MODIFIKASI MODEL FOREST CANOPY DENSITY (FCD) PADA CITRA LANDSAT 8 MULTI-TEMPORAL UNTUK MONITORING PERUBAHAN TUTUPAN VEGETASI DI KECAMATAN SUKASADA-BALI
Abstract
Keywords
Full Text:
PDFReferences
Abdollahnejad, A., Panagiotidis, D., & Surový, P. (2017). Forest canopy density assessment using different approaches - Review. Journal of Forest Science, 63(3), 107–116. https://doi.org/10.17221/110/2016-JFS
Akike, S., & Samanta, S. (2016). Land Use / Land Cover and Forest Canopy Density Monitoring of Wafi-Golpu Project Area , Papua New Guinea. August, 1–14.
Ariyani, R., & B.S., S. H. M. (2016). Transformasi Forest Canopy Density Dan Second Modified Soil Adjusted Vegetation Index Untuk Monitoring Degradasi Hutan Lindung Dan Taman Nasional Di Sarolangun Jambi. Jurnal Bumi Indonesia, 5(3).
Ashaari, F., Kamal, M., & Dirgahayu, D. (2018). Comparison of Model Accuracy in Tree Canopy Density Estimation Using Single Band, Vegetation Indices and Forest Canopy Density (Fcd) Based on Landsat-8 Imagery (Case Study: Peat Swamp Forest in Riau Province). International Journal of Remote Sensing and Earth Sciences (IJReSES), 15(1), 81. https://doi.org/10.30536/j.ijreses.2018.v15.a2845
Azizi, Z., Najafi, A., & Sohrabi, H. (2008). Forest Canopy Density Estimating , Using Satellite Images. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XXXVII(Part B8), 1127–1130.
Balipost. (2019). Bangun Shortcut 7 hingga 10, Pembebasan Lahan Mulai Dilakukan. Www.Balipost.Com. https://www.balipost.com/news/2019/10/24/90778/Bangun-Shortcut-7-hingga-10,...html
Banerjee, K., Panda, S., Bandyopadhyay, J., & Jain, M. K. (2014). Forest Canopy Density Mapping Using Advance Geospatial Technique. IJISET -International Journal of Innovative Science, Engineering & Technology, 1(7), 358–363. www.ijiset.com
Chandrashekhar, M. B., Saran, S., Raju, P. L. N., & Roy, P. S. (2005). Forest Canopy Density Stratification: How Relevant is Biophysical Spectral Response Modelling Approach? Geocarto International, 20(1), 15–21. https://doi.org/10.1080/10106040508542332
Chavez, J. (1988). Animproved dark-object subtraction technique for atmospheric scattering correction of multispectral data. Remote Sensing of Environment, 24, 159–279.
Deka, J., Tripathi, O. P., & Khan, M. L. (2013). Implementation of Forest Canopy Density Model to Monitor Tropical Deforestation. Journal of the Indian Society of Remote Sensing, 41(2), 469–475. https://doi.org/10.1007/s12524-012-0224-5
Department of the Interior U.S. Geological Survey. (2016). Landsat 8 Data Users Handbook. In Nasa (Vol. 8, Issue June). https://landsat.usgs.gov/documents/Landsat8DataUsersHandbook.pdf
Grainger, A. (1993). Rates of Deforestation in the Humid Tropics: Estimates and Measurements. The Geographical Journal, 159(1), 33–44.
Himayah, S., Hartono, & Danoedoro, P. (2016). The Utilization of Landsat 8 Multitemporal Imagery and Forest Canopy Density (FCD) Model for Forest Reclamation Priority of Natural Disaster Areas at Kelud Mountain, East Java. IOP Conference Series: Earth and Environmental Science, 47(1). https://doi.org/10.1088/1755-1315/47/1/012043
Huete, A. (1988). A soil-adjusted vegetation index (SAVI). Remote Sensing of Environment, 25(3), 295–309. https://doi.org/10.1016/0034-4257(88)90106-X
kumar, A., Singh, A., Kumar, S., & Kanga, S. (2018). Estimating the change in Forest Cover Density and Predicting NDVI for West Singhbhum using Linear Regression. ESSENCE International Journal for Environmental Rehabilitation and Conservation, 9(1), 193–203. https://doi.org/10.31786/09756272.18.9.1.125
Kwon, T., Lee, W., Kwak, D., Park, T., Lee, J. Y., Hong, S. Y., Guishan, C., & Kim, S. R. (2012). Forest Canopy Density Estimation Using Airborne Hyperspectral Data. 대한ì›ê²©íƒì‚¬í•™íšŒì§€, 28(3), 297–305.
Loi, D. T., Chou, T.-Y., & Fang, Y.-M. (2017). Integration of GIS and Remote Sensing for Evaluating Forest Canopy Density Index in Thai Nguyen Province, Vietnam. International Journal of Environmental Science and Development, 8(8), 539–542. https://doi.org/10.18178/ijesd.2017.8.8.1012
Muhammad, A., Prasetyo, L. B., & Kartono, A. P. (2014). Pemetaan Perubahan Forest Canopy Density Di Kph Kuningan. Seminar Nasional Penginderaan Jauh, 2008, 652–661.
Nugraha, A. S.A., Gunawan, T., & Kamal, M. (2019). Comparison of Land Surface Temperature Derived from Landsat 7 ETM+ and Landsat 8 OLI/TIRS for Drought Monitoring. IOP Conference Series: Earth and Environmental Science, 313(1), 0–10. https://doi.org/10.1088/1755-1315/313/1/012041
Nugraha, A Sediyo Adi. (2019). Pemanfaatan Metode Split-Windows Algorithm ( SWA ) pada Landsat 8 Menggunakan Data Uap Air MODIS Terra (The Application of Split-Windows Algorithm (SWA) Methods on Landsat 8 Using Modis Terra Water Vapor). Geomatika, 25(1), 9–16. https://doi.org/http://doi.org/10.24895/JIG.2019.25-1.877
Nugraha, A Sediyo Adi, Gunawan, T., & Kamal, M. (2019). Downscaling land surface temperature on multi-scale image for drought monitoring. Sixth Geoinformation Science Symposium, November, 6. https://doi.org/10.1117/12.2544550
Rikimaru, A. (1999). The Concept of FCD Mapping Model and Semi-Expert System. FCD Mapper User’s Guide. 80.
Rikimaru, A., & Miyatake, S. (2009). Development of forest canopy density mapping and monitoring model using indices of vegetation, bare soil and shadow - Geospatial World. 1–5. http://www.geospatialworld.net/article/development-of-forest-canopy-density-mapping-and-monitoring-model-using-indices-of-vegetation-bare-soil-and-shadow/
Rikimaru, A., Roy, P. S., & Miyatake, S. (2002). Tropical forest cover density mapping. Tropical Ecology, 43(1), 39–47.
Septiani, R., Citra, I. P. A., & Nugraha, A. S. A. (2019). Perbandingan Metode Supervised Classification dan Unsupervised Classification terhadap Penutup Lahan di Kabupaten Buleleng. Jurnal Geografi : Media Informasi Pengembangan Dan Profesi Kegeografian, 16(2), 90–96. https://doi.org/10.15294/jg.v16i2.19777
Skokovic, D., Sobrino, J. a., Jiménez Muñoz, J. C., Soria, G., Julien, Y., Mattar, C., & Cristóbal, J. (2014). Calibration and Validation of land surface temperature for Landsat8- TIRS sensor TIRS LANDSAT-8 CHARACTERISTICS. Land Product Validation and Evolution ESA/ESRIN, 27. https://doi.org/10.1063/1.452862
Sobrino, J. A., El Kharraz, J., & Li, Z. L. (2003). Surface temperature and water vapour retrieval from MODIS data. International Journal of Remote Sensing, 24(24), 5161–5182. https://doi.org/10.1080/0143116031000102502
Sobrino, J. A., Li, Z. L., Stoll, M. P., & Becker, F. (1996). Multi-channel and multi-angle algorithms for estimating sea and land surface temperature with atsr data. International Journal of Remote Sensing, 17(11), 2089–2114. https://doi.org/10.1080/01431169608948760
Sobrino, J., Raissouni, N., & Li, Z.-L. (2001). A Comparative Study of Land Surface Emissivity Retrieval from NOAA Data. In Remote Sensing of Environment (Vol. 75). https://doi.org/10.1016/S0034-4257(00)00171-1
Sobrino, José A., Jiménez-Muñoz, J. C., Sòria, G., Romaguera, M., Guanter, L., Moreno, J., Plaza, A., & MartÃnez, P. (2008). Land surface emissivity retrieval from different VNIR and TIR sensors. IEEE Transactions on Geoscience and Remote Sensing, 46(2), 316–327. https://doi.org/10.1109/TGRS.2007.904834
Sukarna, R. M. (2008). Aplikasi Model Forest Canopy Density Citra Landsat 7 Etm Untuk Menentukan Indeks Luas Tajuk (Crown Area Index) Dan Kerapatan Tegakan (Stand Density) Hutan Rawa Gambut Di Das Sebangau Provinsi Kalimantan Tengah. Majalah Geografi Indonesia, 22(2), 1–21. https://doi.org/10.22146/mgi.15383
Zhao, S., Qin, Q., Yang, Y., Xiong, Y., & Qiu, G. (2009). Comparison of two split-window methods for retrieving land surface temperature from MODIS data. Journal of Earth System Science, 118(4), 345–353. https://doi.org/10.1007/s12040-009-0027-4
Refbacks
- There are currently no refbacks.