference, 1127(012034).
- Perdana, T. A., Suprijanto, J., Widowati, I., Pribadi, R., Iskandar, D. D., Firmansyah, Gunanto, E. Y. A., & Bailly, D. (2019). Assessing willingness-to-pay for coastal defenses: A case study in Timbulsloko Village, Sayung, Demak, Indonesia. IOP Conference Series: Earth and Environmental Science, 246(1):1-5.
- Purwanto, A., & Eviliyanto. (2022). Mangrove health analysis using sentinel-2a image with NDVI classification method (Case study: Sungai Batang-Kuala Secapah Mempawah Timur). GeoEco, 8(1):87-97.
- Rhyma, P. P., Norizah, K., Hamdan, O., Faridah-Hanum, I., & Zulfa, A. W. (2020). Integration of normalised different vegetation index and Soil-Adjusted Vegetation Index for mangrove vegetation delineation. Remote Sensing Applications: Society and Environment, 17:1-14.
- Rumora, L., Miler, M., & Medak, D. (2020). Impact of various atmospheric corrections on sentinel-2 land cover classification accuracy using machine learning classifiers. International Journal of Geo-Information, 9(277):1-23.
- Setyadi, G., Pribadi, R., Wijayanti, D. P., & Sugianto, D. N. (2021). Mangrove diversity and community structure of Mimika District, Papua, Indonesia. Biodiversitas, 22(8):3562-3570.
- Suwanto, A., Takarina, N. D., Koestoer, R. H., & Frimawaty, E. (2021). Diversity, biomass, covers, and NDVI of restored mangrove forests in Karawang and Subang Coasts, West Java, Indonesia. Journal of Biodiversity, 22(9):4115-4122.
- Tran, T. V., Reef, R., & Zhu, X. (2022). A Review of Spectral Indices for Mangrove Remote Sensing. Remote Sensing, 14(19):1-29.
- Wachid, M. N., Hapsara, R. P., Cahyo, R. D., Wahyu, G. N., Syarif, A. M., Umarhadi, D. A., Fitriani, A. N., Ramadhanningrum, D. P., & Widyatmanti, W. (2017). Mangrove canopy density analysis using Sentinel-2A imagery satellite data. IOP Conference Series: Earth and Environmental Science, 70(1):1-8.
- Yuwono, B. D., Subiyanto, S., Pratomo, A. S., & Najib. (2019). Time series of land subsidence rate on coastal Demak using GNSS CORS UDIP and DINSAR. E3S Web of Conferences, 94(04004):1-5.
- Xue, J., & Su, B. (2017). Significant remote sensing vegetation indices: A review of developments and applications. Journal of Sensors, 2017:1-17.
References
Aulia, Z. S., Hidayat, R. R., & Amron, A. (2022). Carbon sink estimation of mangrove vegetation using remote sensing in Segara Anakan, Cilacap. Jurnal Ilmiah Perikanan dan Kelautan, 14(1):130-141.
Baloloy, A. B., Blanco, A. C., Ana, R. R. C. S., & Nadaoka, K. (2020). Development and application of a new mangrove vegetation index (MVI) for rapid and accurate mangrove mapping. ISPRS Journal of Photogrammetry and Remote Sensing, 166:95-117.
Cahyaningsih, A. P., Deanova, A. K., Pristiawati, C. M., Ulumuddin, Y. I., Kusumawati, L., & Setyawan, A. D. (2022). Review: Causes and impacts of anthropogenic activities on mangrove deforestation and degradation in Indonesia. International Journal of Bonorowo Wetlands, 12(1):12-22.
Conopio, M., Baloloy, A. B., Medina, J., & Blanco, A. C. (2021). Spatio-Temporal mapping and analysis of mangrove extents around manila bay using landsat satellite imagery and mangrove vegetation index (MVI). The International Society for Photogrammetry and Remote Sensing, 46(4/W6-2021):103-108.
Damastuti, E., & de Groot, R. (2019). Participatory ecosystem service mapping to enhance community-based mangrove rehabilitation and management in Demak, Indonesia. Regional Environmental Change, 19(1):65-78.
Damastuti, E., de Groot, R., Debrot, A. O., & Silvius, M. J. (2022). Effectiveness of community-based mangrove management for biodiversity conservation: A case study from Central Java, Indonesia. Trees, Forests and People, 7:1-13.
Evangelides, C., & Nobajas, A. (2020). Red-Edge Normalised Difference Vegetation Index (NDVI705) from Sentinel-2 imagery to assess post-fire regeneration. Remote Sensing Applications: Society and Environment, 17:1-9.
Handayani, S., Bengen, D. G., Nurjaya, I. W., Adrianto, L., & Wardiatno, Y. (2020). The sustainability status of mangrove ecosystem management in the rehabilitation area of Sayung Coastal Zone, Demak Regency, Central Java Indonesia. AACL Bioflux, 13(2):865-884.
Harini, R., Ariani, R. D., Fistiningrum, W., & Ariestantya, D. (2019). Economic Valuation of Mangrove Management in Kulon Progo Regency. IOP Conference Series: Earth and Environmental Science, 256(1):1-11.
Helmi, M., Satriadi, A., Suryoputro, A. A. D., Marwoto, J., Setiyono, H., & Hariyadi. (2018). Rehabilitation priority area assessment on death coral using cell based modeling approach at Parang Island, Karimunjawa National Park, Indonesia. International Journal of Civil Engineering and Technology, 9(11):2949-2961.
Juniansah, A., Tama, G. C., Febriani, K. R., Baharain, M. N., Kanekaputra, T., Wulandari, Y. S., & Kamal, M. (2018). Mangrove Leaf Area Index Estimation Using Sentinel 2A Imagery in Teluk Ratai, Pesawaran Lampung. IOP Conference Series: Earth and Environmental Science, 165(1):1-8.
Khatami, R., Mountrakis, G., & Stehman, S. V. (2016). A meta-analysis of remote sensing research on supervised pixel-based land-cover image classification processes: General guidelines for practitioners and future research. Remote Sensing of Environment, 177:89-100.
Kuenzer, C., Bluemel, A., Gebhardt, S., Quoc, T. V., & Dech, S. (2011). Remote sensing of mangrove ecosystems: A review. Remote Sensing, 3(5):878-928.
Li, K., Huang, X., Zhang, J., Sun, Z., Huang, J., Sun, C., Xie, Q., & Song, W. (2020). A new method for forest canopy hemispherical photography segmentation based on deep learning. Forests, 11(12):1-16.
Marfai, M.A. (2014). Impact of sea level rise to coastal ecology: a case study on the northern part of Java Island, Indonesia. Quaestiones Geographicae, 33(1):107-114.
Muhsoni, F. F., Sambah, A. B., Mahmudi, M., & Wiadnya, D. G. R. (2018). Comparison of different vegetation indices for assessing mangrove density using sentinel-2 imagery. International Journal of Geomate, 14(45):42-51.
Muskananfola, M.R., Supriharyono, & Febrianto, S. (2020). Spatio-temporal analysis of shoreline change along the coast of Sayung Demak, Indonesia using Digital Shoreline Analysis System. Regional Studies in Marine Science, 34:1-9.
Neri, M. P., Baloloy, A. B., & Blanco, A. C. (2021). Limitation assessment and workflow refinement of the Mangrove Vegetation Index (MVI)-based mapping methodology using Sentinel-2 Imagery. The International Society for Photogrammetry and Remote Sensing, 235-242,
Onyena, A. P., & Sam, K. (2020). A review of the threat of oil exploitation to mangrove ecosystem: Insights from Niger Delta, Nigeria. In Global Ecology and Conservation, 22:1-11.
Pamungkas, S. (2022). Analysis of vegetation index for NDVI, EVI-2, and SAVI for mangrove forest density using Google Earth Engine in Lembar Bay, Lombok Island. Geomatics International Conference, 1127(012034).
Perdana, T. A., Suprijanto, J., Widowati, I., Pribadi, R., Iskandar, D. D., Firmansyah, Gunanto, E. Y. A., & Bailly, D. (2019). Assessing willingness-to-pay for coastal defenses: A case study in Timbulsloko Village, Sayung, Demak, Indonesia. IOP Conference Series: Earth and Environmental Science, 246(1):1-5.
Purwanto, A., & Eviliyanto. (2022). Mangrove health analysis using sentinel-2a image with NDVI classification method (Case study: Sungai Batang-Kuala Secapah Mempawah Timur). GeoEco, 8(1):87-97.
Rhyma, P. P., Norizah, K., Hamdan, O., Faridah-Hanum, I., & Zulfa, A. W. (2020). Integration of normalised different vegetation index and Soil-Adjusted Vegetation Index for mangrove vegetation delineation. Remote Sensing Applications: Society and Environment, 17:1-14.
Rumora, L., Miler, M., & Medak, D. (2020). Impact of various atmospheric corrections on sentinel-2 land cover classification accuracy using machine learning classifiers. International Journal of Geo-Information, 9(277):1-23.
Setyadi, G., Pribadi, R., Wijayanti, D. P., & Sugianto, D. N. (2021). Mangrove diversity and community structure of Mimika District, Papua, Indonesia. Biodiversitas, 22(8):3562-3570.
Suwanto, A., Takarina, N. D., Koestoer, R. H., & Frimawaty, E. (2021). Diversity, biomass, covers, and NDVI of restored mangrove forests in Karawang and Subang Coasts, West Java, Indonesia. Journal of Biodiversity, 22(9):4115-4122.
Tran, T. V., Reef, R., & Zhu, X. (2022). A Review of Spectral Indices for Mangrove Remote Sensing. Remote Sensing, 14(19):1-29.
Wachid, M. N., Hapsara, R. P., Cahyo, R. D., Wahyu, G. N., Syarif, A. M., Umarhadi, D. A., Fitriani, A. N., Ramadhanningrum, D. P., & Widyatmanti, W. (2017). Mangrove canopy density analysis using Sentinel-2A imagery satellite data. IOP Conference Series: Earth and Environmental Science, 70(1):1-8.
Yuwono, B. D., Subiyanto, S., Pratomo, A. S., & Najib. (2019). Time series of land subsidence rate on coastal Demak using GNSS CORS UDIP and DINSAR. E3S Web of Conferences, 94(04004):1-5.
Xue, J., & Su, B. (2017). Significant remote sensing vegetation indices: A review of developments and applications. Journal of Sensors, 2017:1-17.