ABSTRACT
Cropland abandonment is a widespread land-change process globally, which can stem from the accelerated outmigration of the population from rural to urban areas, socio-economic and political changes, catastrophes, and other trigger events. Clouds limit the utility of optical satellite data to monitor cropland abandonment in highly fragmented mountain agricultural landscapes of tropical and subtropical regions, including the south of China. Taking Nanjing County of China as an example, we developed a novel approach by utilizing multisource satellite (Landsat and Sentinel-2) imagery to map multiple trajectories of cropland abandonment (transitioning from cropland to grassland, shrubs and forest) in subtropical mountainous landscapes. Then, we employed a redundancy analysis (RDA) to identify the spatial association of cropland abandonment considering agricultural productivity, physiography, locational characteristics and economic factors. Results indicate the great suitability of harmonized Landsat 8 and Sentinel-2 images to distinguish multiple trajectories of cropland abandonment in subtropical mountainous areas. Our framework of mapping cropland abandonment resulted in good producer's (78.2%) and user's (81.3%) accuracies. The statistical analysis showed 31.85% of croplands cultivated in 2000 were abandoned by 2018, and more than a quarter of townships experienced cropland abandonment with high abandoned rates (>38%). Cropland abandonment mainly occurred in relatively unfavorable areas for agricultural production, for instance with a slope above 6°. Slope and the proximity to the nearest settlement explained 65.4% and 8.1% of the variation of cropland abandonment at the township level, respectively. The developed approaches on both mapping cropland abandonment and modeling determinants can be highly relevant to monitor multiple trajectories of cropland abandonment and ascribe their determinants not only in mountainous China but also elsewhere and thus promote the formulation of land-use policies that aim to steer cropland abandonment.
Subject(s)
Agriculture , Forests , Humans , Agriculture/methods , China , Rural Population , Crops, AgriculturalABSTRACT
Understanding the relationships among multiple land use functions (LUFs) is crucial for land-based spatial planning that can guide targeted land use policy-making in complex socio-ecological systems. However, few studies concerned the interactions among various LUFs integrating the issues of economy, environment, and society at a fine scale. In this study, we quantified 12 LUFs using a geospatial model and statistical analysis at the grid scale in Jiangsu Province. Then, we identified the relationships among three primary LUFs-agricultural production function (APF), urban-rural living function (ULF), and ecological maintenance function (EMF)-and further explored the determinants of LUF trade-offs aimed to provide a reference for policy-makers to make decisions in future land use planning and management. The results revealed that the high trade-off areas for APF and ULF are mainly distributed in central and northern Jiangsu, and the trade-offs for both APF-EMF and ULF-EMF were higher in the area covered with water and forest. The determinants of LUF trade-offs mainly refers to land use/land cover, potential evapotranspiration, and vegetation coverage ratio. Moreover, landscape configuration metrics and distance to the nearest county and nearest road also have remarkable impacts on the trade-offs of APF-EMF and ULF-EMF. Finally, we proposed that the concepts of LUF trade-offs should be incorporated into the processes of delineating boundaries for urban growth, farmland, and natural areas. We also propose that land consolidation projects should be implemented in an orderly manner to alleviate LUF trade-offs.
ABSTRACT
Land consolidation (LC) is an innovative way to improve agricultural production. Spatiotemporal pattern of agricultural production in land consolidation area (LCA) is difficult to quantify with limited field observations and survey data. Satellite data has advantages on recording vegetation status changes frequently, which is very supportive of estimating variation of agricultural production. In this paper, we used Net Primary Productivity (NPP), Normal Difference Vegetation Index (NDVI), and Multiple Band Drought Index (MBDI) from satellite data, to examine five attributes (irrigation capacity, multiple cropping index, crop phenology, farmland productivity, and production stability) of agricultural production after land consolidation (LC) at a site in China. Results show that there were no significant spatial differences in irrigation capacity for farmland in few years after LC due to consistent climatic conditions and uniform irrigation and drainage system. Multiple cropping index shows a pattern of "first reducing, then growing, last reducing", which may result from the disturbed "water-soil" environment and weak farmers' intention. Interannual variation of spatial distribution of phenology for the second-season crop is larger than that for the first-season crop since LC implementation adjusts short-term land use and management. With the improvement of production conditions and balanced distribution of production elements, farmland productivity has been improved and its differences among various farmland patches imply a reducing trend. Production in LCA is slightly less stable than that in the control area (TCA) where LC is not carried out because of limited and short-term effect from LC. We concluded that satellite data presents variation of agricultural production in LCA from different dimensions of time, space and attributes. Multidimensional variation of agricultural production is decided by several factors, including climate condition, LC activity, and farmers' intention.
