Comparative Spatio-temporal Analysis Using NDVI, NDBI, and SAVI based on Landsat 8/9 OLI (2013, 2018 and 2024)
DOI:
https://doi.org/10.30865/klik.v5i1.2088Keywords:
Comparative; Spatio-temporal Analysis; NDVI; NDBI; SAVIAbstract
The research on the comparative spatio-temporal analysis of NDVI, NDBI, and SAVI values for Kumo Island, Kakara Island, and Tagalaya Island from 2013, 2018, and 2024 offers insights into environmental dynamics influenced by human activities, particularly tourism. Key findings indicate that NDVI values, reflecting vegetation health, improved across all three islands, with Kumo Island showing the most significant increase from -0.0549 in 2013 to 0.2456 in 2024. NDBI values, indicative of urban development, also rose on all islands. Kumo Island's NDBI increased from -0.8734 in 2013 to -0.6561 in 2024, and Kakara Island's NDBI rose from -0.8838 in 2013 to -0.7183 in 2024. Tagalaya Island saw a more moderate rise in NDBI values from -0.8818 in 2013 to -0.7118 in 2024, suggesting controlled urban expansion. SAVI values, reflecting soil and vegetation conditions, also improved. Kumo Island's SAVI increased from -0.0365 in 2013 to 0.1138 in 2024, Kakara Island's from -0.1161 to -0.0319, and Tagalaya Island's from -0.1652 to -0.0732. These trends indicate effective soil conservation and sustainable land use practices. The findings highlight the dual impact of urbanization and environmental conservation, suggesting that while urbanization progresses, vegetation health and soil conditions are concurrently improving. This underscores the potential for balancing development with ecological sustainability through targeted conservation efforts. Future research should identify specific practices and policies contributing to these positive trends, ensuring economic development and environmental preservation can continue to coexist harmoniously on these islands
Downloads
References
E. Xu et al., “Assessing burn severity and vegetation restoration in Alberta’s boreal forests following the 2016 Fort McMurray wildfire–a remote sensing time-series study,” Sustain. Environ., vol. 10, no. 1, 2024, doi: 10.1080/27658511.2024.2361569.
P. Mafuratidze, T. P. Chibarabada, M. D. Shekede, and M. Masocha, “A new four-stage approach based on normalized vegetation indices for detecting and mapping sugarcane hail damage using multispectral remotely sensed data,” Geocarto Int., vol. 38, no. 1, p., 2023, doi: 10.1080/10106049.2023.2245788.
B. Chisadza, F. Ncube, M. Macherera, T. Bangira, and O. Gwate, “Spatio-temporal variations in the ecological vulnerability of the Upper Mzingwane sub-catchment of Zimbabwe,” Geomatics, Nat. Hazards Risk, vol. 14, no. 1, p., 2023, doi: 10.1080/19475705.2023.2190857.
G. Sun et al., “Spatial–temporal change patterns of vegetation coverage in China and its driving mechanisms over the past 20 years based on the concept of geographic division,” Geomatics, Nat. Hazards Risk, vol. 11, no. 1, pp. 2263–2281, 2020, doi: 10.1080/19475705.2020.1837967.
A. Ahmad et al., “Unveiling urban violence crime in the State of the Selangor, Kuala Lumpur and Putrajaya: a spatial–temporal investigation of violence crime in Malaysia’s key cities,” Cogent Soc. Sci., vol. 10, no. 1, p., 2024, doi: 10.1080/23311886.2024.2347411.
S. Kwofie, C. Nyamekye, L. Appiah Boamah, F. Owusu Adjei, R. Arthur, and E. Agyapong, “Urban growth nexus to land surface temperature in Ghana,” Cogent Eng., vol. 9, no. 1, 2022, doi: 10.1080/23311916.2022.2143045.
A. Abdelkarim, “Monitoring and forecasting of land use/land cover (LULC) in Al-Hassa Oasis, Saudi Arabia based on the integration of the Cellular Automata (CA) and the Cellular Automata-Markov Model (CA-Markov),” Geol. Ecol. Landscapes, vol. 00, no. 00, pp. 1–32, 2023, doi: 10.1080/24749508.2022.2163741.
T. Wang, J. He, and Z. Ning, “Observations on the development of townships around mega-tourist attraction caused by land use change—the case of Zhangjiajie, China,” J. Asian Archit. Build. Eng., vol. 22, no. 5, pp. 3006–3027, 2023, doi: 10.1080/13467581.2023.2167494.
F. Zhang et al., “Dynamic monitoring and analysis of factors influencing ecological quality in rapidly urbanizing areas based on the Google Earth Engine,” Geocarto Int., vol. 38, no. 1, p., 2023, doi: 10.1080/10106049.2023.2256299.
Z. Deng et al., “Spatio-temporal study on coupling coordination between urbanization and eco-resilience in the Erhai Lake Basin,” All Earth, vol. 36, no. 1, pp. 1–20, 2024, doi: 10.1080/27669645.2024.2317053.
P. C. Mohanty, S. Shetty, R. S. Mahendra, R. K. Nayak, L. K. Sharma, and E. P. Rama Rao, “Spatio-temporal changes of mangrove cover and its impact on bio-carbon flux along the West Bengal coast, Northeast coast of India,” Eur. J. Remote Sens., vol. 54, no. 1, pp. 524–536, 2021, doi: 10.1080/22797254.2021.1977183.
F. Qian, Y. Chi, R. Lal, and K. Lorenz, “Spatio-temporal characteristics of cultivated land fragmentation in different landform areas with a case study in Northeast China,” Ecosyst. Heal. Sustain., vol. 6, no. 1, 2020, doi: 10.1080/20964129.2020.1800415.
Y. Sun et al., “Spatio-temporal evolution of land subsidence and susceptibility zonation of associated ground fissures in the urban area of loess plateau: a case in Xianyang city, China,” Geomatics, Nat. Hazards Risk, vol. 15, no. 1, p., 2024, doi: 10.1080/19475705.2024.2341181.
T. C. Segaran et al., “Mapping the Link between Climate Change and Mangrove Forest: A Global Overview of the Literature,” Forests, vol. 14, no. 2, pp. 1–32, 2023, doi: 10.3390/f14020421.
Y. Peng and Q. Wang, “Spatial distribution and influencing factors of settlements in the farming–pastoral ecotone of Inner Mongolia, China,” Ecosyst. Heal. Sustain., vol. 6, no. 1, 2020, doi: 10.1080/20964129.2020.1771213.
X. Zheng et al., “Construction and spatio-temporal derivation of hazardous chemical leakage disaster chain,” Int. J. Image Data Fusion, vol. 12, no. 4, pp. 335–348, 2021, doi: 10.1080/19479832.2021.1958929.
S. S. Wahla, J. H. Kazmi, and A. Tariq, “Mapping and monitoring of spatio-temporal land use and land cover changes and relationship with normalized satellite indices and driving factors,” Geol. Ecol. Landscapes, vol. 00, no. 00, pp. 1–17, 2023, doi: 10.1080/24749508.2023.2187567.
N. Farmonov et al., “Combining PlanetScope and Sentinel-2 images with environmental data for improved wheat yield estimation,” Int. J. Digit. Earth, vol. 16, no. 1, pp. 847–867, 2023, doi: 10.1080/17538947.2023.2186505.
X. Zhong et al., “Land surface emissivity retrieval from SDGSAT-1: comparison of LSE products with different spatial resolutions,” Int. J. Digit. Earth, vol. 17, no. 1, pp. 1–21, 2024, doi: 10.1080/17538947.2023.2297940.
P. Singh, A. Sarkar Chaudhuri, P. Verma, V. K. Singh, and S. R. Meena, “Earth observation data sets in monitoring of urbanization and urban heat island of Delhi, India,” Geomatics, Nat. Hazards Risk, vol. 13, no. 1, pp. 1762–1779, 2022, doi: 10.1080/19475705.2022.2097452.
P. T. Brandt, V. D’Orazio, L. Khan, Y. F. Li, J. Osorio, and M. Sianan, “Conflict forecasting with event data and spatio-temporal graph convolutional networks,” Int. Interact., vol. 48, no. 4, pp. 800–822, 2022, doi: 10.1080/03050629.2022.2036987.
S. Hussain and S. Karuppannan, “Land use/land cover changes and their impact on land surface temperature using remote sensing technique in district Khanewal, Punjab Pakistan,” Geol. Ecol. Landscapes, vol. 7, no. 1, pp. 46–58, 2023, doi: 10.1080/24749508.2021.1923272.
D. N. Handiani, A. Heriati, and W. A. Gunawan, “Comparison of coastal vulnerability assessment for Subang Regency in North Coast West Java-Indonesia,” Geomatics, Nat. Hazards Risk, vol. 13, no. 1, pp. 1178–1206, 2022, doi: 10.1080/19475705.2022.2066573.
J. Zhao, J. Li, Q. Liu, B. Xu, X. Mu, and Y. Dong, “Generation of a 16 m/10-day fractional vegetation cover product over China based on Chinese GaoFen-1 observations: method and validation,” Int. J. Digit. Earth, vol. 16, no. 2, pp. 4229–4246, 2023, doi: 10.1080/17538947.2023.2264815.
M. B. Moisa et al., “GIS and remote sensing Based Analysis of Land use and Land cover Change in the Upper Anger watershed, Western Ethiopia,” Geol. Ecol. Landscapes, vol. 00, no. 00, pp. 1–10, 2023, doi: 10.1080/24749508.2023.2237323.
S. Guha and H. Govil, “Evaluating the stability of the relationship between land surface temperature and land use/land cover indices: a case study in Hyderabad city, India,” Geol. Ecol. Landscapes, vol. 00, no. 00, pp. 1–13, 2023, doi: 10.1080/24749508.2023.2182083.
E. Amarsaikhan, D. Enkhjargal, E. Jargaldalai, and D. Amarsaikhan, “Comparison of machine learning and parametric methods for the discrimination of urban land cover types,” Geocarto Int., vol. 39, no. 1, p., 2024, doi: 10.1080/10106049.2024.2380372.
B. Babiso Badesso, A. Bajigo Madalcho, and M. Mesene Mena, “Trends in forest cover change and degradation in Duguna Fango, Southern Ethiopia,” Cogent Environ. Sci., vol. 6, no. 1, 2020, doi: 10.1080/23311843.2020.1834916.
J. Yue, Y. Fu, W. Guo, H. Feng, and H. Qiao, “Estimating fractional coverage of crop, crop residue, and bare soil using shortwave infrared angle index and Sentinel-2 MSI,” Int. J. Remote Sens., vol. 43, no. 4, pp. 1253–1273, 2022, doi: 10.1080/01431161.2022.2032454.
Y. Bayissa, Y. Dile, R. Srinivasan, C. Ringler, N. Lefore, and A. W. Worqlul, “Evaluating the impacts of watershed rehabilitation and irrigation interventions on vegetation greenness and soil erosion using remote sensing and biophysical modelling in Feresmay watershed in Ethiopia,” All Earth, vol. 35, no. 1, pp. 112–131, 2023, doi: 10.1080/27669645.2023.2202968.
Y. Wen, B. Guo, W. Zang, D. Ge, W. Luo, and H. Zhao, “Desertification detection model in Naiman Banner based on the albedo-modified soil adjusted vegetation index feature space using the Landsat8 OLI images,” Geomatics, Nat. Hazards Risk, vol. 11, no. 1, pp. 544–558, 2020, doi: 10.1080/19475705.2020.1734100.
L. C. Kulimushi et al., “Evaluation of soil erosion and sediment yield spatio-temporal pattern during 1990–2019,” Geomatics, Nat. Hazards Risk, vol. 12, no. 1, pp. 2676–2707, 2021, doi: 10.1080/19475705.2021.1973118.
Z. Tibhirine, K. Ibno Namr, A. Bouasria, B. El Bourhrami, and H. Ettayeb, “Geospatial and temporal assessment of the variability of soil organic matter and electrical conductivity in irrigated semi-arid area,” Geol. Ecol. Landscapes, vol. 00, no. 00, pp. 1–12, 2023, doi: 10.1080/24749508.2023.2179748.
D. Žížala, A. Ju?icová, T. Zádorová, K. Zelenková, and R. Mina?ík, “Mapping soil degradation using remote sensing data and ancillary data: South-East Moravia, Czech Republic,” Eur. J. Remote Sens., vol. 52, no. sup1, pp. 108–122, 2019, doi: 10.1080/22797254.2018.1482524.
G. Gullà, M. Conforti, and L. Borrelli, “A refinement analysis of the shallow landslides susceptibility at regional scale supported by GIS-aided geo-database,” Geomatics, Nat. Hazards Risk, vol. 12, no. 1, pp. 2500–2543, 2021, doi: 10.1080/19475705.2021.1967204.
P. Subramaniam et al., “Integrated GIS and multivariate statistical approach for spatial and temporal variability analysis for lake water quality index,” Cogent Eng., vol. 10, no. 1, pp. 1–29, 2023, doi: 10.1080/23311916.2023.2190490.
A. Tella, A. L. Balogun, and I. Faye, “Spatio-temporal modelling of the influence of climatic variables and seasonal variation on PM10 in Malaysia using multivariate regression (MVR) and GIS,” Geomatics, Nat. Hazards Risk, vol. 12, no. 1, pp. 443–468, 2021, doi: 10.1080/19475705.2021.1879942.
A. Rehman et al., “Groundwater potential zone mapping using GIS and Remote Sensing based models for sustainable groundwater management,” Geocarto Int., vol. 39, no. 1, p., 2024, doi: 10.1080/10106049.2024.2306275.
F. Abdalla, K. Moubark, and M. Abdelkareem, “Groundwater potential mapping using GIS, linear weighted combination techniques and geochemical processes identification, west of the Qena area, Upper Egypt,” J. Taibah Univ. Sci., vol. 14, no. 1, pp. 1350–1362, 2020, doi: 10.1080/16583655.2020.1822646.
E. F. Wayima, “Comparative evaluation of NDVI strata and livelihood zones as spatial units of the practiced crop calendars,” Geol. Ecol. Landscapes, vol. 00, no. 00, pp. 1–9, 2022, doi: 10.1080/24749508.2022.2144855.
J. Naeff, “Precarious Chronotopes in Beirut: a comparative spatio-temporal analysis of Rafic Hariri’s grave and nightclub B018,” Contemp. Levant, vol. 5, no. 1, pp. 64–76, 2020, doi: 10.1080/20581831.2020.1710677.
S. Niavis, “Evaluating the spatiotemporal performance of tourist destinations: the case of Mediterranean coastal regions,” J. Sustain. Tour., vol. 28, no. 9, pp. 1310–1331, 2020, doi: 10.1080/09669582.2020.1736087.
T. Qu et al., “STGI?a spatio-temporal grid index model for marine big data,” Big Earth Data, vol. 4, no. 4, pp. 435–450, 2020, doi: 10.1080/20964471.2020.1844933.
L. Gandharum, M. E. Mulyani, D. M. Hartono, A. Karsidi, and M. Ahmad, “Remote sensing versus the area sampling frame method in paddy rice acreage estimation in Indramayu regency, West Java province, Indonesia,” Int. J. Remote Sens., vol. 42, no. 5, pp. 1738–1767, 2021, doi: 10.1080/01431161.2020.1842541.
S. Huang, Y. Li, H. Hu, P. Xue, and J. Wang, “Assessment of optimal seasonal selection for RSEI construction: a case study of ecological environment quality assessment in the Beijing-Tianjin-Hebei region from 2001 to 2020,” Geocarto Int., vol. 39, no. 1, p., 2024, doi: 10.1080/10106049.2024.2311224.
L. Mohammad et al., “Assessment of spatio-temporal trends of satellite-based aerosol optical depth using Mann–Kendall test and Sen’s slope estimator model,” Geomatics, Nat. Hazards Risk, vol. 13, no. 1, pp. 1270–1298, 2022, doi: 10.1080/19475705.2022.2070552.
S. Wang, X. Zhao, J. Qiu, H. Wang, and C. Tao, “WDCIP: spatio-temporal AI-driven disease control intelligent platform for combating COVID-19 pandemic,” Geo-Spatial Inf. Sci., vol. 00, no. 00, pp. 1–25, 2023, doi: 10.1080/10095020.2023.2182236.
Z. Lin, K. Chen, K. Jiao, and Z. Li, “Spatio-temporal characteristics of traditional village landscape pattern and its influencing factors from the perspective of tourism development: a case study of Huangcheng Village, China,” J. Asian Archit. Build. Eng., vol. 00, no. 00, pp. 1–13, 2024, doi: 10.1080/13467581.2023.2298877.
A. Gelbman, “Seaside hotel location and environmental impact: land use dilemmas,” J. Tour. Cult. Chang., vol. 20, no. 4, pp. 530–550, 2022, doi: 10.1080/14766825.2021.1961797.
L. Chu, Y. Zou, D. Masili?nas, T. Blaschke, and J. Verbesselt, “Assessing the impact of bridge construction on the land use/cover and socio-economic indicator time series: A case study of Hangzhou Bay Bridge,” GIScience Remote Sens., vol. 58, no. 2, pp. 199–216, 2021, doi: 10.1080/15481603.2020.1868212.
H. Wu, S. Kim, and A. K. F. Wong, “Residents’ perceptions of desired and perceived tourism impact in Hainan Island,” Asia Pacific J. Tour. Res., vol. 25, no. 6, pp. 573–591, 2020, doi: 10.1080/10941665.2020.1752749.
A. Centinaio, N. Comerio, and F. Pacicco, “Arrivederci! An Analysis of Tourism Impact in the Italian Provinces,” Int. J. Hosp. Tour. Adm., vol. 24, no. 4, pp. 563–589, 2022, doi: 10.1080/15256480.2021.2025187.
M. Johann, S. Mishra, G. Malhotra, and S. R. Tiwari, “Participation in active sport tourism: impact assessment of destination involvement and perceived risk,” J. Sport Tour., vol. 26, no. 2, pp. 101–123, 2022, doi: 10.1080/14775085.2021.2017326.
I. E. Munanura and J. D. Kline, “Residents’ Support for Tourism: The Role of Tourism Impact Attitudes, Forest Value Orientations, and Quality of Life in Oregon, United States,” Tour. Plan. Dev., vol. 20, no. 4, pp. 566–582, 2023, doi: 10.1080/21568316.2021.2012713.
Bila bermanfaat silahkan share artikel ini
Berikan Komentar Anda terhadap artikel Comparative Spatio-temporal Analysis Using NDVI, NDBI, and SAVI based on Landsat 8/9 OLI (2013, 2018 and 2024)
ARTICLE HISTORY
Issue
Section
Copyright (c) 2024 Yerik Afrianto Singgalen
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (Refer to The Effect of Open Access).
