scholarly journals Mapping Ratoon Rice Planting Area in Central China Using Sentinel-2 Time Stacks and the Phenology-Based Algorithm

2020 ◽  
Vol 12 (20) ◽  
pp. 3400
Author(s):  
Shishi Liu ◽  
Yuren Chen ◽  
Yintao Ma ◽  
Xiaoxuan Kong ◽  
Xinyu Zhang ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Cropping Systems ◽  
Hubei Province ◽  
Paddy Rice ◽  
Rice Fields ◽  
Central China ◽  
Yellowness Index ◽  
Productivity Cost ◽  
Rice Cropping Systems ◽  
Sentinel 2

Mapping rice cropping systems is important for grain yield prediction and food security assessments. Both single- and double-season rice are the dominant rice systems in central China. However, because of increasing labor shortages and high costs, there has been a gradual decline in double-season rice. Ratoon rice (RR) has been proposed as an alternative system that balances the productivity, cost, and labor requirements of rice cultivation. RR has been expanding in central China, encouraged by the improved cultivars, machinery, and favorable policies. However, to our knowledge, the distribution of RR has not been mapped with remote sensing techniques. This study developed a phenology-based algorithm to map RR at a 10 m resolution in Hubei Province, Central China, using dense time stacks of Sentinel-2 images (cloud cover <80%) in 2018. The key in differentiating RR from the other rice cropping systems is through the timing of maturity. We proposed to use two contrast vegetation indices to identify RR fields. The newly-developed yellowness index (YI) calculated with the reflectance of blue, green, and red bands was used to detect the ripening phase, and the enhanced vegetation index (EVI) was used to detect the green-up of the second-season crop to eliminate the misclassification caused by stubbles left in the field. The RR map demonstrated that RR was mainly distributed in the low alluvial plains of central and southern Hubei Province. The total planting area of RR in 2018 was 2225.4 km2, accounting for 10.03% of the total area of paddy rice fields. The overall accuracy of RR, non-RR rice fields, and non-rice land cover types was 0.76. The adjusted overall accuracy for RR and non-RR was 0.91, indicating that the proposed YI and the phenology-based algorithm could accurately identify RR fields from the paddy rice fields.

scholarly journals Cloud Cover throughout All the Paddy Rice Fields in Guangdong, China: Impacts on Sentinel 2 MSI and Landsat 8 OLI Optical Observations

2021 ◽  
Vol 13 (15) ◽  
pp. 2961
Author(s):  
Rui Jiang ◽  
Arturo Sanchez-Azofeifa ◽  
Kati Laakso ◽  
Yan Xu ◽  
Zhiyan Zhou ◽  
...  
Keyword(s):  
Cloud Cover ◽  
Southern China ◽  
Vegetation Indices ◽  
Paddy Rice ◽  
Rice Fields ◽  
Optical Observations ◽  
Landsat 8 ◽  
Monthly Basis ◽  
Satellite Sensors ◽  
Sentinel 2

Cloud cover hinders the effective use of vegetation indices from optical satellite-acquired imagery in cloudy agricultural production areas, such as Guangdong, a subtropical province in southern China which supports two-season rice production. The number of cloud-free observations for the earth-orbiting optical satellite sensors must be determined to verify how much their observations are affected by clouds. This study determines the quantified wide-ranging impact of clouds on optical satellite observations by mapping the annual total observations (ATOs), annual cloud-free observations (ACFOs), monthly cloud-free observations (MCFOs) maps, and acquisition probability (AP) of ACFOs for the Sentinel 2 (2017–2019) and Landsat 8 (2014–2019) for all the paddy rice fields in Guangdong province (APRFG), China. The ATOs of Landsat 8 showed relatively stable observations compared to the Sentinel 2, and the per-field ACFOs of Sentinel 2 and Landsat 8 were unevenly distributed. The MCFOs varied on a monthly basis, but in general, the MCFOs were greater between August and December than between January and July. Additionally, the AP of usable ACFOs with 52.1% (Landsat 8) and 47.7% (Sentinel 2) indicated that these two satellite sensors provided markedly restricted observation capability for rice in the study area. Our findings are particularly important and useful in the tropics and subtropics, and the analysis has described cloud cover frequency and pervasiveness throughout different portions of the rice growing season, providing insight into how rice monitoring activities by using Sentinel 2 and Landsat 8 imagery in Guangdong would be impacted by cloud cover.

Supporting operational site‐specific fertilization in rice cropping systems with infield smartphone measurements and Sentinel-2 observations

2021 ◽  
Author(s):  
Francesco Nutini ◽  
Roberto Confalonieri ◽  
Livia Paleari ◽  
Monica Pepe ◽  
Laura Criscuolo ◽  
...  
Keyword(s):  
Cropping Systems ◽  
Site Specific ◽  
Rice Cropping Systems ◽  
Sentinel 2

scholarly journals Parametric Definition of Slow Tourism Itineraries for Experiencing Seasonal Landscapes. Application of Sentinel-2 Imagery to the Rural Paddy-Rice Landscape in Northern Italy

2021 ◽  
Vol 13 (23) ◽  
pp. 13155
Author(s):  
Alessandro Scandiffio
Keyword(s):  
Agricultural Landscape ◽  
Paddy Rice ◽  
Rice Fields ◽  
Landscape Changes ◽  
Tourist Destinations ◽  
Tourism Sector ◽  
Major Interest ◽  
Local Roads ◽  
Definition Of ◽  
Sentinel 2

Slow tourism is a growing phenomenon in Italy; it is assuming a key role in the definition of new strategies for sustainable tourism for the enhancement of landscape and cultural heritage, but also as a driver for the revitalization of marginalized and inner areas of the country. In this framework, the aesthetical phenomena related to seasonal landscape changes (e.g., autumn coloring foliage, spring blooming, controlled paddy-rice fields flooding) that occur in specific environments are emerging as new tourist destinations and are of major interest for the experiential tourism sector. This research shows a GIS-based method to draw up parametric slow tourism itineraries, which are defined according to seasonal landscape changes, by exploiting the high frequency of Sentinel-2 data acquisition. The algorithm defines parametric itineraries within the network of existing local roads by detecting the current landscape conditions through NDVI. The algorithm has been tested in the study area, within the historical agricultural landscape of paddy-rice fields in between Turin and Milan, where high scenic conditions related to the flooding occur over the spring season. This tool can support a range of end users’ decisions for the creation of a widespread tourist destination offer year-round, with the aim to promote more sustainable and balanced use of the places and reduce overpressures in the most frequented places.

scholarly journals Decreasing Rice Cropping Intensity in Southern China from 1990 to 2015

2018 ◽  
Vol 11 (1) ◽  
pp. 35 ◽  
Author(s):  
Min Jiang ◽  
Liangjie Xin ◽  
Xiubin Li ◽  
Minghong Tan ◽  
Renjing Wang
Keyword(s):  
Food Security ◽  
High Resolution ◽  
Greenhouse Gas ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Southern China ◽  
Cropping Systems ◽  
Data Availability ◽  
Rice Cropping Systems ◽  
Sown Area

Assessing changes in rice cropping systems is essential for ensuring food security, greenhouse gas emissions, and sustainable water management. However, due to the insufficient availability of images with moderate to high spatial resolution, caused by frequent cloud cover and coarse temporal resolution, high-resolution maps of rice cropping systems at a large scale are relatively limited, especially in tropical and subtropical regions. This study combined the difference of Normalized Difference Vegetation Index (dNDVI) method and the Normalized Difference Vegetation Index (NDVI) threshold method to monitor changes in rice cropping systems of Southern China using Landsat images, based on the phenological differences between different rice cropping systems. From 1990–2015, the sown area of double cropping rice (DCR) in Southern China decreased by 61054.5 km2, the sown area of single cropping rice (SCR) increased by 20,110.7 km2, the index of multiple cropping decreased from 148.3% to 129.3%, and the proportion of DCR decreased by 20%. The rice cropping systems in Southern China showed a “double rice shrinking and single rice expanding” change pattern from north to south, and the most dramatic changes occurred in the Middle-Lower Yangtze Plain. This study provided an efficient strategy that can be applied to moderate to high resolution images with deficient data availability, and the resulting maps can be used as data support to adjust agricultural structures, formulate food security strategies, and compile a greenhouse gas emission inventory.

scholarly journals Nitrogen fertilizer fate after introducing maize and upland-rice into continuous paddy rice cropping systems

2018 ◽  
Vol 258 ◽  
pp. 162-171 ◽  
Author(s):  
Irabella Fuhrmann ◽  
Yao He ◽  
Eva Lehndorff ◽  
Nicolas Brüggemann ◽  
Wulf Amelung ◽  
...  
Keyword(s):  
Nitrogen Fertilizer ◽  
Upland Rice ◽  
Cropping Systems ◽  
Paddy Rice ◽  
Rice Cropping Systems
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