Comprehensive study of the biophysical parameters of agricultural crops based on assessing Landsat 8 OLI and Landsat 7 ETM+ vegetation indices

被引:27
作者
Ahmadian, Nima [1 ]
Ghasemi, Sahar [1 ]
Wigneron, Jean-Pierre [2 ]
Zoelitz, Reinhard [1 ]
机构
[1] Univ Greifswald, Inst Geog & Geol, Fac Nat Sci & Math, Greifswald, Germany
[2] INRA, Bordeaux, France
关键词
Landsat; 8; OLI; agricultural crops; Landsat 7 ETM+; vegetation index; biophysical parameters; LEAF-AREA INDEX; WATER-CONTENT; GREEN LAI; CANOPY; REFLECTANCE; BIOMASS; CORN; WHEAT; NDVI; EVAPOTRANSPIRATION;
D O I
10.1080/15481603.2016.1155789
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
For three agricultural crop types, winter wheat (Triticum aestivum L.), barley (Hordeum vulgare L.), and canola (Brassica napus L.), we estimated biophysical parameters including fresh and dry biomass, leaf area index (LAI), and vegetation water content, for which we found the equivalent water thickness (EWT), fuel moisture content per fresh weight (FMCFW), and fuel moisture content per dry weight (FMCDW). We performed these estimations using data from the newly launched Landsat 8 Operational Land Imager (OLI) sensor, as well as its predecessor the Landsat 7 Enhanced Thematic Mapper Plus (ETM+). Progress in the design of the new sensor (i.e., Landsat 8), including narrower near-infrared (NIR) wavebands, higher signal-to-noise ratio (SNR), and greater radiometric resolution highlights the necessity to investigate the biophysical parameters of agricultural crops, especially compared to data from its predecessor. This study aims to evaluate vegetation indices (VIs) derived from the Landsat 8 OLI and the Landsat 7 ETM+. Both the Landsat 8 OLI and Landsat 7 ETM+ VIs agreed well with in-situ data measurements. However, the Landsat 8 OLI-derived VIs were generally more consistent with in situ data than the Landsat 7 ETM+ VIs. We also note that the Landsat 8 OLI is better able to capture the small variability of the VIs because of its higher SNR and wider radiometric range; in addition, the saturation phenomenon occurred earlier for the Landsat 7 ETM+ than for the Landsat 8 OLI. This indicates that the new sensor is better able to estimate the biophysical parameters of crops.
引用
收藏
页码:337 / 359
页数:23
相关论文
共 71 条
[21]   Monitoring wheat phenology and irrigation in Central Morocco: On the use of relationships between evapotranspiration, crops coefficients, leaf area index and remotely-sensed vegetation indices [J].
Duchemin, B ;
Hadria, R ;
Erraki, S ;
Boulet, G ;
Maisongrande, P ;
Chehbouni, A ;
Escadafal, R ;
Ezzahar, J ;
Hoedjes, JCB ;
Kharrou, MH ;
Khabba, S ;
Mougenot, B ;
Olioso, A ;
Rodriguez, JC ;
Simonneaux, V .
AGRICULTURAL WATER MANAGEMENT, 2006, 79 (01) :1-27
[22]   Quality assessment of Landsat surface reflectance products using MODIS data [J].
Feng, Min ;
Huang, Chengquan ;
Channan, Saurabh ;
Vermote, Eric F. ;
Masek, Jeffrey G. ;
Townshend, John R. .
COMPUTERS & GEOSCIENCES, 2012, 38 (01) :9-22
[23]   Predicting agronomic performance of barley using canopy reflectance data [J].
Fetch, TG ;
Steffenson, BJ ;
Pederson, VD .
CANADIAN JOURNAL OF PLANT SCIENCE, 2004, 84 (01) :1-9
[24]   Discrimination of sugarcane varieties in southeastern brazil with EO-1 hyperion data [J].
Galvao, LS ;
Formaggio, AR ;
Tisot, DA .
REMOTE SENSING OF ENVIRONMENT, 2005, 94 (04) :523-534
[25]   Generating global Leaf Area Index from Landsat: Algorithm formulation and demonstration [J].
Ganguly, Sangram ;
Nemani, Ramakrishna R. ;
Zhang, Gong ;
Hashimoto, Hirofumi ;
Milesi, Cristina ;
Michaelis, Andrew ;
Wang, Weile ;
Votava, Petr ;
Samanta, Arindam ;
Melton, Forrest ;
Dungan, Jennifer L. ;
Vermote, Eric ;
Gao, Feng ;
Knyazikhin, Yuri ;
Myneni, Ranga B. .
REMOTE SENSING OF ENVIRONMENT, 2012, 122 :185-202
[26]   OPTICAL PARAMETERS OF LEAVES OF 30 PLANT SPECIES [J].
GAUSMAN, HW ;
ALLEN, WA .
PLANT PHYSIOLOGY, 1973, 52 (01) :57-62
[27]   Estimating crop water stress with ETM plus NIR and SWIR data [J].
Ghulam, Abduwasit ;
Li, Zhao-Liang ;
Qin, Qiming ;
Yimit, Hamid ;
Wang, Jihua .
AGRICULTURAL AND FOREST METEOROLOGY, 2008, 148 (11) :1679-1695
[28]   Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves [J].
Gitelson, AA ;
Gritz, Y ;
Merzlyak, MN .
JOURNAL OF PLANT PHYSIOLOGY, 2003, 160 (03) :271-282
[29]  
Gitelson AA, 2003, GEOPHYS RES LETT, V30, DOI [10.1029/2002GL016450, 10.1029/2002GL016543]
[30]   Remote sensing of chlorophyll concentration in higher plant leaves [J].
Gitelson, AA ;
Merzlyak, MN .
SYNERGISTIC USE OF MULTISENSOR DATA FOR LAND PROCESSES, 1998, 22 (05) :689-692