The capability of Sentinel-2 image and FieldSpec3 for detecting lithium-containing minerals in central Iran

To date,there are very few studies about the spectroscopy of lithium-containing minerals(LCMs)in the scientific community.The main objective of this study is to investigate the capability of Sentinel-2 image and FieldSpec3 spectro-radiometer in terms of mapping five important LCMs,including spodumene,lepidolite,amblygonite,petalite,and eucryptite.Therefore,first the FieldSpec3 spectro-radiometer was used to create the spectral curves of the LCMs.Then,accurate spectral analysis and comparison of the studied LCMs were performed using The Spectral Geologist(TSG)and the Prism software.These two software can show even slight difference in absorption features of different LCMs,which can discriminate and identify these minerals.Lithium-bearing rocks show absorption features at~365,~2200,and~2350 nm and reflective features at~550-770 nm.These features are consistent with Sentinel-2 bands.Therefore,the created spectral curves were utilized for calibration of Sentinel-2 optical image to detect and map the potential zones of the rock units containing minerals mentioned above in a part of the central Iranian terrane.By using the Spectral Angle Mapper(SAM)classifier module,the potential areas were demarcated.Out of the five LCMs,petalite and spodumene showed more extensive coverage in the study area.Generally speaking,the largest concentration of those LCMs can be seen in southern and centraleastern parts of the study area.The comparison between spectral curves of reference and classified minerals confirmed the high capability of Sentinel-2 image for LCMs mapping.ASTER image classification results also confirmed the presence of the LCMs,but it cannot distinguish the LCMs type successfully.

Evaluating spectral indices for determining conservation and conventional tillage systems in a vetch-wheat rotation

Conservation tillage(CT)systems,which consist of reduced and no-tillage systems,retain considerable quantities of crop residues on the soil surface.These crop residues perform as a barrier to wind and water to decrease soil erosion and evaporation.The use of remote sensing technology provides fast,objective and effective tool for estimating and measuring any agricultural event.The challenge is to differentiate the tillage systems by the crop residue cover on the soil surface.Spectrally derived normalized difference tillage index(NDTI),Shortwave infrared normalized difference residue index(SINDRI),cellulose absorption index(CAI)and Lignin-cellulose absorption index(LCA)were examined to distinguish their value as remote sensing methods for identifying crop residue cover in conventional and conservation tillage systems.Tillage treatments included conventional tillage(MD:Mouldboard plow+Disk harrow),reduced tillage(CD:Chisel plowþDisk harrow),minimum till(MT:Stubble cultivator),and no-tillage(NT_(1) and NT_(2):with standing stubble and standing stubble plus threshing residue,respectively).CAI had a linear relationship with crop residue cover,which the comparative intensity of cellulose and lignin absorption features near 2100 nm can be measure by it.Coefficients of determination(r^(2))for crop residue cover as a function of CAI and LCA were 0.89 and 0.79 respectively.Absorption specifications near 2.1 and 2.3 mm in the reflectance spectra of crop residues in minimum and no-tillage systems were related to cellulose and lignin.These specifications were not evident in the spectra of conventional tillage system.In this study the best index to use was CAI,which showed complete separation tillage systems,followed by LCA and NDTI.Four tillage intensity classes,corresponding to intensive(<6%residue cover),reduced(10–20%cover)minimum(25–40%)and no-tillage(>60%cover)tillage,were recognized in this study.