Spatiotemporal variations in the eco-health condition of China's long-term stable cultivated land using Google Earth Engine from 2001 to 2019

Li, Guangyu; He, Tingting; Zhang, Maoxin; Wu, Cifang

doi:10.1016/j.apgeog.2022.102819

Cited by 12 publications

(4 citation statements)

References 73 publications

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“…(5) The priority promotion region is characterized by excessive fragmentation of cultivated land, low usage efficiency of cultivated land, and poor cultivated land system health. The division needs to innovate the mode of cultivated land production and management and change the mode of agricultural development, strengthen the restraint of the "red line" of cultivated land, reduce the impact of urbanization and industrialization on the ecological regulation and landscape carrying capacity of cultivated land, strengthen the monitoring of the health level of the cultivated land system, and combine the soil improvement project with the comprehensive treatment project to build a healthy and reasonable field road network system and realize the efficient and sustainable utilization of cultivated land resources [85].…”

Section: Policy Enlightenmentmentioning

confidence: 99%

Spatiotemporal Changes of Cultivated Land System Health Based on PSR-VOR Model—A Case Study of the Two Lake Plains, China

Liu

2023

IJERPH

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Cultivated land resources are the material basis of sustainable agricultural development. Climate change, food security, land pollution, and other issues highlight the value of sustainable agricultural development, and the health of the cultivated land system has attracted much attention. By constructing “PSR-VOR” cultivated land system health evaluation framework under the 5 km grid scale and using GIS spatial analysis and mathematical statistics to comprehensively evaluate the health status of the cultivated land system in the two lake plains from 2000 to 2019. The major results have shown that: (1) Over the past 20 years, both the highest and average values of the health index of the cultivated land system have gone down, and the health status of the cultivated land system has changed and gotten worse over time. (2) The health status in the two lake plains has been generally good, mainly in Class I and Class II areas. However, the area of cultivated land with general and poor health status has increased rapidly. On the whole, the health level presents the characteristic of gradually decreasing from the northeast to the southwest and southeast. (3) During the study period, the global Moran’s I value of the cultivated land system health index in the two lake plains increased from 0.686 to 0.729, with significant spatial positive autocorrelation, and the spatial heterogeneity of the cultivated land system health index gradually increased. As shown by the spatial distribution characteristics of high in the north, low in the south, and decreasing from the middle to the outside, the distribution of the high-value cluster area and the low-value cluster area of the cultivated land system health index in the two lake plains has not changed significantly over the past 20 years. (4) The two lake plains are divided into five areas: a moderate optimization area, a collaborative optimization area, a potential improvement area, a key improvement area, and a priority improvement area. The urgency of regulating the health status from the moderate optimization area to the priority improvement area has gradually increased, and the differentiated utilization and management of cultivated land resources need to be carried out according to local conditions.

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Section: Policy Enlightenmentmentioning

confidence: 99%

Spatiotemporal Changes of Cultivated Land System Health Based on PSR-VOR Model—A Case Study of the Two Lake Plains, China

Liu

2023

IJERPH

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“…ALP research began with the FAO land productive potential model (Tian et al, 2014). Existing methods include crop yield estimating models and production potential models derived from remote sensing data (Li et al, 2022; Li, Wang, et al, 2023). However, these models are only suitable for local estimation rather than large‐area evaluation, due to the lack of a comparable standard across vast areas with varied differences (Ye et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Arable land in Northwest China: Dynamics analysis of health and productivity in 2000–2020

Shuchen,

Yimin,

Pingda

et al. 2024

Land Degrad Dev

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Arable land health (ALH) and arable land productivity (ALP) are crucial indicators of agricultural ecological functionality and sustainability. The shift of grain‐producing regions in Northwest China has led to arable land degradation, which endangers both food production and sustainable development. Several studies have focused on arable land quantity, distribution, and regional features, but ALH and sustainable ALP have received little attention. For the first time, we investigated the spatio‐temporal distribution and coupling connection between ALH and ALP in Northwest China (NC) using soil health indicators. Our study revealed the following key findings: (1) A minimal dataset of 12 indicators can efficiently replace the total dataset to evaluate the arable land health index in NC. (2) Over the last 20 years, the high and sub‐high grades of ALH increased by 536.8% and 222.6%, respectively, with a shift toward the northwest. During the specified period, ALH with low health and underutilized grade decreased by 46.01% and 69.4%, respectively, primarily in Xinjiang and Inner Mongolia. At the county level, ALP increased by 26%, primarily in northern Xinjiang and southern Gansu. 71% of counties remained stable, while only 3% experienced a decline. (4) The relationship between ALH and ALP were divided into six coupled groups that form an inverted “U” shape. High‐production areas were generally strongly linked, while low‐production areas were weakly coupled. Over the last 20 years, NC has seen significant improvements in ALH, coinciding with an increase in ALP. However, in most cases, the relationship between ALH and ALP were negative or weak.

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“…Xu et al [22] improved the skip connection in UNet and its loss function (HRUNet) to preserve details, especially the edge details of cropland. Li et al [23] designed a compact graph convolutional neural network (GCNN) for Sentinel-2 time series multi-band optical data to acquire high-resolution cropland maps from low-resolution data sources while greatly reducing the number of model parameters. To conclude, when conducting ground object segmentation with deep learning methods, the similar features exhibited by different ground objects pose a huge challenge to the feature learning ability of deep learning networks, leading to issues such as insufficient segmentation accuracy and missing details.…”

Section: Introductionmentioning

confidence: 99%

Cropland Data Extraction in Mekong Delta Based on Time Series Sentinel-1 Dual-Polarized Data

et al. 2023

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In recent years, synthetic aperture radar (SAR) has been a widely used data source in the remote sensing field due to its ability to work all day and in all weather conditions. Among SAR satellites, Sentinel-1 is frequently used to monitor large-scale ground objects. The Mekong Delta is a major agricultural region in Southeast Asia, so monitoring its cropland is of great importance. However, it is a challenge to distinguish cropland from other ground objects, such as aquaculture and wetland, in this region. To address this problem, the study proposes a statistical feature combination from the Sentinel-1 dual-polarimetric (dual-pol) data time series based on the m/χ decomposition method. Then the feature combination is put into the proposed Omni-dimensional Dynamic Convolution Residual Segmentation Model (ODCRS Model) of high fitting speed and classification accuracy to realize the cropland extraction of the Mekong Delta region. Experiments show that the ODCRS model achieves an overall accuracy of 93.85%, a MIoU of 88.04%, and a MPA of 93.70%. The extraction results show that our method can effectively distinguish cropland from aquaculture areas and wetlands.

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Spatiotemporal variations in the eco-health condition of China's long-term stable cultivated land using Google Earth Engine from 2001 to 2019

Cited by 12 publications

References 73 publications

Spatiotemporal Changes of Cultivated Land System Health Based on PSR-VOR Model—A Case Study of the Two Lake Plains, China

Spatiotemporal Changes of Cultivated Land System Health Based on PSR-VOR Model—A Case Study of the Two Lake Plains, China

Arable land in Northwest China: Dynamics analysis of health and productivity in 2000–2020

Cropland Data Extraction in Mekong Delta Based on Time Series Sentinel-1 Dual-Polarized Data

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