scholarly journals Spatio-Temporal Analysis and Uncertainty of Fractional Vegetation Cover Change over Northern China during 2001–2012 Based on Multiple Vegetation Data Sets

2018 ◽  
Vol 10 (4) ◽  
pp. 549 ◽  
Author(s):  
Linqing Yang ◽  
Kun Jia ◽  
Shunlin Liang ◽  
Meng Liu ◽  
Xiangqin Wei ◽  
...  
Keyword(s):  
Vegetation Cover ◽  
Northern China ◽  
Temporal Analysis ◽  
Data Sets ◽  
Fractional Vegetation Cover ◽  
Spatio Temporal ◽  
Vegetation Cover Change

scholarly journals CLUSTER–STAFF search coil magnetometer calibration – comparisons with FGM

2014 ◽  
Vol 3 (2) ◽  
pp. 153-177 ◽  
Author(s):  
P. Robert ◽  
N. Cornilleau-Wehrlin ◽  
R. Piberne ◽  
Y. de Conchy ◽  
C. Lacombe ◽  
...  
Keyword(s):  
Transfer Functions ◽  
Low Frequency ◽  
Temporal Analysis ◽  
Fluxgate Magnetometer ◽  
Data Sets ◽  
Spectral Matrix ◽  
Spatio Temporal ◽  
Cross Calibration ◽  
The Waves ◽  
The Way

Abstract. The main part of the Cluster Spatio-Temporal Analysis of Field Fluctuations (STAFF) experiment consists of triaxial search coils allowing the measurements of the three magnetic components of the waves from 0.1 Hz up to 4 kHz. Two sets of data are produced, one by a module to filter and transmit the corresponding waveform up to either 10 or 180 Hz (STAFF-SC), and the second by the onboard Spectrum Analyser (STAFF-SA) to compute the elements of the spectral matrix for five components of the waves, 3 × B and 2 × E (from the EFW experiment), in the frequency range 8 Hz to 4 kHz. In order to understand the way the output signals of the search coils are calibrated, the transfer functions of the different parts of the instrument are described as well as the way to transform telemetry data into physical units across various coordinate systems from the spinning sensors to a fixed and known frame. The instrument sensitivity is discussed. Cross-calibration inside STAFF (SC and SA) is presented. Results of cross-calibration between the STAFF search coils and the Cluster Fluxgate Magnetometer (FGM) data are discussed. It is shown that these cross-calibrations lead to an agreement between both data sets at low frequency within a 2% error. By means of statistics done over 10 yr, it is shown that the functionalities and characteristics of both instruments have not changed during this period.

scholarly journals Generating High Spatio-Temporal Resolution Fractional Vegetation Cover by Fusing GF-1 WFV and MODIS Data

2019 ◽  
Vol 11 (19) ◽  
pp. 2324 ◽  
Author(s):  
Tao ◽  
Jia ◽  
Zhao ◽  
Wei ◽  
Xie ◽  
...  
Keyword(s):  
Temporal Resolution ◽  
Vegetation Cover ◽  
Field Survey ◽  
Lower Probability ◽  
Important Indicator ◽  
The Real ◽  
Modis Data ◽  
Fractional Vegetation Cover ◽  
Spatio Temporal ◽  
Reflectance Data

As an important indicator to characterize the surface vegetation, fractional vegetation cover (FVC) with high spatio-temporal resolution is essential for earth surface process simulation. However, due to technical limitations and the influence of weather, it is difficult to generate temporally continuous FVC with high spatio-temporal resolution based on a single remote-sensing data source. Therefore, the objective of this study is to explore the feasibility of generating high spatio-temporal resolution FVC based on the fusion of GaoFen-1 Wide Field View (GF-1 WFV) data and Moderate-resolution Imaging Spectroradiometer (MODIS) data. Two fusion strategies were employed to identify a suitable fusion method: (i) fusing reflectance data from GF-1 WFV and MODIS firstly and then estimating FVC from the reflectance fusion result (strategy FC, Fusion_then_FVC). (ii) fusing the FVC estimated from GF-1 WFV and MODIS reflectance data directly (strategy CF, FVC_then_Fusion). The FVC generated using strategies FC and CF were evaluated based on FVC estimated from the real GF-1 WFV data and the field survey FVC, respectively. The results indicated that strategy CF achieved higher accuracies with less computational cost than those of strategy FC both in the comparisons with FVC estimated from the real GF-1 WFV (CF:R2 = 0.9580, RMSE = 0.0576; FC: R2 = 0.9345, RMSE = 0.0719) and the field survey FVC data (CF: R2 = 0.8138, RMSE = 0.0985; FC: R2 = 0.7173, RMSE = 0.1214). Strategy CF preserved spatial details more accurately than strategy FC and had a lower probability of generating abnormal values. It could be concluded that fusing GF-1 WFV and MODIS data for generating high spatio-temporal resolution FVC with good quality was feasible, and strategy CF was more suitable for generating FVC given its advantages in estimation accuracy and computational efficiency.

scholarly journals Đánh giá biến động độ che phủ thực vật tại một số khu vực đô thị và ven đô Hà Nội từ tư liệu ảnh vệ tinh LANDSAT đa phổ và đa thời gian

2017 ◽  
Vol 33 (2) ◽  
Author(s):  
Hoàng Anh Huy
Keyword(s):  
Vegetation Cover ◽  
Landsat Tm ◽  
Fractional Vegetation Cover ◽  
Vegetation Cover Change

Mục tiêu của nghiên cứu là đánh giá biến động độ che phủ thực vật (Fractional Vegetation Cover Change - FVC) khu vực đô thị và ven đô Hà Nội giai đoạn 2007 - 2015 dựa trên mô hình phân tích lẫn phổ tuyến tính hai đối tượng thuần (SMA) từ tư liệu ảnh vệ tinh đa phổ, đa thời gian LANDSAT TM và OLI. Trên cơ sở chỉ số NDVI, ứng dụng mô hình SMA hai đối tượng thuần xác định FVC, sau đó tiến hành đánh giá biến động độ che phủ thực vật (FVCC). Kết quả nghiên cứu cho thấy: diện tích FVC giảm 699,8 km2 (chiếm 75,5%), trung bình FVC giảm 87,5 km2 mỗi năm tại phía Nam huyện Sóc Sơn, phía Đông huyện Đông Anh và quận Gia Lâm, phía Tây huyện Thanh Trì; FVC giảm ở mức trung bình và nhẹ tại quận Cầu Giấy, Bắc, Nam –Từ Liêm và Tây Sóc Sơn; FVC không thay đổi là 184,5 km2 (chiếm 19,9%) tại các quận Ba Đình, Đống Đa và Hoàn Kiếm; chỉ 44,9 km2 có FVC tăng lên (chiếm 4,9%), FVC tăng 5,6 km2 mỗi năm, xuất hiện tại quận Hoàng Mai, Đông - Bắc Sóc Sơn, Nam huyện Đông Anh. Từ kết quả nghiên cứu có thể kết luận: ứng dụng tư liệu ảnh vệ tinh LANDSAT đa phổ, đa thời gian giúp việc đánh giá FVCC tại khu vực đô thị và ven đô Hà Nội một cách hiệu quả và nhanh chóng.

Impact of fractional vegetation cover change on soil erosion in Miyun reservoir basin, China

2014 ◽  
Vol 72 (8) ◽  
pp. 2741-2749 ◽  
Author(s):  
Rui-qing Niu ◽  
Bo Du ◽  
Yi Wang ◽  
Liang-pei Zhang ◽  
Tao Chen
Keyword(s):  
Soil Erosion ◽  
Vegetation Cover ◽  
Miyun Reservoir ◽  
Fractional Vegetation Cover ◽  
Reservoir Basin ◽  
Vegetation Cover Change

scholarly journals CLUSTER STAFF search coils magnetometer calibration – comparisons with FGM

2013 ◽  
Vol 3 (2) ◽  
pp. 679-751
Author(s):  
P. Robert ◽  
N. Cornilleau-Wehrlin ◽  
R. Piberne ◽  
Y. de Conchy ◽  
C. Lacombe ◽  
...  
Keyword(s):  
Transfer Functions ◽  
Low Frequency ◽  
Temporal Analysis ◽  
Data Sets ◽  
Spectral Matrix ◽  
Magnetic Components ◽  
Spatio Temporal ◽  
Cross Calibration ◽  
The Waves ◽  
The Way

Abstract. The main part of Cluster Spatio Temporal Analysis of Field Fluctuations (STAFF) experiment consists of triaxial search coils allowing the measurements of the three magnetic components of the waves from 0.1 Hz up to 4 kHz. Two sets of data are produced, one by a module to filter and transmit the corresponding waveform up to either 10 or 180 Hz (STAFF-SC) and the second by an onboard Spectrum Analyser (STAFF-SA) to compute the elements of the spectral matrix for five components of the waves, 3 × B and 2 × E (from EFW experiment) in the frequency range 8 Hz to 4 kHz. In order to understand the way the output signal of the search coils are calibrated, the transfer functions of the different parts of the instrument are described as well as the way to transform telemetry data into physical units, across various coordinate systems from the spinning sensors to a fixed and known frame. The instrument sensitivity is discussed. Cross-calibration inside STAFF (SC and SA) is presented. Results of cross-calibration between the STAFF search coils and the Cluster Flux Gate Magnetometer (FGM) data are discussed. It is shown that these cross-calibrations lead to an agreement between both data sets at low frequency within a 2% error. By means of statistics done over 10 yr, it is shown that the functionalities and characteristics of both instruments have not changed during this period.

Spatio-Temporal Analysis of Frontal Midline Theta Rhythm in EEG during 3-D Maze Task

2009 ◽  
Vol 129 (10) ◽  
pp. 1778-1784
Author(s):  
Yasuaki Uehara ◽  
Keita Tanaka ◽  
Yoshinori Uchikawa ◽  
Bong-Soo Kim
Keyword(s):  
Theta Rhythm ◽  
Temporal Analysis ◽  
Maze Task ◽  
Frontal Midline Theta ◽  
Spatio Temporal
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