High Resolution Earth Observation Satellites Research Articles

GF-4 high-resolution texture and FY-4A multispectral data fusion: two case studies for enhancing early convective cloud detection

Early detection of convective clouds is vital for minimizing hazardous impacts. Forecasting convective initiation (CI) using current multispectral geostationary meteorological satellites is often challenged by high false-alarm rates and missed detections caused by limited resolution. In contrast, high-resolution Earth observation satellites offer more detailed texture information, improving early detection capabilities. We propose a novel methodology that integrates the advanced features of China's latest-generation satellites, Gaofen-4 (GF-4) and Fengyun-4A (FY-4A). This fusion method retains GF's high-resolution details and FY-4A's multispectral information. Two cases from different observational scenarios and weather conditions under GF-4’s staring mode were carried out to compare the CI forecast results based on fused data and solely on FY-4A data. The fused data demonstrated superior performance in detecting smaller-scale convective clouds, enabling earlier forecasting with a lead time of 15–30 minutes, and more accurate location identification. Integrating high-resolution earth observation satellites into early convective cloud detection provides valuable insights for forecasters and decision-makers, particularly given the current resolution limitations of geostationary meteorological satellites.

RESEARCH ON COOPERATION STRATEGY BASED ON SATELLITE REMOTE SENSING DATA SERVICE AND TECHNOLOGY APPLICATION BETWEEN CHINA AND ASEAN

Abstract. Remote sensing (RS) and earth observing technology are flourished with the development of a series of high-resolution earthobservation satellites. As the improvement of China’s earth observation data acquisition capability, one critical issue is put on the agenda that is what kind of models and techniques can promote the future data processing into a new level in terms of service model, massive data processing, development methods, business models, resource sharing, and system sustainability (1). In order to embed domestic satellite advantages into global world and provide increasingly more Chinese wisdom and solution to support the ASEAN regional development, China highlights the propositions on ASEAN-China remote sensing cooperation. On November 1, 2022, the ASEAN-China Satellite Remote Sensing Application Centre (hereinafter referred to as the ACSAC) was officially inaugurated in Beijing. The ACSAC will mainly focus on the establishment of a system and mechanism for a series of substantive operation, promoting the comprehensive sharing of China's land and ocean satellite data, comprehensively rich the international application scenarios of Chinese satellites, promoting applications in multiple fields and carrying out satellite remote sensing application promotion and typical demonstration, continuing to carry out technical exchanges and training with mutual demands and development. At present, ACSAC has stepped into the substantive construction stage. It will give full play to the advantages of China's natural resources land and ocean satellite remote sensing resources, to form a multi-scale, full coverage data resource support, jointly carry out the construction of the ASEAN-China satellite remote sensing data network platform based on the cloud environment, and to jointly build an integrated service open portal for land and ocean satellite data products to ASEAN region. Focusing on the core construction content of ACSAC, this paper systematically collects, summarizes and analyse the data and application needs of satellite remote sensing in ASEAN countries, finds out the current needs to meet the gap, and puts forward some thoughts and ideas on cooperation mechanism, data sharing, customized products and application demonstration of advanced products, aiming to lay a solid foundation for the substantial construction of ACSAC.

On-orbit geometric calibration and preliminary accuracy verification of GaoFen-14 (GF-14) optical two linear-array stereo camera

ABSTRACT The GaoFen-14 (GF-14) satellite is China’s most recent high-resolution earth observation satellite system. It is equipped with a two linear-array stereo camera and is intend for topographic mapping at 1:10,000-scale without ground control points (GCPs). The technical parameters of payloads will change once the satellite enters orbit. As a result, strict on-orbit geometric calibration is necessary. This study performs the on-orbit geometric calibration of the GF-14 stereo camera using ground calibration data. The exterior orientation errors are corrected by a comprehensive bias matrix, internal orientation errors are described by a fifth order polynomial. The results of Yinchuan calibration field show that the planar accuracy is better than 286 m (RMS) before calibration, and improved to 2.11 m (front camera) and 1.51 m (back camera) by external orientation, and further improved to 1.46 m (front camera) and 0.99 m (back camera) after internal calibration. The front intersection accuracy reaches 0.67 m in plane (RMS) and 1.10 m in elevation (RMS), respectively. Checking by multiple global check points (CKPs), the planar and elevation RMS reaches 2.38 m (5.09 m in CE90) and 2.08 m (3.43 m in LE90), respectively.

지향성을 가지고 동작하는 위성 안테나 진동저감 장치

Although the magnitude of the disturbance caused by the driving of the motor operated to secure the high-speed and precise directivity of the antenna is small, it acts as a major cause of impairing the image quality of the observation satellite, which requires precision directing performance. In order to acquire high-resolution image information through the improvement of the high-resolution observation satellite, proper vibration isolation and reduction design are required so that jitter generated when the directional antenna motor is driven is not transmitted to the main mission equipment. In this paper, the development process of the directional antenna vibration reduction device applied to real satellites and the effect of micro vibration reduction before and after application will be examined. This device was designed as a way to significantly improve the jitter problem by replacing only one gear in the directional antenna driving unit with a spring damper gear without any additional interface equipment. It was first applied and launched to a high-resolution earth observation satellite, and has been successfully operated so far.

Surveillance of pine wilt disease by high resolution satellite

Pine wilt disease caused by the pinewood nematode Bursaphelenchus xylophilus has led to the death of a large number of pine trees in China. This destructive disease has the characteristics of bring wide-spread, fast onset, and long incubation time. Most importantly, in China, the fatality rate in pines is as high as 100%. The key to reducing this mortality is how to quickly find the infected trees. We proposed a method of automatically identifying infected trees by a convolution neural network and bounding box tool. This method rapidly locates the infected area by classifying and recognizing remote sensing images obtained by high resolution earth observation Satellite. The recognition accuracy of the test data set was 99.4%, and the remote sensing image combined with convolution neural network algorithm can identify and determine the distribution of the infected trees. It can provide strong technical support for the prevention and control of pine wilt disease.

Improved Method to Detect the Tailings Ponds from Multispectral Remote Sensing Images Based on Faster R-CNN and Transfer Learning

The breaching of tailings pond dams may lead to casualties and environmental pollution; therefore, timely and accurate monitoring is an essential aspect of managing such structures and preventing accidents. Remote sensing technology is suitable for the regular extraction and monitoring of tailings pond information. However, traditional remote sensing is inefficient and unsuitable for the frequent extraction of large volumes of highly precise information. Object detection, based on deep learning, provides a solution to this problem. Most remote sensing imagery applications for tailings pond object detection using deep learning are based on computer vision, utilizing the true-color triple-band data of high spatial resolution imagery for information extraction. The advantage of remote sensing image data is their greater number of spectral bands (more than three), providing more abundant spectral information. There is a lack of research on fully harnessing multispectral band information to improve the detection precision of tailings ponds. Accordingly, using a sample dataset of tailings pond satellite images from the Gaofen-1 high-resolution Earth observation satellite, we improved the Faster R-CNN deep learning object detection model by increasing the inputs from three true-color bands to four multispectral bands. Moreover, we used the attention mechanism to recalibrate the input contributions. Subsequently, we used a step-by-step transfer learning method to improve and gradually train our model. The improved model could fully utilize the near-infrared (NIR) band information of the images to improve the precision of tailings pond detection. Compared with that of the three true-color band input models, the tailings pond detection average precision (AP) and recall notably improved in our model, with the AP increasing from 82.3% to 85.9% and recall increasing from 65.4% to 71.9%. This research could serve as a reference for using multispectral band information from remote sensing images in the construction and application of deep learning models.

Remote Sensing of Mine Site Rehabilitation for Ecological Outcomes: A Global Systematic Review

The mining industry has been operating across the globe for millennia, but it is only in the last 50 years that remote sensing technology has enabled the visualization, mapping and assessment of mining impacts and landscape recovery. Our review of published literature (1970–2019) found that the number of ecologically focused remote sensing studies conducted on mine site rehabilitation increased gradually, with the greatest proportion of studies published in the 2010–2019 period. Early studies were driven exclusively by Landsat sensors at the regional and landscape scales while in the last decade, multiple earth observation and drone-based sensors across a diverse range of study locations contributed to our increased understanding of vegetation development post-mining. The Normalized Differenced Vegetation Index (NDVI) was the most common index, and was used in 45% of papers; while research that employed image classification techniques typically used supervised (48%) and manual interpretation methods (37%). Of the 37 publications that conducted error assessments, the average overall mapping accuracy was 84%. In the last decade, new classification methods such as Geographic Object-Based Image Analysis (GEOBIA) have emerged (10% of studies within the last ten years), along with new platforms and sensors such as drones (15% of studies within the last ten years) and high spatial and/or temporal resolution earth observation satellites. We used the monitoring standards recommended by the International Society for Ecological Restoration (SER) to determine the ecological attributes measured by each study. Most studies (63%) focused on land cover mapping (spatial mosaic); while comparatively fewer studies addressed complex topics such as ecosystem function and resilience, species composition, and absence of threats, which are commonly the focus of field-based rehabilitation monitoring. We propose a new research agenda based on identified knowledge gaps and the ecological monitoring tool recommended by SER, to ensure that future remote sensing approaches are conducted with a greater focus on ecological perspectives, i.e., in terms of final targets and end land-use goals. In particular, given the key rehabilitation requirement of self-sustainability, the demonstration of ecosystem resilience to disturbance and climate change should be a key area for future research.

Design of Very High Resolution Satellite Telescopes Part II: Comprehensive Performance Assessment

In Part I [1] , a Korsch-based optical telescope design of a very high resolution earth observation satellite with a ground sampling distance of 25 cm is presented. In this part II, a system performance evaluation of the Korsch optical design employing a time-delay and integration charge-coupled device is investigated. Several key performance metrics are assessed, including the system modulation transfer function (MTF), absolute signal-to-noise ratio (SNR), differential SNR, noise equivalent change of reflectance, and cutoff resolution. The level of the national imagery interpretability rating scales (NIIRS) for measuring the image quality is also predicted. The system MTF has been computed, involving optics, detector, platform, orbit, atmosphere, and target illumination conditions. The SNR has been analyzed at different target albedos, solar, and satellite zenith angles. A new strategy for expressing the system evaluation based on the low- and high-illumination conditions is adopted; providing the operational ranges of such metrics. The assessment shows that for the high- and low-illumination conditions, the predictable performance of the proposed telescope gives promising results and provides an acceptable image quality.

ON THE USE OF SENTINEL-2 IMAGES AND HIGH RESOLUTION DTM FOR LANDSLIDE SUSCEPTIBILITY MAPPING IN A DEVELOPING URBAN SETTLEMENT (MAMAK, ANKARA, TURKEY)

Abstract. Urban planning starts with the selection of suitable sites. The main factors and components for site selection are the geological-geotechnical parameters that directly affect the natural hazards, such as landslide and flood, construction costs and the location and distribution of existing infrastructure. The presence and accuracy of up-to-date maps in planning are very important. With the increase of high resolution Earth observation satellites, the required data can be obtained with high temporal frequency and spatial availability. From these data, the base parameters for planning can be extracted with semi- or fully-automatic methods. Among the Earth observation satellites, the Sentinel-2 mission of European Space Agency (ESA) provides high resolution optical images and the data are freely available also at different processing levels such as orthorectified images. In this study, the possibility of the landslide susceptibility map production which should be one of the base maps in urban planning by using Sentinel-2 satellite images was investigated in Mamak District of Ankara City, Turkey. The land cover and land use data were produced from Sentinel-2 images by using a supervised classification method in SNAP Tool provided by ESA. The lithological definitions were received from the General Directorate of Mineral Research and Explorations. The topographical parameters such as slope, aspect, topographic wetness index, etc. were extracted from a high resolution digital terrain model (DTM) of the area. Manually extracted landslide inventory data were employed in the logistic regression method and the produced landslide susceptibility map of the study area is presented here.

Design of Very High-Resolution Satellite Telescopes Part I: Optical System Design

The telescope design of a very high-resolution earth observation satellite is a challenging task, due to several constraints, including the size, mass, performance, tolerance, assembly, integrating, and environmental aspects. However, the demand for very high-resolution satellite imageries has increased day by day due to the numerous commercial and military applications. In this paper, two different optical configurations with ground sampling distance of 25 cm are investigated according to a definite mission statement. The first configuration represents an on-axis Korsch scheme, whereas the second design is based on the arrangement of the off-axis three-mirror anastigmatic configuration. Both designs have the advantage of small conic mirror constants without higher order parameters. Tolerance analysis of both designs utilizing a Monte Carlo algorithm is performed. The suggested baffling arrangements are simulated and tested according to a series of point sources with different off-axis angles. Finally, a comparison between the performance of the proposed designs and a recent study given by the French space agency is presented. The results show that the proposed designs can be implemented by the existing technologies and launched into space by the available launch vehicles.

Large-Scale Planar Block Adjustment of GaoFen1 WFV Images Covering Most of Mainland China

GaoFen1 is the first high-resolution earth observation satellite built in China, and carries four wide field-of-view (WFV) cameras to achieve large-scale monitoring and mapping. However, the unstable attitude measurement accuracy of the satellite generally imparts low geopositioning accuracy and inconsistent geometric error in overlapping areas of WFV images. A feasible and effective large-scale planar block adjustment (PBA) method is presented that corrects the geometric errors of the vast WFV images integrally, further improving the geometric accuracy of these images. In addition, whether ground control points (GCPs) are needed, and the effect of different numbers of GCPs on PBA accuracy is also investigated. Two key technologies are used in this paper. First, a universal PBA error equation based on the virtual control points is presented to allow PBA with or without GCPs. Second, an adjustment method aided by a digital elevation model is adopted to overcome the weak convergence geometry among WFV images, further ensuring stable estimation of PBA. The effectiveness of the proposed method was verified by 664 WFV images covering most of mainland China. The satisfactory experimental results indicate that the method presented herein is reasonable and effective, but that a certain number of GCPs is needed to ensure the accuracy of large-scale PBA results for WFV images.

Optical Design, Tolerance Analysis, and Baffling of Very High-Resolution Satellite Telescopes

The telescope design of a very high-resolution earth observation satellite is a challenging task due to several constraints, including the size, mass, performance, tolerance and environmental aspects. However, the demand for very high-resolution satellite imagery has increased day by day due to the numerous commercial and military applications. In this paper, an optical configuration for a ground sampling distance (GSD) of 25 cm is investigated according to a definite mission statement. The configuration represents on-axis Korsch scheme with the advantage of small conic mirror constants without higher-order parameters. In addition, a tolerance analysis utilizing a Monte Carlo algorithm is performed. The suggested baffling arrangement based on a series of point sources with different off-axis angles isderived. The size of the telescope is applicable to be launched into space by the current launch vehicles.

An Attitude Jitter Correction Method for Multispectral Parallax Imagery Based on Compressive Sensing

Attitude jitter is a common problem for high-resolution earth-observation satellites and can diminish the geo-positioning and mapping performance of observed images. It is especially necessary to address this problem when high-performance attitude measurements are unavailable. Therefore, an attitude jitter correction method for multispectral parallax imagery that utilizes the compressive-sensing technology is proposed in this letter. In the proposed method, the attitude jitter is estimated from the parallax disparities of different band images, and then the image displacement caused by attitude jitter can be corrected. Using the normalized cross correlation method and compressive-sensing technology, the proposed method can deal with the condition of texture-feature deficiency in the partial image. The multispectral images of the Terra and ZY-3 satellites are used as experimental data to evaluate the proposed method. The registration errors of different bands are greatly reduced in both the cross- and along-track directions, and the experiment results indicate that the proposed method is effective for correcting the attitude jitter of both satellites.

Earth observation brain (EOB): an intelligent earth observation system

Since the twenty-first century, with the rapid development of high-resolution earth observation satellites, the earth observation satellite system has developed from the initial single satellite observation model to the current satellite constellation formed by light and small satellites observation model. All-weather and all-directional fine earth observation can now be realized. In the future, the satellite constellation, communication satellites, navigation satellites, and aircrafts are linked through dynamic linking network to form an air-space information network to realize real-time services of intelligent air-space information. To further enhance the perception, cognition, and quick response ability of the network, we propose the concept and model of the Earth Observation Brain (EOB) − the intelligent earth system based on events perception in this paper. Then, some key technologies needed to be solved in the EOB are also described. An application example is illustrated to show the process of perception and cognition in the primary stage of the EOB. In the future, EOB can observe what change of what object, the when and where to push these right information to mobile terminal of right people at the right time and right place. Global users can obtain any data, information, and knowledge in real-time through the EOB.

Polar Ice Sheet and Glacier Studies-Indian Efforts in last Five Years

Indian scientists have been involved in studies of cryosphere in Polar Regions from past 35 years. For continuous monitoring and expanding research in the fields of atmospheric science, geosciences, glaciology, environmental sciences, etc. specific to these regions, the ESSO - National Centre for Antarctic and Ocean Research (ESSO-NCAOR) has established three permanent research stations in Antarctica. This paper addresses efforts by Indian scientists in last five years in cryospheric studies on the Antarctica using remote sensing data. Inventories of Antarctic glaciers and ice sheet features prepared by Indian researchers have facilitated for detailed long-term studies on glacier dynamics, sea ice, fluctuations of the continental ice margin and snouts of glaciers. For safe and optimal navigation of ships, a sea ice advisory has been also set up. This paper also addresses recent efforts of using high-resolution earth observation satellite data which were acquired for geospatial mapping of cryospheric features and glacial landforms and for delineation of wind induced snow deposition zones in part of the Antarctica. Spatiotemporal dynamics of surface melting over Antarctic was further studied by using moderate resolution satellite data.

High-Spatial-Resolution Aerosol Optical Properties Retrieval Algorithm Using Chinese High-Resolution Earth Observation Satellite I

The high-spatial-resolution aerosol retrieval algorithm using Chinese High-Resolution Earth Observation Satellite I (GF-1) wide-field images is developed, which retrieves the aerosol optical depth (AOD) over China for studying the impact of aerosol on climatic and environmental change. The algorithm is based on the red/blue surface reflectance correlations and the lookup table method. To reduce the enormous relative error caused by the constant surface reflectance relationship in the retrieval algorithm, the correlation is parameterized as a function of low, medium, and high values of normalized difference vegetation index (NDVI). Three linear relationships are simulated using MODIS BRDF-adjusted reflectance products (MCD43A4), and MODIS NDVI products are used to ascertain the value of NDVI. By applying the present algorithm to GF-1 images, two different aerosol cases of clear and turbid are analyzed to test the algorithm. Compared with the 10-km MODIS aerosol properties productions, the GF-1 retrieved AOD by our algorithm revealed a significant correlation coefficient with MODIS Dark Target AOD (R = 0.912) and Deep Blue AOD (R = 0.895). Otherwise, the retrieved AOD results are found to be highly correlated with Aerosol Robotic Network (AERONET) sunphotometer observations (R = 0.931). Compared with the results relying on the MODIS surface reflectance model, preliminary validation is encouraging that the method based on our updated surface reflectance assumptions successfully improved the accuracy, particularly under the clear sky background and over bright surface.

Evaluation of the performance of KOMPSAT-3 stereo images in terms of positioning and the generation of digital surface models

ABSTRACTKOMPSAT-3 is an optical high-resolution earth observation satellite launched on 19 May 2012. It provides panchromatic optical images at a nominal ground sampling distance (GSD) of 70 cm. This letter provides geometric accuracy evaluation of KOMPSAT-3 stereo images, including position determination and automated digital surface model (DSM) generation. Bias-compensated KOMPSAT-3 stereo achieved positioning accuracy of 0.65 m and 0.70 m in horizontal and vertical directions, respectively. Bias-compensated KOMPSAT-3 images were utilized for automated DSM generation. A DSM showed height errors of about 3.8 m (RMS) when all grids were compared with reference LIDAR data. Geometric performance of KOMPSAT-3 images was also compared with that of WorldView-1 images whose nominal GSD is 46 cm, over the same test area. The positioning accuracy and the accuracy of DSM generation from KOMPSAT-3 were slightly inferior to those of WorldView-1. However, overall performance of the two satellite images was comparable, when the difference of GSD is taken into account.

Design and analysis of optimum baffle for a Cassegrain telescope

Optimum baffle parameters to shield the direct rays of stray light are arrived at for a Cassegrain telescope using the iterative method. Further, we have proposed here a design procedure that improves the performance of an optimum baffle arrived at in view of finite reflective nature of the practical blackened-baffle structure. The modeling and performance evaluation of the designed baffle are demonstrated on a realistic numerical Cassegrain telescope using ZEMAX® optical design software. The effectiveness of this method is more perceivable on a wide field of view, large aperture, long focal length Ritchey–Chretien telescope of high resolution earth observation satellites.

Multispectral and Panchromatic Image Fusion using Empirical Wavelet Transform

Pan sharpening is the process of fusion of panchromatic and multispectral image to obtain an output image of high spatial and spectral resolution. It is very important for various remote sensing applications such as image segmentation studies, image classification, temporal change detection etc. The present work demonstrates the application of Empirical Wavelet Transform for the fusion of panchromatic image and multispectral image by simple average fusion rule. The Proposed method is experimented on panchromatic and multispectral images captured by high resolution earth observation satellites such as GeoEye-1, QuickBird, WorldView-2 and World View-3. The effectiveness of our proposed method is evaluated by visual perception and quantitative assessment measures. The experimental analysis shows that the proposed method performs comparable to the existing fusion algorithms such as Multi-resolution Singular Value Decomposition and Discrete Wavelet Transform.

On-Orbit Camera Misalignment Estimation Framework and Its Application to Earth Observation Satellite

Despite the efforts for precise alignment of imaging sensors and attitude sensors before launch, the accuracy of pre-launch alignment is limited. The misalignment between attitude frame and camera frame is especially important as it is related to the localization error of the spacecraft, which is one of the essential factors of satellite image quality. In this paper, a framework for camera misalignment estimation is presented with its application to a high-resolution earth-observation satellite—Deimos-2. The framework intends to provide a solution for estimation and correction of the camera misalignment of a spacecraft, covering image acquisition planning to mathematical solution of camera misalignment. Considerations for effective image acquisition planning to obtain reliable results are discussed, followed by a detailed description on a practical method for extracting many GCPs automatically using reference ortho-photos. Patterns of localization errors that commonly occur due to the camera misalignment are also investigated. A mathematical model for camera misalignment estimation is described comprehensively. The results of simulation experiments showing the validity and accuracy of the misalignment estimation model are provided. The proposed framework was applied to Deimos-2. The real-world data and results from Deimos-2 are presented.