Classification of multitemporal Sentinel-2 data for field-level monitoring of rice cropping practices in Taiwan

Cadastral information of rice fields is important for monitoring cropping practices in Taiwan due to official initiatives. Remote sensing based rice monitoring has been a challenge for years because the size of rice fields is small, and crop mapping requires information of crop phenology, relating to spatiotemporal resolution of satellite data. This study aims to develop an approach for mapping rice-growing areas at field level using multi-temporal Sentinel-2 data in Taiwan. The data were processed for 2018, following four main steps: (1) construct time-series Enhanced Vegetation Index (EVI) and Land Surface Water Index (LSWI), (2) noise filtering of the time-series data using wavelet transform, (3) rice crop classification using information of crop phenology, and (4) parcel-based accuracy assessment of the mapping results. The parcel-to-parcel comparisons between mapping results and ground reference data indicated satisfactory results. These findings were confirmed by close agreement between satellite-derived rice area and government’s statistics. Although some factors, including mixed-pixel issues and cloud-cover effects, lowered the mapping accuracies of townships along the coastline, this study has demonstrated the efficacy of using multitemporal Sentinel-2 data to create a reliable database of rice-growing areas over a large and heterogeneous region. Such a quantitative information was important for updating rice crop maps and monitoring cropping practices.     

A simplified data assimilation method for reconstructing time-series MODIS NDVI data

The Normalized Difference Vegetation Index (NDVI) is an important vegetation index, widely applied in research on global environmental and climatic change. However, noise induced by cloud contamination and atmospheric variability impedes the analysis and application of NDVI data. In this work, a simplified data assimilation method is proposed to reconstruct high-quality time-series MODIS NDVI data. We extracted 16-Day L3 Global 1 km SIN Grid NDVI data sets for western China from MODIS vegetation index (VI) products (MOD13A2) for the period 2003–2006. NDVI data in the first three years (2003–2005) were used to generate the background field of NDVI based on a simple three-point smoothing technique, which captures annual features of vegetation change. NDVI data for 2006 were used to test our method. For every time step, the quality assurance (QA) flags of the MODIS VI products were adopted to empirically determine the weight between the background field and NDVI observations. Ultimately, more reliable NDVI data can be produced. The results indicate that the newly developed method is robust and effective in reconstructing high-quality MODIS NDVI time-series.     

Study on extraction of crop information using time-series MODIS data in the Chao Phraya Basin of Thailand

In order to acquire the crop-related information in Chao Phraya Basin, time-series MODIS data were used in this paper. Although the spatial resolution of MODIS data is not very high, it is still useful for detecting very large-scale phenomenon, such as changes in seasonal vegetation patterns. After the data processing a general crop-related LULC (land use and land cover) map, cropping intensity map and cropping patterns map were produced. Analysis of these maps showed that the main land use type in the study area was farmland, most of which was dominated by rice. Rice fields mostly concentrated in the flood plains and double or triple rice-cropping system was commonly employed in this area. Maize, cassava, sugarcane and other upland crops were mainly distributed in the high alluvial terraces. Because these area often have water shortage problem particularly in the dry season which can support only one crop in a year, the cropping intensity was very low. However, some upland areas can be cultivated twice a year with crops which have short growing seasons. The crop information extracted from MODIS data sets were assessed by CBERS data, statistic data and so on. It was shown that MODIS derived crop information coincided well with the statistic data at the provincial level. At the same time, crop information extracted by MODIS data sets and CBERS were compared with each other which also showed similar spatial patterns.     

Object-based rice mapping using time-series and phenological data

Remote sensing techniques are often used in mapping rice, but high quality time-series remote sensing data are difficult to obtain due to the cloudy weather of rice growing areas and long satellite revisit interval. As such, rice mapping is usually based on mono-temporal Landsat TM/ETM+ data, which have large uncertainties due to the spectral similarity of different vegetation types. Moreover, conventional pixel-based classification method is unable to meet the required accuracy for rice mapping. Therefore, this study proposes a new strategy for mapping rice in cloud-prone areas using fused data of Landsat-8 OLI time-series and phenological parameters, based on the object-based method. We determine the critical growth stages of paddy rice from observed phenological data and MODIS-NDVI time-series data. The spatial and temporal adaptive reflectance fusion model (STARFM) is used to blend the MODIS and Landsat data to obtain a multi-temporal Landsat-like dataset for classification. Finally, an object-oriented algorithm is used to extract rice paddies from the Landsat-like, time-series dataset. The validation experiments show that the proposed method can provide high accuracy rice mapping, with an overall accuracy of 92.38% and a kappa coefficient of 0.85.     

Reconstructing pathfinder AVHRR land NDVI time-series data for the Northwest of China

Vegetation typically elicits dynamics at the seasonal and annual level. Time-series of normalized difference vegetation index (NDVI) datasets, such as the pathfinder AVHRR land (PAL) NDVI dataset, have proven to be appropriate for the detection of long-term vegetation cover changes. It has been applied in modelling experiments for terrestrial ecosystems at the global, continental, and regional scales. But some PAL NDVI time series remain significant residual effects and noise levels. A simple method, the mean-value iteration filter (MVI), has been developed to reduce the noise and to enable the reconstruction of high quality NDVI time-series. A comparison between the newly developed method and other existing methods (the modified BISE algorithm and a fast Fourier transform algorithm) indicates that the newly developed method is an effective tool for reconstructing high-quality time series of PAL NDVI time series.     

Cross testing of ionosphere models IRI-2001 and IRI-2007, data from satellite altimeters (Topex/Poseidon and Jason-1) and global ionosphere maps

In this study, we use a great body of statistical data covering the entire 23rd solar cycle to cross test data of satellite altimeters, Global Ionosphere Maps and the International Reference Ionosphere models, IRI-2001 and IRI-2007. It is revealed that experimental TEC values of the satellite altimeters regularly exceed the model ones by ∼3 TECU (1 TECU = 10¹⁶ m⁻²). The best possible value of difference between TECs obtained from altimeter and GIM-map data significantly differs for different laboratories: the maximum for CODG data falls on 2.5 TECU, ESAG – 3 TECU, JPLG – 0 TECU, UPCG – 2 TECU. The dependence of experimental and model data root-mean-square deviation on the F10.7 index is shown to be nearly linear. IRI-2001 and IRI-2007 relative errors are characterized by considerable 11-year and annual variations. Given the geomagnetic planetary index K_p under 7, IRI-2001 and IRI-2007 reproduce TEC in the ionosphere with an accuracy of ∼30% relative to measurement data from satellite altimeters. The amplitude of absolute error variations resulting from the difference in ionization enhancement between the model and the real ionosphere during the morning solar terminator transit is ∼5 TECU.     

Total electron content monitoring using triple frequency GNSS: Results with Giove-A/-B data

Triple frequency GNSS will be fully operational within the next decade, opening opportunities for new applications. Dual frequency GNSS already allow to study the ionosphere through the estimation of Total Electron Content (TEC). However, the precision is limited by the ambiguity resolution process. This paper studies a triple frequency TEC monitoring technique in which the use of Geometry-Free and Iono-Free linear combinations improves the ambiguity resolution process and therefore the precision of TEC. We have tested it on a set of triple frequency Giove-A/-B data from January and December 2008. The conclusions achieved are (1) TEC values are affected by an error of about 2–2.5 TECU produced through the ambiguity resolution process; (2) the error caused by the Geometric Free phase combination delays (hardware, multipath, noise, antenna phase center) on TEC is about 0.2 TECU; (3) the total error on TEC approximately reach 2–3 TECU.     

Surface temperature estimation in Singhbhum Shear Zone of India using Landsat-7 ETM+ thermal infrared data

Land surface temperature (LST) is an important factor in global change studies, heat balance and as control for climate change. A comparative study of LST over parts of the Singhbhum Shear Zone in India was undertaken using various emissivity and temperature retrieval algorithms applied on visible and near infrared (VNIR), and thermal infrared (TIR) bands of high resolution Landsat-7 ETM+ imagery. LST results obtained from satellite data of October 26, 2001 and November 2, 2001 through various algorithms were validated with ground measurements collected during satellite overpass. In addition, LST products of MODIS and ASTER were compared with Landsat-7 ETM+ and ground truth data to explore the possibility of using multi-sensor approach in LST monitoring. An image-based dark object subtraction (DOS3) algorithm, which is yet to be tested for LST retrieval, was applied on VNIR bands to obtain atmospheric corrected surface reflectance images. Normalized difference vegetation index (NDVI) was estimated from VNIR reflectance image. Various surface emissivity retrieval algorithms based on NDVI and vegetation proportion were applied to ascertain emissivities of the various land cover categories in the study area in the spectral range of 10.4–12.5 μm. A minimum emissivity value of about 0.95 was observed over the reflective rock body with a maximum of about 0.99 over dense forest. A strong correlation was established between Landsat ETM+ reflectance band 3 and emissivity. Single channel based algorithms were adopted for surface radiance and brightness temperature. Finally, emissivity correction was applied on ‘brightness temperature’ to obtain LST. Estimated LST values obtained from various algorithms were compared with field ground measurements for different land cover categories. LST values obtained after using Valor’s emissivity and single channel equations were best correlated with ground truth temperature. Minimum LST is observed over dense forest as about 26 °C and maximum LST is observed over rock body of about 38 °C. The estimated LST showed that rock bodies, bare soils and built-up areas exhibit higher surface temperatures, while water bodies, agricultural croplands and dense vegetations have lower surface temperatures during the daytime. The accuracy of the estimated LST was within ±2 °C. LST comparison of ASTER and MODIS with Landsat has a maximum difference of 2 °C. Strong correlation was found between LST and spectral radiance of band 6 of Landsat-7 ETM+. Result corroborates the fact that surface temperatures over land use/land cover types are greatly influenced by the amount of vegetation present.     

A morphological study of GPS-TEC data at Agra and their comparison with the IRI model

The temporal and seasonal variations of Total Electron Content (TEC) are studied at Agra (Geographic Lat. 27.17°N, Long. 78.89°E, Dip: 41.4°), India, which is in the equatorial anomaly region, for a period of 12 months from 01 January to 31 December, 2007 using a Global Positioning System (GPS) receiver. The mean TEC values show a minimum at 0500 h LT (LT = UT + 5.5 h) and a peak value at about 1400 h LT. The lowest TEC values are observed in winter whereas largest values are observed in equinox and summer. Anomalous variations are found during the period of magnetic disturbances. These results are compared with the TEC derived from IRI-2007 using three different options of topside electron density, NeQuick, IRI01-corr, and IRI-2001. A good agreement is found between the TEC obtained at Agra and those derived from IRI models.     

基于经验模分解的PPP时间比对数据消噪方法

精密单点定位(PPP)时间比对数据会受到观测噪声的影响,因此对时间比对数据进行消噪是一项重要工作。提出一种基于经验模分解(EMD)的PPP时间比对数据消噪方法,并将该方法与Vondrak滤波方法的消噪效果进行对比。结果表明,两种方法的消噪效果相当,均能有效滤除PPP时间比对数据中的随机噪声,明显改善时间比对的稳定度。     

基于经验模分解的PPP时间比对数据消噪方法

精密单点定位(PPP)时间比对数据会受到观测噪声的影响,因此对时间比对数据进行消噪是一项重要工作。提出一种基于经验模分解(EMD)的PPP时间比对数据消噪方法,并将该方法与Vondrak滤波方法的消噪效果进行对比。结果表明,两种方法的消噪效果相当,均能有效滤除PPP时间比对数据中的随机噪声,明显改善时间比对的稳定度。     

Modified gradiometer technique applied to Double Star (TC-1)

On TC-1 (Tan Ce 1), the equatorial spacecraft of the Double Star mission, a strong spin-synchronized magnetic interference from the solar panels was observed. In-flight correction techniques for spinning spacecraft that are based on minimizing spin tones in the spin-aligned component and in the magnitude of the ambient magnetic field are therefore not possible in this case. However, due to the fortunate situation that the spacecraft carries two flux-gate magnetometers on the same boom (at 0.5 m distance from each other), the spacecraft field effects could be removed from the spin-averaged data to achieve 0.2 nT relative accuracy, by using a gradiometer technique. Methodology and results are presented. The obtained accuracy allows the use of the data in multi-spacecraft studies together with the Cluster satellites.     

Noise analysis of continuous GPS coordinate time series for CMONOC

The Crustal Movement Observation Network of China (CMONOC) is one of the major scientific infrastructures, mainly using Global Positioning System (GPS) measurements, to monitor crustal deformation in the Chinese mainland. In this paper, decade-long coordinate time series of 26 continuous GPS sites of CMONOC are analyzed for their noise content using maximum likelihood estimation (MLE). We study the noise properties of continuous GPS time series of CMONOC for the unfiltered, filtered solutions and also the common mode signals in terms of power law plus white noise model. In the spatial filtering, we remove for every time series a common mode error that was estimated from a modified stacking of position residuals from other sites within ∼1000 km of the selected site. We find that the common mode signal in our network has a combination of spatially correlated flicker noise and a common white noise with large spatial extent. We demonstrate that for the unfiltered solutions of CMONOC continuous GPS sites the main colored noise is a flicker process, with a mean spectral index of ∼1. For the filtered solutions, the main colored noise is a general power law process, indicating that a major number of the filtered regional solutions have a combination of noise sources or local effects. The velocity uncertainties from CMONOC continuous GPS coordinate time series may be underestimated by factors of 8–16 if a pure white noise model is assumed. In addition, using a white plus flicker noise model, the median values of velocity errors for the unfiltered solutions are 0.16 (north), 0.17 (east) and 0.58 (vertical) mm/yr, and the median values for the filtered solutions are 0.09 (north), 0.10 (east) and 0.40 (vertical) mm/yr.     

Detection and mapping vegetation cover based on the Spectral Angle Mapper algorithm using NOAA AVHRR data

Satellite data, taken from the National Oceanic and Atmospheric Administration (NOAA) have been proposed and used for the detection and the cartography of vegetation cover in North Africa. The data used were acquired at the Analysis and Application of Radiation Laboratory (LAAR) from the Advanced Very High Resolution Radiometer (AVHRR) sensor of 1 km spatial resolution. The Spectral Angle Mapper Algorithm (SAM) is used for the classification of many studies using high resolution satellite data. In the present paper, we propose to apply the SAM algorithm to the moderate resolution of the NOAA AVHRR sensor data for classifying the vegetation cover. This study allows also exploiting other classification methods for the low resolution. First, the normalized difference vegetation index (NDVI) is extracted from two channels 1 and 2 of the AVHRR sensor. In order to obtain an initial density representation of vegetal formation distribution, a methodology, based on the combination between the threshold method and the decision tree, is used. This combination is carried out due to the lack of accurate data related to the thresholds that delimit each class. In a second time, and based on spectral behavior, a vegetation cover map is developed using SAM algorithm. Finally, with the use of low resolution satellite images (NOAA AVHRR) and with only two channels, it is possible to identify the most dominant species in North Africa such as: forests of the Liege oaks, other forests, cereal’s cultivation, steppes and bar soil.     

Properties of traveling atmospheric disturbances (TADs) inferred from CHAMP accelerometer observations

Densities derived from accelerometer measurements on the CHAMP satellite near 400 km are used to statistically establish characteristics of large-scale (>1000 km) traveling atmospheric disturbances (TADs). Only TADs that at least propagate from the auroral zone to the equator are analyzed here, and a total of 21 identifiable events are found over the years 2001–2007. The average speed of all TADs, regardless of local time, is 646 ± 122 ms⁻¹. The average speeds on the dayside and nightside are 595 ± 127 ms⁻¹ and 685 ± 106 ms⁻¹, respectively, i.e., the speed appears to be 10% higher on average on the nightside. On six occasions TADs were only detected on the night side; however, TADs on the dayside often appear more distinctly in the data. Moreover, contrary to some theoretical expectations, dayside TADs do not dissipate more readily than night side TADs, although much less are detected between 8–20 solar local time. No clear dependence of TAD amplitude or phase speed with respect to Kp, or rate of increase of Kp, is found.     

基于CCD的单缝衍射条纹光强测量与小波去噪技术研究

通过CCD的数据采集对单缝衍射条纹的光强进行测量试验,简要分析了试验中的噪声来源。提出使用小波技术对CCD的采集信号进行噪声滤除,详细讨论了小波的分解与重构以及在去除噪声中的应用。试验结果表明,小波技术能完全滤除噪声。     

基于CCD的单缝衍射条纹光强测量与小波去噪技术研究

通过CCD的数据采集对单缝衍射条纹的光强进行测量试验,简要分析了试验中的噪声来源.提出使用小波技术对CCD的采集信号进行噪声滤除,详细讨论了小波的分解与重构以及在去除噪声中的应用.试验结果表明,小波技术能完全滤除噪声.     

Impact of emissions from anthropogenic sources on satellite-derived reflectance

The present study deals with the impact of extensive anthropogenic activities associated with festivities and agricultural crop residues burning in the Indo-Gangetic Plains (IGP) on satellite-derived reflectance during November 2007. Intense smoke plumes were observed in the IRS-P4 OCM satellite data over IGP associated with agricultural crop residue burning during the study period. Terra-MODIS AOD and CALIPSO LIDAR backscatter datasets were analysed over the region to understand the spatial and temporal variation of the aerosol properties. Ground-based measurements on aerosol optical properties and black carbon (BC) mass concentration were carried out during 7–14 November 2007 over urban region of Hyderabad, India. Top of the Atmosphere (TOA) reflectance estimated from IRS-P4 Ocean Color Monitor (OCM) data showed large variations due to anthropogenic activities associated with crop residue burning and fireworks. Atmospheric corrections to OCM satellite data using 6S radiative transfer code with inputs from ground and satellite measurements could account for the variations due to differential aerosol loading. Results are discussed in this paper.     

转轴扭转变形动态测量噪声消除方法研究

转轴的扭转变形信号中包含了大量与转轴运行状态相关的信息,但往往被噪声所淹没,合理的去噪处理能够得到更有效的信号成分,有助于对转轴的工作状态做出正确的判断。相比于传统滤波方法,基于EMD的去噪方法有较强的自适应性,更适合动态信号的处理。从转轴相互正交的两个方向采集的相位差信号,依据两路信号EMD分解后各阶本征模态函数的相关性去除噪声并恢复出有效信号。仿真验证了该方法的有效性,并将其运用到实际转轴扭转变形信号的处理中,得到了更为准确的扭转变形信息。