Forest status assessment in China with SDG indicators based on high-resolution satellite data

To assess the status and change trend of forest in China,an indicator framework was developed using SDG sub-indicators.In this paper,we propose an improved methodology and a set of workflows for calculating SDG indicators.The main modification include the use of moderate and high spatial resolution satellite data,as well as state-of-the-art machine learning techniques for forest cover classification and estimation of forest above-ground biomass(AGB).This research employs GF-1 and GF-2 data with enhanced texture information to map forest cover,while time series Landsat data is used to estimate forest AGB across the whole territory of China.The study calculate two SDG sub-indicators:SDG_(15.1.1) for forest area and SDG_(15.2.1) for sustainable forest management.The evaluation results showed that the total forest area in China was approximately 219 million hectares at the end of 2021,accounting for about 23.51%of the land area.The average annual forest AGB from 2015 to 2021 was estimated to be 105.01Mg/ha,and the overall trend of forest AGB change in China was positive,albeit with some spatial differences.

Generation of ready to use (RTU) products over China based on Landsat series data

Earth observation community has entered into the era of big data.Family of Landsat sensors have collected massive medium resolution satellite images,which are valuable for long-term land surface monitoring.In order to significantly reduce the magnitude of data processing for remote sensing data users,Landsat-based Ready to Use(RTU)products have been produced.Main RTU products,including orthorectified products,land surface reflectance,land surface temperature,large-area mosaic image,and standard image map products,are described.The resulting Landsat RTU products are hosted on the RSGS earth observation data sharing web site for free download(http://ids.ceode.ac.cn/rtu/).These new products will provide consistent,standardized,multi-decadal image data for robust land cover change detection and monitoring across the Earth sciences.In the coming years,CASEarth DataBank system will be constructed,which is an intelligent data service platform for providing not only the RTU products from multi-source satellite data,but also big earth data analysis methods.