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Geographical conditions monitoring (GCM) has elicited significant concerns from the Chinese Government and is closely related to the “Digital China” program. This research aims to focus on object-based change detection (OBCD) methods integrating very-high-resolution (VHR) imagery and vector data for GCM.

The main content of this paper is as follows: a multi-resolution segmentation (MRS) algorithm is proposed for obtaining homogeneous and contiguous image objects in two phases; a post-classification comparison (PCC) method based on the nearest neighbor algorithm and an image-object analysis (IOA) technique based on a differential entropy algorithm are used to improve the accuracy of the change detection; and a vector object-based accuracy assessment method is proposed.

Results show that image objects obtained using the MRS algorithm attain the objectives of the “same spectrum within classes” and “different spectrum among classes”. Moreover, the two OBCD methods can detect over 85 per cent of the changed regions. The PCC strategy can obtain the categories of image objects with a high degree of precision. The IOA technique is easy to use and largely automated.

On the basis of the VHR satellite imagery and vector data, the above methods can effectively and accurately provide technical support for GCM implementation.

The purpose of this paper is to analyze the characteristics of spatio-temporal dynamics and the evolution of land use change is essential for understanding and assessing the status and transition of ecosystems. Such analysis, when applied to Horqin sandy land, can also provide basic information for appropriate decision-making.

By integrating long time series Landsat imageries and geographic information system (GIS) technology, this paper explored the spatio-temporal dynamics and evolution-induced land use change of the largest sandy land in China from 1983 to 2016. Accurate and consistent land use information and land use change information was first extracted by using the maximum likelihood classifier and the post-classification change detection method, respectively. The spatio-temporal dynamics and evolution were then analyzed using three kinds of index models: the dynamic degree model to analyze the change of regional land resources, the dynamic change transfer matrix and flow direction rate to analyze the change direction, and the barycenter transfer model to analyze the spatial pattern of land use change.

The results indicated that land use in Horqin sandy land during the study period changed dramatically. Vegetation and sandy land showed fluctuating changes, cropland and construction land steadily increased, water body decreased continuously, and the spatial distribution patterns of land use were generally unbalanced. Vegetation, sandy land and cropland were transferred frequently. The amount of vegetation loss was the largest. Water body loss was 473.6 km², which accounted for 41.7 per cent of the total water body. The loss amount of construction land was only 1.0 km². Considerable differences were noted in the rate of gravity center migration among the land use types in different periods, and the overall rate of construction land migration was the smallest. Moreover, the gravity center migration rates of the water body and sandy land were relatively high and were related to the fragile ecological environment of Horqin sandy land.

The results not only confirmed the applicability and effectiveness of the combined method of remote sensing and GIS technology but also revealed notable spatio-temporal dynamics and evolution-induced land use change throughout the different time periods (1983-1990, 1990-2000, 2000-2010, 2010-2014, 2014-2016 and 1983-2016).

The purpose of this paper is to examine the factors that lead to the controversy within the existing empirical literature on the relationship between land tenure and agricultural investments in China.

This study conducts a meta-regression analysis (MRA) based on 265 samples from 29 selected studies. These studies are collected from different regions and populations; therefore, this study utilizes a random-effects meta-regression model to control between-study heterogeneity.

The empirical results show that the variable “land-related long-term investments” significantly affects the relationship between land tenure and agricultural investments. The variables: “ration land,” “land titling” and “land transfer rights” all have significant effects on this relationship, but at different levels. The study area (e.g. “western China,” “central/inland China,” “two regions contained”), “plot level,” “panel data,” “sample size,” “considered endogeneity” and “off-farm employment” variables all significantly influence the relationship. Additionally, the results show that the relationship is significantly affected by the survey time.

Policymakers should treat the existing research conclusions with caution and pay more attention to defining land tenure. The relationship between land tenure and agricultural investments also depends on regional resource availability. Therefore, land property rights policies should be region-specific in order to successfully encourage agricultural investments.

In this study, the author collectively examines existing empirical studies to investigate whether their inconsistent results are affected by research characteristics. To the author’s knowledge, this is the first study that analyzes land tenure and agricultural investments in China using MRA. Future research should refine the definition of land tenure, the selection of agricultural investment types, the research method and the method of data collection.