• Title/Summary/Keyword: soil reflectance spectra

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Spectral Reflectance Characteristics for Five Soils at Chungbuk Prefecture and Tideland Soil Using Remote Sensing Technology (원격탐사(RS) 기법을 이용한 충북지역 5개 토양과 갯벌토양의 분광반사특성)

  • Park, Jong-Hwa;Shin, Yong-Hee;Lee, Sang-Hyuk
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.6 no.1
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    • pp.34-40
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    • 2003
  • The deterioration of agricultural environment, which is characterized by dryness and desertification of land, is one of the main reasons which explain the recent decrease of land productivity. To solve these environmental problems, it is very important to make clear the mechanism between soil, water, vegetation and temperature. The main objective of this study is to provide a soil surface information, which represent a soil reflectance spectrum, by remote sensing technology. The soil reflectance of the soil was measured using a spectro-radiometer in the wavelength range from 300nm to 1100nm. The results suggest that the reflectance properties of soils are related to their mineral composition and soil moisture. Increasing soil moisture resulted in an decrease in the rate of reflectance which leads to parallel curves of soil reflectance spectra.

A soil surface information obtained by remote sensing technology (Remote Sensing 기법에 의한 토양정보추출(지역환경 \circled1))

  • 박종화;전택기
    • Proceedings of the Korean Society of Agricultural Engineers Conference
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    • 2000.10a
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    • pp.507-512
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    • 2000
  • The main objective of this study is to provide a soil surface information, which represent a soil reflectance spectrum, by remote sensing technology. The soil reflectance of the soil was measured using a spectroradiometer in the wavelength range from 300nm to 1100nm. Measurements of soil reflectance have been made in four different soils. The results suggest that the reflectance properties of soils are related to their mineral composition and soil moisture. Increasing soil moisture resulted in an decrease in the rate of reflectance which leads to parallel curves of soil reflectance spectra. The soil line representing the relationship between red and near-infrared soil reflectance is characterized by soil types.

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Spectral Reflectance of Soils Related to the Interaction of Soil Moisture and Soil Color Using Remote Sensing Technology (RS 기법을 이용한 토양수분과 토양 색에 관련된 토양의 분광반사)

  • 박종화
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.45 no.5
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    • pp.77-84
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    • 2003
  • Recent advances in remote sensing techniques provide the potential for monitoring soil color as well as soil moisture conditions at the spatial and temporal scales required for detailed local modeling efforts. Soil moisture as well as soil color is a key feature used in the identification and classification of soils. Soil spectral reflectance has a direct relationship with soil color, as well as to other parameters such as soil moisture, soil texture. and organic matter. We evaluate the influence of seven soil properties, soil color and soil moisture, on soil spectral reflectance. This paper presents the results obtained from the ground-truth spectral reflectance measurements in the 300-1100 nm wavelength range for various land surfaces. The results suggest that the reflectance properties of soils are related to soil color, soil texture, and soil moisture. Increasing soil moisture content generally decreases soil reflectance which leads to parallel curves of soil reflectance spectra across the entire shortwave spectrum. We discuss the relationships between the soil reflectance and the Munsell Soil Color Charts which contain standard color chips with colors specified by designations for hue, value, and chroma.

Preprocessing and Calibration of Optical Diffuse Reflectance Signal for Estimation of Soil Physical and Chemical Properties in the Central USA (미국 중부 토양의 이화학적 특성 추정을 위한 광 확산 반사 신호 전처리 및 캘리브레이션)

  • La, Woo-Jung;Sudduth, Kenneth A.;Chung, Sun-Ok;Kim, Hak-Jin
    • Journal of Biosystems Engineering
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    • v.33 no.6
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    • pp.430-437
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    • 2008
  • Optical diffuse reflectance sensing in visible and near-infrared wavelength ranges is one approach to rapidly quantify soil properties for site-specific management. The objectives of this study were to investigate effects of preprocessing of reflectance data and determine the accuracy of the reflectance approach for estimating physical and chemical properties of selected Missouri and Illinois, USA surface soils encompassing a wide range of soil types and textures. Diffuse reflectance spectra of air-dried, sieved samples were obtained in the laboratory. Calibrations relating spectra to soil properties determined by standard methods were developed using partial least squares (PLS) regression. The best data preprocessing, consisting of absorbance transformation and mean centering, reduced estimation errors by up to 20% compared to raw reflectance data. Good estimates ($R^2=0.83$ to 0.92) were obtained using spectral data for soil texture fractions, organic matter, and CEC. Estimates of pH, P, and K were not good ($R^2$ < 0.7), and other approaches to estimating these soil chemical properties should be investigated. Overall, the ability of diffuse reflectance spectroscopy to accurately estimate multiple soil properties across a wide range of soils makes it a good candidate technology for providing at least a portion of the data needed in site-specific management of agriculture.

Development of real-time chemical properties analysis technique in paddy soil for precision farming (정밀농업을 위한 토양의 실시간 이화학 성분 분석 기술 개발)

  • Yun, Hyun-Woong;Choi, Chang-Hyun;Kim, Yong-Joo;Hong, Soon-Jung
    • Korean Journal of Agricultural Science
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    • v.41 no.1
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    • pp.59-63
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    • 2014
  • Precision farming aims at reduced environmental impacts with increased productivity. Soils are multi-functional media in which air, water and biota occur together and form an essential part of the landscape with a fundamental role in the environment. The requirement for herbicides and fertilizers can vary within a field in response to spatial differences in soil properties. Near infrared (NIR) spectroscopy is widely used today as a nondestructive analytical technique which is capable of determining a number of physio-chemical parameters. The objectives of this study were to develop optimal models to predict chemical properties of paddy soils by visible and NIR reflectance spectra. Total of 60 soil samples were collected in spring from 20 paddy fields within central regions in Korea. Reflectance spectra, moisture contents, pH, total nitrogen (N), organic matter, available phosphate ($P_2O_5$) of soil samples were measured. The reflectance spectra were measured in wavelength ranges of 400-2,500 nm with 2 nm interval. The method of partial least square (PLS) analysis was used to determine the soil properties. The PLS analyses showed good correlation between predicted and measured chemical properties of paddy soils in the wavelength range of 1,800-2,400 nm. Especially, it showed better performance than the previous results which used the entire wavelength range of the spectrophotometer, without considering the optimal wavelength of each soil properties.

Development of Nondestructive Grouping System for Soil Organic Matter Using VIS and NIR Spectral Reflectance

  • Sung J.H.
    • Agricultural and Biosystems Engineering
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    • v.6 no.1
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    • pp.15-21
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    • 2005
  • This study was conducted to develop a nondestructive grouping system for soil organic matter using visible (VIS) and near infrared (NIR) spectroscopic method. The artificial light was irradiated on the cut soil surface at 15 to 20 cm depths to reduce the errors of light at open field. The reflectance energy from the cut soil surface was measured to group the soil organic matter using VIS/NIR light sensor with narrow band pass filter. From reflectance spectra of soil samples, the sensitive wavelengths for measuring the soil organic matter were selected and compared to previous research results. The grouping system for soil organic matter consisted of light sensor with band pass filter measuring the reflectance energy of the cut soil surface, global positing system (GPS), analog-to-digital (AD) converter, computer and operating software. The regression models to predict the soil organic matter were developed and evaluated. From field test, the accuracies of the developed light sensor system were 81.3% for five-stage grouping of the soil organic matters and 91.0% for three-stages grouping of the soil organic matters, respectively. It could be possible to support the decision making for variable rate applications with the developed grouping system for soil organic matter in precision agriculture.

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Predicting Soil Chemical Properties with Regression Rules from Visible-near Infrared Reflectance Spectroscopy

  • Hong, Suk Young;Lee, Kyungdo;Minasny, Budiman;Kim, Yihyun;Hyun, Byung Keun
    • Korean Journal of Soil Science and Fertilizer
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    • v.47 no.5
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    • pp.319-323
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    • 2014
  • This study investigates the prediction of soil chemical properties (organic matter (OM), pH, Ca, Mg, K, Na, total acidity, cation exchange capacity (CEC)) on 688 Korean soil samples using the visible-near infrared reflectance (VIS-NIR) spectroscopy. Reflectance from the visible to near-infrared spectrum (350 to 2500 nm) was acquired using the ASD Field Spec Pro. A total of 688 soil samples from 168 soil profiles were collected from 2009 to 2011. The spectra were resampled to 10 nm spacing and converted to the 1st derivative of absorbance (log (1/R)), which was used for predicting soil chemical properties. Principal components analysis (PCA), partial least squares regression (PLSR) and regression rules model (Cubist) were applied to predict soil chemical properties. The regression rules model (Cubist) showed the best results among these, with lower error on the calibration data. For quantitatively determining OM, total acidity, CEC, a VIS-NIR spectroscopy could be used as a routine method if the estimation quality is more improved.

Spectra assessment for the soil Hg contamination

  • Wu, Yunzhao;Chen, Jun;Wu, Xinmin;Tian, Qingjiu;Ji, Junfeng
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.1368-1370
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    • 2003
  • Conventional methods investigating soil Hg contamination are time-consuming and expensive. A quicker method is developed to predict soil Hg content with convolved HyMap, ASTER, and TM spectra. The prediction accuracy for each sensor is satisfactory and similar. It suggests that low spectral resolution is not a limitation for predicting soil Hg content. Correlation analysis reveals that Hg -sorption by iron oxides is the mechanism by which to predict spectrally featureless Hg with reflectance spectra. Future study with field measurements and remote sensing data is recommended.

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On-line Real Time Soil Sensor

  • Shibusawa, S.
    • Agricultural and Biosystems Engineering
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    • v.4 no.1
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    • pp.28-33
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    • 2003
  • Achievements in the real-time soil spectro-photometer are: an improved soil penetrator to ensure a uniform soil surface under high speed conditions, real-time collecting of underground soil reflectance, getting underground soil color images, use of a RTK-GPS, and all units are arranged for compactness. With the soil spectrophotometer, field experiments were conducted in a 0.5 ha paddy field. With the original reflectance, averaging and multiple scatter correction, Kubelka-Munk (KM) transformation as soil absorption, its 1st and 2nd derivatives were calculated. When the spectra was highly correlated with the soil parameters, stepwise regression analysis was conducted. Results include the best prediction models for moisture, soil organic matter (SOM), nitrate nitrogen (NO$_3$-N), pH and electric conductivity (EC), and soil maps obtained by block kriging analysis.

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Predicting Organic Matter content in Korean Soils Using Regression rules on Visible-Near Infrared Diffuse Reflectance Spectra

  • Chun, Hyen-Chung;Hong, Suk-Young;Song, Kwan-Cheol;Kim, Yi-Hyun;Hyun, Byung-Keun;Minasny, Budiman
    • Korean Journal of Soil Science and Fertilizer
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    • v.45 no.4
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    • pp.497-502
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    • 2012
  • This study investigates the prediction of soil OM on Korean soils using the Visible-Near Infrared (Vis-NIR) spectroscopy. The ASD Field Spec Pro was used to acquire the reflectance of soil samples to visible to near-infrared radiation (350 to 2500 nm). A total of 503 soil samples from 61 Korean soil series were scanned using the instrument and OM was measured using the Walkley and Black method. For data analysis, the spectra were resampled from 500-2450 nm with 4 nm spacing and converted to the $1^{st}$ derivative of absorbance (log (1/R)). Partial least squares regression (PLSR) and regression rules model (Cubist) were applied to predict soil OM. Regression rules model estimates the target value by building conditional rules, and each rule contains a linear expression predicting OM from selected absorbance values. The regression rules model was shown to give a better prediction compared to PLSR. Although the prediction for Andisols had a larger error, soil order was not found to be useful in stratifying the prediction model. The stratification used by Cubist was mainly based on absorbance at wavelengths of 850 and 2320 nm, which corresponds to the organic absorption bands. These results showed that there could be more information on soil properties useful to classify or group OM data from Korean soils. In conclusion, this study shows it is possible to develop good prediction model of OM from Korean soils and provide data to reexamine the existing prediction models for more accurate prediction.