Magnitude Of Land Cover Changes Research Articles

Hydrological changes in Serra da Mantiqueira Range watersheds (Southeast Brazil)

The Serra da Mantiqueira Environmental Protection Area is one of the most important Atlantic Forest biodiversity hotspots in the World, and one of the main water sources for the Brazilian Southeast Region. In this study, we analyze the existence and characteristics of streamflow changes in two watersheds (Sapucaí-Mirim and Sapucaí-Guaçu River watersheds) of the Serra da Mantiqueira Range, and if these changes are due to climate change, alterations of land cover and/or external factors. Mann-Kendall and Pettit tests were used to detect changes in streamflow, rainfall and evapotranspiration data series, at different time scales. The characteristics and magnitude of land cover changes were evaluated from multi-temporal maps, produced from satellite images and the supervised classification technique. The results show an increase in winter rainfall at the two watersheds studied. No changes were detected in the streamflows of the Sapucaí-Mirim River Basin. The summer streamflow of Sapucaí-Guaçu River watershed reduced at a rate of −0.035 m³.s−1. year−1. In addition, there were sudden streamflow changes in the summer (from the year 1967) and autumn (from the year 1988) in Sapucaí-Guaçu watershed. Furthermore, the reference summer evapotranspiration of the Sapucaí-Guaçu watershed showed an increasing trend and an abrupt increase (in 1988), besides a sudden reduction of actual evapotranspiration in 2006. The integrated analysis of these results, together with the changes in land cover and population, allow us to conclude that the reductions in summer and autumn streamflows at the Sapucaí-Guaçu watershed were probably due to the increase in the water withdrawal for public supply, added to the effects of urbanization on the hydrology of the watershed.

Land Use Changes in the Southeastern United States: Quantitative Changes, Drivers, and Expected Environmental Impacts

Land use change analysis provides valuable information for landscape monitoring, managing, and prioritizing large area conservation practices. There has been significant interest in the southeastern United States (SEUS) due to substantial land change from various economic activities since the 1940s. This study uses quantitative data from the Economic Research Service (ERS) for landscape change analysis, addressing land change among five major land types for twelve states in the SEUS from 1945 to 2012. The study also conducted a literature review using the PSALSAR framework to identify significant drivers related to land type changes from research articles within the region. The analysis showed how each land type changed over the period for each state in the time period and the percentage change for the primary drivers related to land use change. The literature review identified significant drivers of land use and land cover change (LULCC) within the SEUS. The associated drivers were categorized into natural and artificial drivers, then further subdivided into eight categories related to land type changes in the region. A schematic diagram was developed to show land type changes that impacted environmental changes from various studies in the SEUS. The results concluded that Forest land accounted for 12% change and agricultural land for 20%; population growth in the region is an average of 2.59% annually. It also concluded that the need for research to understand past land use trends, direction and magnitude of land cover changes is essential. Significant drivers such as urban expansion and agriculture are critical to the impending use of land in the region; their impacts are attributed to environmental changes in the region and must be monitored.

Trends in the development of Estonian coastal land cover and landscapes caused by natural changes and human impact

The structure of coastal land cover in Estonia is intricate and exhibits considerable differences from site to site. The diverse geomorphology of the seashores is one of the key factors affecting the speed and magnitude of land cover changes. Likewise, the history of human inhabitance on the coast has also shaped the character of land cover. The Estonian coastal zone has experienced abrupt and radical changes in land ownership and its related land use during the last century. The main objectives of this paper are: 1) to give an overview of land use and the trends of development of land cover pattern along different parts of the Estonian coast; and 2) to analyze the relationships of natural and human processes and their cumulative impact on the evolution of coastal land cover pattern in Estonia. This study is based on results obtained during fieldwork in the study areas and on the analysis of large-scale (1:10,000) historical maps. In agriculturally dominant coastal areas, the traditional open landscape of fields and grassland at the beginning of the 20th century had been replaced by woodland and grasslands with shrubs by the start of the 21st century. Expansion of reed beds in areas of former seashore grasslands is another striking phenomenon. The structure of land cover on forested coasts has been fairly stable during the last 100 years. Areas of urban sprawl are characterised by dramatic changes in land cover structure. Rapidly increasing population and expanding settlements imposes on the ecological balance of the fragile dune forests in the coastal zone.

Remote sensing of within-class change in urban neighborhood structures

Two conceptual models for urban neighborhood change and urban landscape ecology are used to devise an integrative methodology for measuring temporal changes in the urban morphology of Los Angeles, California, based on the techniques of multiple endmember spectral mixture analysis (MESMA), landscape metrics, and fuzzy logic. To illustrate an application of the methodology, the research utilizes two Landsat Thematic Mapper images acquired in 1990 and 2000. Through a wall-to-wall exercise, the paper discusses: (1) how the spatially continuous character of the urban morphology in Los Angeles is analyzed through the use of MESMA technique to capture and quantify within-class changes in land cover at the sub-pixel level; (2) how the magnitude of land cover changes is assessed through fuzzy logic; and (3) how landscape metrics are applied to quantify patterns of change in land cover at the census tract level. The results of the case study indicate that the integration of MESMA, fuzzy logic and landscape metrics can provide a systematic way to derive comparable measures of change in urban neighborhoods in Los Angeles. Further research is however needed to develop more rigorous methods for assessing the accuracy of land cover fractions generated by MESMA. The paper concludes with a discussion of how the proposed methodology may present a step towards a closer integration of remote sensing technology into the reformation of planning policies concerning urban sustainable development.

Impact of short‐term rainfall fluctuation on interannual land cover change in sub‐Saharan Africa

ABSTRACTAim Interannual land cover change plays a significant role in food security, ecosystem processes, and regional and global climate modelling. Measuring the magnitude and location and understanding the driving factors of interannual land cover change are therefore of utmost importance to improve our understanding and prediction of these impacts and to better differentiate between natural and human causes of land cover change. Despite advances in quantifying the magnitude of land cover change, the interpretation of the observed land cover change in terms of climatic, ecological and anthropogenic processes still remains a complex issue. In this paper, we map land cover change across sub‐Saharan Africa and examine the influences of rainfall fluctuations on interannual change.Location The analysis was applied to sub‐Saharan Africa.Methods Ten‐day rainfall estimates (RFE) obtained from National Oceanic and Atmospheric Administration's (NOAA) Climate Prediction Center (CPC) were used to extract information on inter and intra‐annual rainfall fluctuations. The magnitude of land cover change was quantified based on the multitemporal change vector method measuring year‐to‐year differences in bidirectional reflectance distribution function (BRDF) corrected 16‐day enhanced vegetation index (EVI) data from the Moderate Resolution Imaging Spectro‐radiometer (MODIS). Statistical models were used to estimate the relationship between short‐term rainfall variability and the magnitude of land cover change. The analysis was stratified first by physiognomic vegetation type and second by chorological data on species distribution to gain insights into spatial variations in response to short‐term rainfall fluctuations.Results The magnitude of land cover change was significantly related to rainfall variability at the 5% level. Stratification considerably strengthened the relationship between the magnitude of change and rainfall variability. Explanatory power of the models ranged from R2 = 0.22 for the unstratified model to 0.40–0.96 for the individual models stratified by patterns of species distribution. The total variability explained by the combined models including the influence of rainfall and differences in vegetation response ranged from 22% for the model not stratified by vegetation to 76% when stratified by chorological data.Main conclusions Using this methodology, we were able to measure the contribution of natural variation in precipitation to land cover change. Several ecosystems across sub‐Saharan Africa are highly sensitive to short‐term rainfall variability.

Detection of partial land cover change associated with the migration of inter-class transitional zones

Post-classification comparison techniques are frequently used in studies of change detection. If the classifications used were derived with the use of conventional 'hard' classification techniques, change detection is constrained to the identification of complete changes in class label. This may be inappropriate in circumstances when the land cover conversion is operating at a scale finer than the spatial resolution of the sensor which acquired the imagery and for the detection of land cover modifications. By basing the change detection on the comparison of fuzzy classifications it should be possible to identify partial changes, including both land cover conversion and modification. Fuzzy classifications of Advanced Very High Resolution Radiometer (AVHRR) data were used to identify changes in the apparent position of the forest-savanna transition in West Africa. A comparison of the classifications revealed the variations in the nature and magnitude of land cover change. It was apparent that the migration of the transitional area could be characterized and showed similarity to a simple hypothesized model of land cover change. The comparison of fuzzy classifications was able to provide a richer information base on class membership and its dynamics than that obtainable through the comparison of conventional 'hard' classifications.

Indicators of land-cover change for change-vector analysis in multitemporal space at coarse spatial scales

Abstract Change-vector analysis in multi-temporal space is a powerful tool to analyse the nature and magnitude of land-cover change. The change vector compares the difference in the time-trajectory of a biophysical indicator for successive time periods. This change detection method is applied to three remotely-sensed indicators of land-surface conditions—vegetation index, surface temperature and spatial structure—in order to improve the capability to detect and categorize subtle forms of land-cover change. It is tested in a region of West Africa, using multi-temporal Local Area Coverage imagery obtained by the Advanced Very-High Resolution Radiometer on NOAA-9 and NOAA-II orbiting platforms. The three indicators show a low degree of redundancy and detect different land-cover change processes, which operate at different time scales. Change vector analysis is being developed for application to the land-cover change product to be produced using NASA's Moderate-Resolution Imaging Spectroradiometer instrument, scheduled for flight in 1998 and 2000on EOS-AM and -PM platforms.

Change-vector analysis in multitemporal space: A tool to detect and categorize land-cover change processes using high temporal-resolution satellite data

Analysis of change vectors in the multitemporal space, applied to multitemporal local area coverage imagery obtained by the Advanced Very-High Resolution Radiometer on NOAA-9 and NOAA-11 orbiting platforms, clearly reveals the nature and magnitude of land-cover change in a region of West Africa. The change vector compares the difference in the time-trajectory of a biophysical indicator, such as the normalized difference vegetation index, for two successive time periods, such as hydrological years. In establishing the time-trajectory, the indicator is composited for each pixel in a registered multidate image sequence. The change vector is simply the vector difference between successive time-trajectories, each represented as a vector in a multidimensional measurement space. The length of the change vector indicates the magnitude of the interannual change, while its direction indicates the nature of the change. A principal components analysis of change vectors for a Sudanian-Sahelian region in West Africa shows four major classes of change magnitude and four general contrasting types of change. Scene-specific changes, such as reservoir water level storage changes, are also identified. The technique is easily extended to other biophysical parameters, such as surface temperature, and can incorporate noneuclidean distance measures. Change vector analysis is being developed for application to the land-cover change product to be produced using NASA's Moderate-Resolution Imaging Spectroradiometer instrument, scheduled for flight in 1998 and 2000 on EOS-AM and -PM platforms.