Regional estimates of evapotranspiration over Northern China using a remote-sensing-based triangle interpolation method

2013 ◽  
Vol 30 (5) ◽  
pp. 1479-1490 ◽  
Author(s):  
Hesong Wang ◽  
Gensuo Jia
Keyword(s):  
Remote Sensing ◽  
Interpolation Method ◽  
Northern China ◽  
Regional Estimates

Dune bistability identified by remote sensing in a semi-arid dune field of northern China

2021 ◽  
Vol 53 ◽  
pp. 100751
Author(s):  
Yongxin Chen ◽  
Hezi Yizhaq ◽  
Joseph A. Mason ◽  
Xueliang Zhang ◽  
Zhiwei Xu
Keyword(s):  
Remote Sensing ◽  
Northern China ◽  
Dune Field ◽  
Semi Arid

scholarly journals Garlic and Winter Wheat Identification Based on Active and Passive Satellite Imagery and the Google Earth Engine in Northern China

2020 ◽  
Vol 12 (21) ◽  
pp. 3539
Author(s):  
Haifeng Tian ◽  
Jie Pei ◽  
Jianxi Huang ◽  
Xuecao Li ◽  
Jian Wang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Winter Wheat ◽  
Satellite Imagery ◽  
Remote Sensing Data ◽  
Northern China ◽  
Google Earth ◽  
Kappa Coefficient ◽  
Landsat 8 ◽  
Winter Crops ◽  
Sentinel 2

Garlic and winter wheat are major economic and grain crops in China, and their boundaries have increased substantially in recent decades. Updated and accurate garlic and winter wheat maps are critical for assessing their impacts on society and the environment. Remote sensing imagery can be used to monitor spatial and temporal changes in croplands such as winter wheat and maize. However, to our knowledge, few studies are focusing on garlic area mapping. Here, we proposed a method for coupling active and passive satellite imagery for the identification of both garlic and winter wheat in Northern China. First, we used passive satellite imagery (Sentinel-2 and Landsat-8 images) to extract winter crops (garlic and winter wheat) with high accuracy. Second, we applied active satellite imagery (Sentinel-1 images) to distinguish garlic from winter wheat. Third, we generated a map of the garlic and winter wheat by coupling the above two classification results. For the evaluation of classification, the overall accuracy was 95.97%, with a kappa coefficient of 0.94 by eighteen validation quadrats (3 km by 3 km). The user’s and producer’s accuracies of garlic are 95.83% and 95.85%, respectively; and for the winter wheat, these two accuracies are 97.20% and 97.45%, respectively. This study provides a practical exploration of targeted crop identification in mixed planting areas using multisource remote sensing data.

A robust interpolation method for constructing digital elevation models from remote sensing data

Geomorphology ◽  
2016 ◽  
Vol 268 ◽  
pp. 275-287 ◽  
Author(s):  
Chuanfa Chen ◽  
Fengying Liu ◽  
Yanyan Li ◽  
Changqing Yan ◽  
Guolin Liu
Keyword(s):  
Remote Sensing ◽  
Interpolation Method ◽  
Digital Elevation Models ◽  
Remote Sensing Data ◽  
Sensing Data ◽  
Digital Elevation

scholarly journals EVALUATION DIGITAL ELEVATION MODEL GENERATED BY SYNTHETIC APERTURE RADAR DATA

2016 ◽  
Vol XLI-B1 ◽  
pp. 57-62
Author(s):  
H. B. Makineci ◽  
H. Karabörk
Keyword(s):  
Remote Sensing ◽  
Digital Elevation Model ◽  
Interpolation Method ◽  
Digital Elevation Models ◽  
European Space Agency ◽  
Mountain Area ◽  
Synthetic Aperture Radar Data ◽  
Radar Images ◽  
Digital Elevation ◽  
Elevation Model

Digital elevation model, showing the physical and topographical situation of the earth, is defined a tree-dimensional digital model obtained from the elevation of the surface by using of selected an appropriate interpolation method. DEMs are used in many areas such as management of natural resources, engineering and infrastructure projects, disaster and risk analysis, archaeology, security, aviation, forestry, energy, topographic mapping, landslide and flood analysis, Geographic Information Systems (GIS). Digital elevation models, which are the fundamental components of cartography, is calculated by many methods. Digital elevation models can be obtained terrestrial methods or data obtained by digitization of maps by processing the digital platform in general. Today, Digital elevation model data is generated by the processing of stereo optical satellite images, radar images (radargrammetry, interferometry) and lidar data using remote sensing and photogrammetric techniques with the help of improving technology. <br><br> One of the fundamental components of remote sensing radar technology is very advanced nowadays. In response to this progress it began to be used more frequently in various fields. Determining the shape of topography and creating digital elevation model comes the beginning topics of these areas. <br><br> It is aimed in this work , the differences of evaluation of quality between Sentinel-1A SAR image ,which is sent by European Space Agency ESA and Interferometry Wide Swath imaging mode and C band type , and DTED-2 (Digital Terrain Elevation Data) and application between them. The application includes RMS static method for detecting precision of data. Results show us to variance of points make a high decrease from mountain area to plane area.

scholarly journals SUPER RESOLUTION RECONSTRUCTION BASED ON ADAPTIVE DETAIL ENHANCEMENT FOR ZY-3 SATELLITE IMAGES

2016 ◽  
Vol III-7 ◽  
pp. 213-217 ◽  
Author(s):  
Hong Zhu ◽  
Weidong Song ◽  
Hai Tan ◽  
Jingxue Wang ◽  
Di Jia
Keyword(s):  
Remote Sensing ◽  
Large Scale ◽  
Satellite Images ◽  
Interpolation Method ◽  
Super Resolution ◽  
Bilateral Filter ◽  
Redundant Information ◽  
Evaluation Standard ◽  
Detail Enhancement ◽  
Image Details

Super-resolution reconstruction of sequence remote sensing image is a technology which handles multiple low-resolution satellite remote sensing images with complementary information and obtains one or more high resolution images. The cores of the technology are high precision matching between images and high detail information extraction and fusion. In this paper puts forward a new image super resolution model frame which can adaptive multi-scale enhance the details of reconstructed image. First, the sequence images were decomposed into a detail layer containing the detail information and a smooth layer containing the large scale edge information by bilateral filter. Then, a texture detail enhancement function was constructed to promote the magnitude of the medium and small details. Next, the non-redundant information of the super reconstruction was obtained by differential processing of the detail layer, and the initial super resolution construction result was achieved by interpolating fusion of non-redundant information and the smooth layer. At last, the final reconstruction image was acquired by executing a local optimization model on the initial constructed image. Experiments on ZY-3 satellite images of same phase and different phase show that the proposed method can both improve the information entropy and the image details evaluation standard comparing with the interpolation method, traditional TV algorithm and MAP algorithm, which indicate that our method can obviously highlight image details and contains more ground texture information. A large number of experiment results reveal that the proposed method is robust and universal for different kinds of ZY-3 satellite images.

scholarly journals Remote sensing of the impact of flash drought events on terrestrial carbon dynamics over China

2020 ◽  
Vol 15 (1) ◽  
Author(s):  
Miao Zhang ◽  
Xing Yuan ◽  
Jason A. Otkin
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Large Scale ◽  
Structural Changes ◽  
Terrestrial Ecosystems ◽  
Northern China ◽  
Carbon Dynamics ◽  
Western China ◽  
Terrestrial Carbon ◽  
The Impact

Abstract Background Flash drought poses a great threat to terrestrial ecosystems and influences carbon dynamics due to its unusually rapid onset and increasing frequency in a warming climate. Understanding the response of regional terrestrial carbon dynamics to flash drought requires long-term observations of carbon fluxes and soil moisture at a large scale. Here, MODIS satellite observations of ecosystem productivity and ERA5 reanalysis modeling of soil moisture are used to detect the response of ecosystems to flash drought over China. Results The results show that GPP, NPP, and LAI respond to 79–86% of the flash drought events over China, with highest and lowest response frequency for NPP and LAI, respectively. The discrepancies in the response of GPP, NPP, and LAI to flash drought result from vegetation physiological and structural changes. The negative anomalies of GPP, NPP, and LAI occur within 19 days after the start of flash drought, with the fastest response occurring over North China, and slower responses in southern and northeastern China. Water use efficiency (WUE) is increased in most regions of China except for western regions during flash drought, illustrating the resilience of ecosystems to rapid changes in soil moisture conditions. Conclusions This study shows the rapid response of ecosystems to flash drought based on remote-sensing observations, especially for northern China with semiarid climates. Besides, NPP is more sensitive than GPP and LAI to flash drought under the influence of vegetation respiration and physiological regulations. Although the mean WUE increases during flash drought over most of China, western China shows less resilience to flash drought with little changes in WUE during the recovery stage. This study highlights the impacts of flash drought on ecosystems and the necessity to monitor rapid drought intensification.

scholarly journals Spatial and temporal dust source variability in northern China identified using advanced remote sensing analysis

2012 ◽  
Vol 38 (8) ◽  
pp. 793-809 ◽  
Author(s):  
A. Taramelli ◽  
M. Pasqui ◽  
J. Barbour ◽  
D. Kirschbaum ◽  
L. Bottai ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Northern China ◽  
Dust Source
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