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A special issue of Land (ISSN 2073-445X).

Deadline for manuscript submissions: closed (20 February 2023) | Viewed by 18825

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Prof. Dr. Li Wang

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Guest Editor

State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
Interests: land cover and use change (LCLUC); terrestrial carbon cycle; carbon disturbance; socio-ecological consequence of LCLUC
Special Issues, Collections and Topics in MDPI journals

Dr. Wei Song

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Guest Editor

Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Interests: land use change and simulation; ecological effects of land use change; land use policy; rural land consolidation; land use planning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Land change plays an important role in a wide variety of issues, such as biosphere–atmosphere interaction, biodiversity, ecosystem functionality, land surface energy balance, biogeochemical cycles, and sustainable development. Furthermore, land change is shaped by and in turn reflects natural and human forces. With the development of society and the growth of the world population, substantial land change has occurred at local, regional, and global scales. Monitoring land change trends helps us to comprehend change drivers and the interaction between land change and environment, contributing to regional or global change research programs and environment protection policy making. As science and technology rapidly develop, oceans of new data sources and methods come into existence. Various high-quality and open data, such as high special or temporal resolution satellite images and volunteered geographic information, provide more choices for researchers. State-of-the-art methods such as deep learning and Google Earth Engine reduce calculation time and improve accuracy. However, these data sources and methods have not been widely applied in monitoring land change trends, and current analysis and results are not fine, accurate, and timely enough for practical application.

For this Special Issue, our aim is to discuss these two questions: (1) How can we accurately monitor, quantify and simulate trends in land change? (2) How can we find and explain the different drivers of land change?

Papers may address topics including but not limited to:

Mapping land use/cover change;
Monitoring land use transition using remote sensing technology;
Monitoring changes in key land types such as abandoned cropland, rural settlement and wetland;
Land use/cover classification using state-of-the-art methods such as deep learning and Google Earth Engine;
Tracking land use/cover trajectory using remote sensing technology and big data;
Analyzing driving forces of land use/cover change;
Modelling land change;
Assessing environmental and ecological effects of land change.

Prof. Dr. Li Wang
Dr. Wei Song
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Land is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

land use/cover change
land change monitoring
land use transition
land use trajectory
land change mapping
land use/cover classification
Google Earth Engine
land use/cover change modelling
driving forces of land change
ecological effects of land change

Published Papers (9 papers)

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Research

16 pages, 4697 KiB

Open AccessArticle

Revealing the Impact of Protected Areas on Land Cover Volatility in China

by Yajuan Wang, Yongheng Rao and Hongbo Zhu

Land 2022, 11(8), 1361; https://doi.org/10.3390/land11081361 - 21 Aug 2022

Cited by 3 | Viewed by 1520

Abstract

Protected areas are fundamental for maintaining ecosystem functions and have generally been considered to affect land use change. Here, we explored how protected areas affected land cover volatility in China from 2011 to 2020 with LandTrendr using the Google Earth Engine (GEE) platform by comparing the difference in volatility of the Normalized Difference Vegetation Index (NDVI) in protected and unprotected areas. The results show that the regions with frequent land cover volatility are mainly located in eastern, central, and southwestern China, indicating that land cover volatility with high NDVI loss values is spatially aggregated in most cases. Considering the impact of protected areas, land cover volatility is relatively consistent inside and outside the protected area throughout the study period, showing a trend of first fluctuating and then rising. Approximately 22% of detected land cover volatility occurred in protected areas, though the average NDVI loss value (0.56) for protected areas was greater than unprotected areas (0.51). Combined with the outliers, land cover volatility accompanied by larger NDVI loss values is still primarily distributed in unprotected areas in most years. The detection of NDVI gain values in protected areas shows that protected areas (average value is 0.48) are larger than unprotected areas (average value is 0.47) almost every year, even combined with the outliers, and land cover volatility accompanied by larger NDVI gain values is also primarily distributed in protected areas in most years. Elucidating land cover volatility is helpful in understanding land cover changes and how to formulate an effective land use policy. Full article

(This article belongs to the Special Issue Trends in Land Change Monitoring)

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22 pages, 4132 KiB

Open AccessArticle

Construction of a System of Indices for Determining the Contribution of Biodiversity to Human Well-Being in the Sanjiangyuan Area: A Spatiotemporal Distribution Study

by Wenting Chen, Yongcai Wang, Tong Li, Huawei Wan and Yuxuan Chen

Land 2022, 11(8), 1176; https://doi.org/10.3390/land11081176 - 28 Jul 2022

Viewed by 1336

Abstract

The contribution of biodiversity to human well-being is key to exploring the relationships between biodiversity, ecosystem services (ES), and human well-being. In this work, a composite index, termed the human well-being index (HWI), was constructed for evaluating the contribution of biodiversity to human well-being in the Sanjiangyuan area. This index consists of material, ecological regulation, and spiritual and cultural contributions, represented by the material index (MI), the ecological regulation index (ERI), and the spiritual and cultural index (SCI), respectively. The system was further used to evaluate the spatiotemporal distribution of human well-being at the county level in 2000, 2010, and 2020. HWI increased steadily across Sanjiangyuan over the study period, especially in the western and northeastern counties; its center of gravity shifted in the northward direction. The MI increased (decreased) in the west and northeast (southeast); its center of gravity shifted in the northeast direction. All counties showing changes in the ERI were located in the eastern part of Sanjiangyuan. The center of gravity of ERI did not change significantly. The SCI increased steadily across the study area, but was high in the west and low in the east; the center of gravity shifted in the northwest direction. The study findings can contribute toward quantifying biodiversity contributions to human well-being and the formulation of biodiversity conservation policies. Full article

(This article belongs to the Special Issue Trends in Land Change Monitoring)

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18 pages, 37686 KiB

Open AccessArticle

Spatiotemporal Heterogeneity Monitoring of Cropland Evolution and Its Impact on Grain Production Changes in the Southern Sanjiang Plain of Northeast China

by Tao Pan and Ru Zhang

Land 2022, 11(8), 1159; https://doi.org/10.3390/land11081159 - 26 Jul 2022

Viewed by 1134

Abstract

High-speed cropland changes are taking place in Northeast China, bringing about the sustainable changes in ecological landscape and food production; however, the lack of continuous research limits the revelation of new findings in this region. The integrated approach of land migration tracking, ecological landscape and mathematical statistics was established to conduct a comprehensive survey of land change–landscape–food security in a typical grain-planting region of Northeast China to reveal new changes from 1990 to 2020. Results display that the cropland area continued to increase from 25,885.16 km² in 1990 to 31,144.46 km² in 2020, leading to the loss of forest land, grassland, water body and unused land. For cropland structure, the proportion of paddy fields in cropland increased rapidly from 7.18 to 39.53% during 1990–2020; in contrast, upland crops decreased sharply. The richness of landscape presented gradually complex characteristics with SHDI from 0.258 to 0.671 and other ecological indicators underwent similar changes with strong regularity. Total grain production displayed a continuous increase, with values from 523.79 × 10⁴ t to 1839.12 × 10⁴ t, increasing by 2.51 times from 1990 to 2020. We also revealed the contribution rate of unchanged upland crops to grain increments was the largest (i.e., 46.29%), and the conversion of internal cropland structure (i.e., the paddy fields converted from upland crops) contributed 12.17% from 1990 to 2020, showing a positive signal for food security. These new findings provide studies on land use change, ecological landscape and food security in China and abroad. Full article

(This article belongs to the Special Issue Trends in Land Change Monitoring)

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17 pages, 2802 KiB

Open AccessArticle

Spatio-Temporal Patterns of Land-Use Changes and Conflicts between Cropland and Forest in the Mekong River Basin during 1990–2020

by Jiahao Zhai, Chiwei Xiao, Zhiming Feng and Ying Liu

Land 2022, 11(6), 927; https://doi.org/10.3390/land11060927 - 17 Jun 2022

Cited by 10 | Viewed by 2131

Abstract

The Mekong River Basin (MRB) has experienced drastic and extensive land-use and land-cover changes (LULCCs) since the 1990s, including the conflicts between cropland and forest, yet remain quantitatively uninvestigated. With three decades (1990–2020) of land-use products, here we reveal the characteristics of LULCCs and the conflicts between cropland and forest in the MRB and its three sub-basins, i.e., upstream area (UA), midstream area (MA), and downstream area (DA). The four main results are as follows: (1) Since 1990, the dominated features are forest loss and cropland expansion in the MRB and show obvious sub-basin differences. (2) The LULCC was most active before 2000, with a comprehensive dynamic degree of almost 2%. Among them, construction land has the highest single dynamic degree (5%), especially in the DA, reaching 12%. (3) The key features of land-use transfer are the interconversions of forest and cropland, as well as cropland converted into construction land. About 18% (63,940 km²) of forest was reclaimed as cropland, and 17% (45,967 km²) of cropland was returned to forest in the past 31 years. (4) The conflict between cropland and forest was the most dominant LULCC, accounting for 86% of the MRB area. Overall, cropland expansion and forest loss (CEFL) were more dominant in the DA, while cropland fallow and forest restoration (CFFR) had an advantage in the MA. Indeed, CEFL was mainly seen in the plains below a 200 m elevation level, while CFFR tended to occur in the highlands. Our basin-scale study can enrich the existing pan-regional results of LULCCs, and facilitates the understanding of the dynamics and related mechanisms of CFER and CFFR in the tropics. Full article

(This article belongs to the Special Issue Trends in Land Change Monitoring)

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18 pages, 7420 KiB

Open AccessArticle

Evaluation of Ecosystem Service Change Patterns in a Mining-Based City: A Case Study of Wu’an City

by Yuqing Xiong, Hong Li, Meichen Fu, Xiuhua Ma and Lei Wang

Land 2022, 11(6), 895; https://doi.org/10.3390/land11060895 - 12 Jun 2022

Cited by 3 | Viewed by 1629

Abstract

To coordinate the economy and environment in mining cities, it is critical to understand the ecological effects of land use/cover change (LUCC). Therefore, we selected a typical mining city to analyze LUCC-driven ecosystem service changes. In this study, we first used the equivalent factor method to calculate the ecosystem services valuation (ESV) in Wu’an and verified the rationality of the ESV coefficient through the sensitivity index. Secondly, ArcGIS was used to analyze the spatial change of ecosystem service value and explore the reasons for the change. Finally, the spatial autocorrelation index was calculated to analyze the spatial aggregation characteristics of ESV. The results showed that (1) between 2009 and 2018, the total value of ecosystem services decreased by USD 7.41 million, mainly due to the conversion of cropland to construction land. (2) The individual ecosystem services that contributed the most were waste disposal, water conservation, and soil conservation. The pollution caused by the development of mining has reduced the value of the waste disposal function, and the reduction in water body area has been the main factor limiting the water conservation function. (3) The areas with the most significant changes in ecosystem services were concentrated in the east-north direction, where mining resources were widely distributed, and near the central city. Furthermore, there were relatively small losses in the north-west direction, which was related to the protection of ecological resources influenced by topographical factors and less anthropogenic disturbance. (4) The value of ecosystem services and their dynamics exhibited obvious spatial autocorrelation and high-low value (HL) clustering in Wu’an. The high-value and low-value areas dissolved and penetrated each other, and the low-high value (LH) clustering and HL clustering were scattered. The high-value areas were mostly shown in strips, as they were the main locations of water bodies. This study is crucial for mining cities to maintain spatial stability and sustainable development, and the results provide a scientific basis for land use management decision makers to regulate land more precisely. Full article

(This article belongs to the Special Issue Trends in Land Change Monitoring)

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26 pages, 8660 KiB

Open AccessArticle

Evolution and Optimization of Territorial-Space Structure Based on Regional Function Orientation

by Shilei Wang, Yanbo Qu, Weiying Zhao, Mei Guan and Zongli Ping

Land 2022, 11(4), 505; https://doi.org/10.3390/land11040505 - 31 Mar 2022

Cited by 11 | Viewed by 2073

Abstract

In accordance with the ecological civilization strategy, it is necessary to conduct in-depth analyses and provide a systematic elaboration of the characteristics of territorial-space structure (TSS). In the present paper, we examine Shandong Province and construct a framework for the evolution and optimization of TSS based on regional functions. The evolutionary process, pattern, and driving mechanisms of TSS are clarified using a geo-information atlas, the gravity center shift model, spatial autocorrelation analyses, and a geographic detector model. Furthermore, multi-scenario territorial-space simulations are carried out using the CA–Markov model, based on which an optimal pattern of territorial space is constructed. The results show that the comprehensive dynamic degree of territorial space in Shandong Province was valued at 0.56% from 2000 to 2020. Furthermore, six geo-information Tupu of TSS evolution changed, with a total area of 35,485 km², distributed mainly in the Yellow River Delta, the central and southern Shandong Mountain area, and the Jiaodong Peninsula. The migration route of the TSS gravity center curved over time. Territorial spaces are characterized by the exchange of ecological and agricultural space, while urban spaces occupy agricultural ones. The level of economic development, policy, and the institutional environment are driving forces in the transformation of ecological into agricultural spaces, as well as in transforming agricultural space into ecological and urban spaces. The trade-off connection of TSSs is made evident after a multi-scenario simulation of territorial space considering the 2020–2025 timeframe. Based on the goal of regional function co-ordination, Shandong Province is divided into three and four types of single and complex TSS, respectively. The obtained results may provide scientific reference for the co-ordination between human–land relationships and the sustainable use of territorial space, and serve to guide territorial spatial planning. Full article

(This article belongs to the Special Issue Trends in Land Change Monitoring)

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20 pages, 5881 KiB

Open AccessArticle

Continuous Change Detection and Classification—Spectral Trajectory Breakpoint Recognition for Forest Monitoring

by Yangjian Zhang, Li Wang, Quan Zhou, Feng Tang, Bo Zhang, Ni Huang and Biswajit Nath

Land 2022, 11(4), 504; https://doi.org/10.3390/land11040504 - 31 Mar 2022

Cited by 6 | Viewed by 2352

Abstract

Forest is one of the most important surface coverage types. Monitoring its dynamics is of great significance in global ecological environment monitoring and global carbon circulation research. Forest monitoring based on Landsat time-series stacks is a research hotspot, and continuous change detection is a novel approach to real-time change detection. Here, we present an approach, continuous change detection and classification-spectral trajectory breakpoint recognition, running on Google Earth Engine (GEE) for monitoring forest disturbance and forest long-term trends. We used this approach to monitor forest disturbance and the change in forest cover rate from 1987 to 2020 in Nanning City, China. The high-resolution Google Earth images are collected for the validation of forest disturbance. The classification accuracy of forest, non-forest, and water maps by using the optima classification features was 95.16%. For disturbance detection, the accuracy of our map was 86.4%, significantly higher than 60% of the global forest change product. Our approach can successfully generate high-accuracy classification maps at any time and detect the forest disturbance time on a monthly scale, accurately capturing the thinning cycle of plantations, which earlier studies failed to estimate. All the research work is integrated into GEE to promote the use of the approach on a global scale. Full article

(This article belongs to the Special Issue Trends in Land Change Monitoring)

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15 pages, 3530 KiB

Open AccessArticle

Classifying the Nunivak Island Coastline Using the Random Forest Integration of the Sentinel-2 and ICESat-2 Data

by Changda Liu, Jie Li, Qiuhua Tang, Jiawei Qi and Xinghua Zhou

Land 2022, 11(2), 240; https://doi.org/10.3390/land11020240 - 05 Feb 2022

Cited by 7 | Viewed by 1852

Abstract

Shore zone information is essential for coastal habitat assessment, environmental hazard monitoring, and resource conservation. However, traditional coastal zone classification mainly relies on in situ measurements and expert knowledge interpretation, which are costly and inefficient. This study classifies a shore zone area using satellite remote sensing data only and investigates the effect of the statistical indicators from Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) information with the Sentinel-2 data-derived spectral variables on the prediction results. Google Earth Engine was used to synthesize long time-series Sentinel-2 images, and different features were calculated for this synthetic image. Then, statistical indicators reflecting the characteristics of the shore zone profile were extracted from ICESat-2. Finally, a random forest algorithm was used to develop characteristics and shore zone classification. Comparing the results with the data measured shows that the proposed method can effectively classify the shore zone; it has an accuracy of 83.61% and a kappa coefficient of 0.81. Full article

(This article belongs to the Special Issue Trends in Land Change Monitoring)

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17 pages, 1285 KiB

Open AccessArticle

Decoupling Analysis between Rural Population Change and Rural Construction Land Changes in China

by Xueru Zhang, Jie Wang, Wei Song, Fengfei Wang, Xing Gao, Lei Liu, Kun Dong and Dazhi Yang

Land 2022, 11(2), 231; https://doi.org/10.3390/land11020231 - 04 Feb 2022

Cited by 15 | Viewed by 2105

Abstract

Developing countries account for about 86.5% of the world’s population and are experiencing rapid urbanization. Globally, the increase in the urban population is generally accompanied by the expansion of the latter and construction lands, as well as the reduction in the rural population and rural construction lands. However, with the rapid development of urbanization in China, the rural population has decreased, while the proportion of rural construction lands has increased, resulting in a significant waste of land resources. In order to quantitatively characterize the degree of deviation between the permanent rural population and rural construction lands based on the 2009–2016 demographic data and land survey data in China, we comprehensively used the decoupling model and the coordination degree model to analyze the temporal change characteristics, spatial distribution law, and the degree of deviation of rural construction land areas and the number of rural permanent residents. Firstly, according to the decoupling model, the type of decoupling between the area of rural construction lands and the number of rural permanent residents at the national scale was strongly negative. Secondly, according to the coordination degree model, the coordination type between rural construction land areas and the rural resident population was uncoordinated; at the provincial scale, the coordination system involved one city and one district (Beijing and the Tibet Autonomous Region) and the basic coordination of two cities (Tianjin and Shanghai). Xinjiang and Qinghai belonged to the reconcilable type, and the other 25 provinces belonged to the uncoordinated type. Finally, according to the comprehensive measurement model, the number of rural permanent residents and rural construction lands showed two types of decoupling: highly strong negative decoupling incoordination and moderately and weakly strong negative decoupling incoordination. Full article

(This article belongs to the Special Issue Trends in Land Change Monitoring)

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