scholarly journals Classificação Espectral de Fitofisionomias em Área de Floresta Tropical Utilizando Dados do Sensor Aster

2019 ◽  
Vol 23 (2) ◽  
pp. 132
Author(s):  
Gustavo Manzon Nunes ◽  
Carlos Roberto De Souza Filho ◽  
Laerte Guimarães Ferreira ◽  
Luiz Eduardo Vicente ◽  
Maricéia Tatiana Vilani
Keyword(s):  
Sustainable Development ◽  
Near Infrared ◽  
Thermal Emission ◽  
Matched Filtering ◽  
Spectral Angle Mapper ◽  
Ndvi Index ◽  
Close Relationship ◽  
Spectral Patterns ◽  
Shortwave Infrared ◽  
Spectral Angle

Este artigo pretende avaliar a capacidade dos dados gerados pelo sensor Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)/Terra, na discriminação de fitofisionomias existentes na Reserva de Desenvolvimento Sustentável Amanã (RDSA). Os dados ASTER analisados incluem os intervalos espectrais do visível (0.52-0.69 μm), infravermelho próximo (0.78-0.86 μm) e infravermelho de ondas curtas (1.60 a 2.43 μm), sendo que nas bandas destes intervalos foram aplicadas técnicas de classificação espectral adaptadas para os dados deste sensor como Spectral Angle Mapper (SAM), Mixture Tuned Matched Filtering (MTMF), além do NDVI. Através da técnica SAM foi possível a discriminação de seis fitofisionomias predominantes na RDSA. Através da técnica MTMF, que envolve um algoritmo de classificação mais robusto, informações equivalentes foram obtidas. Foi possível ainda a associação e detecção dos padrões espectrais da cobertura vegetal, mostrando a estreita relação com o índice NDVI. Palavras-chave: Mapeamento. Reserva de Desenvolvimento Sustentável Amanã. Vegetação.  Abstract This article aims to evaluate the data capacity created by a sensor named Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)/Terra, in the phytophysiognomies description of Amanã Sustainable Development Reserve (RDSA). The ASTER data analyzed include the spectral intervals of visible (0.52-0.69 μm), near-infrared (0.78-0.86 μm) and shortwave infrared (1.60 to 2:43 μm), wherein these intervals bands were applied the spectral classification techniques adapted to the data from this sensor as Spectral Angle Mapper (SAM), Mixture Tuned Matched Filtering (MTMF) plus NDVI. By SAM technique was possible to distinguish six predominant phytophysiognomies in the RDSA. By MTMF technique that involves a more robust classification algorithm, equivalent information was obtained. It was also possible to associate and detect spectral patterns of vegetation, showing the close relationship with the NDVI index. Keywords: Amanã Sustainable Development Reserve. Mapping. Vegetation. 

scholarly journals Mineral Detection Using Sharpened VNIR and SWIR Bands of Worldview-3 Satellite Imagery

2021 ◽  
Vol 13 (10) ◽  
pp. 5518
Author(s):  
Honglyun Park ◽  
Jaewan Choi
Keyword(s):  
Spatial Resolution ◽  
Satellite Imagery ◽  
Near Infrared ◽  
False Negative ◽  
Similarity Score ◽  
Majority Voting ◽  
Similarity Analysis ◽  
Spectral Angle Mapper ◽  
Mineral Detection ◽  
Shortwave Infrared

Worldview-3 satellite imagery provides panchromatic images with a high spatial resolution and visible near infrared (VNIR) and shortwave infrared (SWIR) bands with a low spatial resolution. These images can be used for various applications such as environmental analysis, urban monitoring and surveying for sustainability. In this study, mineral detection was performed using Worldview-3 satellite imagery. A pansharpening technique was applied to the spatial resolution of the panchromatic image to effectively utilize the VNIR and SWIR bands of Worldview-3 satellite imagery. The following representative similarity analysis techniques were implemented for the mineral detection: the spectral angle mapper (SAM), spectral information divergence (SID) and the normalized spectral similarity score (NS3). In addition, pixels that could be estimated to indicate minerals were calculated by applying an empirical threshold to each similarity analysis result. A majority voting technique was applied to the results of each similarity analysis and pixels estimated to indicate minerals were finally selected. The results of each similarity analysis were compared to evaluate the accuracy of the proposed methods. From that comparison, it could be confirmed that false negative and false positive rates decreased when the methods proposed in the present study were applied.

scholarly journals Applying spectral analysis for identification of alteration zones in north Saveh area, Iran

2020 ◽  
Author(s):  
Kazem Rangzan ◽  
Somayeh Beyranvand ◽  
Hoshang Pourkaseb ◽  
Hojjatollah Ranjbar ◽  
Alireza Zarasvandi
Keyword(s):  
Hydrothermal Alteration ◽  
Near Infrared ◽  
Thermal Emission ◽  
Spectral Response ◽  
Volcanic Rocks ◽  
Short Wave ◽  
Rapid Identification ◽  
Spectral Angle Mapper ◽  
Alteration Zones ◽  
The North

An extensive series of volcanic rocks are exposed in the north of Saveh city, Iran, which consist of phyllic, argillic and propylitic hydrothermal alteration types. For the purpose of the investigation, a FieldSpec3® spectroradiometer was used to measure the spectral response of the mineral content of these rocks. The spectral analyses of reflectance curve by The Spectral Geologist (TSG) software could discriminate kaolinite and montmorillonite (argillic), illite, muscovite, phengite and paragonite (phyllic), hornblende and chlorite, siderite (propylitic), hematite and goethite from the gossans. It also detected gypsum of hydrothermal alteration zones. The Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) image, which was used for mapping the hydrothermal alteration minerals, contains the Visible and Near Infrared (VNIR) wavelengths between 0.52 µm and 0.86 µm, Short Wave Infrared (SWIR) wavelengths between 1.6 µm and 2.43 µm and Thermal Infrared (TIR) wavelengths between 8.125 µm and 11.65 µm with 15, 30 and 90 m spatial resolutions, respectively. For calibration of the ASTER images, the extracted spectra of different rocks and minerals were used for atmospheric and radiometric corrections. Mixture tuned matched filtering (MTMF) and Spectral Angle Mapper (SAM) were applied on ASTER data to map the hydrothermal alteration of minerals. The use of the spectroradiometry techniques in conjunction with other data exhibits the ability of these new methods for non-destructive and rapid identification of mineral types for more detailed investigation. The results show that the area has undergone different levels of hydrothermal alteration, so much so that phyllic, argillic and propylitic types of hydrothermal alteration are present in the study area. This may point to high potential and promising zones for the exploration of porphyry mineralisation.

scholarly journals Hyperspectral Monitoring of Non-Native Tropical Grasses over Phenological Seasons

2021 ◽  
Vol 13 (4) ◽  
pp. 738
Author(s):  
Kirrilly Pfitzner ◽  
Renee Bartolo ◽  
Tim Whiteside ◽  
David Loewensteiner ◽  
Andrew Esparon
Keyword(s):  
Near Infrared ◽  
Spectral Response ◽  
Grass Species ◽  
Wet Season ◽  
Native Grass ◽  
Data Collections ◽  
Spectral Patterns ◽  
Shortwave Infrared ◽  
Over Time

The miniaturisation of hyperspectral sensors for use on drones has provided an opportunity to obtain hyper temporal data that may be used to identify and monitor non-native grass species. However, a good understanding of variation in spectra for species over time is required to target such data collections. Five taxological and morphologically similar non-native grass species were hyper spectrally characterised from multitemporal spectra (17 samples over 14 months) over phenological seasons to determine their temporal spectral response. The grasses were sampled from maintained plots of homogenous non-native grass cover. A robust in situ standardised sampling method using a non-imaging field spectrometer measuring reflectance across the 350–2500 nm wavelength range was used to obtain reliable spectral replicates both within and between plots. The visible-near infrared (VNIR) to shortwave infrared (SWIR) and continuum removed spectra were utilised. The spectra were then resampled to the VNIR only range to simulate the spectral response from more affordable VNIR only hyperspectral scanners suitable to be mounted on drones. We found that species were separable compared to similar but different species. The spectral patterns were similar over time, but the spectral shape and absorption features differed between species, indicating these subtle characteristics could be used to distinguish between species. It was the late dry season and the end of the wet season that provided maximum separability of the non-native grass species sampled. Overall the VNIR-SWIR results highlighted more dissimilarity for unlike species when compared to the VNIR results alone. The SWIR is useful for discriminating species, particularly around water absorption.

VNIR-SWIR Superspectral Mineral Mapping: An Example from Cuprite, Nevada

2020 ◽  
Vol 86 (11) ◽  
pp. 695-700
Author(s):  
Kathleen E. Johnson ◽  
Krzysztof Koperski
Keyword(s):  
Near Infrared ◽  
Thermal Emission ◽  
High Spatial Resolution ◽  
Ground Truth ◽  
Random Forest Classifier ◽  
Hyperspectral Data ◽  
United States Geological Survey ◽  
Mineral Mapping ◽  
Mapping Techniques ◽  
Shortwave Infrared

Cuprite, Nevada, is a location well known for numerous studies of its hydrothermal mineralogy. This region has been used to validate geological interpretations of airborne hyperspectral imagery (AVIRIS HSI ), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER ) imagery, and most recently eight-band WorldView-3 shortwave infrared (SWIR ) imagery. WorldView-3 is a high-spatial-resolution commercial multispectral satellite sensor with eight visible-to-near-infrared (VNIR ) bands (0.42–1.04 μm) and eight SWIR bands (1.2–2.33 μm). We have applied mineral mapping techniques to all 16 bands to perform a geological analysis of the Cuprite, Nevada, location. Ground truth for the training and validation was derived from AVIRIS hyperspectral data and United States Geological Survey mineral spectral data for this location. We present the results of a supervised mineral-mapping classification applying a random-forest classifier. Our results show that with good ground truth, WorldView-3 SWIR + VNIR imagery produces an accurate geological assessment.

scholarly journals Implementation of the NHI (Normalized Hot Spot Indices) Algorithm on Infrared ASTER Data: Results and Future Perspectives

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1538
Author(s):  
Giuseppe Mazzeo ◽  
Micheal S. Ramsey ◽  
Francesco Marchese ◽  
Nicola Genzano ◽  
Nicola Pergola
Keyword(s):  
Near Infrared ◽  
Thermal Emission ◽  
Hot Spot ◽  
Thermal Anomaly ◽  
Google Earth ◽  
Thematic Mapper ◽  
Landsat 8 ◽  
Thermal Anomalies ◽  
Aster Data ◽  
Shortwave Infrared

The Normalized Hotspot Indices (NHI) tool is a Google Earth Engine (GEE)-App developed to investigate and map worldwide volcanic thermal anomalies in daylight conditions, using shortwave infrared (SWIR) and near infrared (NIR) data from the Multispectral Instrument (MSI) and the Operational Land Imager (OLI), respectively, onboard the Sentinel 2 and Landsat 8 satellites. The NHI tool offers the possibility of ingesting data from other sensors. In this direction, we tested the NHI algorithm for the first time on Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data. In this study, we show the results of this preliminary implementation, achieved investigating the Kilauea (Hawaii, USA), Klyuchevskoy (Kamchatka; Russia), Shishaldin (Alaska; USA), and Telica (Nicaragua) thermal activities of March 2000–2008. We assessed the NHI detections through comparison with the ASTER Volcano Archive (AVA), the manual inspection of satellite imagery, and the information from volcanological reports. Results show that NHI integrated the AVA observations, with a percentage of unique thermal anomaly detections ranging between 8.8% (at Kilauea) and 100% (at Shishaldin). These results demonstrate the successful NHI exportability to ASTER data acquired before the failure of SWIR subsystem. The full ingestion of the ASTER data collection, available in GEE, within the NHI tool allows us to develop a suite of multi-platform satellite observations, including thermal anomaly products from Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+), which could support the investigation of active volcanoes from space, complementing information from other systems.

scholarly journals Neural Network and Multiple Linear Regression for Estimating Surface Albedo from ASTER Visible and Near-Infrared Spectral Bands

2013 ◽  
Vol 17 (3) ◽  
pp. 1-20 ◽  
Author(s):  
Mohammad H. Mokhtari ◽  
Ibrahim Busu ◽  
Hossein Mokhtari ◽  
Gholamreza Zahedi ◽  
Leila Sheikhattar ◽  
...  
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Surface Albedo ◽  
Near Infrared ◽  
Thermal Emission ◽  
Current Model ◽  
Primary Analysis ◽  
Aster Data ◽  
Spectral Bands ◽  
Shortwave Infrared

Abstract The current Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)-based broadband albedo model requires shortwave infrared bands 5 (2.145–2.185 nm), 6 (2.185–2.225 nm), 8 (2.295–2.365 nm), and 9 (2.360–2.430 nm) and visible/near-infrared bands 1 (0.52–0.60 nm) and 3 (0.78–0.86 nm). However, because of sensor irregularities at high temperatures, shortwave infrared wavelengths are not recorded in the ASTER data acquired after April 2008. Therefore, this study seeks to evaluate the performance of artificial neural networks (ANN) in estimating surface albedo using visible/near-infrared bands available in the data obtained after April 2008. It also compares the outcomes with the results of multiple linear regression (MLR) modeling. First, the most influential spectral bands used in the current model as well as band 2 (0.63–0.69 nm) (which is also available after April 2008 in the visible/near-infrared part) were determined by a primary analysis of the data acquired before April 2008. Then, multiple linear regression and ANN models were developed by using bands with a relatively high level of contribution. The results showed that bands 1 and 3 were the most important spectral ones for estimating albedo where land cover consisted of soil and vegetation. These two bands were used as the study input, and the albedo (estimated through a model that utilized bands 1, 3, 5, 6, 8, and 9) served as a target to remodel albedo. Because of its high collinearity with band 1, band 2 was identified less effectively by MLR as well as ANN. The study confirmed that a combination of bands 1 and 3, which are available in the current ASTER data, could be modeled through ANN and MLR to estimate surface albedo. However, because of its higher accuracy, ANN method was superior to MLR in developing objective functions.

scholarly journals Recognition of Minerals Using Multispectral Remote Sensing Data: A Case Study in the Sultanate of Oman

2015 ◽  
Vol 19 (2) ◽  
pp. 37 ◽  
Author(s):  
Sankaran Rajendran ◽  
Sobhi Nasir
Keyword(s):  
Near Infrared ◽  
Thermal Emission ◽  
Image Interpretation ◽  
Remote Sensing Data ◽  
Source Rocks ◽  
Sultanate Of Oman ◽  
Alluvial Deposits ◽  
Study Region ◽  
Spectral Angle Mapper ◽  
Rock Types

The present study demonstrates the capability of a multispectral sensor for the detection of the minerals in the rocks surrounding the Rusayl and Al Jafnayn regions, Sultanate of Oman. The study of spectral absorptions of rocks and minerals in the visible and near infrared (VNIR) and short wavelength infrared (SWIR) spectral bands of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) using the Spectral Angle Mapper (SAM) supervised image classification technique has provided information on the occurrence of minerals in the rock types of the regions. The study shows the occurrence of carbonate minerals in the limestone formations and of poorly altered silicate minerals in the basic dyke rocks of the study regions. The analysis of minerals over the ancient terraces and recent alluvial deposits show that the deposit materials are derived from the dykes and foliated gabbro source rocks. The image interpretation is compared to the geological map, verified in the field and confirmed through laboratory analyses. The satellite data and the image processing techniques used have potential in the recognition of minerals in the rocks of the study region and could be used in similar arid regions elsewhere in the world.  

Quantifying Lygus (Hemiptera: Miridae) damage in faba bean (Fabaceae) seeds using shortwave-infrared imaging

2019 ◽  
Vol 151 (04) ◽  
pp. 442-455
Author(s):  
A.M. Smith ◽  
B. Rivard ◽  
J. Feng ◽  
H.A. Carcamo
Keyword(s):  
Faba Bean ◽  
Infrared Imaging ◽  
Seed Quality ◽  
Strong Relationship ◽  
Economic Losses ◽  
Spectral Angle Mapper ◽  
Analysis Techniques ◽  
Seed Damage ◽  
Shortwave Infrared ◽  
Spectral Angle

AbstractLygus Hahn (Hemiptera: Miridae) feeding in faba beans (Vicia faba Linnaeus (Fabaceae)) often results in a reduction in seed quality and economic losses. Traditionally, seed damage is assessed subjectively through visual examination by a trained individual, but the use of non-destructive imaging to evaluate seed quality is gaining momentum. The focus of this study was to determine the ability to quantify Lygus species damage in faba bean using shortwave-infrared imaging and two analysis techniques: (1) spectral angle mapper and (2) simple reflectance indices. Seed samples were visually assessed for damage before imaging in 242 wavebands between 980 and 2500 nm. Four spectral intervals, involving 102 wavebands, were identified as optimal for the detection of seed damage using spectral angle mapper. A strong relationship was obtained between the area of seed damage derived using spectral angle mapper and visually (R2 = 0.95). Seed damage derived by thresholding of two normalised faba bean damage indices involving reflectance at 1086 and 1313 nm and 2218 and 2342 nm also showed a strong relationship with the visual assessment (R2 = 0.92). The two image analysis techniques provided similar results. The study suggests that imaging in the shortwave-infrared wavelengths and the derivation of simple indices can effectively quantify faba bean damage by Lygus feeding.

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