Remote Sensing-Based Biomass Estimation and Its Spatio-Temporal Variations in Temperate Grassland, Northern China
نویسندگان
چکیده
Grassland biomass is essential for maintaining grassland ecosystems. Moreover, biomass is an important characteristic of grassland. In this study, we combined field sampling with remote sensing data and calculated five vegetation indices (VIs). Using this combined information, we quantified a remote sensing estimation model and estimated biomass in a temperate grassland of northern China. We also explored the dynamic spatio-temporal variation of biomass from 2006 to 2012. Our results indicated that all VIs investigated in the study were strongly correlated with biomass (α < 0.01). The precision of the model for estimating biomass based on ground data and remote sensing was greater than 73%. Additionally, the results of our analysis indicated that the annual average biomass was 11.86 million tons and that the average yield was 604.5 kg/ha. The distribution of biomass exhibited substantial spatial heterogeneity, and the biomass decreased from the eastern portion of the study area to the western portion. The interannual biomass exhibited strong fluctuations during 2006–2012, with a coefficient of variation of OPEN ACCESS Remote Sens. 2014, 6 1497 26.95%. The coefficient of variation of biomass differed among the grassland types. The highest coefficient of variation was found for the desert steppe, followed by the typical steppe and the meadow steppe.
منابع مشابه
Remote Sensing Estimates of Grassland Aboveground Biomass Based on MODIS Net Primary Productivity (NPP): A Case Study in the Xilingol Grassland of Northern China
The precise and rapid estimation of grassland biomass is an important scientific issue in grassland ecosystem research. In this study, based on a field survey of 1205 sites together with biomass data of the Xilingol grassland for the years 2005–2012 and the ―accumulated‖ MODIS productivity starting from the beginning of growing season, we built regression models to estimate the aboveground biom...
متن کاملSpatio-temporal distribution of off-shore ships in the Pars Special Economic Energy Zone based on satellite imagery
Special Economic Zones (SEZs) are areas controlled by specific legislations so as toattain economic prosperity. These zones are commonly established and controlled bygovernment officials and are primarily characterized by growing population and developingtransport infrastructure. One relevant case is the Pars Special Economic Energy Zone(PSEEZ) situated in the south of Iran, on the northern sho...
متن کاملSpatio-temporal analysis of diurnal air temperature parameterization in Weather Stations over Iran
Diurnal air temperature modeling is a beneficial experimental and mathematical approach which can be used in many fields related to Geosciences. The modeling and spatio-temporal analysis of air Diurnal Temperature Cycle (DTC) was conducted using data obtained from 105 synoptic stations in Iran during the years 2013-2014 for the first time; the key variable for controlling the cosine term i...
متن کاملApplication of Synthetic NDVI Time Series Blended from Landsat and MODIS Data for Grassland Biomass Estimation
Accurate monitoring of grassland biomass at high spatial and temporal resolutions is important for the effective utilization of grasslands in ecological and agricultural applications. However, current remote sensing data cannot simultaneously provide accurate monitoring of vegetation changes with fine temporal and spatial resolutions. We used a data-fusion approach, namely the spatial and tempo...
متن کاملSpatio-Temporal Patterns and Climate Variables Controlling of Biomass Carbon Stock of Global Grassland Ecosystems from 1982 to 2006
Grassland ecosystems play an important role in subsistence agriculture and the global carbon cycle. However, the global spatio-temporal patterns and environmental controls of grassland biomass are not well quantified and understood. The goal of this study was to estimate the spatial and temporal patterns of the global grassland biomass and analyze their driving forces using field measurements, ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Remote Sensing
دوره 6 شماره
صفحات -
تاریخ انتشار 2014