Wide-band Imaging Spectrometer Research Articles

NaSC-TG2: Natural Scene Classification With Tiangong-2 Remotely Sensed Imagery

Scene classification is one of the most important applications of remote sensing. Researchers have proposed various datasets and innovative methods for remote sensing scene classification in recent years. However, most of the existing remote sensing scene datasets are collected uniquely from a single data source: Google Earth. In addition, scenes in different datasets are mainly human-made landscapes with high similarity. The lack of richness and diversity of data sources limits the research and applications of remote sensing classification. This article describes a large-scale dataset named “NaSC-TG2,” which is a novel benchmark dataset for remote sensing natural scene classification built from Tiangong-2 remotely sensed imagery. The goal of this dataset is to expand and enrich the annotation data for advancing remote sensing classification algorithms, especially for the natural scene classification. The dataset contains 20 000 images, which are equally divided into ten scene classes. The dataset has three primary advantages: 1) it is large scale, especially in terms of the number of each class, and the numbers of scenes are evenly distributed; 2) it has a large number of intraclass differences and high interclass similarity, because all images are carefully selected from different regions and seasons; and 3) it offers natural scenes with novel spatial scale and imaging performance compared with other datasets. All images are acquired from the new generation of wideband imaging spectrometer of Tiangong-2. In addition to RGB images, the corresponding multispectral scene images are also provided. This dataset is useful in supporting the development and evaluation of classification algorithms, as demonstrated in the present study.

Wetland Monitoring and Land Surface Temperature Response in Panjin City Based on Tiangong-2 Data

In the research area Panjin city, visible and near-infrared remote sensing images by Tiangong-2 wide-band imaging spectrometer was used to extracte wetland. According to the established remote sensing interpretation signs, the wetland types of Panjin city in 2018 are extracted by using the method of partition classification. The thermal infrared imaging spectrometer of Tiangong-2 was used to invert the land surface temperature based on the split-window algorithm. This paper comprehensively analyzed the distribution of wetland cover types of Panjin city in 2018 and their impact on land surface temperature. The results show that in 2018, Panjin wetland covers an area of 3,184.89 km2 and the major type of wetland is artificial wetland. The area is reduced successively according to paddy field, reed swamp, mudflat wetland, suaeda salsa swamp, aquaculture farm, reservoir/pond and river wetland. The overall accuracy of partition classification method is 89.97%, kappa coefficient is 0.8761. The applicability of Tiangong-2 wide-band imaging spectrometer in wetland monitoring is verified. The split-window algorithm can be used to effectively invert the land surface temperature of Tiangong-2 data, and the land surface temperature results obtained by inversion are in good consistency with those obtained by MODIS inversion, the correlation coefficient reached 0.79. Through counting, the land surface temperature of different wetland types is different, among which the land surface temperature of mudflat wetland is the highest and that of reservoir is the lowest.

基于多源遥感数据的草地净初级生产力质量评价

PDF HTML阅读 XML下载 导出引用 引用提醒 基于多源遥感数据的草地净初级生产力质量评价 DOI: 10.5846/stxb201901190153 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 新疆草原总站委托项目（201604051290）；新疆青年科技创新人才工程（QN2016YX0347） Evaluation of grassland NPP quality based on multi-source remote sensing data Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:植被净初级生产力NPP（Net Primary Production）的遥感估算与分析对全球生态系统具有重要指导意义，不同尺度的遥感影像上占主导地位的地物景观信息是不同的，现代生态研究多尺度分析至关重要。以青海省海北藏族自治州为研究区，使用Landsat 8 OLI遥感影像、天宫二号宽波段成像仪影像、融合影像（Landsat 8 OLI影像和天宫二号宽波段成像仪影像融合）联同MODIS影像，作为CASA模型的输入参数，探究不同尺度下的研究区域NPP的空间分布情况，并对比分析不同数据源数据在估算NPP时的精度。结果表明：（1）Landsat 8 OLI数据的NPP值位于150-200 g C m-2 a-1所占比例最高；天宫二号宽波段成像仪影像数据和融合后影像的NPP值位于50-100 g C m-2 a-1所占比例最高；MODIS数据的NPP值位于小于50 g C m-2 a-1比例最高。（2）天宫二号宽波段成像仪影像数据的均方根误差（RMSE）、平均绝对误差（MAE）和平均绝对百分比误差（MAPE）最小，与Landsat 8 OLI影像反演的草地NPP值相关度最高，表明天宫二号宽波段成像仪影像数据在描述草地NPP时精度高于融合影像和MODIS影像；MODIS影像在描述该区域的草地NPP时误差值较大，精度最低。 Abstract:Remote sensing estimation and analysis of Net Primary Production (NPP) have important roles for global ecosystem conservation. The dominant information of ground object landscape in remote sensing images of different scales is different. The multi-scale analysis of modern ecological research is crucial. This study area is Haibei Tibetan Autonomous Prefecture in Qinghai Province. We used Landsat 8 OLI remote sensing image, Wide-band Imaging Spectrometer (WIS) of Tiangong-2, fusion image (Landsat 8 OLI images and WIS of Tiangong-2 fusion), and MODIS image as input parameters of CASA model. We aim to explore the spatial distribution of NPP at different scales in study area, and to comparatively analyze different source data in estimating the accuracy of the NPP. The results showed that:(1) the NPP value using Landsat 8 OLI data was 150-200 g C m-2 a-1 and the proportion was the highest. The NPP value of the WIS of Tiangong-2 data and the fusion image were 50-100 g C m-2 a-1, which accounted for the highest proportion. The NPP value of MODIS data's proportion of less than 50 g C m-2 a-1 was the highest. (2) The root mean square error (RMSE), MAE, and MAPE of the WIS of Tiangong-2 data were the smallest. The correlation between the WIS of Tiangong-2 image's grassland NPP value inversed by Landsat 8 OLI image was the highest. It indicated that the accuracy of the WIS of Tiangong-2 data for describing grassland NPP was higher than that of fusion image and MODIS image. The MODIS image has a large error value and the lowest accuracy in describing the grassland NPP in this region. 参考文献 相似文献 引证文献

DATA QUALITY EVALUATION AND APPLICATION POTENTIAL ANALYSIS OF TIANGONG-2 WIDE-BAND IMAGING SPECTROMETER

Abstract. Tiangong-2 is the first space laboratory in China, which launched in September 15, 2016. Wide-band Imaging Spectrometer is a medium resolution multispectral imager on Tiangong-2. In this paper, the authors introduced the indexes and parameters of Wideband Imaging Spectrometer, and made an objective evaluation about the data quality of Wide-band Imaging Spectrometer in radiation quality, image sharpness and information content, and compared the data quality evaluation results with that of Landsat-8. Although the data quality of Wide-band Imager Spectrometer has a certain disparity with Landsat-8 OLI data in terms of signal to noise ratio, clarity and entropy. Compared with OLI, Wide-band Imager Spectrometer has more bands, narrower bandwidth and wider swath, which make it a useful remote sensing data source in classification and identification of large and medium scale ground objects. In the future, Wide-band Imaging Spectrometer data will be widely applied in land cover classification, ecological environment assessment, marine and coastal zone monitoring, crop identification and classification, and other related areas.

Wide-band imaging spectrometer with scintillator-deposited charge-coupled device

We report on a new photon-counting detector possessing unprecedented spatial resolution and moderate spectral resolution for 0.1– 100 keV X-rays. It consists of an X-ray charge-coupled device (CCD) and a scintillator. The scintillator is directly coupled to the back surface of the X-ray CCD. Low-energy X-rays below 10 keV can be directly detected by the CCD. The majority of hard X-rays above 10 keV pass through the CCD but can be absorbed by the scintillator, generating visible light photons. Since CCDs have a moderate detection efficiency, visible light photons can be detected by the CCD. We coupled the needlelike CsI(Tl) on the front surface of the back-illuminated (BI) CCD. We evaluated the spectroscopic performance for hard X-rays at the synchrotron facility, SPring-8, and found a good linear relationship between the incident X-ray energy and the pulse height up to 80 keV. The on-axis image of the hard X-ray telescope, supermirror, was measured by our device at 40 keV. A sharp core and the wing structure can be clearly imaged and high imaging capability of the SD-CCD can be demonstrated.