Satellite remote sensing of sea-ice and its operational monitoring method along the coast of China

Sea-ice is an important operational item for real timely monitoring and forecasting marine environment of China. This paper introduces an operational method of satellite remote sensing to monitor sea- ice using quantitative data of NOAA, and its contents include computer processing of AVHRR sounding data of NOAA and its program design, imagery processing of sea-ice imagery from satellite and their thematic analysis. The sea-ice satellite colour imageries processed via this software system are able to interpret sea-ice pattern, characterizing it by thickness, maximum position of ice boundary, floe concentration and dynamic process of ice changing. At the same time, analyses of the ice condition of the Bohai Sea for the two-year period (1986-1988) as monitored by satellite have been summarized.

HJ-1C Satellite for Environmental and Disaster Monitoring Launched into Orbit

A LM-2C launch vehicle was launched from the Taiyuan Satellite Launch Center on November 19, 2012, carrying HJ-1C, a technology demonstration satellite and the Fengniao satellite. The three satellites were placed to the preset orbits respectively. Developed by DFH Satellite Co., Ltd., HJ-1C is a SAR Earth observation satellite for civilian use, which

Applications of Satellite Remote Sensing Technology in China's Environmental Monitoring

The environmental conditions in China are still very serious. In the years to come, the mission for environmental treatment and protection, supervision,

RESEARCH ON AUTOMATIC FOG IDENTIFICATION TECHNOLOGY BY METEOROLOGICAL SATELLITE REMOTE SENSING

There is an urgent need for the development of a method that can undertake rapid, effective, and accurate monitoring and identification of fog by satellite remote sensing, since heavy fog can cause enormous disasters to China’s national economy and people's lives and property in the urban and coastal areas. In this paper, the correlative relationship between the reflectivity of land surface and clouds in different time phases is found, based on the analysis of the radiative and satellite-based spectral characteristics of fog. Through calculation and analyses of the relative variability of the reflectivity in the images, the threshold to identify quasi-fog areas is generated automatically. Furthermore, using the technique of quick image run-length encoding, and in combination with such practical methods as analyzing texture and shape fractures, smoothness, and template characteristics, the automatic identification of fog and fog-cloud separation using meteorological satellite remote sensing images are studied, with good results in application.

Current Status and Main Application Achievements of Ocean Satellites

Ocean satellites have realized multi-satellite networked operation.The HY-1D satellite launched in June 2020 realized networked with HY-1C satellite,and completed the construction of ocean color satellite constellation.The HY-2D satellite launched in May 2021 is networked with the on orbit HY-2B and HY-2C satellites to complete the construction of marine dynamic environment satellite constellation.The 1 mC-SAR satellite 01 launched in November 2021 is networked with GF-3,which initially forms the marine monitoring satellite constellation.This year,the networking of 1 mC-SAR satellite 02 with satellite 01 and GF-3 is realized,and the construction of marine monitoring satellite constellation is completed.At present,the ocean satellites have the operational application capabilities of remote sensing investigation,monitoring,evaluation and supervision of marine ecology,marine disaster prevention and reduction,global oceans and Polar Regions,Sea Islands,rights and interests maintenance.

The Development Status and Main Application Progress of China’s Ocean Satellites

China’s ocean satellites are divided into three series based on ocean color satellites(HY-1),ocean dynamic environment satellites(HY-2)and ocean monitoring satellites(HY-3).The three series of ocean satellites operate today in a multi-satellite network.The HY-1 D satellite launched in June 2020 and the HY-1 C satellite,already in orbit,realized a network observation capability and completed the formation of the ocean color satellite constellation.The HY-2 D satellite launched in May 2021 joined the HY-2 B and HY-2 C satellites,which have been on orbit already and completed a network observation capability,thus establishing the ocean dynamic environment satellite constellation.The GF-302 satellite(1 m C-SAR 01)launched in November 2021 has networked with GF-3,initially establishing an ocean monitoring satellite constellation,which has finally completed its construction with the launch of the GF-303 satellite(1 m C-SAR 02)in April 2022.The GF-3 three-satellite network effectively boasts a wide capability in applications of satellite data products and services in many fields,such as ocean environmental monitoring,ocean disaster prevention and mitigation,marine scientific research and polar research.

Multi-temporal monitoring of wheat growth by using images from satellite and unmanned aerial vehicle

Recently near-ground remote sensing using unmanned aerial vehicles(UAV)witnessed wide applications in obtaining field information.In this research,four Rapideye satellite images and eight RGB images acquired from UAV were used from early June to the end of July,2015 covering two experimental winter wheat fields,in order to monitor wheat canopy growth status and analyze the correlation among satellite images based normalized difference vegetation index(NDVI)with UAV’s RGB images based visible-band difference vegetation index(VDVI)and ground variables of the sampled grain protein contents.Firstly,through image interpretation of UAV’s multi-temporal RGB images with fine spatial resolution,the wheat canopy color changes could be intuitively and clearly monitored.Subsequently,by monitoring the changes of satellite images based NDVI as well as VDVI values and UAV’s RGB images based VDVI values,the conclusions were made that these three vegetation indices demonstrated the same and synchronized trend of increasing at the early stage of wheat growth season,reaching up to peak values at the same timing,and starting to decrease since then.The results of the correlation analysis between NDVI of satellite images and sampled grain protein contents show that NDVI has good predicative capability for mapping grain protein content before ripening growth stage around June7,2015,while the reliability of using satellite image based NDVI to predict grain protein contents becomes worse as ripening stage approaches.The regression analysis between UAV’s RGB image based VDVI and satellite image based VDVI as well as NDVI showed good coefficients of determination.It is concluded that it is feasible and practical to temporally complement satellite remote sensing by using UAV’s RGB images based vegetation indices to monitor wheat growth status and to map within-field spatial variations of grain protein contents for small scale farmlands.

Space view of the decadal variation for typical air pollutants in the Pearl River Delta （PRD） region in China

The Pearl River Delta （PRD） is one of the most industrialized, urbanized and populated regions in China, and thus has been long suffering from severe air pollutions. Space data provide a unique perspective for investigating the atmospheric environment at a regional scale. By utilizing multiple satellite retrievals from 2005 to 2013, this study presented, for the first time, the spatial patterns and temporal trends of typical air pollutants over PRD and its vicinity. As viewed from space, aerosol optical depth （AOD）, NO2 and SO2 all had their higher values at the central part of PRD, and showed clear descending gradients as moving to the outskirt of this region. As to the inter-annual variation, all these pollutants had decreasing trends in PRD during the study period, which generally agreed with the relevant in situ measurements. However, the satellite retrievals differed from ground measurements when addressing NO2 and SO2 in the vicinity of PRD. This work also provides the inter-comparison among PRD and three other metropolitan clusters in China： PRD had relatively high AOD, moderate NO2 and low SO2 levels, and it was the only region achieving the effective reduction of NO2 and SO2 during last decade. Unlike the previous three pollutants, HCHO observed by satellite showed very special patterns： it had a relatively homogeneous spatial distribution over both of PRD and its vicinity, and presented an opposite increasing trend from 2005 to 2010. Moreover, PRD had the highest HCHO level among all the metropolitan clusters, hinting a considerable contribution of biogenic origins of HCHO in PRD.