SDGSAT-1: Capabilities for Monitoring and Evaluating SDG Indicators

SDGSAT-1,the world's first science satellite dedicated to assisting the United Nations 2030 Sustainable Development Agenda,has been operational for over two and a half years.It provides valuable data to aid in implementing the Sustainable Development Goals internationally.Through its Open Science Program,the satellite has maintained consistent operations and delivered free data to scientific and technological users from 88 countries.This program has produced a wealth of scientific output,with 72 papers,including 28 on data processing methods and 44 on applications for monitoring progress toward SDGs related to sustainable cities,clean energy,life underwater,climate action,and clean water and sanitation.SDGSAT-1 is equipped with three key instruments:a multispectral imager,a thermal infrared spectrometer,and a glimmer imager,which have enabled ground-breaking research in a variety of domains such as water quality analysis,identification of industrial heat sources,assessment of environmental disaster impacts,and detection of forest fires.The precise measurements and ongoing monitoring made possible by this invaluable data significantly advance our understanding of various environmental phenomena.They are essential for making well-informed decisions on a local and global scale.Beyond its application to academic research,SDGSAT-1 promotes global cooperation and strengthens developing countries'capacity to accomplish their sustainable development goals.As the satellite continues to gather and distribute data,it plays a pivotal role in developing strategies for environmental protection,disaster management and relief,and resource allocation.These initiatives highlight the satellite's vital role in fostering international collaboration and technical innovation to advance scientific knowledge and promote a sustainable future.

结合显著性检测和超像素分割的遥感信息提取算法研究

针对目前显著性检测算法在复杂多目标遥感图像中检测能力不足的问题,提出一种结合显著性检测和超像素分割的遥感信息提取算法。该算法通过GBVS(graph-based visual saliency)方法检测出原始影像中部分显著性较高的区域,然后利用SLIC(simple linear iterative clustering)方法分割显著区域,并修正显著区域边缘得到训练样本数据,进一步对训练样本进行统计学习,构造显著目标提取的阈值区间,最后实现对整幅超像素图像的显著目标提取。实验结果表明,该算法具有较高的准确率和召回率,能更加有效地检测出遥感图像中的显著目标,比目前主流的显著区域检测算法提取效果更好,可以很好地应用于具有明显显著区域的复杂多目标遥感图像信息提取中。

Research on the different content of weathered sand influence on expansive characteristic of a highway expansive soil in Yichang

This paper aims at widespread presence of expansive soil which can be obtained in the project from Xiaoxita to Yaqueling first-class highway rebuilding engineering in Yichang City of Hubei Province and weathered sand which can be made full use locally,many experiments have been made. Compaction experiments and expansibility index indoor experiments of undisturbed expansive soil and expansive soil mixed with sand ranging from 10 % to 50 % have been made. Through the test mixing undisturbed expansive soil with different content of weathered sand,it can change the expansive soil water characteristics and compaction characteristics. It can influence the expansibility of the expansive soil index and significantly inhibit the expansibility of the expansive soil and reach the standard of roadbed filler.

Experimental research on the mixed sand ratio and initial dry density of weathered sand improved expansive soil free load swelling rate

In this paper, through the indoor free load swelling rate test, expansive soil in a section of a first- class highway reconstruction project in Yichang City was studied. It emphatically analyzed the interrelations among free load swelling rate, non-load time, the proportion of mixed sand and initial dry density. Experimen- tal studies have shown that： Free load swelling deformation is mainly divided into three stages of rapid expan- sion, slow expansion and final stability; when the initial dry density is constant, free load swelling rate of the weathered sand modified soil will reduce rapidly before they slow down with the increase of sand proportion, and weathered sand modified soil free load swelling rate is not sensitive to the large amount of sand mixed; in the same mixed sand ratio, weathered sand modified soil free load swelling rate increases rapidly with the in- crease of initial dry density, there is a good linear correlation between them. To take appropriate control of the initial dry density during the expansive soil subgrade construction helps to reduce its swelling deformation and ensures the stability of the embankment.

基于卷积神经网络的高分遥感影像单木树种分类

树种调查一直面临着成本高、效率低、精度不高等问题。利用遥感手段能大大提高树种类型调查的工作效率、节省成本;卷积神经网络(CNN)虽然已经在自然图像分类领域取得了许多突破,但是较少有人将CNN模型用于单木树种分类。基于上述考虑,搭建出CNN模型,并与高分遥感影像相结合,进行单木树种分类。在利用高分影像半自动化构建单木树种遥感影像样本集过程中,采用了影像冠层切片(CSI)圈定、人工标注、数据增强等方法;同时为了训练单木树种遥感影像样本集,对5个CNN模型进行针对性改写。通过对比分析发现:LeNet5_relu和AlexNet_mini都未取得最佳分类效果;GoogLeNet_mini56、ResNet_mini56和DenseNet_BC_mini56分别对不同的树种具有最佳分类效果;DenseNet_BC_mini56总体精度最高(94.14%),Kappa系数最高(0.90),是总体最佳分类模型。该研究证明了CNN在单木树种分类中的有效性,能为森林资源调查提供重要的解决方案。

Misclassification error propagation in land cover change categorization

It is important to describe misclassification errors in land cover maps and to quantify their propagation through geo-processing to resultant information products,such as land cover change maps.Geostatistical simulation is widely used in error modeling,as it can generate equal-probable realizations of the fields being considered,which can be summarized to facilitate error propagation analysis.To fix noninvariance in indicator simulation,discriminant space-based methods were proposed to enhance consistency in area-class mapping and replicability in uncertainty modeling,as the former is achieved by imposing means while the latter is ensured by projecting spatio-temporal correlated residuals in discriminant space to geographic space through a mapping process.This paper explores discriminant models for error propagation in land cover change detection,followed by experiments based on bi-temporal remote sensing images.It was found that misclassification error propagation is effectively characterized with discriminant covariate-based stochastic simulation,where spatio-temporal interdependence is taken into account.