scholarly journals Using Hyperspectral Crop Residue Angle Index to Estimate Maize and Winter-Wheat Residue Cover: A Laboratory Study

2019 ◽  
Vol 11 (7) ◽  
pp. 807 ◽  
Author(s):  
Jibo Yue ◽  
Qingjiu Tian ◽  
Xinyu Dong ◽  
Kaijian Xu ◽  
Chengquan Zhou
Keyword(s):  
Remote Sensing ◽  
Laboratory Study ◽  
Crop Residue ◽  
Near Infrared ◽  
Crop Residues ◽  
Broad Band ◽  
Field Testing ◽  
Short Wave ◽  
Spectral Indices ◽  
Infrared Band

Crop residue left in the field after harvest helps to protect against water and wind erosion, increase soil organic matter, and improve soil quality, so a proper estimate of the quantity of crop residue is crucial to optimize tillage and for research into environmental effects. Although remote-sensing-based techniques to estimate crop residue cover (CRC) have proven to be good tools for determining CRC, their application is limited by variations in the moisture of crop residue and soil. In this study, we propose a crop residue angle index (CRAI) to estimate the CRC for four distinct soils with varying soil moisture (SM) content and crop residue moisture (CRM). The current study uses laboratory-based tests ((i) a dry dataset (air-dried soils and crop residues, n = 392); (ii) a wet dataset (wet soils and crop residues, n = 822); (iii) a saturated dataset (saturated soils and crop residues, n = 402); and (iv) all datasets (n = 1616)), which allows us to analysis the soil and crop residue hyperspectral response to varying SM/CRM. The CRAI combines two features that reflect the moisture content in soil and crop residue. The first is the different reflectance of soil and crop residue as a function of moisture in the near-infrared band (833 nm) and short-wave near-infrared band (1670 nm), and the second is different reflectance of soils and crop residues to lignin, cellulose, and moisture in the bands at 2101, 2031, and 2201 nm. The effects of moisture and soil type on the proposed CRAI and selected traditional spectral indices ((i) hyperspectral cellulose absorption index; (ii) hyperspectral shortwave infrared normalized difference residue index; and (iii) selected broad-band spectral indices) were compared by using a laboratory-based dataset. The results show that the SM/CRM significantly affects the broad-band spectral indices and all other spectral indices investigated are less correlated with CRC when using all datasets than when using only the dry, wet, or saturated dataset. Laboratory study suggests that the CRAI is promising for estimating CRC with the four soils and with varying SM/CRM. However, because the CRAI was only validated by a laboratory-based dataset, additional field testing is thus required to verify the use of satellite hyperspectral remote-sensing images for different crops and ecological areas.

scholarly journals Forest and land fire smoke detection using GCOM-C data (case study: Pulang Pisau, Central Kalimantan)

2021 ◽  
Vol 893 (1) ◽  
pp. 012068
Author(s):  
K I N Rahmi ◽  
N Febrianti ◽  
I Prasasti
Keyword(s):  
Near Infrared ◽  
Thermal Infrared ◽  
Short Wave ◽  
Forest Land ◽  
Visual Interpretation ◽  
Infrared Band ◽  
Central Kalimantan ◽  
Fire Smoke ◽  
Shortwave Infrared

Abstract Forest/land fire give bad impact of heavy smoke on peatland area in Indonesia. Forest/land fire smoke need to be identified the distribution periodically. New satellite of GCOM-C has been launched to monitor climate condition and have visible, near infrared and thermal infrared. This study has objective to identify fire smoke from GCOM-C data. GCOM-C data has wavelength range from 0.38 to 12 μm it covers visible, near infrared, short-wave infrared and thermal infrared. It is relatively similar to MODIS or Himawari-8 images which could identify forest/land fire smoke. The methodology is visual interpretation to detect forest/land fire smoke using near infrared band (VN08), shortwave infrared band (SW03), and thermal bands (T01 and T02). Hotspot data is overlaid with GCOM-C image to represent the location of fire events. Combination of composite RGB image has been applied to detect forest/land fire smoke. GCOM-C image of VN8 bands and combination of thermal band in composite image could be used to detect fire smoke in Pulang Pisau, Central Kalimantan.

scholarly journals Radiometric Calibration of UAV Remote Sensing Image with Spectral Angle Constraint

2019 ◽  
Vol 11 (11) ◽  
pp. 1291 ◽  
Author(s):  
Kaiqiu Xu ◽  
Yan Gong ◽  
Shenghui Fang ◽  
Ke Wang ◽  
Zhiheng Lin ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Near Infrared ◽  
Linear Method ◽  
Radiometric Calibration ◽  
Constraint Condition ◽  
Infrared Band ◽  
Spectral Bands ◽  
Quantitative Remote Sensing ◽  
Spectral Channels ◽  
Spectral Angle

In recent years, the acquisition of high-resolution multi-spectral images by unmanned aerial vehicles (UAV) for quantitative remote sensing research has attracted more and more attention, and radiometric calibration is the premise and key to the quantification of remote sensing information. The traditional empirical linear method independently calibrates each channel, ignoring the correlation between spectral bands. However, the correlation between spectral bands is very valuable information, which becomes more prominent as the number of spectral channels increases. Based on the empirical linear method, this paper introduces the constraint condition of spectral angle, and makes full use of the information of each band for radiometric calibration. The results show that, compared with the empirical linear method, the proposed method can effectively improve the accuracy of radiometric calibration, with the improvement range of Mean Relative Percent Error (MRPE) being more than 3% in the range of visible band and within 1% in the range of near-infrared band. Besides, the method has great advantages in agricultural remote sensing quantitative inversion.

Rapid dehazing algorithm based on large-scale median filtering for high-resolution visible near-infrared remote sensing images

2014 ◽  
Vol 12 (05) ◽  
pp. 1461010 ◽  
Author(s):  
Changmiao Hu ◽  
Ping Tang
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Land Surface ◽  
Large Scale ◽  
Near Infrared ◽  
Low Frequency ◽  
Median Filtering ◽  
Remote Sensing Images ◽  
Infrared Band ◽  
Remote Sensing Image Processing

In recent years, China's demand for satellite remote sensing images increased. Thus, the country launched a series of satellites equipped with high-resolution sensors. The resolutions of these satellites range from 30 m to a few meters, and the spectral range covers the visible to the near-infrared band. These satellite images are mainly used for environmental monitoring, mapping, land surface classification and other fields. However, haze is an important factor that often affects image quality. Thus, dehazing technology is becoming a critical step in high-resolution remote sensing image processing. This paper presents a rapid algorithm for dehazing based on a semi-physical haze model. Large-scale median filtering technique is used to extract large areas of bright, low-frequency information from images to estimate the distribution and thickness of the haze. Four images from different satellites are used for experiment. Results show that the algorithm is valid, fast, and suitable for the rapid dehazing of numerous large-sized high-resolution remote sensing images in engineering applications.

RealSens™: An Advanced Passive Airborne Natural Gas Leak Detection Technology

2006 ◽  
Author(s):  
Adrian Banica ◽  
Chris K. Sheard ◽  
Boyd T. Tolton
Keyword(s):  
Remote Sensing ◽  
Natural Gas ◽  
Near Infrared ◽  
New Technology ◽  
Infrared Band ◽  
Underground Pipelines ◽  
Detection Technology ◽  
Gas Leak ◽  
Gas Leaks ◽  
Transmission And Distribution

Detecting natural gas leaks from the worlds nearly 5 million kilometers of underground pipelines is a difficult and costly challenge. Existing technologies are limited to ground deployment and have a number of limitations such as slow response, false leak readings and high costs. Various remote sensing solutions have been proposed in the past and a few are currently being developed. This paper starts by describing the remote sensing concept and then will focus on a new technology developed by Synodon scientists. This airborne instrument is a passive Gas Filter Correlation Radiometer (GFCR) that is tuned to measure ethane in the 3.3 microns near-infrared band. With its target natural gas column sensitivity of 50 μm, the instrument is capable of detecting very small leaks in the range of 5–10 cuft/hr in winds that exceed 6 miles/hr. The paper concludes with a description of the service which Synodon will be offering to the transmission and distribution pipeline operators using the new technology.

Results of Field Trials of Realsens™, An Airborne Natural Gas Leak Detection Technology

2008 ◽  
Author(s):  
Adrian Banica ◽  
Doug Miller ◽  
Boyd T. Tolton
Keyword(s):  
Remote Sensing ◽  
Natural Gas ◽  
Near Infrared ◽  
New Technology ◽  
Field Tests ◽  
Field Trials ◽  
Infrared Band ◽  
Detection Technology ◽  
Gas Leak ◽  
Gas Leaks

Detecting natural gas leaks from the worlds nearly 5 million kilometers of underground pipelines is a difficult and costly challenge. Existing technologies are limited to ground deployment and have a number of limitations such as slow response, false leak readings and high costs. Various remote sensing solutions have been proposed in the past and a few are currently being developed. This paper starts by describing the remote sensing concept and then will focus on a new technology developed by Synodon scientists. This airborne instrument is a passive Gas Filter Correlation Radiometer (GFCR) that is tuned to measure ethane in the 3.3 microns near-infrared band. The paper will then present the results of the first airborne field tests and conclude with a description of the service which Synodon will be offering to the transmission and distribution pipeline operators using the new technology.

Forest-fire-scar aging using SPOT-VEGETATION for Canadian ecoregions

2003 ◽  
Vol 33 (6) ◽  
pp. 1116-1125 ◽  
Author(s):  
Brian D Amiro ◽  
Jing M Chen
Keyword(s):  
Near Infrared ◽  
Forest Succession ◽  
Short Wave ◽  
Federal Agencies ◽  
Infrared Band ◽  
Fire Scars ◽  
Fire Scar ◽  
Remote Sensing Techniques ◽  
Large Effort ◽  
Nominal Resolution

The mapping of Canadian fires is a large effort supported by provincial, territorial, and federal agencies. Remote sensing techniques can aid in mapping, especially in remote areas and during busy fire seasons. The SPOT-VEGETATION (SPOT-VGT) sensor has previously shown promise at distinguishing fire scars on the landscape. The usefulness of SPOT-VGT to age fires in 18 Canadian ecoregions was evaluated for a period up to 50 years since fire, analysing more than 250 000 pixels (nominal resolution about 1 km2). The SPOT-VGT reflectances were evaluated using the ratio of the short-wave infrared band (1.58–1.75 µm) to near-infrared band (0.78–0.89 µm), compared with the Canadian large-fire database (fires greater than 200 ha in size). Nonlinear regressions were significant for all ecoregions with r2 values being greater than 0.57 for 16 of them. Five ecoregions groupings had similar relationships, consistent with their contiguous pattern on the landscape. The prediction of fire-scar age depends on ecoregion and can be successful over periods as short as 6 years to as long as 30 years. The root mean square error for all ecoregions ranged from 5 years for recent burns to about 12 years for three decades following fire. This tool is useful to get approximate fire-scar ages, but the accuracy is limited because of the variation in forest succession on the landscape, and it cannot replace more detailed mapping done currently by fire agencies.

X-ray diffraction and infrared characterization of Oxisols from central and southeastern Brazil

Clay Minerals ◽  
2008 ◽  
Vol 43 (4) ◽  
pp. 549-560 ◽  
Author(s):  
R. P. Nitzsche ◽  
J. B. Percival ◽  
J. K. Torrance ◽  
J. A. R. Stirling ◽  
J. T. Bowen
Keyword(s):  
Remote Sensing ◽  
Near Infrared ◽  
Microwave Remote Sensing ◽  
Short Wave ◽  
Southeastern Brazil ◽  
X Ray Diffraction ◽  
X Ray ◽  
Sensing Applications ◽  
Remote Sensing Applications

AbstractEleven Oxisols with high clay contents, 2.6–59.7 wt.% Fe2O3, and containing hematite, goethite, magnetite and maghemite, from São Paulo, Minas Gerais and Goiás, Brazil, were studied for the purpose of microwave remote sensing applications in the 0.3 to 300 GHz range. Of special interest are: the pseudosand effect caused by Fe-oxide cementation of clusters of soil particles; the mineralogy; and whether the soil magnetic susceptibility affected by ferromagnetic magnetite and maghemite interferes with microwave propagation. Quantitative mineralogical analyses were conducted using X-ray diffraction with Rietveld refinement. Visible, near infrared and short wave infrared spectroscopic analyses were used to characterize the samples qualitatively for comparison with published spectral radiometry results. Quartz (3–88%), hematite (2–36%) and gibbsite (1–40%) occurred in all soils, whereas kaolinite (2–70%) and anatase (2–13%) occurred in nine samples. Ilmenite (1–8%) was found in eight soils and goethite (2–39%) in seven. Of the ferromagnetic minerals, maghemite occurred in seven soils (1–13%) and three contained magnetite (<2%). These results will be applied to the interpretation of the effect of Fe oxides, particularly the ferromagnetic oxides, on microwave interaction with high-Fe soils, with ultimate application to the monitoring of soil water content by microwave remote sensing.

scholarly journals Drought Monitoring With Spectral Indices Calculated From Modis Satellite Images In Hungary

2015 ◽  
Vol 8 (3-4) ◽  
pp. 11-20 ◽  
Author(s):  
András Gulácsi ◽  
Ferenc Kovács
Keyword(s):  
Drought Index ◽  
Vegetation Index ◽  
Near Infrared ◽  
Normalized Difference Vegetation Index ◽  
Short Wave ◽  
Drought Indices ◽  
High Temporal Resolution ◽  
Spectral Indices ◽  
Water Index ◽  
Water Indices

Abstract In this study a new remote sensing drought index called Difference Drought Index (DDI) was introduced. DDI was calculated from the Terra satellite’s MODIS sensor surface reflectance data using visible red, near-infrared and short-wave-infrared spectral bands. To characterize the biophysical state of vegetation, vegetation and water indices were used from which drought indices can be derived. The following spectral indices were examined: Difference Vegetation Index (DVI), Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Difference Water Index (DWI), Normalized Difference Water Index (NDWI), Difference Drought Index (DDI) and Normalized Difference Drought Index (NDDI). Regression analysis with the Pálfai Drought Index (PaDi) and average annual yield of different crops has proven that the Difference Drought Index is applicable in quantifying drought intensity. However, after comparison with reference data NDWI performed better than the other indices examined in this study. It was also confirmed that the water indices are more sensitive to changes in drought conditions than the vegetation ones. In the future we are planning to monitor drought during growing season using high temporal resolution MODIS data products.

scholarly journals KLUM: An Urban VNIR and SWIR Spectral Library Consisting of Building Materials

2019 ◽  
Vol 11 (18) ◽  
pp. 2149
Author(s):  
Rebecca Ilehag ◽  
Andreas Schenk ◽  
Yilin Huang ◽  
Stefan Hinz
Keyword(s):  
Remote Sensing ◽  
Urban Areas ◽  
Building Materials ◽  
Near Infrared ◽  
Imaging Spectroscopy ◽  
Short Wave ◽  
Spectral Library ◽  
Spectral Libraries ◽  
Roofing Materials

Knowledge about the existing materials in urban areas has, in recent times, increased in importance. With the use of imaging spectroscopy and hyperspectral remote sensing techniques, it is possible to measure and collect the spectra of urban materials. Most spectral libraries consist of either spectra acquired indoors in a controlled lab environment or of spectra from afar using airborne systems accompanied with in situ measurements. Furthermore, most publicly available spectral libraries have, so far, not focused on facade materials but on roofing materials, roads, and pavements. In this study, we present an urban spectral library consisting of collected in situ material spectra with imaging spectroscopy techniques in the visible and near-infrared (VNIR) and short-wave infrared (SWIR) spectral range, with particular focus on facade materials and material variation. The spectral library consists of building materials, such as facade and roofing materials, in addition to surrounding ground material, but with a focus on facades. This novelty is beneficial to the community as there is a shift to oblique-viewed Unmanned Aerial Vehicle (UAV)-based remote sensing and thus, there is a need for new types of spectral libraries. The post-processing consists partly of an intra-set solar irradiance correction and recalculation of reference spectra caused by signal clipping. Furthermore, the clustering of the acquired spectra was performed and evaluated using spectral measures, including Spectral Angle and a modified Spectral Gradient Angle. To confirm and compare the material classes, we used samples from publicly available spectral libraries. The final material classification scheme is based on a hierarchy with subclasses, which enables a spectral library with a larger material variation and offers the possibility to perform a more refined material analysis. The analysis reveals that the color and the surface structure, texture or coating of a material plays a significantly larger role than what has been presented so far. The samples and their corresponding detailed metadata can be found in the Karlsruhe Library of Urban Materials (KLUM) archive.

scholarly journals CCD CBERS and ASTER data in dasometric characterization of Pinus radiata D. Don (North-western Spain)

CERNE ◽  
2013 ◽  
Vol 19 (1) ◽  
pp. 103-110 ◽  
Author(s):  
Eva Sevillano-Marco ◽  
Alfonso Fernández-Manso ◽  
Carmen Quintano ◽  
Marcela Poulain
Keyword(s):  
Remote Sensing ◽  
Pinus Radiata ◽  
Near Infrared ◽  
Thermal Emission ◽  
Correlation Coefficients ◽  
Basal Area ◽  
Remote Sensing Data ◽  
Cost Effective ◽  
Infrared Band ◽  
Western Spain

A Chinese-Brazilian Earth Resources Satellite (CBERS) and an Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) scenes coupled with ancillary georeferenced data and field survey were employed to examine the potential of the remote sensing data in stand basal area, volume and aboveground biomass assessment over large areas of Pinus radiata D. Don plantations in Northwestern Spain. Statistical analysis proved that the near infrared band and the shade fraction image showed significant correlation coefficients with all stand variables considered. Predictive models were accordingly selected and utilized to undertake the spatial distribution of stand variables in radiata stands delimited by the National Forestry Map. The study reinforces the potentiality of remote sensing techniques in a cost-effective assessment of forest systems.

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