The dynamics of grassland vegetation fractional coverage using time-series MODIS data in Gannan region of China

Author(s):  
Wenlong Li ◽  
Jing Xu ◽  
Hao Wang
Land ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 344
Author(s):  
Haochen Yu ◽  
Jiu Huang ◽  
Chuning Ji ◽  
Zi’ao Li

A large-scale energy and chemical industry base is an important step in the promotion of the integrated and coordinated development of coal and its downstream coal-based industry. A number of large-scale energy and chemical industrial bases have been built in the Yellow River Basin that rely on its rich coal resources. However, the ecological environment is fragile in this region. Once the eco-environment is destroyed, the wildlife would lose its habitat. Therefore, this area has attracted wide attention regarding the development of the coal-based industry while also protecting the ecological environment. An ecological network could improve landscape connectivity and provide ideas for ecological restoration. This study took the Ningdong Energy and Chemical Industrial Base as a case study. Morphological spatial pattern analysis was applied to extract core patches. The connectivity of the core patches was evaluated, and then the ecological source patches were recognized. The minimum cumulative resistance model, hydrologic analysis and circuit theory were used to simulate the ecological network. Then, ecological corridors and ecological nodes were classified. The results were as follows: (1) The vegetation fractional coverage has recently been significantly improved. The area of core patches was 22,433.30 ha. In addition, 18 patches were extracted as source patches, with a total area of 9455.88 ha; (2) Fifty-eight potential ecological corridors were simulated. In addition, it was difficult to form a natural ecological corridor because of the area’s great resistance. Moreover, the connectivity was poor between the east and west; (3) A total of 52 potential ecological nodes were simulated and classified. The high-importance nodes were concentrated in the western grassland and Gobi Desert. This analysis indicated that restoration would be conducive to the ecological landscape in this area. Furthermore, five nodes with high importance but low vegetation fractional coverage should be given priority in later construction. In summary, optimizing the ecological network to achieve ecological restoration was suggested in the study area. The severe eco-environmental challenges urgently need more appropriate policy guidance in the large energy and chemical bases. Thus, the ecological restoration and ecological network construction should be combined, the effectiveness of ecological restoration could be effectively achieved, and the cost could also be reduced.


2012 ◽  
Vol 5 (1) ◽  
pp. 89-101 ◽  
Author(s):  
Fei Zhang ◽  
Tashpolat Tiyip ◽  
JianLi Ding ◽  
Mamat Sawut ◽  
Verner Carl Johnson ◽  
...  

2011 ◽  
Vol 115 (7) ◽  
pp. 1706-1720 ◽  
Author(s):  
Douglas C. Morton ◽  
Ruth S. DeFries ◽  
Jyoteshwar Nagol ◽  
Carlos M. Souza ◽  
Eric S. Kasischke ◽  
...  

2020 ◽  
Vol 63 (6) ◽  
pp. 1795-1804
Author(s):  
Yanli Chen ◽  
Weihua Mo ◽  
Jianfei Mo ◽  
Meihua Ding

HighlightsThe spatial and temporal fusion model ESTARFM was used to obtain NDVI timing data with high fusion accuracy and high spatial and temporal resolution.High-quality NDVI timing data could be obtained by using ESTARFM to fuse HJ-1 CCD and MODIS data.Fused NDVI data coupled with ground seeding survey data could effectively monitor sugarcane growth status.Abstract. This study addressed the instability of clear-sky remote sensing data with high spatial resolution in sugarcane growing areas in southern China and the current inconsistency between traditional survey results and remote sensing results for seedling growth. Moderate-resolution imaging spectroradiometer (MODIS) data and China land resources satellite (HJ-1 CCD) data were used to build high-resolution normalized difference vegetation index (NDVI) time series using the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM). Agronomic indicators of sugarcane were obtained by field sampling and were used for determining the remote sensing monitoring index (NDVI) of sugarcane growth. The method provided satisfactory results for evaluating sugarcane growth, with accuracy exceeding 90%. Moreover, sugarcane growth monitoring in a wider area was highly correlated with yield per unit area. Keywords: Growth status, HJ-1 CCD, MODIS, NDVI time series, Spatial and temporal fusion, Sugarcane.


Sign in / Sign up

Export Citation Format

Share Document