“Black Soil Land” recognition at Maduo County in source region of Yellow River based on quantitative remote sensing

In this study, we proposed climate use efficiency (CUE), a new index in monitoring grassland ecosystem function, to mitigate the disturbance of climate fluctuation. A comprehensive evaluation index (EI), combining with actual vegetation net primary productivity (NPP), CUE, vegetation coverage, and surface bareness, was constructed for the dynamic remote sensing monitoring of grassland degradation/restoration on a regional scale. By using this index, the grassland degradation/restoration in the Three-River Source Region (TRSR) was quantitatively evaluated during 2001–2016, which has been an important ecological barrier area in China. Results showed the following: During the study period, the grassland of Yellow River source (SRYe) had high vegetation coverage, NPP, CUE, and low bareness, whereas Yangtze River source (SRYa) had low vegetation coverage, NPP, CUE, and high bareness. The vegetation coverage and CUE of the grassland showed upward trends, with annual change rates of 0.75% and 0.45% year −1. The surface bareness and NPP showed downward trends, with annual change rates of −0.37% year−1 and −0.24 g C m−2 yr−2, respectively. Assessment of EI revealed that 67.18% of the grassland of TRSR showed a recovery trend during the study period. The overall restoration of the SRYe was the best, followed by SRYa. However, the status of Lancang River source (SRLa) was poor.

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A Study of Lake Wetland Information Automatic Extraction Based on the Interpolation and Threshold Method

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.433-440.6674 ◽

2012 ◽

Vol 433-440 ◽

pp. 6674-6677

Author(s):

Zhi Hong An ◽

Yong Jun Sun ◽

De Zhi Chen ◽

Yun Feng Qiu

Keyword(s):

Remote Sensing ◽

Yellow River ◽

Source Region ◽

Structural Features ◽

Automatic Extraction ◽

Threshold Method ◽

Remote Sensing Technology ◽

Sensing Technology ◽

Human Material ◽

Yellow River Source

Lake is one of the most type important wetland; remote sensing technology applied on wetland had become a research hotspot of wetlands. Automatic or semi-automatic extraction using computer wetland information extraction can improve the efficiency in the human, material, etc. From remote sensing images automatically extract wetland information is important for Wetland research and putting forward Utilization. In this paper, Yellow River source region for the test area, we use interpolation and threshold method automatically to extract lake information from ETM + images. Making use of both spectral and structural features of lake, this method acquired a good result.

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Derivation of Vegetation Optical Depth and Water Content in the Source Region of the Yellow River using the FY-3B Microwave Data

Remote Sensing ◽

10.3390/rs11131536 ◽

2019 ◽

Vol 11 (13) ◽

pp. 1536 ◽

Cited By ~ 2

Author(s):

Rong Liu ◽

Jun Wen ◽

Xin Wang ◽

Zuoliang Wang ◽

Zhenchao Li ◽

...

Keyword(s):

Remote Sensing ◽

Water Content ◽

Optical Depth ◽

Yellow River ◽

Source Region ◽

Microwave Remote Sensing ◽

Microwave Frequency ◽

The Yellow River ◽

Growing Period ◽

Vegetation Water

This study uses the brightness temperature at the given microwave frequency (18.7 GHz) from the Microwave Radiation Imager (MWRI) on-board the Fengyun-3B (FY-3B) satellite to improve the τ-ω model by considering the radiative contribution from waterbody in the pixels over the wetland of the Yellow River source region, China. In order to retrieve vegetation optical depth (VOD), a dual-polarization slope parameter is defined to express the surface emissivity in the τ-ω model as the sum of soil emissivity and waterbody emissivity. In the regions with no waterbody, the original τ-ω model without considering waterbody impact is used to derive VOD. With use of the field observed vegetation water content (VWC) in the source region of the Yellow River during the summer of 2012, a regression relationship between VOD and VWC is established and then the vegetation parameter b is estimated. The relationship is employed to derive the spatial VWC during the entire vegetation growing period. The VOD retrieved is invalid and failed in some part of the study area by using the previous τ-ω model, while the results from the improved τ-ω model indicate that the VOD is in the range of 0.20 to 1.20 and the VWC is in the range of 0.20kg/m2 to 1.40kg/m2 in the entire source region of the Yellow River in 2012. Both VOD and VWC exhibit a pattern of low values in the west part and high values in the east part. The largest regional variations appear along the Yellow River. The comparison between the remote-sensing-estimated VWC and the ground-measured VWC gives the root mean square error of 0.12kg/m2. These assessments reveal that with considering the fractional seasonal wetlands in the source region of the Yellow River, the microwave remote sensing measurements from the FY-3B MWRI can be successfully used to retrieve the VWC in the source region of the Yellow River.

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