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Estimation and counter- validation of LISS-III derived leaf area index in Deltaic vegetation | ||
| Caspian Journal of Environmental Sciences | ||
| دوره 19، شماره 2، تیر 2021، صفحه 239-249 اصل مقاله (1.66 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22124/cjes.2021.4741 | ||
| نویسندگان | ||
| Abhisek Santra* ؛ Shreyashi Santra Mitra؛ Suman Sinha | ||
| Department of Civil Engineering, Haldia Institute of Technology, ICARE Complex, HIT Campus, Haldia-721657, Midnapore(E), West Bengal, India | ||
| چکیده | ||
| Leaf area index (LAI), a dimensionless biophysical variable is considered as one of the most important factors in characterizing canopy structure. It estimates the amount of foliage area per unit of ground area and helps indirectly to assess biomass and energy balance in an ecosystem. Remote sensing techniques established a strong correlation between the vegetation reflectance characteristics in red and near infra-red bands and LAI. Good number of image derived vegetation indices has been applied so far to estimate LAI successfully. In this paper correlation is established between field-collected LAI and three soil adjusted vegetation indices, i.e., SAVI, MSAVI and OSAVI derived from IRS-LISS-III data in deltaic ecosystem in Sagar Island of West Bengal, India. LAI was estimated from OSAVI for the whole island as OSAVI yielded best result (R2= 0.92). Coarse resolution MODIS LAI (MOD 15A3) product was counter-validated with respect to the LISS-III derived LAI image following the upscale validation approach. Out of the six best-fit models applied, the logistic regression showed strong positive correspondence between the two products (R2 = 0.71). Uncertainty of the model was also assessed and probable reasons were identified. | ||
| کلیدواژه‌ها | ||
| SAVI؛ LAI؛ LISS-III؛ MODIS؛ ATCOR-2 | ||
| مراجع | ||
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Alexandre, C, Tillard, E, Salgado, P, Lajoie, G 2018, Validation of an empirical model, LAI~VI, to force a grass growth model on Reunion Island, France. Photo Interpretation European Journal of Applied Remote Sensing, 54: 4-10.
Bonan, G 1993, Importance of leaf area index and forest type when estimating photosynthesis in boreal forests. Remote Sensing of Environment, 43: 303-314.
Chaurasia, S, Nigam, R, Bhattacharya, BK, Sridhar, VN, Mallick, K, Vyas, SP, Patel, NK, Mukherjee, J, Shekhar, C, Kumar, D, Singh, KRP, Bairagi, GD, Purohit, NL & Parihar, JS 2011, Development of regional wheat VI - LAI models using Resourcesat-1 AWiFS data. Journal of Earth System Science, 120: 1113-1125.
Clevers, JGPW 1989, The application of a weighted infra-red vegetation index for estimating leaf area index by correcting for soil moisture. Remote Sensing of Environment, 29: 25-37.
Clough, BF, Ong, JE & Gong, GW 1997, Estimating leaf area index and photosynthetic production in canopies of the mangrove Rhizophora apiculate. Marine Ecology Progress Series, 159: 285-292.
George, R, Padalia, H, Sinha, SK & Kumar, AS 2018, Evaluation of the Use of Hyperspectral Vegetation Indices for Estimating Mangrove Leaf Area Index in Middle Andaman Island, India. Remote Sensing Letters, 9: 1099-1108.
Gopinath, G 2010, Critical coastal issues of Sagar Island, east coast of India. Environmental Monitoring and Assessment, 160: 555-561.
Green, EP, Mumby, PJ, Edwards, AJ, Clark, CD & Ellis, AC 1997, Estimating leaf area index of mangroves from satellite data. Aquatic Botany, 58: 11-19.
Huete, AR 1988, ‘A soil-adjusted vegetation index (SAVI). Remote Sensing of Environment, 25: 295-309.
Jarvis, PG & Leverenz, JW 1983, Productivity of temperate, deciduous and evergreen forests. In: O L Lange, P S Nobel, CB, Osmond & H Ziegler (eds), Physiological Plant Ecology IV. Ecosystem Processes, Mineral Cycling, Productivity and Man's Influence, Springer-Verlag.
Jonckheere, I, Fleck, S, Nackaerts, K, Muys, B, Coppin, P, Weiss, M, Baret, F 2004, Review of methods for in situ leaf area index determination: Part I. Theories, sensors and hemispherical photography. Agricultural and Forest Meteorology, 121: 19-35.
Jordon, CF 1969, Derivation of leaf-area index from quality of light on forest floor. Ecology, 50: 663-666.
Juniansah, A, Tama, GC, Febriani, KR, Baharain, MN, Kanekaputra, T, Wulandari, YS & 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: 012004.
Kovacs, JM, Flores-Verdugo, F, Wang, J & Aspden, LP 2004, Estimating leaf area index of a degraded mangrove forest using high spatial resolution satellite data. Aquatic Botany, 80: 13-22.
Liu, HQ & Huete, A 1995, A feedback based modification of the NDVI to minimize canopy background and atmospheric noise. IEEE Transactions on Geoscience and Remote Sensing, 33: 457-465.
Liu, J, Chen, JM, Cihlar, J & Park, WM 1997, A process-based Boreal ecosystem productivity simulator using remote sensing inputs. Remote Sensing of Environment, 62: 158-175.
Maas, SJ 1991, ‘Use of remotely sensed information in plant growth simulation models. Advances in Agronomy, 1: 17-26.
Maki, M & Homma, K 2014, ‘Empirical regression models for estimating multiyear leaf area index of rice from several vegetation indices at the field scale. Remote Sensing, 6: 4764-4779.
Mondal, I, Thakur, S, Ghosh, PDeTK & Bandyopadhyay, J 2019, ‘Land use/land cover modeling of Sagar Island, India using remote sensing and GIS techniques. In: Abraham, A, Dutta, P, Mandal, J K, Bhattacharya, A & Dutta, S (Eds.), Emerging Technologies in Data Mining and Information Security. Springer Singapore, Singapore, pp. 771-785.
Monteith, JL 1977, ‘Climate and efficiency of crop production in Britain. Philosophical Transactions of the Royal Society of London, Series B, Biological Sciences, 281: 277-294.
Myneni, RB, Keeling, CD, Tucker, CJ, Asrar, G & Nemani, RR 1997, Increased plant growth in the northern high latitudes from 1981 to 1991. Letters to Nature. Nature, 386: 698-702.
Nemry, B, Francois, L, Warnant, P, Robinet, F & Gerard, JC 1996, ‘The seasonality of the CO2 exchange between the atmosphere and the land biosphere: A study with global mechanistic vegetation model. Journal of Geophysical Research, 101: 7111-7125.
Ovakoglou, G, Alexandridis, TK, Clevers, JGPW, Cherif, I, Kasampalis, DA, Navrozidis, I, Iordanidis, C, Moshou, D, Laneve, G & Beltran, J S 2018, Spatial enhancement of Modis leaf area index using regression analysis with Landsat vegetation index. IGARSS 2018- IEEE International Geoscience and Remote Sensing Symposium, pp. 8232-8235.
Pandya, MR, Singh, RP, Chaudhari, KN, Bairagi, GD, Sharma, R, Dadhwal, VK & Parihar, JS 2006, Leaf area index retrieval using IRS LISS-III sensor data and validation of the MODIS LAI product over central India. IEEE Transactions on Geoscience and Remote Sensing, 44: 1858-1865.
Papadavid, G, Hadjimitsis, DG, Toulios, L & Michaelides, S 2013, A modified SEBAL modeling approach for estimating crop evapotranspiration in semi-arid conditions. Water Resources Management, 27: 3493-3506.
Pasqualotto, N, Delegido, J, Van Wittenberghe, S, Rinaldi, M & Moreno, J 2019, Multi-crop green LAI estimation with a new simple Sentinel-2 LAI index (SeLI). Sensors (Basel), 19: 904.
Qi, J, Chehbouni, A, Huete, AR, Kerr, YH & Sorooshian, S 1994, A modified soil adjusted vegetation index. Remote Sensing of Environment, 48: 119-126.
Qi, J, Kerr, YH, Moran, MS, Weltz, M, Huete, AR, Sorooshian, S & Bryant, R 2000, Leaf area index estimates using remotely sensed data and BRDF models in semiarid region. Remote Sensing of Environment, 73:18-30
ReSe 2015, Features of ATCOR2 and ATCOR3. retrieved from http://www.rese.ch/about/index.html
Richter, R 1996, A spatially adaptive fast atmospheric correction algorithm. International Journal of Remote Sensing, 17: 1201-1214.
Richter, R 1998, Correction of satellite imagery over mountainous terrain. Applied Optics, 37: 4004-4015.
Rondeaux, G, Steven, M & Baret, F 1996, Optimization of soil-adjusted vegetation indices. Remote Sensing of Environment, 55: 95-107.
Santra, A, Santra Mitra, S, Mitra, D & Sarkar, A 2019, Relative radiometric normalisation - performance testing of selected techniques and impact analysis on vegetation and water bodies. Geocarto International, 34: 98-113.
Stenberg, P, Rautiainen, M, Manninen, T, Voipio, P & Smolander, H 2004, Reduced simple ratio better than NDVI for estimating LAI in Finnish pine and spruce stands. Silva Fennica, 38: 3-14.
Tan, B, Hu, J, Zhang, P, Huang, D, Shabanov, N, Weiss, M, Knyazikhin, Y & Myneni, RB 2005, Validation of Moderate Resolution Imaging Spectroradiometer leaf area index product in croplands of Alpilles, France. Journal of Geophysical Research: Atmospheres, 110: D01107.
Tucker, C J 1979, ‘Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment, 8: 127-150.
Zhang, Z & Tang, B 2018, Estimation of leaf area index with various vegetation indices from Gaofen-5 band reflectances. IGARSS 2018 - IEEE International Geoscience and Remote Sensing Symposium, 22-27 July 2018, pp. 2619-2622. | ||
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