Improving Estimates of Grassland Fractional Vegetation Cover Based on a Pixel Dichotomy Model: A Case Study in Inner Mongolia, China

Li, Fēi; Wei, Changfu; Zeng, Yuan; Zhao, Qian; Wu, Bingfang

doi:10.3390/rs6064705

Cited by 88 publications

(51 citation statements)

References 49 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The average air temperature and accumulated precipitation values were calculated every 10 days from 2000 to 2014. Biomass (the total aboveground biomass) was collected in small plots (1 × 1 m [23], in three repeated samplings) at each meteorological station. Plant samples were heated to above 100 • C and oven dried at 80 • C until they reached a constant weight in the laboratory.…”

Section: Station Datamentioning

confidence: 99%

Suitability Assessment of Satellite-Derived Drought Indices for Mongolian Grassland

Chang

Niu

et al. 2017

Remote Sensing

Self Cite

View full text Add to dashboard Cite

Abstract:In Mongolia, drought is a major natural disaster that can influence and devastate large regions, reduce livestock production, cause economic damage, and accelerate desertification in association with destructive human activities. The objective of this article is to determine the optimal satellite-derived drought indices for accurate and real-time expression of grassland drought in Mongolia. Firstly, an adaptability analysis was performed by comparing nine remote sensing-derived drought indices with reference indicators obtained from field observations using several methods (correlation, consistency percentage (CP), and time-space analysis). The reference information included environmental data, vegetation growth status, and region drought-affected (RDA) information at diverse scales (pixel, county, and region) for three types of land cover (forest steppe, steppe, and desert steppe). Second, a meteorological index (PED), a normalized biomass (NorBio) reference indicator, and the RDA-based drought CP method were adopted for describing Mongolian drought. Our results show that in forest steppe regions the normalized difference water index (NDWI) is most sensitive to NorBio (maximum correlation coefficient (MAX_R): up to 0.92) and RDA (maximum CP is 87%), and is most consistent with RDA spatial distribution. The vegetation health index (VHI) and temperature condition index (TCI) are most correlated with the PED index (MAX_R: 0.75) and soil moisture (MAX_R: 0.58), respectively. In steppe regions, the NDWI is most closely related to soil moisture (MAX_R: 0.69) and the VHI is most related to the PED (MAX_R: 0.76), NorBio (MCC: 0.95), and RDA data (maximum CP is 89%), exhibiting the most consistency with RDA spatial distribution. In desert steppe areas, the vegetation condition index (VCI) correlates best with NorBio (MAX_R: 0.92), soil moisture (MAX_R: 0.61), and RDA spatial distribution, while TCI correlates best with the PED (MAX_R: 0.75) and the RDA data (maximum CP is 79%). The VHI is a combination of constructed VCI and TCI, and can be used instead of them. Finally, the mode method was adopted to identify appropriate drought indices. The best two indices (VHI and NDWI) can be utilized to develop a combination drought model for accurately monitoring and quantifying drought in the future. Additionally, the new framework can be adopted to investigate and analyze the suitability of satellite-derived drought indices and determine the most appropriate index/indices for other countries or areas.

show abstract

Section: Station Datamentioning

confidence: 99%

Suitability Assessment of Satellite-Derived Drought Indices for Mongolian Grassland

Chang

Niu

et al. 2017

Remote Sensing

Self Cite

View full text Add to dashboard Cite

show abstract

“…There was a shortcoming when using the NDVI, with a response effect inconspicuous to highly-vegetation-covered areas. When the FVC is smaller than 15%, the NDVI can differentiate the soil and vegetation, but when the FVC is larger than 80%, the capacity of the NDVI response to vegetation is weak [65][66][67]. The visual angle in FVC definition was vertical to the surface, but when the satellite sensor acquired remote sensing data, the angle was normally not vertical to the ground.…”

Section: Limitations and Future Workmentioning

confidence: 99%

Human Activity Influences on Vegetation Cover Changes in Beijing, China, from 2000 to 2015

et al. 2017

View full text Add to dashboard Cite

For centuries, the rapid development of human society has already made human activity the dominant factor in the terrestrial ecosystem. As the city of greatest importance in China, the capital Beijing has experienced eco-environmental changes with unprecedented economic and population growth during the past few decades. To better understand the ecological transition and its correlations in Beijing, Landsat Thematic Mapper (TM) and Operational Land Imager (OLI) images were used to investigate vegetation coverage changes using a dimidiate pixel model. Piecewise linear regression, bivariate-partial correlation analysis, and factor analysis were applied to the probing of the relationship between vegetation coverage changes and climatic/human-induced factors. The results showed that from 2000 to 2005, 2005 to 2010, and 2010 to 2015, Beijing experienced both restoration (6.33%, 10.08%, and 12.81%, respectively) and degradation (13.62%, 9.35%, and 9.49%, respectively). The correlation analysis results between climate and vegetation changes demonstrated that from 2000 to 2015, both the multi-year annual mean temperature (r = −0.819, p < 0.01) and the multi-year annual mean precipitation (r = 0.653, p < 0.05) had a significantly correlated relationship with vegetation change. The Beijing-Tianjin Sandstorm Source Control Project (BTSSCP) has shown beneficial spatial effects on vegetation restoration; the total effectiveness in conservation areas (84.94 in 2000-2010) was much better than non-BTSSCP areas (34.34 in 2000-2010). The most contributory socioeconomic factors were the population (contribution = 54.356%) and gross domestic product (GDP) (contribution = 30.677%). The population showed a significantly negative correlation with the overall vegetation coverage (r = −0.684, p < 0.05). The GDP was significantly negatively correlated with vegetation in Tongzhou, Daxing, Central city, Fangshan, Shunyi, and Changping (r = −0.601, p < 0.01), while positively related in Huairou, Miyun, Pinggu, Mentougou and Yanqing (r = 0.614, p < 0.01). These findings confirm that human activity is a very significant factor in impacting and explaining vegetation changes, and that some socioeconomic influences on vegetation coverage are highly spatially heterogeneous, based on the context of different areas.

show abstract

“…The feasibility and precision of RS must be verified before data can be applied [4]. One way of validating and re-scaling RS products is the use of field measurements, especially the application of digital photography [5,6].…”

Section: Introductionmentioning

confidence: 99%

Estimation of Vegetation Cover Using Digital Photography in a Regional Survey of Central Mexico

Aguilar¹,

Sánchez-Sánchez

Rojas-García

et al. 2017

Forests

View full text Add to dashboard Cite

Abstract:The methods for measuring vegetation cover in Mexican forest surveys are subjective and imprecise. The objectives of this research were to compare the sampling designs used to measure the vegetation cover and estimate the over and understory cover in different land uses, using digital photography. The study was carried out in 754 circular sampling sites in central Mexico. Four spatial sampling designs were evaluated in three spatial distribution patterns of the trees. The sampling designs with photographic captures in diagonal form had lower values of mean absolute error (MAE < 0.12) and less variation in random and grouped patterns. The Carbon and Biomass Sampling Plot (CBSP) design was chosen due to its smaller error in the different spatial tree patterns. The image processing was performed using threshold segmentation techniques and was automated through an application developed in the Python language. The two proposed methods to estimate vegetation cover through digital photographs were robust and replicable in all sampling plots with different land uses and different illumination conditions. The automation of the process avoided human estimation errors and ensured the reproducibility of the results. This method is working for regional surveys and could be used in national surveys due to its functionality.

show abstract

Improving Estimates of Grassland Fractional Vegetation Cover Based on a Pixel Dichotomy Model: A Case Study in Inner Mongolia, China

Cited by 88 publications

References 49 publications

Suitability Assessment of Satellite-Derived Drought Indices for Mongolian Grassland

Suitability Assessment of Satellite-Derived Drought Indices for Mongolian Grassland

Human Activity Influences on Vegetation Cover Changes in Beijing, China, from 2000 to 2015

Estimation of Vegetation Cover Using Digital Photography in a Regional Survey of Central Mexico

Contact Info

Product

Resources

About