Establishing evaluation index system for desertification of Keerqin sandy land with remote sensing data

2005 ◽  
Vol 16 (3) ◽  
pp. 209-212 ◽  
Author(s):  
Fan Wen-yi ◽  
Zhang Wen-hua ◽  
Yu Su-fang ◽  
Liu Dan
Keyword(s):  
Remote Sensing ◽  
Index System ◽  
Remote Sensing Data ◽  
Evaluation Index System ◽  
Evaluation Index ◽  
Sandy Land ◽  
Sensing Data ◽  
Keerqin Sandy Land

Estimation of Vegetation Coverage in Semi-arid Sandy Land Based on Multivariate Statistical Modeling Using Remote Sensing Data

2013 ◽  
Vol 18 (5) ◽  
pp. 547-558 ◽  
Author(s):  
Wei Chen ◽  
Tetsuro Sakai ◽  
Kazuyuki Moriya ◽  
Lina Koyama ◽  
Chunxiang Cao
Keyword(s):  
Remote Sensing ◽  
Statistical Modeling ◽  
Remote Sensing Data ◽  
Vegetation Coverage ◽  
Sandy Land ◽  
Multivariate Statistical ◽  
Sensing Data ◽  
Semi Arid

Construction and application of quality evaluation index system for remote-sensing image fusion

2021 ◽  
Vol 16 (01) ◽  
Author(s):  
Chao Chen ◽  
Liyan Wang ◽  
Zili Zhang ◽  
Chang Lu ◽  
Huixin Chen ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Image Fusion ◽  
Index System ◽  
Quality Evaluation ◽  
Remote Sensing Image ◽  
Evaluation Index System ◽  
Evaluation Index ◽  
Remote Sensing Image Fusion

scholarly journals A Precision Evaluation Index System for Remote Sensing Data Sampling Based on Hexagonal Discrete Grids

2021 ◽  
Vol 10 (3) ◽  
pp. 194
Author(s):  
Yue Ma ◽  
Guoqing Li ◽  
Xiaochuang Yao ◽  
Qianqian Cao ◽  
Long Zhao ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Spatial Data ◽  
Evaluation Method ◽  
Remote Sensing Data ◽  
Evaluation Index System ◽  
Accuracy Evaluation ◽  
Remote Sensing Images ◽  
Sensing Data ◽  
Hexagonal Grids ◽  
Discrete Grid

With the rapid development of earth observation, satellite navigation, mobile communication, and other technologies, the order of magnitude of the spatial data we acquire and accumulate is increasing, and higher requirements are put forward for the application and storage of spatial data. As a new form of data management, the global discrete grid can be used for the efficient storage and application of large-scale global spatial data, which is a digital multiresolution georeference model that helps to establish a new model of data association and fusion. It is expected to make up for the shortcomings in the organization, processing, and application of current spatial data. There are different types of grid systems according to the grid division form, including global discrete grids with equal latitude and longitude, global discrete grids with variable latitude and longitude, and global discrete grids based on regular polyhedrons. However, there is no accuracy evaluation index system for remote sensing images expressed on the global discrete grid to solve this problem. This paper is dedicated to finding a suitable way to express remote sensing data on discrete grids, as well as establishing a suitable accuracy evaluation system for modeling remote sensing data based on hexagonal grids to evaluate modeling accuracy. The results show that this accuracy evaluation method can evaluate and analyze remote sensing data based on hexagonal grids from multiple levels, and the comprehensive similarity coefficient of the images before and after conversion is greater than 98%, which further proves the availability of the hexagonal-grid-based remote sensing data of remote sensing images. This evaluation method is generally applicable to all raster remote sensing images based on hexagonal grids, and it can be used to evaluate the availability of hexagonal grid images.

Methods for sandy land detection based on multispectral remote sensing data

Geoderma ◽  
2018 ◽  
Vol 316 ◽  
pp. 89-99 ◽  
Author(s):  
Junjun Wu ◽  
Zhihai Gao ◽  
Qinhuo Liu ◽  
Zengyuan Li ◽  
Bo Zhong
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Sandy Land ◽  
Sensing Data ◽  
Multispectral Remote Sensing

Monitoring the trends of aeolian desertified lands based on time-series remote sensing data in the Horqin Sandy Land, China

CATENA ◽  
2017 ◽  
Vol 157 ◽  
pp. 286-298 ◽  
Author(s):  
Yongfang Wang ◽  
Jiquan Zhang ◽  
Siqin Tong ◽  
Enliang Guo
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Remote Sensing Data ◽  
Horqin Sandy Land ◽  
Sandy Land ◽  
Sensing Data

Improving canopy variables estimation from remote sensing data by exploiting ancillary information. Case study on sugar beet canopies

Agronomie ◽  
2002 ◽  
Vol 22 (2) ◽  
pp. 205-215 ◽  
Author(s):  
Bruno Combal ◽  
Fr�d�ric Baret ◽  
Marie Weiss
Keyword(s):  
Remote Sensing ◽  
Sugar Beet ◽  
Remote Sensing Data ◽  
Sensing Data ◽  
Ancillary Information

Assessment of the national market demand for high-resolution remote sensing data

2002 ◽  
Vol 8 (1) ◽  
pp. 15-22
Author(s):  
V.N. Astapenko ◽  
◽  
Ye.I. Bushuev ◽  
V.P. Zubko ◽  
V.I. Ivanov ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Remote Sensing Data ◽  
Market Demand ◽  
Sensing Data ◽  
National Market
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