Combination Of Different Bands Research Articles

ASTER VNIR‐SWIR Based Lithological Mapping of Granitoids in the Western Junggar Orogen (NW Xinjiang): Improved Inputs to Random Forest Method

AbstractAlthough advanced spaceborne thermal emission and reflection radiometer multispectral analysis for lithological mapping has been widely applied, traditional methods such as band ratios (BR) and principal component analysis (PCA) are still hampered by cumbersome data processing and poor classification performance. In this study, we utilize improved data inputs for random forest (RF) to extract lithological information of granitoids, which are the predominant rock type for intrusion‐related polymetallic ore deposits in the western Junggar Orogen (NW Xinjiang). Based on spectral absorption features of minerals (e.g., orthoclase, K‐feldspar, hornblende, biotite, plagioclase, and oligoclase), image statistical information and textural features, we tested different combinations of bands, BR, PCA, and texture using RF method, and found that the combination of B13678 + T1 (Mean texture) achieved the highest weighted‐F1 score for granitoids, with an accuracy of 87.32%. Compared to the support vector machine, RF effectively distinguishes lithological differences between different types of granitoid and wallrocks, especially the granite, granodiorite, and alkali granite in the Akebasito intrusion, as well as the alkali granite, plagiogranite and biotite granite in the Karamay intrusions. Moreover, the large number of rare metal deposits (including Cu, Au, Mo, etc.) distributed near the granitoid intrusions in the western Junggar, our result facilitates the analysis of regional tectonic evolution and mineralization controlling.

Monitoring tree mortality in Ukrainian Pinus sylvestris L. forests using remote sensing data from earth observing satellites

This article considers the application of remote sensing data to solve the problems of forestry in the Polissia zone (Ukraine). The satellite remote sensing was shown to be applicable to monitoring the damage caused by diseases and pests to forest resources and to assessing the effects of fires. During the research, a detailed analysis and optimization of the information content of Sentinel-2 long-term data sets was performed to detect changes in the forest cover of Polissia, affected by pests and damaged by fires. The following classification algorithms were used for automated decryption: the maximum likelihood method; cluster classification without training; Principal Component Analysis (PCA); Random Forest classification. The results of this study indicate the high potential of Sentinel-2 data for application in applied problems of forestry and vegetation analysis, despite the decametric spatial resolution. Our proposed workflow has achieved an overall classification accuracy of 90 % for the Polissia region, indicating its reliability and potential for scaling to a higher level, and the proposed forecast model is stationary and does not depend on time parameters. To improve the classification results, testing of different combinations of bands emphasized the importance of Band 8 in combination with red edge bands, as well as other bands with a resolution of 10 m for summer scenes. The red margin shows clearly visible differences in the spectral profiles, but bands with a higher resolution of 10 m were crucial for good results.

Teledetección aplicada al mapeo geomorfológico de los volcanes de la cuenca alta del río Chaschuil, provincia de Catamarca, Argentina

Contexto: La cuenca alta del río Chaschuil se encuentra en las provincias geomorfológicas de codillera Frontal y sistema de Famatina, se extiende desde el límite superior de la cuenca, a los 26° 45' 6,35" de latitud S y 68° 2'22 15" de longitud O, hasta el volcán Aguas Calientes, a los 27° 13' 25,81" de latitud S y 68° 19'5 48" de longitud O. La zona se inserta en el Cinturón de Fuego del Pacífico, que se caracteriza por concentrar algunas zonas de subducción más importantes del mundo, donde se genera una intensa actividad sísmica y volcánica.
 Método: A través de operaciones estadísticas y numéricas aplicadas sobre los datos de las matrices que componen una imagen satelital, se generó la cartografía geomorfológica volcánica. Para dicho análisis, se utilizó el software libre SoPI 3.0, en el que se procesaron las imágenes satelitales Landsat 7 y 8, de los años 2002 y 2015. La cartografía fue elaborada en el software libre QGIS 3.2.2, con el apoyo del software libre Google Earth Pro.
 Resultados: Los mejores resultados del procesamiento digital se dieron en las bandas de rango visible y mediante distintas combinaciones de bandas en RGB. Se describen 13 aparatos volcánicos principales, altamente erosionados, con lavas pahoehoe asociadas; y erupciones secundarias, con lavas rugosas tipo aa sobrepuestas a las lavas más fluidas.
 Conclusiones: La aplicación del procesamiento digital de imágenes satelitales es una herramienta óptima para el estudio de estructuras volcánicas, que permite su delimitación y clasificación.

A User-Oriented Simplification of the ( $V,W$ ) Burn-Sensitive Vegetation Index System

Remote sensing from spaceborne sensors combining near- and middle-infrared information has proved to be an efficient means to monitor the effects of vegetation fires. Burn-sensitive spectral indices, such as the ( $V,W$ ) index system, have been developed and successfully applied for burned area discrimination. The ( $V,W$ ) index system provides useful capability to discriminate burned pixels, but the elaborate numerical computations involved are a major drawback in operational applications. This letter presents a simplified algorithm to compute the approximate values of indices $V$ and $W$ . The methodology developed is tested in a region located in the Brazilian Cerrado using remote-sensed data from the MODIS instrument. The simplification allows performing burned area discrimination with the same quality as the original algorithm. The methodology may be extended to other sensors and different combinations of bands and opens new perspectives to the generation of synergic long-term databases of burned area.

A Study toward the Evaluation of ALOS Images for LAI Estimation in Rice Fields

Abstract. For expanding and managing agricultural sources, satellite data have a key role in determining required information about different factors in plants Including Leaf Area Index (LAI).This paper has studied the potential of spectral indices in estimating rice canopy LAI in Amol city as one of the main sources of rice production in Iran. Due to its importance in provision of food and calorie of a major portion of population, rice product was chosen for study. A field campaign was conducted when rice was in the max growth stage (late of June). Also, two satellite images from ALOS-AVNIR-2 were used (simultaneous with conducted field works) to extract and determine vegetation indices. Then the Regression between measured data and vegetation indices, derived from combination of different bands, was evaluated and after that suitable vegetation indices were realized. Finally, statistics and calculations for introduction of a suitable model were presented. After examination of models, the results showed that RDVI and SAVI2, by determination coefficient and RMSE of 0.12–0.59 and 0.24–0.62, have more accuracy in LAI estimation. Results of present study demonstrated the potential of ALOS images, for LAI estimation and their significant role in monitoring and managing the rice plant.

Review on Study of Lake Water Using Multi Sensor Remote Sensing Data

In this paper multi sensor satellite data i.e. IRS LISS III or Landsat TM/ETM+ or OCEANSAT1(IRS-P4) consisting of an Ocean Color Monitoring operating in eight spectral band data are used for extracting information useful to hydrological projects such as monitoring the water quality of lakes. Changes of the area extent of the lakes are estimated from the multitemporal satellite images. Surface water temperature patterns of the lakes are mapped and anomalies are identified. Emphasis is given on the investigation of capabilities of IRS LISS III or Landsat TM/ETM+ or OCEANSAT-1(IRS-P4) data in monitoring water quality of lakes. A classification scheme regarding various water quality parameters (Secchi depth, Turbitidity, Chlorophylle –α and Total Total phosphorus) is created based on combinations of different bands.

Crude protein electrophoresis of seeds of ten species of <i>Solanum</i> L

Seeds of mature fruits of ten species of Solanum were collected from the gardens near the screen house, Botany Department, Obafemi Awolowo University, Ile Ife, Osun State, Nigeria. Crude seed proteins were extracted from them and characterised using polyacrylamide gel electrophoresis. Inter and intra specific qualitative and quantitative protein bands depicting some degree of relationships among the taxa were observed. The degree of variation in bands as a measure of genetic divergence of Solanum species is discussed. Electrophoretic mobility of seed proteins revealed different combinations of bands at various distances from the anode was taxon specific and could be used in separating Solanum species Keywords : Solanum species, Polyacrylamide electrophoresis, Taxonomy. Global Journal of Pure and Applied Sciences Vol. 14 (3) 2008: pp. 257-262