Land Change Analysis Research Articles

Determining(Estimating) Ratios for Enhancing Publicness Through Analysis of Changes in Land Prices Influenced by Upzoning

Determining(Estimating) Ratios for Enhancing Publicness Through Analysis of Changes in Land Prices Influenced by Upzoning

Distinguishing Land Change from Natural Variability and Uncertainty in Central Mexico with MODIS EVI, TRMM Precipitation, and MODIS LST Data

Precipitation and temperature enact variable influences on vegetation, impacting the type and condition of land cover, as well as the assessment of change over broad landscapes. Separating the influence of vegetative variability independent and discrete land cover change remains a major challenge to landscape change assessments. The heterogeneous Lerma-Chapala-Santiago watershed of central Mexico exemplifies both natural and anthropogenic forces enacting variability and change on the landscape. This study employed a time series of Enhanced Vegetation Index (EVI) composites from the Moderate Resolution Imaging Spectoradiometer (MODIS) for 2001–2007 and per-pixel multiple linear regressions in order to model changes in EVI as a function of precipitation, temperature, and elevation. Over the seven-year period, 59.1% of the variability in EVI was explained by variability in the independent variables, with highest model performance among changing and heterogeneous land cover types, while intact forest cover demonstrated the greatest resistance to changes in temperature and precipitation. Model results were compared to an independent change uncertainty assessment, and selected regional samples of change confusion and natural variability give insight to common problems afflicting land change analyses.

Trajectories, drivers, and probabilities of land cover change in a disturbed forested watershed in eastern Taiwan

Understanding the trajectories, drivers, and probabilities of land cover change can provide essential information for forested watershed planning and sustainable management. This paper demonstrates that the Taimali watershed in eastern Taiwan underwent a dramatic decrease in forest cover under the influences of frequent earthquakes and typhoons during 2005–2011. To grasp the dynamics of land cover change, this study applied a combined land-change analysis approach using trajectory analysis and logistic regression. The results of trajectory analysis indicate that three change trajectories, covering 75.65 % of the total changed area, were considered the major trends of alterations, including the trajectories of Forest-Landslide, Forest-Channel, and vegetation recovery. Based on the causes of land conversion, most land transformation resulted from natural causes. Therefore, natural forces play a pivotal role in land cover change in the Taimali watershed. The results of logistic regression analysis show that lithology is the most important spatial determinant for occurrence probability of three change trajectories, followed by aspect and slope. Three maps of occurrence probability of the change trajectories were produced using regression coefficients. With the validation of the relative change intensity index, the results reveal that the observed change trajectories considerably coincided with the zones that had higher probabilities of change and covered a small area. Thus, three spatial statistical models are helpful tools for projecting the occurrence probabilities of the change trajectories.

Pengendalian Urban Sprawl di Wilayah Pinggiran (Studi Kasus: Perkembangan Kota di Indonesia dan Perancis)

The progress in urbanization within downtown areas has been expanded to the surrounding areas (i.e. periphery). This has been considered by the changes of the land uses in two geographically different countries. These areas have experienced a phenomenon of space consumption due to the urban development, which eventually triggered the urban sprawl, such as Mlati in Indonesia, Vertou, Caquefou and Sainte Luce Sur Loire in Nantes, France. This present study aims to examine the practices in the management of space consumption by urbanization in several municipals within periphery of Nantes, such as Carquefou, Sainte Luce sur Loire, Vertou and to compare with the sub-region of Mlati, in Sleman, Indonesia. The objective of this research was to answer the question; what are the major factors that influence the implementation of the policy controlling the urban sprawl in the periphery, in Indonesia and in France? These factors were decomposed in four components: regulations, institutions, resources and implementation. The approaches used in this study were, first of all, the quantitative method and based on its results. The second approach was done by descriptive qualitative method. The first approach was analysis of changes in land uses using evolution matrices of the change of land use, in order to study how a particular type of land use evolved and how it changed. The second step was done by an interview with the people key who are mastering the research subject, and then SWOT analysis was done from the interview. The results show that there is a significant difference between Indonesia and France, particularly in the human resources and implementation.

Retrospective analysis of changes in land uses on vertic soils of closed mesodepressions on the Azov plain

A retrospective analysis of changes in land uses within the bottoms of closed mesodepressions in Azov district of Rostov oblast for the period from 1968 to 2014 was performed. A cartographic analysis of changes in the degree of waterlogging of these depressions and the related changes in the character of land use was based on remote sensing data. This study was performed within the framework of a general problem-oriented system of the retrospective monitoring of the soil and land cover. It was found that the waterlogged area in the mesodepressions in the particular years does not depend on the anthropogenic loads and is subjected to cyclic variations. Temporal intervals for the wetting–drying cycles were determined. The maximum drying of the bottoms of mesodepressions was observed in 1975, 1990, and 2011.

Quantifying uncertainty and confusion in land change analyses: a case study from central Mexico using MODIS data

Land cover classifications of coarse-resolution data can aid the identification and quantification of natural variability and anthropogenic change at regional scales, but true landscape change can be distorted by misrepresentation of map classes. The Lerma–Chapala–Santiago (LCS) is biophysically diverse and heavily modified by urbanization and agricultural expansion. Land cover maps classified with a Mahalanobis distance algorithm and possibilistic metrics of class membership were used to quantify uncertainty (potential error in class assignment) and change confusion (potential error in land change identification). While land change analysis suggests that ~33% of the landscape underwent a change in class, led by changes from or to the mosaic class (~19% of landscape), classification uncertainty values for 2001 and 2007 were 0.59 and 0.62, respectively, with highest uncertainty among bare soil classes, and an average confusion index value of 0.65, with pixels experiencing change at 0.67 and pixels experiencing persistence at 0.61 on average. These results indicate that uncertainty and potential error in land cover classifications estimates may inhibit accurate assessments of land change. Estimates of land change may be refined using these metrics to more confidently identify true landscape change and to find classes and locations that are contributing to errors in land change assessments.

Monitoring land changes in an urban area using satellite imagery, GIS and landscape metrics

Monitoring land changes is an important activity in landscape planning and resource management. In this study, we analyze urban land changes in Atlanta metropolitan area through the combined use of satellite imagery, geographic information systems (GIS), and landscape metrics. The study site is a fast-growing large metropolis in the United States, which contains a mosaic of complex landscape types. Our method consisted of two major components: remote sensing-based land classification and GIS-based land change analysis. Specifically, we adopted a stratified image classification strategy combined with a GIS-based spatial reclassification procedure to map land classes from Landsat Thematic Mapper (TM) scenes acquired in two different years. Then, we analyzed the spatial variation and expansion of urban land changes across the entire metropolitan area through post classification change detection and a variety of GIS-based operations. We further examined the size, pattern, and nature of land changes using landscape metrics to examine the size, pattern, and nature of land changes. This study has demonstrated the usefulness of integrating remote sensing with GIS and landscape metrics in land change analysis that allows the characterization of spatial patterns and helps reveal the underlying processes of urban land changes. Our results indicate a transition of urbanization patterns in the study site with a limited outward expansion despite the dominant suburbanization process.

Understanding forest loss and recovery: a spatiotemporal analysis of land change in and around Bannerghatta National Park, India

Bangalore is India’s third fastest-growing city and a major information technology center of India. The city is unusual in also having a major protected area located at its periphery, which creates a significant challenge for conservation. Bannerghatta National Park and its surrounding landscape, situated south of Bangalore, have experienced significant land-use and land-cover changes over the last two decades. This analysis combines discrete and continuous approaches of satellite remote-sensing-based change detection using multitemporal Landsat and IRS LISS III imagery to analyze the rate and extent of spatiotemporal changes in and around the Bannerghatta National Park between 1973, 1992 and 2007. Most of the native forest cover loss and decrease in forest density has taken place outside the park, or at the edge of the park, and relates to increased agriculture, suburban development, grazing and illegal logging. However, forest cover inside the park has been maintained, counter to the dominant global theme of deforestation as a consequence of urbanization. Overall, despite the decrease in native forest cover the landscape has experienced a net increase in tree cover or reforestation, which can be attributed to an increase in tree plantations outside the Bannerghatta National Park.

Processes of land use change in mining regions

Mining regions undergo abrupt and extensive land use change, the impacts of which pose management challenges for mining companies and regulatory agencies. In this study we investigated 20 years of land use change in Brazil's Iron Quadrangle (QF) mining region. We classified remote sensing images to produce land use maps and conducted a Land Change analysis to investigate the causes and consequences of observed changes. The QF underwent extensive land use change between 1990 and 2010, including deforestation, plantation expansion, urbanization and mine expansion. Comparing our results with those of surrounding non-mining landscapes illustrated important differences. For example, QF contained additional highly profitable land uses, including mining and plantation forestry, which were driven by globalized markets for mineral resources. This finding suggests processes of land use change within mining regions are distinct from those found elsewhere and, as such, land management policies should reflect this. We also hypothesized four generalizations regarding these processes: 1) the direct footprints of mining expands over time, 2) the offsite footprints of mining are extensive and also often expanding, 3) the direct and indirect land used by mines causes environmental and social impacts, some of which are not captured by current management approaches, and 4) the footprints of mining (and associated impacts) are driven by global factors, many of which are uncontrollable by local land holders and regional land management plans and policies. We describe and discuss these generalizations, drawing on published evidence from other mining regions to illustrate both their generality and implications for land management.

Analysis of Multi-Scale Changes in Arable Land and Scale Effects of the Driving Factors in the Loess Areas in Northern Shaanxi, China

In this study, statistical data on the national economic and social development, including the year-end actual area of arable land, the crop yield per unit area and 10 factors, were obtained for the period between 1980 and 2010 and used to analyze the factors driving changes in the arable land of the Loess Plateau in northern Shaanxi, China. The following areas of arable land, which represent different spatial scales, were investigated: the Baota District, the city of Yan’an, and the Northern Shaanxi region. The scale effects of the factors driving the changes to the arable land were analyzed using a canonical correlation analysis and a principal component analysis. Because it was difficult to quantify the impact of the national government policies on the arable land changes, the contributions of the national government policies to the changes in arable land were analyzed qualitatively. The primary conclusions of the study were as follows: between 1980 and 2010, the arable land area decreased. The trends of the year-end actual arable land proportion of the total area in the northern Shaanxi region and Yan’an City were broadly consistent, whereas the proportion in the Baota District had no obvious similarity with the northern Shaanxi region and Yan’an City. Remarkably different factors were shown to influence the changes in the arable land at different scales. Environmental factors exerted a greater effect for smaller scale arable land areas (the Baota District). The effect of socio-economic development was a major driving factor for the changes in the arable land area at the city and regional scales. At smaller scales, population change, urbanization and socio-economic development affected the crop yield per unit area either directly or indirectly. Socio-economic development and the modernization of agricultural technology had a greater effect on the crop yield per unit area at the large-scales. Furthermore, the qualitative analysis indicated that government policies had a more significant impact on the large-scale arable land areas.

Deforestation and fragmentation of seasonal tropical forests in the southern Yucatán, Mexico (1990–2006)

The southern Yucatán (SY) has been recognized as a hotspot of biodiversity with great risk of deforestation. Land change analysis, based on classified Landsat TM and ETM + satellite imagery (1990, 2000 and 2006), was used to estimate the annual deforestation rates of 141 land management units of the SY, and spatial patterns of forest fragmentation around and within the Calakmul Biosphere Reserve (CBR), which comprises approximately one-third of the region. Results indicate a decrease in annual deforestation rates over 1990–2006, from 0.15% year−1 to 0.06% year−1, but with significant sub-regional variations in the quantity and rate of forest loss. Despite a decline in deforestation during this period, there was considerable fragmentation both inside and outside the CBR. While population pressures and the expansion of pasture have caused deforestation across the region, agricultural intensification, diversified income strategies and reserve conservation may have contributed to reduced forest loss during the study period.

Landscape metrics and change analysis of a national wildlife refuge at different spatial resolutions

For the past three decades, ecologists and biogeographers have increasingly incorporated remote sensing and geographical information systems (GISs) to inventory and analyse spatially organized data. Although there are many studies exploring the effects of fine resolution on remote sensing and GIS mapping, there is still a gap on how to identify the most appropriate spatial resolutions for studying landscapes and their structures and dynamics. This study investigated the effects of landscape changes over a 64-year study period at different spatial resolutions using four resampling schemes. The study was conducted on a national wildlife refuge of five land-use and land-cover (LULC) categories using aerial photos recorded in three distant years (1938, 1971, and 2001). This refuge has undergone major landscape changes in the last 64 years. Among the five LULC categories studied, the one that lost the most surface is agriculture; the most gain was made in forest and water. In terms of net change and swapping, agriculture and forest were the most dynamic categories in the National Wildlife Refuge. Our findings showed considerable spatial variability in landscape dynamics at different scales. We specifically observed that hard-classified maps with spatial resolutions of 30 m or finer provided better analysis of landscape dynamics, whereas with soft-classified maps it could go up to 90 m or finer. This implies that there is a range of optimum resolution that could allow for the use of medium-resolution data, such as Landsat, for reliable land change analysis. These findings offer further insight on landscape change analysis at different spatial resolutions and advance our understanding and knowledge on the effect of scale on landscape ecology.

Spatial Econometric Analysis of Cultivated Land Change and its Influencing Factors in the Poyang Lake Eco-Economics Zone

Spatio-temporal pattern of cultivated land change and its influencing factors in the Poyang Lake Ecological Economic Zone were conducted by exploratory spatial data analysis and spatial autocorrelation analysis. Results show that there is an obvious correlation for the spatial distribution of cultivated land in the Poyang Lake Eco-economics Zone. Its value of Morans I reduced from 0.4574 in 2002 to 0.4092 in 2008, and then increased to 0.4352 in 2009, which roughly presented a "U" type distribution. Total population is the most important factor that affecting the change of cultivated areas in the Poyang Lake Eco-economics Zone. Agricultural growth, average wage of urban residents and the fixed assets investment are also the main driving factors. Spatial auto-regression model is an effective tool for revaluating the spatial distribution of regional cultivated land, and revealing the evolution mechanisms of cultivated land.

Characterizing tree canopy loss using multi-source GIS data in Central Massachusetts, USA

Despite numerous ecosystem services provided by urban trees, they are continually threatened by combined natural disturbances, invasive species, development and negligent management practices. This research characterizes the amount and cause of tree loss in Worcester, Massachusetts, in the northeast United States, and neighbouring towns between 2008 and 2010 using multi-source remotely sensed imagery and historical land cover maps (1976–2009). Historical land-change analysis reveals that proportional forest cover loss in the Worcester County study area exceeds that of the state by 0.26% per year, 67% of which was driven by the expansion of low-density residential land use. Between 2008 and 2010, 2% of Worcester County’s tree canopy was lost to high- and low-density urban development (47% of the total loss), United States Department of Agriculture (USDA) tree removal for Asian longhorned beetle (ALB) eradication (25%), timber harvest (15%) and ice storm damage (6%). The use of multi-source geographic information system (GIS) data to characterize tree canopy loss makes it a flexible and replicable method to monitor urban tree health.

Historical and Contemporary Geographic Data Reveal Complex Spatial and Temporal Responses of Vegetation to Climate and Land Stewardship

Vegetation and land-cover changes are not always directional but follow complex trajectories over space and time, driven by changing anthropogenic and abiotic conditions. We present a multi-observational approach to land-change analysis that addresses the complex geographic and temporal variability of vegetation changes related to climate and land use. Using land-ownership data as a proxy for land-use practices, multitemporal land-cover maps, and repeat photography dating to the late 19th century, we examine changing spatial and temporal distributions of two vegetation types with high conservation value in the southwestern United States: grasslands and riparian vegetation. In contrast to many reported vegetation changes, notably shrub encroachment in desert grasslands, we found an overall increase in grassland area and decline of xeroriparian and riparian vegetation. These observed change patterns were neither temporally directional nor spatially uniform over the landscape. Historical data suggest that long-term vegetation changes coincide with broad climate fluctuations while fine-scale patterns are determined by land-management practices. In some cases, restoration and active management appear to weaken the effects of climate on vegetation; therefore, if land managers in this region act in accord with on-going directional changes, the current drought and associated ecological reorganization may provide an opportunity to achieve desired restoration endpoints.

Cyclone Sidr Impacts on the Sundarbans Floristic Diversity

The Sundarbans - the world’s largest single block of tidal halophytic mangrove forest situated at the southwest of Bangladesh, plays a vital role in maintaining environmental sustainability of the country and the world in general. This study identified and quantified the extent and degree of damage caused to the floristic diversity of the Sundarbans by the tropical cyclone Sidr in 15 November 2007. It also quantified the extent and rate of the post-cyclone regeneration in the damaged flora. Unsupervised classification - ISODATA and the normalized difference vegetation index (NDVI) were carried out over a temporal series of 2007-2010 on four Landsat 7 Enhanced Thematic Mapper Plus (ETM +) images for the months of February. Land change analysis from the classification results show that three important floristic taxa - Heritiera fomes (Sundari), Excoecaria agallocha (Gewa) and Sonneratia apetala (Kewra) have been significantly affected by the cyclone. NDVI analysis indicates that 45% area of the Bangladesh’s part of the Sundarbans (approximately 2500 sq.km) was affected due to the cyclone action. Results further indicated that the average rate of post-cyclone floristic growth in 2009-2010 is four times higher than the average rate in 2008-2009. Thus the study identified a temporary loss of the diversity (in terms of relative abundance) in the affected three floristic taxa of the Sundarbans after that severe exogenous perturbation; which took three years to regenerate. Moreover, it showed the higher efficiency and promptness of remote sensing techniques in similar cases than the ground data based studies.

The Relative Importance of Socioeconomic and Environmental Variables in Explaining Land Change in Bolivia, 2001–2010

This study assesses the relationship between trends in land change from 2001 to 2010 and socioeconomic and environmental variables in Bolivia at multiple spatial scales using a nonparametric, tree-based modeling approach. It also explores the theoretical dimensions surrounding the debate over the relative importance of socioeconomic and environmental variables in explaining land change. Results from the land change analysis show several hotspots of dynamic change. The majority of woody vegetation loss occurred in the eastern lowlands of Santa Cruz, Beni, and Pando and was attributable to the expansion of industrial agriculture. Gains in woody vegetation took place in the drylands of Santa Cruz and Beni savanna, and these changes were attributed to shifting patterns in precipitation and fire rather than human-induced change. Other hotspots of woody vegetation gain were attributed to abandonment of agriculture and herbaceous lands in the intermontane valleys of the southern Andes. Regression analyses showed that population and other demographic variables were poor predictors of land change. There is a clear relationship, however, between changes in woody and agriculture/herbaceous vegetation and environmental variables such as precipitation, temperature, and elevation. Municipalities with adequate precipitation and moderate temperature tended to show increases in agriculture and herbaceous vegetation and woody vegetation declines. Woody vegetation tended to increase in municipalities at higher elevations. This study also shows that explanations of only wealth or population as the main drivers of land change undervalue the role that natural features, like topography and precipitation, play in limiting or permitting certain land-use decisions.

Coastal Environmental Studies: Importance, Problem and Prospect

Coastal Environmental Studies: Importance, Problem and Prospect

Monitoring Urban Sprawl and the National Ecological Reserve in Sintra-Cascais, Portugal: Multiple OLS Linear Regression Model Evaluation

A methodology is proposed to assess the effectiveness of the National Ecological Reserve (REN) law, which aims to protect ecologically valuable and/or vulnerable areas, in the municipalities of Sintra and Cascais, Portugal. Landsat satellite data classification and land change analysis show that urban area almost doubled between 1989 and 2001, when REN was already in force covering 36.5% of the study area. The approach involved multiple ordinary least squares (OLS) linear regression models to evaluate the evolution of five landscape metrics that translate the impact of urban sprawl in REN main functions: soil, water, and nature protection, and protection of people and belongings settled in hazard-vulnerable areas. Results show that REN had an impact on landscape change attributable to urbanization. However, these changes were unfavorable to its core ecological functions. Multiple linear OLS regression modeling proved to be an effective and simple method to compare and understand the evolution of landscape structure between areas protected by REN and their surroundings.

Modelling of land cover and agricultural change in Europe: Combining the CLUE and CAPRI-Spat approaches

Recent European research projects have developed approaches that downscale land use related results of economic models. These results are primarily downscaled from the national or regional scale to a spatial resolution appropriate for environmental impact analysis. Different studies represent the interactions between the economic and geographic components of the land system in different ways. This paper explores how interactions between economic and geographic aspects of the land system can be strengthened in modelling studies. It does so by comparing two existing approaches (CLUE and Capri-Spat) for the European Union (EU27). CLUE focuses on disaggregating national level changes in claims for agricultural and urban area to a 1 km × 1 km grid, explicitly addressing consequences of changing demands for agricultural and urban area for other land uses such as (semi-) natural vegetation. Whereas, CAPRI-Spat is concerned with agricultural land use, disaggregating cropping shares, animal stocking densities, yield and agricultural input use for mapping units. The mapping units are clusters of 1 km × 1 km pixels considered homogenous in terms of soil, slope, land cover and administrative region. This paper discusses differences between the two models relating to geographical units, distribution algorithm and most importantly diverging interpretation of ‘agricultural land’, in relationship to their respective concepts and objectives. It concludes that a stronger integration of the geographic and economic aspects can be achieved by linking the overall land use dynamics simulated by CLUE to the detailed representation of the agricultural sector by CAPRI-Spat. Therefore, relative changes in land use classes at 1 km × 1 km resolution obtained from CLUE simulations update a priori means in CAPRI-Spat entering a Highest Posterior Density Estimator. The findings of this study contribute to our overall capacity to integrate approaches from different disciplines in the integrated analysis of land change and the ex ante assessment of environmental and economic effects of agricultural policies.