Remote sensing of water vapor in the near IR from EOS/MODIS

Kaufman, Yoram J.; Gao, Bo‐Cai

doi:10.1109/36.175321

Cited by 353 publications

(227 citation statements)

References 29 publications

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“…Total precipitable water b MODIS near-infrared daily total precipitable water product (MOD05; Gao and Kaufman, 2003;Kaufman and Gao, 1992); monthly values were generated by averaging daily values. Calculated from estimated incoming solar radiation obtained with the solar analyst tool in ArcGIS and SRTM DEM-elevation data, and remote sensing-based A s , T dry , and T s images in estimating outgoing and incoming reflected shortwave and long-wave radiation surfaces for R n and a NDVI-based correction of incident solar radiation for the ground heat flux (G; see Matin and Bourque, 2013b).…”

Section: Monthmentioning

confidence: 99%

Relating seasonal dynamics of enhanced vegetation index to the recycling of water in two endorheic river basins in north-west China

Matin

Bourque

2015

Hydrol. Earth Syst. Sci.

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Abstract. This study associates the dynamics of enhanced vegetation index in lowland desert oases to the recycling of water in two endorheic (hydrologically closed) river basins in Gansu Province, north-west China, along a gradient of elevation zones and land cover types. Each river basin was subdivided into four elevation zones representative of (i) oasis plains and foothills, and (ii) low-, (iii) mid-, and (iv) highmountain elevations. Comparison of monthly vegetation phenology with precipitation and snowmelt dynamics within the same basins over a 10-year period (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009) suggested that the onset of the precipitation season (cumulative % precipitation > 7-8 %) in the mountains, typically in late April to early May, was triggered by the greening of vegetation and increased production of water vapour at the base of the mountains. Seasonal evolution of in-mountain precipitation correlated fairly well with the temporal variation in oasisvegetation coverage and phenology characterised by monthly enhanced vegetation index, yielding coefficients of determination of 0.65 and 0.85 for the two basins. Convergent cross-mapping of related time series indicated bi-directional causality (feedback) between the two variables. Comparisons between same-zone monthly precipitation amounts and enhanced vegetation index provided weaker correlations. Start of the growing season in the oases was shown to coincide with favourable spring warming and discharge of meltwater from low-to mid-elevations of the Qilian Mountains (zones 1 and 2) in mid-to-late March. In terms of plant requirement for water, mid-seasonal development of oasis vegetation was seen to be controlled to a greater extent by the production of rain in the mountains. Comparison of water volumes associated with in-basin production of rainfall and snowmelt with that associated with evaporation seemed to suggest that about 90 % of the available liquid water (i.e. mostly in the form of direct rainfall and snowmelt in the mountains) was recycled locally.

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Section: Monthmentioning

confidence: 99%

Relating seasonal dynamics of enhanced vegetation index to the recycling of water in two endorheic river basins in north-west China

Matin

Bourque

2015

Hydrol. Earth Syst. Sci.

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“…The values of the A and B regions are higher than the values of their surroundings, as can be seen from Figures 3 and 4. The reflectance at the sea is complex (mixed pixel), and the general algorithm cannot depict the conditions very well [2]. The RM-NN can overcome this shortcoming by compensating the training database.…”

Section: Results and Evaluationmentioning

confidence: 99%

“…Until now, many algorithms have been proposed to estimate water vapor content from near-infrared at around 1 µm from MODIS data [2][3][4][5][6]. The general method uses ratios of water vapor absorbing channels at 0.905, 0.936 and 0.94 µm, with atmospheric window channels at 0.865 and 1.24 µm, to estimate water vapor content [2][3][4][5][6].…”

Section: Introductionmentioning

confidence: 99%

An Advanced Radiative Transfer and Neural Network Scheme and Evaluation for Estimating Water Vapor Content from MODIS Data

et al. 2017

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This work made an improvement upon and a further evaluation of previous work for estimating water vapor content from near-infrared around 1 µm from MODIS data. The accuracy of RM-NN is determined by the complicated relationship of the geophysical parameters. An advanced scheme is proposed for building different training databases for different seasons in different regions to reduce the complexity. The training database includes three parts. The first part is a simulation database by MODTRAN for different weather conditions, which is made as a basic database; the second part is reliable field measurement data in observation stations; and the third part is the MYD05_L2 product on clear days, which is produced by the standard product algorithm for water vapor content. The comparative analyses based on simulation data indicate that maximum accuracy of single condition could be improved by about 34% relative to the "all conditions" results. Two study regions in China and America are selected as test areas, and the evaluation shows that the mean and the standard deviation of estimation error are about 0.08 g cm −2 and 0.09 g cm −2 , respectively. All the analysis indicates that the advanced scheme can improve the retrieval accuracy of water vapor content, which can make full use of the advantages of previous methods.

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“…[2] Selain GPS, aplikasi lain yang digunakan seperti penginderaan jauh dapat digunakan untuk menurunkan informasi transmitan uap air dengan melakukan perbandingan reflektan permukaan antara kanal absorbsi dan kanal non absorbsi dengan mengabaikan pengaruh variasi reflektansi permukaan [8].…”

Section: Pendahuluanunclassified

“…Sehingga dapat disimpulkan bahwa keadaan topografi memperngaruhi pola distribusi PWV. Hasil analisis ini sesuai dengan teori [7][8][9][10][11][12].…”

Section: Hasil Pola Distribusi Pwv Secara Spasialunclassified

Analisa Penentuan Water Vapor Terhadap Pengaruh Erupsi Gunung Sinabung Menggunakan Data SUGAR Dan Citra Satelit Terra MODISs

Audah¹,

Cahyadi

Taufik

2017

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The eruption of Mount Sinabung in 2010 caused bursts of volcanic ash particles into the atmosphere layer to impact the weather. This is because volcanic ash is hydrocopic which can cause condensation process and block the process of solar radiation earth surface. Precivitable Water vapor (PWV) as one of the parameters of the atmosphere that can be used as information to determine the weather conditions in an area. Utilization of data Sumatran GPS Array (SUGAR) and data satellite Terra sensors MODIS (Moderate Resolution Imaging Spektroradiometer) can be used to find out PWV through GPS inversion method by utilizing estimated estimation of slowing and rotating GPS signals overlaid with troposphere. While the transmittance method is performed by comparing the surface reflectance between the channel absorption and the channel non absorption contained in the sensor MODIS. The results showed that spatial variation of PWV distribution pattern showed wetness pattern during eruption. This was indicated by some areas that have PWV distribution pattern almost in each region and PWV verification result from GPS showed ± 47.65 mm-66.81 mm, while PWV value from MODIS ranges from ± 13.02 mm -80.05 mm. Based on the results of PWV-GPS correlation test from June to October of 2010 has a correlation coefficient of 0.0173 to PWV from MODIS and explains the positive relationship between PWV of GPS with PWV value from MODIS, but correlation value of the variable variables including low category because of location points Station SUGAR are spread unevenly and are more likely to spread along the western coast of Sumatra, which borders the Indian Ocean.Keywords: Mount Sinabung, Precipitable Water Vapor, SUGAR, MODIS. PendahuluanAtmosfer adalah suatu lapisan udara yang mengelilingi bumi. 75% dari massa atmosfer yang terdapat awan, hujan dan konversi udara. Lapisan ini mempunyai pengaruh yang besar terhadap kehidupan semesta, seperti meredam panas matahari, merambatkan gelombang -gelombang suara, menimbulkan gejala senja, dan memegang peranan yang sangat penting dalam perubahan cuaca [16].Gejala fisis atmosfer yang terjadi akibat letusan gunung merapi yang mengeluarkan awan panas dalam bentuk abu vulkanik yang menyembur ke lapisan atmosfer bumi dapat menyebabkan dampak yang cukup signifikan. Partikel debu vulkanik yang dikeluarkan dalam lapisan troposfer bumi akan menghalangi proses radiasi matahari dan tidak dapat masuk kepermukaan bumi sehingga menyebabkan suhu di daerah tersebut rendah (menurun), lebih dari itu partikel debu vulkanik tersebut bersifat higroskopis, yakni dapat mengikat uap air, sehingga dapat memicu proses terjadinya kondensasi dan terbentuklah awan dengan (kelembaban) tinggi. Hal ini tente saja akan mempengaruhi pola sistem cuaca, karena radiasi matahari merupakan salah satu unsur utama dari unsur-unsur yang mempengaruhi cuaca.Pada peristiwa letusan gunung berapi ratusan ton sulfur yang menyembur ke atmosfer dengan kecepatan vertical tertentu sehingga dapat menembus ke lapisan tropofer dan lapisan stratosfer ya...

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Remote sensing of water vapor in the near IR from EOS/MODIS

Cited by 353 publications

References 29 publications

Relating seasonal dynamics of enhanced vegetation index to the recycling of water in two endorheic river basins in north-west China

Relating seasonal dynamics of enhanced vegetation index to the recycling of water in two endorheic river basins in north-west China

An Advanced Radiative Transfer and Neural Network Scheme and Evaluation for Estimating Water Vapor Content from MODIS Data

Analisa Penentuan Water Vapor Terhadap Pengaruh Erupsi Gunung Sinabung Menggunakan Data SUGAR Dan Citra Satelit Terra MODISs

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