Research on the Strategy for Improving Cultivated Land Quality in China

2018 ◽  
Vol 20 (5) ◽  
pp. 16 ◽  
Author(s):  
Hongqi Zhang ◽  
Minghong Tan ◽  
Xiangbin Kong ◽  
Yongmei Xu ◽  
Erqi Xu ◽  
...  
Keyword(s):  
Cultivated Land ◽  
Land Quality

Study on evaluation of regional cultivated land quality based on resource-asset-capital attributes and its spatial mechanism

2020 ◽  
Vol 125 ◽  
pp. 102284 ◽  
Author(s):  
Yunyang Shi ◽  
Wenkai Duan ◽  
Luuk Fleskens ◽  
Mu Li ◽  
Jinmin Hao
Keyword(s):  
Cultivated Land ◽  
Land Quality ◽  
Spatial Mechanism

scholarly journals The Optimal Image Date Selection for Evaluating Cultivated Land Quality Based on Gaofen-1 Images

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4937 ◽  
Author(s):  
Ziqing Xia ◽  
Yiping Peng ◽  
Shanshan Liu ◽  
Zhenhua Liu ◽  
Guangxing Wang ◽  
...  
Keyword(s):  
Regression Models ◽  
Vegetation Index ◽  
Southern China ◽  
Regional Scale ◽  
Growth Stages ◽  
Maturity Stage ◽  
Cultivated Land ◽  
Flowering Stage ◽  
Area Index ◽  
Land Quality

This study proposes a method for determining the optimal image date to improve the evaluation of cultivated land quality (CLQ). Five vegetation indices: leaf area index (LAI), difference vegetation index (DVI), enhanced vegetation index (EVI), normalized difference vegetation index (NDVI), and ratio vegetation index (RVI) are first retrieved using the PROSAIL model and Gaofen-1 (GF-1) images. The indices are then introduced into four regression models at different growth stages for assessing CLQ. The optimal image date of CLQ evaluation is finally determined according to the root mean square error (RMSE). This method is tested and validated in a rice growth area of Southern China based on 115 sample plots and five GF-1 images acquired at the tillering, jointing, booting, heading to flowering, and milk ripe and maturity stage of rice in 2015, respectively. The results show that the RMSEs between the measured and estimated CLQ from four vegetation index-based regression models at the heading to flowering stage are smaller than those at the other growth stages, indicating that the image date corresponding with the heading to flowering stage is optimal for CLQ evaluation. Compared with other vegetation index-based models, the LAI-based logarithm model provides the most accurate estimates of CLQ. The optimal model is also driven using the GF-1 image at the heading to flowering stage to map CLQ of the study area, leading to a relative RMSE of 14.09% at the regional scale. This further implies that the heading to flowering stage is the optimal image time for evaluating CLQ. This study is the first effort to provide an applicable method of selecting the optimal image date to improve the estimation of CLQ and thus advanced the literature in this field.

A new grading system for evaluating China's cultivated land quality

2020 ◽  
Vol 31 (12) ◽  
pp. 1482-1501
Author(s):  
Liming Liu ◽  
De Zhou ◽  
Xiao Chang ◽  
Zhulu Lin
Keyword(s):  
Grading System ◽  
Cultivated Land ◽  
Land Quality

scholarly journals GIS and RS based Assessment of Cultivated Land Quality of Shandong Province

2012 ◽  
Vol 12 ◽  
pp. 823-830 ◽  
Author(s):  
Zhen Wang ◽  
Liming Wang ◽  
Ruina Xu ◽  
Haitao Huang ◽  
Fang Wu
Keyword(s):  
Shandong Province ◽  
Cultivated Land ◽  
Land Quality ◽  
Gis And Rs
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