Land Use Change Processes Research Articles

Analisis Perubahan Penggunaan Lahan Sekitar Danau Limboto Di Kabupaten Gorontalo

Limboto Lake in Gorontalo Province has been around since 1932 with an area of ± 7,000 Ha. In 1991 the area of the lake shrank to ± 3,644.5 Ha and in 2017 the area of the lake again declined to ± 2,693.9 Ha. The purpose of this research was to identify the type of change in lake land use into non-lake land and the process of changing land use around Limboto Lake. The method used is an overlay analysis of regional Landsat imagery maps around Lake Limboto using the Geographic Information System (GIS) and then described descriptively qualitatively to explain the types and processes of land use change around Limboto Lake from 1991 to 2017. Methods of data collection are secondary data studies related maps of Landsat area images around Limboto Lake in 1991, 2001, 2015, and 2017 and also field observations and interviews to clarify changes in land use that occurred around Limboto Lake from 1991 - 2017. The results of this research indicate that within 26 years (1991 - 2017), there has been a change in the use of lake land around Limboto Lake in the amount of ± 936.56 Ha to agricultural and plantation land, ± 14.29 Ha to become residential land, and ± 0.35 Ha to become a tourist area. The process of changing the physical land use around Limboto Lake, namely: (1) lake land is turned into swamps and then turned into agricultural land (wetlands and dry land) and plantations (coconut); (2) the lake area becomes swamps and then becomes agricultural land (wetlands and dry land) and then turns into residential land; (3) lake land changes into residential land; and (4) lake land directly turns into a tourist area. Keywords: Gorontalo Regency, Limboto Lake Depreciation, Land Use Changes

A mathematical partitioning of the effects of habitat loss and habitat degradation on species abundance

Worldwide, anthropogenic habitat loss and degradation have led to substantial biodiversity declines. Preserving biodiversity requires an understanding of how habitat loss and degradation interact to impact species populations, and how land-use decisions can limit these losses. We present a mathematical partitioning of changes in landscape-level population abundance in response to land-use change using a modified version of the Price equation from evolutionary biology. The Price equation partitions changes in species abundance into multiple drivers related to habitat loss, habitat degradation, and their interaction. We describe its development and exemplify its applicability using simulated data. Applying the Price equation to simulated data reveals the roles of habitat loss, habitat degradation, and their interaction in driving population change in patchy landscapes undergoing complex land-use change processes. The Price equation is a theoretical tool that may enhance our understanding of the effects of land-use change on populations by accounting for the specific processes by which land-use change operates across landscapes.

Spatial Changes and Land Use of Arable Land in China

Numerous concerns have been raised in China over the issues of limited arable land resources and food security in China. Especially, the record levels of soil pollution and the conversion of the arable land become the serious threat to the nation’s capacity to produce adequate levels of staple cereal crops for Chinese people. Most of arable land, only 15% of the country, mainly concentrated on the central eastern coast and along the Yangtze and Yellow river valleys which had the highest sediment deposit among the lands in China. An agricultural land in China was classified into four categories including arable land. The survey of spatial distribution and types of land use by in China established by remote sensing data and conventional aerial photography showed main land use features and the spatial pattern and processes of land use change for 15 regions covering China. The agricultural land area in 2015 was increased by 64.9% from that in 1960 while the changes of the arable land area ranged from decrease of 6.6% in 1980 to increase of 20.2% in 1990. Conclusively, we assume that Chinese government may have to figure out the practically adequate arable land area to produce safe food for people in China, bearing in mind of 135 million ha that is a minimum threshold to ensure adequate food production. The spatial change in arable land area in China.

Land use and land cover change processes in China's eastern Loess Plateau

Using Landsat remote sensing images, we analyzed changes in each land use type and transitions among different land use types during land use and land cover change(LUCC) in Ningwu County, located in the eastern Loess Plateau of China, from 1990 to 2010. We found that grassland, woodland, and farmland were the main land use types in the study area, and the area of each type changed slightly from 1990 to 2010, whereas the area of water, construction land, and unused land increased greatly. For the whole area, the net change and total change were insignificant due to weak human activity intensity in most of the study area, and the LUCC was dominated by quasi-balanced two-way transitions from 1990 to 2010. The insignificant overall amount of LUCC appears to have resulted from offsetting of rapid increases in population, economic growth, and the implementation of a program to return farmland to woodland and grassland in 2000. This program converted more farmland into woodland and grassland from 2000 to 2010 than from 1990 to 2000, but reclamation of woodland and grassland for use as farmland continued from 2000 to 2010, and is a cause for concern to the local government.

An Analysis of Land-Use Change and Grassland Degradation from a Policy Perspective in Inner Mongolia, China, 1990–2015

Land-use and land-cover changes have important effects on ecology, human systems, the environment, and policy at both global and regional scales. Thus, they are closely related to human activities. The extraction of more details about land-use change and grassland degradation is necessary to achieve future sustainable development in Inner Mongolia. The current study presents the patterns and processes of land-use changes over space and time, while also analyzing grassland degradation that is based on an analysis of land-use changes using a transition matrix, the Markov chain model and Moran’s I index, and a combination of long-time-scale remote sensing data as the data source. The major results indicate the following. (1) In 1990–2015, 13% (123,445 km2) of the total study area, including eight land-use types, changed. Woodland increased the most and moderate grassland decreased the most. (2) Grassland degradation, which occupied 2.8% of the total area of Inner Mongolia, was the major land-use conversion process before 2000, while, after 2000, 8.7% of the total area was restored; however, grassland degradation may still be the major ecological issue in Inner Mongolia. (3) Environmental protection policies show a close relationship with land-use conversion.

Dynamic trade-off analysis of multiple ecosystem services under land use change scenarios: Towards putting ecosystem services into planning in Iran

This study dynamically analyzes the trade-off between three ecosystem services (ESs), including soil retention, habitat quality, and food supply in the Gorganrood watershed, northeastern Iran. In this regard, several analytic tools including the Integrated Valuation of Ecosystem Services and Tradeoff (InVEST) model, Cellular Automata-Markov Chain (CA-MC) model, Intensity Analysis and Trade-Off (TO) index are employed to dynamically link the process of land use change with the temporal flow of ESs. Two scenarios of business as usual (BAU) and environmentally sound planning (ESP) are developed to produce land use layers under various planning strategies. Accordingly, the BAU scenario is more successful at providing a landscape with a higher acreage of agricultural fields and rangelands. Based on tradeoff index results, the BAU scenario establishes a landscape in which food supply is intensified by declining land capability for providing soil retention and habitat quality services. In contrast, the ESP scenario generates a landscape in which the outputs of the TO index indicate that habitat quality and soil retention benefits are improved by decreasing the potential of the area to supply food. This study emphasizes that a dynamic trade-off analysis of multiple ESs can assist planners and policy makers to make informed decisions and undertake strategic planning in Iran.

Land use/land cover change and extreme climatic events in the arid and semi-arid ecoregions of Mexico

Arid and semi-arid lands in Mexico dominate 60% of the national territory. They harbor many endemic species, as well as a large proportion of the population, and offer diverse ecosystem services. These regions are subjected to anthropogenic impacts derived from agriculture and livestock farming, which have caused land degradation and desertification. In addition, these ecosystems are highly sensitive to climate variability and projected global environmental change. However, information about how land use/land cover change and climate variability processes overlap and synergize each other in these ecoregions is scattered in different publications, and it is desirable to integrate it to provides more complete information for decision making. In this study we describe both land cover and land use changes in the five arid and semi-arid ecoregions in Mexico (Sonoran, Chihuahuan, Tamaulipan, Mexican High Plateau and Tehuacan-Cuicatlan valley) between 2002 and 2011, and their current exposure to droughts, low temperatures, floods and tropical cyclones. These results are discussed in terms of regional climate trends documented in the literature. We found that land use and land cover change differ between ecoregions, with the Sonoran and Chihuahuan ecoregions being the least affected. The overall exposure to extreme climate events is high in all ecoregions except for the Tehuacan-Cuicatlan valley, although each region has different exposure profiles. Observed trends for all ecoregions generally point towards an increase in both maximum and minimum temperatures, while trends for precipitation are less clear. Our results can serve as a guideline for identifying areas where anthropogenic processes of land use and land cover changes and extremes climatic events synergize, to better guide management under a changing environment

An Analysis of Land-Use and Land-Cover Change in the Zhujiang–Xijiang Economic Belt, China, from 1990 to 2017

Land-use and land-cover change (LUCC) are currently contested topics in the research of global environment change and sustainable change. Identifying the historic land-use change process is important for the new economic development belt (the Zhujiang–Xijiang Economic Belt, ZXEB). During this research, based on long-time-series land-use and land-cover data, while using a combination of a transition matrix method and Markov chain model, the authors derive the patterns, processes, and spatial autocorrelations of land-use and land-cover changes in the ZXEB for the periods 1990–2000 and 2000–2017. Additionally, the authors discuss the spatial autocorrelation of land-use in the ZXEB and the major drivers of urbanization. The results indicate the following: (1) The area of cropland reduces during the two periods, and woodland decreases after the year 2000. The woodland is the most stable land-use type in both periods. (2) Built-up land expansion is the most important land-use conversion process; the major drivers of built-up land expansion are policy intervention, GDP (gross domestic product), population growth, and rural population migration. (3) Transition possibilities indicate that after 2000, most land-use activities become stronger, the global and local Moran’s I of all land-use types show that the spatial autocorrelations have become more closely related, and the spatial autocorrelation of built-up land has become stronger. Policies focus on migration from rural to urban, and peri-urban development is crucial for future sustainable urbanization.

Unravelling Land-Use Change Mechanisms at Global and Regional Scales

Unravelling the dynamics of land-use change is key to assess the environmental and socioeconomic impacts of land-based strategies regarding climate or energy. In this prospect, this paper proposes an analytical decomposition of land-use change resulting from a shock in agricultural demand which takes into account indirect effects from price signals. This analytical equation is numerically estimated using a global model of land-use combining biophysics and economics. While being relatively simple, this model captures the main processes of land-use change: change in the intensive and extensive margins, international trade, change in intermediary demand and possible by-products. At the global scale, our results show that yield losses due to the conversion of marginal land amount approximately to half of yield gains due to fertiliser use. At the regional scale, patterns of yield and area responses are depicted by assessing the potentials for intensification (yield gaps) and extensification (areas of extensive pastures) given the future pathways of agricultural demand.

Latent Drivers of Landscape Transformation in Eastern Europe: Past, Present and Future

Land-use changes in Europe have been influenced by social forces including economic, demographic, political, technological and cultural factors. Contributing to a refined conceptualization of multifaceted processes of landscape transformation in the European continent, the present study proposes an extensive review of land-use trends in Eastern Europe, focusing on past, present and future conditions that may characterize latent drivers of change. Three time periods with a specific institutional, political and socioeconomic context reflecting distinct processes of land-use change were identified including: (i) the rapid transition to a centralized political system since the early 1950s (up to the late 1980s); (ii) a progressive transition from communist regimes to parliamentary democracy in 1989–1990 (up to the early 2000s); and (iii) the subsequent accession of individual countries to the European Union (2004–2007) up to nowadays. The most recent land-use trends are increasingly influenced by European directives on the environment, while national policies continue to shape economic development in member states.

Spatial variation in determinants of agricultural land abandonment in Europe

Agricultural abandonment is widespread and growing in many regions worldwide, often because of agricultural intensification on productive lands, conservation policies, or the spatial decoupling of agricultural production from consumption. Abandonment has major environmental and social impacts, which differ starkly depending on the geographical context, as does its potential to serve as a land reservoir for recultivation. Understanding determinants of abandonment patterns, and especially how their influence varies across broad geographic extents, is therefore important. Using a pan-European map of agricultural abandonment derived from MODIS NDVI time series between 2001 and 2012, we quantified the importance of farm management, climatic, environmental, and socio-economic variables in explaining abandonment patterns. We chose a machine learning modelling framework that accounts for spatial variation in the relationship between abandonment and its determinants. We predicted abandonment probability as well as determinant coefficients for the entire study area and summarised them for regions under selected EU support schemes. Our results highlight that agricultural abandonment was mainly explained by climate conditions suboptimal for agriculture (i.e., low/high growing degrees days). Determinants related to farm management (smaller field size, lower yields) and socio-economic conditions (high unemployment, negative migration balance) also contributed to describing agricultural abandonment patterns in Europe. Several determinants influenced abandonment in strongly non-linear ways and we found substantial spatial non-stationarity effects, although abandonment patterns were equally well-explained by predictors specified with spatially constant and varying effects. Predicted abandonment probability was similar inside and outside EU support or conservation zones, whereas observed MODIS-based abandonment was generally higher outside these zones, suggesting that schemes such as Natura 2000 or High Nature Value Farmland likely influence abandonment patterns. Our work highlights the potential value of spatial boosting for gaining insights into land-use change processes and their outcomes, which should increase the ability of such models to inform context-specific, regionalised decision making.

Long-term monitoring of citrus orchard dynamics using time-series Landsat data: a case study in southern China

ABSTRACTCitrus orchard planting is a typical land-use change process that can impact terrestrial ecosystem services both locally and globally. Long-term monitoring of citrus orchard dynamics is critical for understanding its change patterns as well as the potential driving factors. Satellite remote-sensing imagery has been a primary data source for this purpose. However, most previous studies with multi-year intervals only captured some, but not all detailed information on citrus orchard expansion. In this study, we developed a framework for mapping annual citrus orchard extent and track its long-term dynamics in Xunwu County, China, using the historical Landsat repository from 1990 to 2016. The results suggested that the average overall accuracy of original annual mapping was 87.73%, and its performance was significantly improved after the temporal filtering approach (91.46%). Several features (e.g. elevation, slope, normalized difference vegetation index) played more important roles in citrus orchard identification. With the achieved annual mapping layers, we found a rapid citrus orchard expansion trend during the study interval (i.e. from 22.18 to 697.21 km2). Moreover, this expansion process was unevenly distributed in time. Spatially, emerging citrus orchards were primarily transformed from forests and croplands and mainly distributed in areas with elevations from 200 to 500 m and slopes range from 5° to 20°. This study demonstrated the potential of mapping citrus orchard dynamics at a higher temporal frequency with remote-sensing time-series, which can contribute to providing reference for sustainable land-use policy.

URBAN EXPANSION MODELING APPROACH BASED ON MULTI-AGENT SYSTEM AND CELLULAR AUTOMATA

Abstract. Urban expansion is a land-use change process that transforms non-urban land into urban land. This process results in the loss of natural vegetation and increase in impervious surfaces. Urban expansion also alters the hydrologic cycling, atmospheric circulation, and nutrient cycling processes and generates enormous environmental and social impacts. Urban expansion monitoring and modeling are crucial to understanding urban expansion process, mechanism, and its environmental impacts, and predicting urban expansion in future scenarios. Therefore, it is important to study urban expansion monitoring and modeling approaches. We proposed to simulate urban expansion by combining CA and MAS model. The proposed urban expansion model based on MSA and CA was applied to a case study area of Changsha-Zhuzhou-Xiangtan urban agglomeration, China. The results show that this model can capture urban expansion with good adaptability. The Kappa coefficient of the simulation results is 0.75, which indicated that the combination of MAS and CA offered the better simulation result.

Representing anthropogenic gross land use change, wood harvest, and forest age dynamics in a global vegetation model ORCHIDEE-MICT v8.4.2

Abstract. Land use change (LUC) is among the main anthropogenic disturbances in the global carbon cycle. Here we present the model developments in a global dynamic vegetation model ORCHIDEE-MICT v8.4.2 for a more realistic representation of LUC processes. First, we included gross land use change (primarily shifting cultivation) and forest wood harvest in addition to net land use change. Second, we included sub-grid evenly aged land cohorts to represent secondary forests and to keep track of the transient stage of agricultural lands since LUC. Combination of these two features allows the simulation of shifting cultivation with a rotation length involving mainly secondary forests instead of primary ones. Furthermore, a set of decision rules regarding the land cohorts to be targeted in different LUC processes have been implemented. Idealized site-scale simulation has been performed for miombo woodlands in southern Africa assuming an annual land turnover rate of 5 % grid cell area between forest and cropland. The result shows that the model can correctly represent forest recovery and cohort aging arising from agricultural abandonment. Such a land turnover process, even though without a net change in land cover, yields carbon emissions largely due to the imbalance between the fast release from forest clearing and the slow uptake from agricultural abandonment. The simulation with sub-grid land cohorts gives lower emissions than without, mainly because the cleared secondary forests have a lower biomass carbon stock than the mature forests that are otherwise cleared when sub-grid land cohorts are not considered. Over the region of southern Africa, the model is able to account for changes in different forest cohort areas along with the historical changes in different LUC activities, including regrowth of old forests when LUC area decreases. Our developments provide possibilities to account for continental or global forest demographic change resulting from past anthropogenic and natural disturbances.

Urban Land Systems: An Ecosystems Perspective

We live in an urbanizing world. Since 2008, more than half of humanity lives in cities, both large and small, and old and new.[...]

A multiscale gaming approach to understand farmer’s decision making in the boom of maize cultivation in Laos

In Southeast Asia, the rapid expansion of boom crops like hybrid maize, rubber, oil palm, or banana, has brought about daunting environmental and socioeconomic impacts such as deforestation, land degradation, and indebtedness. Why do farmers engage in and keep on pursuing this farming strategy despite the adverse effects on local landscapes and livelihoods? In the context of the northern uplands of Lao People's Democratic Republic (Lao PDR), we developed an innovative approach to understanding the decisions that lead to the emergence of the maize boom. We successively studied the adoption, expansion, intensification, diversification, and abandonment of intensive maize practices in locations in which these phases were ongoing at the time of study. To better contextualize decision making, we designed and applied local, serious games with farmers in seven different villages that were going through a maize boom. Then we designed a metagame that summarized our findings across all decision phases and local games in a generalized form. National agricultural experts validated the structure of the metagame by taking on the role of farmers and they witnessed that their cumulative decision making within the metagame lead to a maize boom too. Core findings include: (1) the maize boom and bust can be reproduced in a game environment that simulates the change of six factor combinations; and (2) Farmers in northern Laos reinvest maize profits into their long-term, socioeconomic goals. The approach presented combines micro- and macrolevel analysis of land-use change. On the one hand, it allows the exploration of the local, social-ecological contexts of land-use decisions. On the other hand, it provides a systematic procedure to scale up, generalize, and test the contextual knowledge and systemic understanding of a complex, large-scale land-use change process.

Competition for water in a xeric forest ecosystem – Effects of understory removal on soil micro-climate, growth and physiology of dominant Scots pine trees

Abstract In many Central European areas, forests have been altered by century-long management practices, including grazing with domestic ungulates and litter harvesting. During the last century, most of these agro-forestry practices have been abandoned in many regions of Switzerland. As a consequence, stand density has increased, leading to higher competition for resources among trees, and particularly between overstory trees and understory vegetation. Only few studies investigated the effects of understory on the growth and physiology of overstory trees. We conducted an understory removal experiment at a xeric Scots pine (Pinus sylvestris L.) forest in an inner-Alpine valley of Switzerland over a period of 5 years and compared data of soil temperature and water content, needle and shoot length, and radial growth and sap flow. The removal of the understory increased soil temperature as well as soil water content at 5 to 60 cm soil depth, and led to a 4.6-fold higher mean annual radial growth and significantly longer needles and shoots. The removal of the understory further decreased tree water deficit and increased sap flow. We conclude that reduced competition for soil water after removal of the understory vegetation was the primary cause of the increased performance of the overstory trees since light was not a limiting factor already before the understory removal. Thus, increases in understory density due to altered forest management may have exacerbated observed drought-induced decline processes. Therefore, our study demonstrates the need for a careful disentangling of climate and land-use change processes as they may evolve in parallel and potentially intensify their impact on the ecosystems. In contrast, the findings suggest decreasing understory density as a suitable management practice to increase overstory tree growth and vigour, and hence reduce mortality risk for a species like Scots pine in a drought-prone environment.

Assessment of urbanization-induced ecological risks in an area with significant ecosystem services based on land use/cover change scenarios

ABSTRACTEcosystem services are facing numerous potential threats in rapidly developing areas. In this study, we investigated land use/cover change scenarios related to ecological risks due to urban development in an area with significant ecosystem services. Expansion of developed areas was considered as a risk source, and regional ecosystem services, such as soil conservation, soil erosion, and water conservation, were considered as risk receptors. Xiamen City was selected as a study case. Land-use and land-cover change processes in the study area were analyzed and used to predict future changes in urban spatial morphology. The analytic hierarchy process and ordered weighted averaging methods were employed to evaluation of urban comprehensive ecological risk and corresponding risk scenario settings. Most of northern and southern Xiamen City displayed a high level of ecosystem service under various high- or low-risk scenarios. Under the high-risk scenario, the average values of ecological risk due to newly developed land and total developed land were 0.402 and 0.324, respectively, in 2030 (power function exponent = 0.1). The average value of ecological risk due to newly developed land was generally higher than that caused by total developed land. In some local areas, such as Maluanwan and the small watershed Houxi, the ecological risk due to newly developed land was two to three times the average value for the entire study area. The results of this study provide an important reference for urban development.

A comparative approach to modelling multiple urban land use changes using tree-based methods and cellular automata: the case of Greater Tokyo Area

ABSTRACTUrban multiple land use change (LUC) modelling enables the realistic simulation of LUC processes in complex urban systems; however, such modelling suffers from technical challenges posed by complicated transition rules and high spatial heterogeneity when predicting the LUC of a highly developed area. Tree-based methods are powerful tools for addressing this task, but their predictive capabilities need further examination. This study integrates tree-based methods and cellular automata to simulate multiple LUC processes in the Greater Tokyo Area. We examine the predictive capability of 4 tree-based models – bagged trees, random forests, extremely randomised trees (ERT) and bagged gradient boosting decision trees (bagged GBDT) – on transition probability prediction for 18 land use transitions derived from 8 land use types. We compare the predictive power of a tree-based model with multi-layer perceptron (MLP) and among themselves. The results show that tree-based models generally perform better than MLP, and ERT significantly outperforms the three other tree-based models. The outstanding predictive performance of ERT demonstrates the advantages of introducing bagging ensemble and a high degree of randomisation into transition probability modelling. In addition, through variable importance evaluation, we found the strongest explanatory powers of neighbourhood characteristics for all land use transitions; however, the size of the impacts depends on the neighbourhood land use type and the neighbourhood size. Furthermore, socio-economic and policy factors play important roles in transitions ending with high-rise buildings and transitions related to industrial areas.

Application of land-use management scenarios to mitigate desertification risk in northern Iran

The environmentally sensitive areas (ESAs) model has been applied to evaluate the risk of desertification in the Chehel-Chai Watershed, northern Iran. This research is mainly conducted to quantify and assess the effect of land-use change processes on desertification risk in areas with humid climate. Water erosion, soil, vegetation, climate and management practices were used as five main criteria for desertification mapping in this study. The degree of sensitivity to desertification was determined for each land unit using the categorization table of desertification intensity. For providing insights into optimal management programs, the desertification sensitivity map was used to analyze different scenarios of management strategies. By assuming that other indices are constant, these scenarios were replaced by altering land-use intensity parameter. Based on five above-mentioned criteria, the mean weight of quantitative value for desertification sensitivity was calculated, which was 1.32 for the research location. By comparing this value to ESAs table, the desertification class of the study area was determined as fragile (type 2). Scenario analysis results indicated that the relative frequencies of areas with critical states of desertification (i.e., classes 1, 2 and 3) are reduced by 18.84 and 14.27% in vegetation management scenario and land ecological capability evaluation scenario, respectively. Results of this study also highlighted that scenario maps are efficient tools for analyzing and identifying areas at high risk of desertification in Chehel-Chai Watershed, where desertification process could be alleviated if appropriate land-use planning and vegetation management programs are adopted.