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During the sweltering heat of midsummer, Xi'an has experienced continuous high temperatures for days, with countless individuals steadfastly remaining at their posts under the blazing sun. To convey care and boost confidence in development, members of the Airport New City Party Committee and Management Committee, representing the New City Trade Union, conducted [activities/activities]."Summer Coolness"The outreach activity brought refreshing coolness and sincere greetings to frontline workers in various industries within the jurisdiction.

In modern agriculture, remote sensing technology is gradually changing the way we perceive and manage land. Hyperspectral remote sensing, in particular, is like giving satellites a "chemical sense of smell," enabling them to identify subtle differences in plants. Compared to traditional cameras that can only record red, green, and blue, hyperspectral cameras can record hundreds of continuous spectral bands, accurately "seeing" the differences between different crops, soils, and even pests and diseases.

On July 25th, CAS Xiguang Aerospace successfully won the title of "China's Hidden Champion" enterprise in the 2024-2025 China POWER50 Enterprise List, recognizing its leading technological strength and outstanding market potential in the field of commercial hyperspectral remote sensing satellites.。Simultaneously, commercial aerospace companies LandSpace, Galactic Energy, and Yuanxin Satellite were also selected for the Rongzhong 2024-2025 China POWER50 Enterprises List.

The 11th China International Smart Agriculture and Informatization Summit Forum was held in Shanghai on July 24. As a leading commercial aerospace enterprise and satellite remote sensing data service provider in China, CAS Xiguang Aerospace was invited to attend this grand event. It showcased its "Xiguang-1 05 Satellite (Tianxianpei)" and satellite remote sensing technology and smart agriculture application solutions. Together with government leaders, industry experts, research institutions and representatives of agricultural enterprises, they discussed the cutting-edge trends and practical paths of aerospace technology empowering the development of modern agriculture.

Cross-calibration uses a sensor with higher calibration accuracy as a reference to calibrate the sensor to be calibrated. The principle is to select synchronous or near-synchronous image pairs imaging the same target, and based on the analysis of the matching of the two sensors' spectral responses, observation geometry, and atmospheric parameters, establish the relationship between the digital count values ​​of the two sensor images. The calibration coefficients of the sensor to be calibrated are then solved using the known radiometric calibration coefficients of the reference sensor. Typically, the DN value of a satellite remote sensor has a linear relationship with its entrance pupil radiance (apparent radiance, Top-of-Atmosphere Radiance, TOA): L = gain·DN + offset, where gain and offset are the gain and intercept of the calibration coefficients, respectively, L represents the sensor's entrance pupil radiance, and DN represents the digital count value of the image.

Recently, in accordance with《Charter of the Commercial Aerospace Professional Committee of the National Earth Observation Science Data Center》Xi'an Xi'an Institute of Optics and Precision Mechanics CAS Aerospace Science and Technology Group Co.,LTD Technology Co., Ltd. (hereinafter referred to as "Xi'an Institute of Optics and Precision Mechanics CAS Aerospace Science and Technology Group Co.,LTD") has officially joined the Commercial Aerospace Professional Committee of the National Earth Observation Science Data Center, becoming its 15th member unit.

In the field of remote sensing, spectral imaging techniques are often classified into three categories based on spectral resolution: multispectral, hyperspectral, and ultraspectral. Generally, with the same spatial resolution, the higher the spectral resolution, the more image bands there are, the larger the data volume, and the richer the information obtained about the object being measured.

On July 8, 2025, the 2025 Aerospace Information Conference and CAS StarMap Ecosystem Development Conference, themed "Integration of Space and Air, Symbiosis of Nebula," grandly opened in Hefei. As a key player in the commercial aerospace sector, Xi'an CAS Xiguang Aerospace Technology Co., Ltd. (hereinafter referred to as "CAS Xiguang Aerospace") was invited to participate and signed a strategic agreement on commercial aerospace with 16 leading companies in the industry, marking a new stage of collaborative innovation in the construction of my country's commercial aerospace industry ecosystem.

Rice is one of Indonesia's most important food crops, with approximately 90% of the population relying on it as a staple food. Its production directly impacts national food security and social stability. As the world's third-largest rice producer, Indonesia cultivates over 14 million hectares of rice, primarily in Java, Sumatra, and Bali. However, due to climate change, arable land loss, and diversified planting patterns, accurately monitoring rice acreage and growth status presents significant challenges. Accurate and efficient extraction of rice acreage information is crucial for agricultural monitoring, farmland management, food yield assessment, and policy formulation.

In the field of agricultural remote sensing, hyperspectral technology reveals the health status of vegetation by capturing fine spectral information of crop reflectance. The red edge (680-750 nm) is a rapid transition region in the vegetation spectrum from low red light reflectance to high near-infrared reflectance, and is extremely sensitive to chlorophyll content, stress conditions, and growth stages. This article will introduce six red edge indices (REP, NDVIre, RedEdgeSlope, RedEdgeArea, mSRre, and RedEdgeCurvature) based on hyperspectral data spectral curves, including their calculation methods, application scenarios, and comparisons with traditional vegetation indices (such as NDVI and SAVI), revealing the unique advantages of hyperspectral indices.