数据下载包含两种方式。第一种是官网下载方法，打开data.ess.tsinghua.edu.cn...进入下载界面，无需注册与审核。下载影像时，需注意影像名称代表的是最左下角坐标，经纬度以偶数递增，最高纬度为南北纬84°。例如，下载北京市中心影像（北纬39°56′，东经116°20′），则需要下载北纬38°，东经116°...
data.ess.tsinghua.edu.cn,打开直接进入下载界面,无需注册与审核。 2.1.2影像确定 该网站按照影像的经纬度提供数据下载,影像名称代表的含义分别如下: 其中经纬度是影像的最左下角坐标: 在官网每一景土地覆盖影像的坐标是偶数递增,其中最高纬度为南北纬84°: 纬度:-84,-82...-4,-2,0,2,4...82,84 经度...
Due to its high spatial resolution and reliable global accuracy, we evaluated the suitability of FROM-GLC10 data for understanding agricultural ecosystems in Beijing using a comparable vector data set, Google Earth images and field survey data. The overall accuracy (OA) for FROM-GLC10 based on ...
This dataset contains annual change information of global impervious surface area from 1985 to 2018 at a 30m resolution. Change from pervious to impervious was determined using a combined approach of supervised classification and temporal consistency checking. Impervious pixels are defined as above 50% ...
上述研究成果以“Dual Data- and Knowledge-Driven Land Cover Mapping Framework for Monitoring Annual and Near-Real-Time Changes”(知识与数据双驱动的土地覆盖年度及近实时变化监测框架)为题,发表在IEEE Transactions on Geoscience and ...
The results showed (1) the area proportion of different land cover types in the FROM-GLC30 2017 dataset was generally consistent with that of the reference data. (2) The overall accuracy of the FROM-GLC30 2017 dataset was 72.78%, and was highest in West Asia–Northeast Africa, and lowest...
FROM-GLC (Fine Resolution Observation and Monitoring of Global Land Cover) is the first 30m resolution global land-cover map produced using Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) data. Due to the lack of temporal features as inputs in producing FROM-GLC, conside...
Accessing the Dataset Users have the convenience to download the GLASS-GLC dataset directly from theofficial website. The data is formatted in a manner conducive to spatial analysis and model simulation. Usage Scenarios The GLASS-GLC dataset is widely applied across various fields, including but not...
python train_rcnn.py --cfg_file cfgs/default.yaml --batch_size 4 --train_mode rcnn_offline --epochs 30 --ckpt_save_interval 1 --rcnn_training_roi_dir ../output/rpn/default/eval/epoch_200/train_aug/detections/data --rcnn_training_feature_dir ../output/rpn/default/eval/epoch_200/...
A new global land cover database for the year 2000 (GLC2000) has been produced by an international partnership of 30 research groups coordinated by the European Commission's Joint Research Centre. The database contains two levels of land cover information—detailed, regionally optimized land cover...