scholarly journals Spatiotemporal Variations of Satellite Microwave Emissivity Difference Vegetation Index in China Under Clear and Cloudy Skies

2020 ◽  
Vol 7 (5) ◽  
Author(s):  
Rui Li ◽  
Yipu Wang ◽  
Jiheng Hu ◽  
Yu Wang ◽  
Qilong Min ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Spatiotemporal Variations ◽  
Microwave Emissivity ◽  
Satellite Microwave

scholarly journals Impacts of Climate on Spatiotemporal Variations in Vegetation NDVI from 1982–2015 in Inner Mongolia, China

2019 ◽  
Vol 11 (3) ◽  
pp. 768 ◽  
Author(s):  
Xinxia Liu ◽  
Zhixiu Tian ◽  
Anbing Zhang ◽  
Anzhou Zhao ◽  
Haixin Liu
Keyword(s):  
Inner Mongolia ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Grassland Management ◽  
Spatiotemporal Variations ◽  
Study Region ◽  
Temperature And Precipitation ◽  
Vegetation Activity ◽  
One Year ◽  
Scale Data

By using the Global Inventory Modeling and Mapping Studies (GIMMS) third-generation normalized difference vegetation index (NDVI3g) data, this paper explores the spatiotemporal variations in vegetation and their relationship with temperature and precipitation between 1982 and 2015 in the Inner Mongolia region of China. Based on yearly scale data, the vegetation changes in Inner Mongolia have experienced three stages from 1982 to 2015: the vegetation activity kept a continuous improvement from 1982–1999, then downward between 1999–2009, and upward from 2009 to 2015. On the whole, the general trend is increasing. Several areas even witnessed significant vegetation increases: in the east and south of Tongliao and Chifeng, north of Xing’anmeng, north and west of Hulunbir, and in the west of Inner Mongolia. Based on monthly scale data, one-year and half-year cycles exist in normalized difference vegetation index (NDVI) and temperature but only a one-year cycle in precipitation. Finally, based on the one-year cycle, the relationship between NDVI and climatic were studied; NDVI has a significant positive correlation with temperature and precipitation, and temperature has a greater effect in promoting vegetation growth than precipitation. Moreover, based on a half-year changing period, NDVI is only affected by temperature in the study region. Those findings can serve as a critical reference for grassland managers or policy makers to make informed decisions on grassland management.

scholarly journals Drought Risk Assessment in Cultivated Areas of Central Asia Using MODIS Time-Series Data

Water ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1738
Author(s):  
Nurgul Aitekeyeva ◽  
Xinwu Li ◽  
Huadong Guo ◽  
Wenjin Wu ◽  
Zeeshan Shirazi ◽  
...  
Keyword(s):  
Central Asia ◽  
Vegetation Index ◽  
Time Series Data ◽  
Climate Change Impacts ◽  
Monitoring And Evaluation ◽  
Condition Index ◽  
Series Data ◽  
Drought Risk ◽  
Spatiotemporal Variations ◽  
Agriculture Sector

Drought is one of the most damaging environmental hazards and a naturally occurring phenomenon in Central Asia that is accompanied by crucial consequences for the agriculture sector. This research aimed at understanding the nature and extent of drought over the cropland regions of Central Asia with the help of spatiotemporal information from the region. We assessed drought occurrence using the vegetation health index (VHI). An algorithm was developed to reduce the noise of heterogeneous land surfaces by adjusting the vegetation index and brightness temperature. The vegetation condition index (VCI) and temperature condition index (TCI) were calculated using Moderate Resolution Imaging Spectroradiometer (MODIS) products for the growing season (April–September) from 2000 to 2015. The intense drought years were identified and a drought map (drought probability occurrence) was generated. The findings of this research indicated regional heterogeneity in the cropland areas having experienced droughts, observed through spatiotemporal variations. Some of the rain-fed and irrigated croplands of Kazakhstan demonstrated a higher vulnerability to annual drought occurrences and climate change impacts, while other cropland regions were found to be more resistant to such changes. The development of policy tools is required to support informed decision-making and planning processes to adapt to the occurrence of droughts. This could be achieved by the timely assessment, monitoring, and evaluation of the spatiotemporal distribution trends and variabilities of drought occurrences in this region. The results from this study focus on the spatiotemporal variations in drought to reveal the bigger picture in order to better understand the regional capacity for sustainable land management and agricultural activities within a changing environment.

scholarly journals A PCA–OLS Model for Assessing the Impact of Surface Biophysical Parameters on Land Surface Temperature Variations

2019 ◽  
Vol 11 (18) ◽  
pp. 2094 ◽  
Author(s):  
Firozjaei ◽  
Alavipanah ◽  
Liu ◽  
Sedighi ◽  
Mijani ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Correlation Coefficient ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Single Channel ◽  
Ordinary Least Squares ◽  
Spatiotemporal Variations ◽  
Biophysical Parameters ◽  
The Impact

Analysis of land surface temperature (LST) spatiotemporal variations and characterization of the factors affecting these variations are of great importance in various environmental studies and applications. The aim of this study is to propose an integrated model for characterizing LST spatiotemporal variations and for assessing the impact of surface biophysical parameters on the LST variations. For this purpose, a case study was conducted in Babol City, Iran, during the period of 1985 to 2018. We used 122 images of Landsat 5, 7, and 8, and products of water vapor (MOD07) and daily LST (MOD11A1) from the MODIS sensor of the Terra satellite, as well as soil and air temperature and relative humidity data measured at the local meteorological station over 112 dates for the study. First, a single-channel algorithm was applied to estimate LST, while various spectral indices were computed to represent surface biophysical parameters, which included the normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), normalized difference water index (NDWI), normalized difference built-up index (NDBI), albedo, brightness, greenness, and wetness from tasseled cap transformation. Next, a principal component analysis (PCA) was conducted to determine the degree of LST variation and the surface biophysical parameters in the temporal dimension at the pixel scale based on Landsat imagery. Finally, the relationship between the first component of the PCA of LST and each surface biophysical parameter was investigated by using the ordinary least squares (OLS) regression with both regional and local optimizations. The results indicated that among the surface biophysical parameters, variations of NDBI, wetness, and greenness had the highest impact on the LST variations with a correlation coefficient of 0.75, −0.70, and −0.44, and RMSE of 0.71, 1.03, and 1.06, respectively. The impact of NDBI, wetness, and greenness varied geographically, but their variations accounted for 43%, 38%, and 19% of the LST variation, respectively. Furthermore, the correlation coefficient and RMSE between the observed LST variation and modeled LST variation, based on the most influential biophysical factors (NDBI, wetness, and greenness) yielded 0.85 and 1.06 for the regional approach and 0.93 and 0.26 for the local approach, respectively. The results of this study indicated the use of an integrated PCA–OLS model was effective for modeling of various environmental parameters and their relationship with LST. In addition, the PCA–OLS with the local optimization was found to be more efficient than the one with the regional optimization.

scholarly journals A Remotely Sensed Assessment of Surface Ecological Change over the Gomishan Wetland, Iran

2020 ◽  
Vol 12 (18) ◽  
pp. 2989 ◽  
Author(s):  
Salman Qureshi ◽  
Seyed Kazem Alavipanah ◽  
Maria Konyushkova ◽  
Naeim Mijani ◽  
Solmaz Fathololomi ◽  
...  
Keyword(s):  
Land Surface ◽  
Vegetation Index ◽  
Temporal Variations ◽  
Ecological Change ◽  
Spatiotemporal Variations ◽  
Landsat Images ◽  
The Caspian Sea ◽  
Ecological Index ◽  
Ecological Conditions ◽  
The Mean

Due to the excessive use of natural resources in the contemporary world, the importance of ecological and environmental condition modeling has increased. Wetlands and cities represent the natural and artificial strategic areas that affect ecosystem conditions. Changes in the ecological conditions of these areas have a great impact on the conditions of the global ecosystem. Therefore, modeling spatiotemporal variations of the ecological conditions in these areas is critical. This study was aimed at comparing degrees of variation among surface ecological conditions due to natural and unnatural factors. Consequently, the surface ecological conditions of Gomishan city and Gomishan wetland in Iran were modeled for a period of 30 years, and the spatiotemporal variations were evaluated and compared with each other. To this end, 20 Landsat 5, 7, and 8, and 432 Moderate Resolution Imaging Spectroradiometer (MODIS), monthly land surface temperature (LST) (MOD11C3) and normalized difference vegetation index (NDVI) (MOD13C3) products were utilized. The surface ecological conditions were modeled according to the Remote Sensing-based Ecological Index (RSEI), and the spatiotemporal variation of the RSEI values in the study area (Gomishan city, Gomishan wetland) were evaluated and compared with each other. According to MODIS products, the mean of the LST and NDVI variance values for the study area (Gomishan city, Gomishan wetland) were obtained to be 6.5 °C (2.1, 12.1) and 0.009 (0.005, 0.013), respectively. The highest LST and NDVI temporal variations were found for Gomishan wetland near the Caspian Sea. According to Landsat images, Gomishan wetland and Gomishan city have the highest and lowest temporal variations in surface biophysical characteristics, respectively. The mean RSEI for the study area (Gomishan city, Gomishan wetland) was 0.43 (0.65, 0.29), respectively. Additionally, the mean Coefficient of Variation (CV) of RSEI for the study area (Gomishan city, Gomishan wetland) was 0.10 (0.88, 0.51), respectively. The surface ecological conditions of Gomishan city were worse than those of the Gomishan wetland at all dates. Temporal variations in the surface ecological conditions of Gomishan wetland were greater than those of the study area and Gomishan city. These results can provide useful and effective information for environmental planning and decision-making to improve ecological conditions, protect the environment, and support sustainable ecosystem development.

scholarly journals Retrieval of Total Water Vapour in the Arctic Using Microwave Humidity Sounders

2017 ◽  
Author(s):  
Raul Cristian Scarlat ◽  
Christian Melsheimer ◽  
Georg Heygster
Keyword(s):  
Water Vapour ◽  
The Arctic ◽  
Measured Signal ◽  
Physical Analysis ◽  
Atmospheric Water ◽  
Satellite Measurements ◽  
Atmospheric Water Vapour ◽  
Microwave Emissivity ◽  
Satellite Microwave ◽  
Microwave Radiometers

Abstract. Quantitative retrievals of atmospheric water vapour in the Arctic are faced with numerous challenges because of the particular climate characteristics of this area. Here, we attempt to build upon the work of Melsheimer and Heygster (2008) to retrieve total atmospheric water vapour (TWV) in the Arctic from satellite microwave radiometers. While the above mentioned algorithm deals primarily with the ice-covered central Arctic, with this work we are aiming to extend the coverage to low ice cover and ice-free areas. By using modeled values for the microwave emissivity of the ice-free sea surface, we develop two sub-algorithms using different sets of channels that deal solely with open ocean areas. This approach allows us to apply the algorithm to regions where previously no data were available and ensures a more consistent physical analysis of the satellite measurements by taking into account the contribution of the surface emissivity to the measured signal.

scholarly journals Estimating Frost during Growing Season and Its Impact on the Velocity of Vegetation Greenup and Withering in Northeast China

2020 ◽  
Vol 12 (9) ◽  
pp. 1355
Author(s):  
Guorong Deng ◽  
Hongyan Zhang ◽  
Lingbin Yang ◽  
Jianjun Zhao ◽  
Xiaoyi Guo ◽  
...  
Keyword(s):  
Global Climate Change ◽  
Northeast China ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Global Climate ◽  
Growing Season ◽  
Vegetation Phenology ◽  
Spatiotemporal Variations ◽  
The Past ◽  
Global Inventory

Vegetation phenology and photosynthetic primary production have changed simultaneously over the past three decades, thus impacting the velocity of vegetation greenup (Vgreenup) and withering (Vwithering). Although climate warming reduces the frequency of frost events, vegetation is exposed more frequently to frost due to the extension of the growing season. Currently, little is known about the effect of frost during the growing season on Vgreenup and Vwithering. This study analyzed spatiotemporal variations in Vgreenup and Vwithering in Northeast China between 1982 to 2015 using Global Inventory Modeling and Mapping Studies Normalized Difference Vegetation Index (GIMMS 3g NDVI) data. Frost days and frost intensity were selected as indicators to investigate the influence of frost during the growing season on Vgreenup and Vwithering, respectively. Increased frost days during the growing season slowed Vgreenup and Vwithering. The number of frost days had a greater impact on Vwithering compared to Vgreenup. In addition, Vgreenup and Vwithering of forests were more vulnerable to frost days, while frost days had a lesser effect on grasslands. In contrast to frost days, frost intensity, which generally decreased during the growing season, accelerated Vgreenup and Vwithering for all land cover types. Changes in frost intensity had less of an impact on forests, whereas the leaf structure of grasslands is relatively simple and thus more vulnerable to frost intensity. The effects of frost during the growing season on Vgreenup and Vwithering in Northeast China were highlighted in this study, and the results provide a useful reference for understanding local vegetation responses to global climate change.

scholarly journals EVALUATION OF MICROWAVE VEGETTION INDEX (MVI) IN MULTI-FREQUENCY AND MULTI-ANGLE

2017 ◽  
Vol XLII-4/W4 ◽  
pp. 259-263
Author(s):  
S. Talebi ◽  
J. Shi ◽  
T. Zhao ◽  
Y. Li ◽  
X. Chuan ◽  
...  
Keyword(s):  
Optical Depth ◽  
Vegetation Index ◽  
Zero Order ◽  
Electromagnetic Spectrum ◽  
Order Model ◽  
Satellite Mission ◽  
Microwave Emissivity ◽  
Scattering Effects ◽  
Scattering Contribution ◽  
Vegetation Study

Microwave portion of the electromagnetic spectrum are effective for observations of vegetation not only to leaf but also woody parts of vegetation. Specifically, microwave emissivity varies strongly with surface roughness, polarization, look–angle and water content. Microwave Vegetation Index (MVI) is one of the microwave indexes that are based on zero-order model. The zero order models applicable when the scattering contribution with in the vegetation is negligible. In this paper MVI in different frequencies (Base on WCOM project) and different angles (Base on SMOS data) are calculated by Matrix Doubling model to take in to account multi-scattering effects within the vegetation. Then because MVI is depends on vegetation information we tried to analysis its behaviour in different densities of corn canopy by comparing to vegetation optical depth. The result shows linear relationship with height correlation between MVI and effective optical depth. So it can be a useful index in vegetation study for future satellite mission as WCOM.

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