PERTANIKA JOURNAL OF TROPICAL AGRICULTURAL SCIENCE

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• Aisabokhae, J. E., & Oresajo, S. B. (2018). Supervised classification of Landsat-8 band ratio images for geological interpretation of Sokoto, Nigeria. South African Journal of Geomatics, 7(3), 360-371.

• Arisanty, D. (2017). The influence of tide on suspended sediment transport in barito delta, Southern Kalimantan, Indonesia. Ecology, Environment and Conservation, 23(2), 696-703.

• Arisanty, D., Adyatma, S., Muhaimin, M., & Nursaputra, A. (2019). Landsat 8 OLI TIRS imagery ability for monitoring post forest fire changes. Pertanika Journal of Science & Technology, 27(3), 1105-1120.

• Arisanty, D., Jędrasiak, K., Rajiani, I., & Grabara, J. (2020). The destructive impact of burned peatlands to physical and chemical properties of soil. Acta Montanistica Slovaca, 25(2), 213-223. https://doi.org/10.46544/AMS.v25i2.8

• Cardoso, G. F., Souza, C., & Souza-Filho, P. W. M. (2014). Using spectral analysis of Landsat-5 TM images to map coastal wetlands in the Amazon River mouth, Brazil. Wetlands Ecology and Management, 22(1), 79-92. https://doi.org/10.1007/s11273-013-9324-4

• D’Arcy, M., Mason, P. J., Roda-Boluda, D. C., Whittaker, A. C., Lewis, J. M. T., & Najorka, J. (2018). Alluvial fan surface ages recorded by Landsat-8 imagery in Owens Valley, California. Remote Sensing of Environment, 216, 401-414. https://doi.org/10.1016/j.rse.2018.07.013

• Darmawan, I. G. B., Yassar, M. F., Elvarani, A. Y., Vira, B. A., & Damayanti, L. (2020). Preliminary study of mining material prospects based on hydrothermal alteration distribution using composite and density slicing of Landsat 8 image in Ulubongka Regency, Central Sulawesi. PROMINE, 8(1), 1-7. https://doi.org/10.33019/promine.v8i1.1799

• Davranche, M., Dia, A., Fakih, M., Nowack, B., Gruau, G., Ona-nguema, G., Petitjean, P., Martin, S., & Hochreutener, R. (2013). Organic matter control on the reactivity of Fe (III)-oxyhydroxides and associated As in wetland soils: A kinetic modeling study. Chemical Geology, 335, 24-35. https://doi.org/10.1016/j.chemgeo.2012.10.040

• Demattê, J. A. M., Horák-Terra, I., Beirigo, R. M., da Silva Terra, F., Marques, K. P. P., Fongaro, C. T., Silva, A. C., & Vidal-Torrado, P. (2017). Genesis and properties of wetland soils by VIS-NIR-SWIR as a technique for environmental monitoring. Journal of Environmental Management, 197, 50-62. https://doi.org/10.1016/j.jenvman.2017.03.014

• Ducart, D. F., Silva, A. M., Toledo, C. L. B., & de Assis, L. M. (2016). Mapping iron oxides with Landsat-8/OLI and EO-1/Hyperion imagery from the Serra Norte iron deposits in the Carajás Mineral Province, Brazil. Brazilian Journal of Geology, 46(3), 331-349. https://doi.org/10.1590/2317-4889201620160023

• Frutuoso, R., Lima, A., & Teodoro, A. C. (2021). Application of remote sensing data in gold exploration: Targeting hydrothermal alteration using Landsat 8 imagery in northern Portugal. Arabian Journal of Geosciences, 14(6), 1-18. https://doi.org/10.14419/ijbas.v3i3.2821

• Govil, H., Tripathi, M. K., Diwan, P., & Guha, S. (2018). Identification of iron oxides minerals in Western Jahajpur Region, India using aviris-ng hyperspectral remote sensing. International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences, 43(5), 233237. https://doi.org/10.5194/isprs-archives-XLII-5-233-2018

• Guan, J., Qi, K., Wang, J., Zhuang, J., Yuan, X., Yan, B., Lu, N., & Qu, J. (2020). Effects of conversion from boreal natural wetlands to rice paddy fields on the dynamics of total dissolved iron during extreme precipitation events. Chemosphere, 242, Article 125153. https://doi.org/10.1016/j.chemosphere.2019.125153

• Guo, B., Zang, W., Luo, W., Wen, Y., Yang, F., Han, B., Fan, Y., Chen, X., Qi, Z., & Wang, Z. (2020). Detection model of soil salinization information in the Yellow River Delta based on feature space models with typical surface parameters derived from Landsat 8 OLI image. Geomatics, Natural Hazards and Risk, 11(1), 288-300. https://doi.org/10.1080/19475705.2020.1721573

• Guo, M., Li, J., Sheng, C., Xu, J., & Wu, L. (2017). A review of wetland remote sensing. Sensors, 17(4), Article 777. https://doi.org/10.3390/s17040777

• Haq, M. A. (2017). Analysis of land surface temperature, distribution of clay minerals and fault fracture density using Landsat 8 imagery in the Dieng geothermal system and its surroundings, Central Java Province, Indonesia (Doctoral dissertation). Faculty of Engineering, Diponegoro University, Semarang, Indonesia.

• Ihlen, V. (2019). Landsat 8 data users handbook. U.S. Geological Survey. USGS Publication.

• Kamal, M., Adi, N. S., & Arjasakusuma, S. (2012). Jaz EL-350 VIS NIR portable spectrometer: Panduan operasional pengukuran dan pengelolaan data pantulan spektral obyek (Versi 1 2012) [Jaz EL-350 VIS NIR portable spectrometer: Operational guide for spectral object data measuring and managing (Version 1/2012)]. Universitas Gadjah Mada.

• Liu, J. G., & Mason, P. J. (2009). Essential image processing and GIS for remote sensing (1st Edit). Wiley Online Library. https://doi.org/10.1002/9781118687963

• Meng, L., Zhou, S., Zhang, H., & Bi, X. (2016). Estimating soil salinity in different landscapes of the Yellow River Delta through Landsat OLI/TIRS and ETM+ Data. Journal of Coastal Conservation, 20(4), 271-279. https://doi.org/10.1007/s11852-016-0437-9

• Nugroho, Y. A., & Purwanto, T. H. (2013). Study of estimation iron oxide content using mutispectral medium resolution imagery. Jurnal Bumi Indonesia, 2(3), 117-126.

• Pour, A. B., & Hashim, M. (2015). Hydrothermal alteration mapping from Landsat-8 data, Sar Cheshmeh copper mining district, south-eastern Islamic Republic of Iran. Journal of Taibah University for Science, 9(2), 155-166. https://doi.org/10.1016/j.jtusci.2014.11.008

• Putra, I. D., Nasution, R. A. F., & Harijoko, A. (2017). Aplikasi Landsat 8 OLI/TIRS dalam mengidentifikasi alterasi hidrotermal skala regional: studi kasus Daerah Rejang Lebong dan sekitarnya, Provinsi Bengkulu [Landsat 8 OLI/TIRS application in identifying regional scale hydrothermal alterations: A case study]. Proseding Seminar Nasional Kebumian, 10, 1812-1826.

• Qing, K., Zhao, Y. J., & Cui, X. (2019). Research on information extraction technology of iron oxide based on airborne hyperspectral data. In IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium (pp. 6764-6767). IEEE Publishing. https://doi.org/10.1109/IGARSS.2019.8900647

• Radeva, K., Velizarova, E., & Dancheva, A. (2019). Land cover monitoring as part of a survey on wetland ecosystem conservation in the Negovan village area using remote sensing tools. Glasnik Sumarskog Fakulteta, 119, 175-188. https://doi.org/10.2298/GSF1919175R

• Ridwan, M. A., Radzi, N. A. M., Ahmad, W., Mustafa, I. S., Din, N. M., Jalil, Y. E., Isa, A. M., Othman, N. S., & Zaki, W. (2018). Applications of landsat-8 data: A Survey. International Journal of Engineering & Technology, 7(4), 436-441. https://doi.org/10.14419/ijet.v7i4.35.22858

• Rockwell, B. W. (2013). Automated mapping of mineral groups and green vegetation from Landsat Thematic Mapper imagery with an example from the San Juan Mountains, Colorado. US Geological Survey Scientific Investigations Map.

• Rozpondek, R., Wancisiewicz, K., & Kacprzak, M. (2016). GIS in the studies of soil and water environment. Journal of Ecological Engineering, 17(3), 134-142. https://doi.org/10.12911/22998993/63476

• Silvero, N. E. Q., Demattê, J. A. M., Amorim, M. T. A., dos Santos, N. V., Rizzo, R., Safanelli, J. L., Poppiel, R. R., de Sousa Mendes, W., & Bonfatti, B. R. (2021). Soil variability and quantification based on Sentinel-2 and Landsat-8 bare soil images: A comparison. Remote Sensing of Environment, 252, Article 112117. https://doi.org/10.1016/j.rse.2020.112117

• Sulaeman, Y., Poggio, L., Minasny, B., & Nursyamsi, D. (2020). Tropical wetlands-innovation in mapping and management. International Workshop on Tropical Wetlands: Innovation in Mapping and Management, 2018, Article 197. https://doi.org/10.1201/9780429264467

• Traore, M., Wambo, J. D. T., Ndepete, C. P., Tekin, S., Pour, A. B., & Muslim, A. M. (2020). Lithological and alteration mineral mapping for alluvial gold exploration in the south east of Birao area, Central African Republic using Landsat-8 Operational Land Imager (OLI) data. Journal of African Earth Sciences, 170, Article 103933. https://doi.org/10.1016/j.jafrearsci.2020.103933

• Xing, L., & Niu, Z. (2019). Mapping and analyzing China’s wetlands using MODIS time series data. Wetlands Ecology and Management, 27(5), 693-710. https://doi.org/10.1007/s11273-019-09687-y

• Zabloskii, V. R. (2019). The method of detection of clay minerals and iron oxide based on landsat multispectral images (as exemplified in the Territory of Thai Nguyen Province, Vietnam). Mining Science and Technology, 4(1), 65-75. https://doi.org/10.17073/2500-0632-2019-1-65-75

• Zhai, M. (2019). Inversion of organic matter content in wetland soil based on Landsat 8 remote sensing image. Journal of Visual Communication and Image Representation, 64, Article 102645. https://doi.org/10.1016/j.jvcir.2019.102645

• Zribi, M., Baghdadi, N., & Nolin, M. (2011). Remote Sensing of Soil. Applied and Environmental Soil Science, 2011, 1-2. https://doi.org/10.1155/2011/904561