A Simplified Approach for Interpreting Principal Component Images

Principal component transformation is a standard technique for multi-dimensional data analysis. The purpose of the present article is to elucidate the procedure for interpreting PC images. The discussion focuses on logically explaining how the negative/positive PC eigenvectors (loadings) in combination with strong reflection/absorption spectral behavior at different pixels affect the DN values in the output PC images. It is an explanatory article so that fuller potential of the PCT applications can be realized.

Multi-polarized Radarsat-2 satellite sensor in assessing forest vigor from above ground biomass

Accurate estimates of forest biomass are increasingly important in relation to sequestration of carbon by forest trees. Satellite remote sensing is a useful tool for biomass estimation and monitoring of forest ecological processes. Microwave synthetic aperture radar （SAR） can increase the accuracy of estimations of forest biomass in comparison to optical remote sensing, due to the unique capacities of SAR, including high penetrability, volumetric scattering, interaction with surface roughness, and dielectric property. We studied the potential of multi-polarized C-band Radarsat-2, a SAR technology, with HH, HV and VV polarization for estimating biomass of moist tropical Indian forest. Backscatter values are correlated with fieldbased biomass values and axe regressed to generate models for estimating biomass. HH polarization provided maximum information regarding tree biomass. A coefficient of determination of 0.49 was calculated for HH polarized C-band image with in situ measurements. An exponential model was proved to be best suited for estimating forest biomass. Correlation of 0.62 and RMSE of 24.6 t ha-1 were calculated for the relationship between estimated and predicted biomass values for the best fit model. The aver- age absolute accuracy of the model was 61%, while Willmott＇s index of agreement was 0.87. Results suggest that most of the biomass of the area ranged within 70 t ha-1 a probably due to the saturation of C-band around 60-70 t ha-1 for tropical forests.

Insights into chondrule formation process and shock-thermal history of the Dergaon chondrite (H4-5)

The Dergaon fall represents a shock-melted H4-5 （S5） ordinary chondrite which includes at least ten textural varieties of chondrules and belongs to the high chondrule-matrix ratio type. Our study reveals that the chondrules are of diverse mineralogy with variable olivine-pyroxene ratios （Type Ⅱ）, igneous melt textures developed under variable cooling rates and formed through melt fractionations from two different melt reservoirs. Based on the experimental analogues, mineralogical associations and phase compositions, it is suggested that the Dergaon chondrules reflect two contrasting environments： a hot, dust-enriched and highly oxidized nebular environment through melting, without significant evapora- tion, and an arrested reducing environment concomitant with major evaporation loss of alkali and highly volatile trace elements. Coexistence of chlorapatite and merrillite suggests formation of the Dergaon matrix in an acidic accretionary environment. Textural integration and chemical homogenization occurred at - I atmospheric pressure and a mean temperature of 765 ℃ mark the radiogenic thermal event. Equilibrated shock features （olivine mosaicism, diaplectic plagioclase, polycrystalline troilite） due to an impact-induced thermal event reflect a shock pressure 〉45 GPa and temperature of 600 ℃. By contrast, the local disequilibrium shock features （silicate melt veins comprising of olivine crystallites, troilite melt veins and metal droplets） correspond to a shock pressure up to 75 GPa and temperature 〉950 ℃.

Evaluation of Radarsat-2 quad-pol SAR time-series images for monitoring groundwater irrigation

Groundwater assists farmers to irrigate crops for fulfilling the crop-water requirement.Indian agriculture system is characterized by three cropping seasons known as Kharif(monsoon),Rabi(post-monsoon)and summer(pre-monsoon).In tropical countries like India,monitoring cropping practices using optical remote sensing during Kharif and Rabi seasons is constraint due to the cloud cover,which can be well addressed by microwave remote sensing.In the proposed research,the strength of C-band polarimetric Synthetic Aperture Radar(SAR)time series images were evaluated to classify groundwater irrigated croplands for the Kharif and Rabi cropping seasons of the year 2013.The present study was performed in the Berambadi experimental watershed of Kabini river basin,southern peninsular India.A total of fifteen polarimetric variables were estimated includes four backscattering coefficients(HH,HV,VH,VV)and eleven polarimetric indices for all Radarsat-2 SAR images.The cumulative temporal sum(seasonal and dual-season)of these parameters was supervised classified using Support Vector Machine(SVM)classifier with intensive ground observation samples.Classification results using the best equation(highest accuracy and kappa)shows that the Kharif,Rabi and irrigated double croplands are respectively 9.58 km2(20.6%),16.14 km2(34.7%)and 6.22 km2(13.4%)with a kappa coefficient respectively 0.84,0.74 and 0.94.