scholarly journals Comparison of the Normalized Difference Vegetation Index (NDVI) Between the Sensors OLI-Landsat Satellite-8 and MSI-Sentinel-2 Satellite in Semi-Arid Region

2018 ◽  
Vol 41 (3) ◽  
pp. 167-177
Author(s):  
U. A. BEZERRA ◽  
L. M. M. OLIVEIRA ◽  
A. L. B. CANDEIAS ◽  
B. B. SILVA ◽  
A. C. L. S. LEITE ◽  
...  
Keyword(s):  
Arid Region ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Semi Arid Region ◽  
Landsat Satellite ◽  
Semi Arid ◽  
Sentinel 2

scholarly journals Soil Moisture and Irrigation Mapping in A Semi-Arid Region, Based on the Synergetic Use of Sentinel-1 and Sentinel-2 Data

2018 ◽  
Vol 10 (12) ◽  
pp. 1953 ◽  
Author(s):  
Safa Bousbih ◽  
Mehrez Zribi ◽  
Mohammad El Hajj ◽  
Nicolas Baghdadi ◽  
Zohra Lili-Chabaane ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Arid Region ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Cloud Model ◽  
Remotely Sensed Data ◽  
Semi Arid Region ◽  
Semi Arid ◽  
Sentinel 2 ◽  
Reference Fields

This paper presents a technique for the mapping of soil moisture and irrigation, at the scale of agricultural fields, based on the synergistic interpretation of multi-temporal optical and Synthetic Aperture Radar (SAR) data (Sentinel-2 and Sentinel-1). The Kairouan plain, a semi-arid region in central Tunisia (North Africa), was selected as a test area for this study. Firstly, an algorithm for the direct inversion of the Water Cloud Model (WCM) was developed for the spatialization of the soil water content between 2015 and 2017. The soil moisture retrieved from these observations was first validated using ground measurements, recorded over 20 reference fields of cereal crops. A second method, based on the use of neural networks, was also used to confirm the initial validation. The results reported here show that the soil moisture products retrieved from remotely sensed data are accurate, with a Root Mean Square Error (RMSE) of less than 5% between the two moisture products. In addition, the analysis of soil moisture and Normalized Difference Vegetation Index (NDVI) products over cultivated fields, as a function of time, led to the classification of irrigated and rainfed areas on the Kairouan plain, and to the production of irrigation maps at the scale of individual fields. This classification is based on a decision tree approach, using a combination of various statistical indices of soil moisture and NDVI time series. The resulting irrigation maps were validated using reference fields within the study site. The best results were obtained with classifications based on soil moisture indices only, with an accuracy of 77%.

Use of MSI/Sentinel-2 and airborne LiDAR data for mapping vegetation and studying the relationships with soil attributes in the Brazilian semi-arid region

2018 ◽  
Vol 73 ◽  
pp. 179-190 ◽  
Author(s):  
Hilton Luís Ferraz da Silveira ◽  
Lênio Soares Galvão ◽  
Ieda Del’Arco Sanches ◽  
Iedo Bezerra de Sá ◽  
Tatiana Ayako Taura
Keyword(s):  
Arid Region ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Soil Attributes ◽  
Semi Arid Region ◽  
Airborne Lidar Data ◽  
Semi Arid ◽  
Sentinel 2

scholarly journals Drivers and Environmental Impacts of Vegetation Greening in a Semi-Arid Region of Northwest China since 2000

2021 ◽  
Vol 13 (21) ◽  
pp. 4246
Author(s):  
Zhenzong Wu ◽  
Jian Bi ◽  
Yifei Gao
Keyword(s):  
Arid Region ◽  
Vegetation Index ◽  
Climatic Factors ◽  
Agricultural Practices ◽  
Northwest China ◽  
Terrestrial Vegetation ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Semi Arid Region ◽  
Semi Arid ◽  
Dynamics Of Vegetation

The dynamics of terrestrial vegetation have changed a lot due to climate change and direct human interference. Monitoring these changes and understanding the mechanisms driving them are important for better understanding and projecting the Earth system. Here, we assessed the dynamics of vegetation in a semi-arid region of Northwest China for the years from 2000 to 2019 through satellite remote sensing using Vegetation Index (VI) data from the Moderate Resolution Imaging Spectroradiometer (MODIS), and analyzed the interannual covariation between vegetation and three climatic factors—air temperature, precipitation, and vapor pressure deficit (VPD)—at nine meteorological stations. The main findings of this research are: (1) herbaceous land greened up much more than forests (2.85%/year vs. 1.26%/year) in this semi-arid region; (2) the magnitudes of green-up for croplands and grasslands were very similar, suggesting that agricultural practices, such as fertilization and irrigation, might have contributed little to vegetation green-up in this semi-arid region; and (3) the interannual dynamics of vegetation at high altitudes in this region correlate little with temperature, precipitation, or VPD, suggesting that factors other than temperature and moisture control the interannual vegetation dynamics there.

scholarly journals Assessment of rice growth conditions in a semi-arid region of India using the Generalized Radar Vegetation Index derived from RADARSAT-2 polarimetric SAR data

2020 ◽  
Vol 237 ◽  
pp. 111561 ◽  
Author(s):  
Dipankar Mandal ◽  
Vineet Kumar ◽  
Debanshu Ratha ◽  
Juan M. Lopez-Sanchez ◽  
Avik Bhattacharya ◽  
...  
Keyword(s):  
Arid Region ◽  
Vegetation Index ◽  
Growth Conditions ◽  
Polarimetric Sar ◽  
Rice Growth ◽  
Sar Data ◽  
Semi Arid Region ◽  
Semi Arid
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