Using Landsat data to determine land use changes in Datong basin,China

The aim of this study was to determine land use changes in Datong basin using multitemporal Landsat data for the period of 1977–2006. Four dates of Landsat images from 1977, 1990, 2000, and 2006 were selected to classify the study area. Based on the supervised classification method of maximum likelihood algorithm, images were classified into six classes: water, urban, forest, agriculture, wetland, and barren land. A multidate postclassification comparison change detection algorithm was used to determine changes in land use in four intervals. It is found that (1) urban land area increased 213% due to urbanization that resulted from rapid increase of urban population and high-speed economic development, (2) agriculture area increased 34.0% due to land reclamation that resulted from rapid increase of rural population and improvement of irrigation capacity, (3) forest area decreased 20.9% due to deforestation for urban area and agricultural use, (4) barren land area decreased 78.2% due to cultivation for agricultural use, and (5) water and wetland decreased 39.1 and 67.1%, respectively, due to exploitation of surface water and decrease of recharge from groundwater to surface water that resulted from over exploitation of groundwater.     

Implications of urban expansion on land use and land cover: towards sustainable development of Mega Manila,Philippines

GeoJournal - Planning of land use and infrastructure in advance for a population that is projected to grow rapidly is highly important for its sustainable development. A correlative approach of...     

Land use/land cover classification of the vicinity of Lake Chad using NigeriaSat-1 and Landsat data

Lake Chad in Africa experienced severe droughts in the 1970s and 1980s and overexploitations of water resulting in a decline of water level in the Lake and surrounding rivers. Such droughts and overexploitation of water caused a significant change of land use and water management practices over the last 50 years. Understanding the change of land use and land cover is, therefore, crucial to understand disturbance of the water cycle around the Lake. The present study analyzed satellite images of Lake Chad from Landsat-MSS, Landsat-TM, and NigeriaSat-1 to investigate the change of land cover during three time periods: the 1970s, 1991, and 2006. Unsupervised and supervised classifications were performed for the land cover analysis. The overall accuracies of the classification of Landsat-TM and NigeriaSat-1 are 93.33 and 95.24 %, respectively. It is evident that a 35 % decrease of waterbodies occurred from the 1970s to 1991, but a slight increase of 0.9 % occurred between 1991 and 2006. The Shrubland has overtaken most of the waterlog areas, as much as seven times of what it was in the 1970s. The interpretation of NigeriaSat-1 images indicates that NigeriaSat-1 has similar capabilities to Landsat-TM and Landsat-MSS for the detection of various land cover types because land cover and land use features are discernible on the processed images, especially depletion of waterbodies and vegetation. These are similarities justify the quality of the NigeriaSat-1 images for land cover and land use analysis.     

Probabilistic landslide hazards and risk mapping on Penang Island, Malaysia

This paper deals with landslide hazards and risk analysis of Penang Island, Malaysia using Geographic Information System (GIS) and remote sensing data. Landslide locations in the study area were identified from interpretations of aerial photographs and field surveys. Topographical/geological data and satellite images were collected and processed using GIS and image processing tools. There are ten landslide inducing parameters which are considered for landslide hazard analysis. These parameters are topographic slope, aspect, curvature and distance from drainage, all derived from the topographic database; geology and distance from lineament, derived from the geologic database; landuse from Landsat satellite images; soil from the soil database; precipitation amount, derived from the rainfall database; and the vegetation index value from SPOT satellite images. Landslide susceptibility was analyzed using landslide-occurrence factors employing the probability-frequency ratio model. The results of the analysis were verified using the landslide location data and compared with the probabilistic model. The accuracy observed was 80.03%. The qualitative landslide hazard analysis was carried out using the frequency ratio model through the map overlay analysis in GIS environment. The accuracy of hazard map was 86.41%. Further, risk analysis was done by studying the landslide hazard map and damageable objects at risk. This information could be used to estimate the risk to population, property and existing infrastructure like transportation network.     

Co-kriging for modeling shallow groundwater level changes in consideration of land use/land cover pattern

This study aimed at clarifying the relationship between the dynamics of land use/land cover (LULC) changes and decline in the groundwater levels, and specifying an LULC category strongly affecting such decline in a Quaternary sedimentary basin. Groundwater level data recorded at 26 observation wells for a 14-year period in the Kumamoto Plain, central Kyushu, southwest Japan, were used for the analysis. The general trends of LULC were detected by a satellite image classification technique and surface spline method, which highlighted the decreases in groundwater-recharge materials. As the next step, those trends of groundwater levels that were closely correlated with rainfall were removed from the level data set, and the resultant residual component levels were applied to co-kriging analysis with LULC categories. Co-kriging provided a detailed map of groundwater level variability. Furthermore, we propose a method, prediction of residual of groundwater level (PWL), to infer future residual groundwater levels from the supposed LULC pattern by co-kriging-based modeling. PWL was demonstrated to be effective because it clearly represented the decrease and increase in negative residual level areas, depending on the extent of rice fields in the past and in predicted future distribution scenarios.     

Monitoring land use/land cover change using multi-temporal Landsat satellite images in an arid environment: a case study of El-Arish,Egypt

Environment in arid conditions is dynamic and needs more investigation to understand the complexity of change. This spatiotemporal study will help to assess and monitor the land use and land cover change in the arid region of El-Arish area, where the climate and human activities are the major threats to rural development. In the past 11 years, dramatic changes of environment have been recorded in case studies. The post-classification comparison method was used to observe the changes using multi-temporal satellite images which were captured in the years 1999, 2001, 2005, and 2010. The overall accuracy of the produced thematic images was assessed regarding to the quantity and allocation disagreements. Five classes were defined in this investigation: bare soil, vegetation, urban, sand dunes, and fertile soil. From the year 1999 to 2010, fertile soil was increased by 13 %. Bare soil class occupied more than 50 % of land in the case study during for over a decade. From year 1999 to 2010, vegetation cover witnessed a dramatic increase. Soil and water management are the keys of land development and positive land use and land cover dynamics. Changing agricultural policies of using the available water resources are needed in the case study to prevent severe food shortage in the future.     

The relationship between land surface temperature and land use/land cover in Guangzhou,China

The integration of remote sensing, geographic information system, landscape ecology and statistical analysis methods was applied to study the urban thermal environment in Guangzhou. Normalized Difference Vegetation Index (NDVI), Normalized Difference Build-up Index (NDBI), Normalized Difference Barren Index (NDBaI) and Modified Normalized Difference Water Index (MNDWI) were used to analyze the relationships between land surface temperature (LST) and land use/land cover (LULC) qualitatively. The result revealed that, most urban built-up lands were located in the middle part, and high LST areas mostly and were in the middle and southern parts. Therefore, the urbanization and thermal environment in the middle and southern parts need to be determined. Land surface temperature increased with the density of urban built-up and barren land, but decreased with vegetation cover. The relationship between MNDWI and LST was found to be negative, which implied that pure water would decrease the surface temperature and the polluted water would increase the surface temperature. A multiple regression between LST and each indices as well as the elevation was created to elevate the urban thermal environment, which showed that NDVI, NDBI, NDBaI, MNDWI were effective indicators for quantifying LULC impacts on LST.     

Dynamics of land use/cover changes and the analysis of landscape fragmentation in Dhaka Metropolitan, Bangladesh

Rapid urban expansion due to large scale land use/cover change, particularly in developing countries becomes a matter of concern since urbanization drives environmental change at multiple scales. Dhaka, the capital of Bangladesh, has been experienced break-neck urban growth in the last few decades that resulted many adverse impacts on the environment. This paper was an attempt to document spatio-temporal pattern of land use/cover changes, and to quantify the landscape structures in Dhaka Metropolitan of Bangladesh. Using multi-temporal remotely sensed data with GIS, dynamics of land use/cover changes was evaluated and a transition matrix was computed to understand the rate and pattern of land use/cover change. Derived land use statistics subsequently integrated with landscape metrics to determine the impact of land use change on landscape fragmentation. Significant changes in land use/cover were noticed in Dhaka over the study period, 1975–2005. Rapid urbanization was manifested by a large reduction of agricultural land since urban built-up area increased from 5,500?ha in 1975 to 20,549?ha in 2005. At the same time, cultivated land decreased from 12,040 to 6,236?ha in the same period. Likewise, wetland and vegetation cover reduced to about 6,027 and 2,812?ha, respectively. Consequently, sharp changes in landscape pattern and composition were observed. The landscape became highly fragmented as a result of rapid increase in the built-up areas. The analysis revealed that mean patch size decreased while the number of patches increased. Landscape diversity declined, urban dominance amplified, and the overall landscape mosaics became more continuous, homogenous and clumped. In order to devise sustainable land use planning and to determine future landscape changes for sound resource management strategies, the present study is expected to have significant implications in rapidly urbanizing cities of the world in delivering baseline information about long term land use change and its impact on landscape structure.     

The impact of land use and land cover changes on soil erosion in western Iran

Natural Hazards - Analysis of long-term land use and land cover (LULC) changes requires up-to-date remotely sensed data to assess their effects on erosion. This is a particularly important...     

Long term changes in forest cover and land use of Similipal Biosphere Reserve of India using satellite remote sensing data

The spatial changes in forest cover of Similipal biosphere reserve, Odisha, India over eight decades (1930–2012) has been quantified by using multi-temporal data from different sources. Over the period, the forest cover reduced by 970.8 km² (23.6% of the total forest), and most significantly during the period, 1930–1975. Human-induced activities like conversion of forest land for agriculture, construction of dams and mining activities have been identified as major drivers of deforestation. Spatial analysis indicates that 399 grids (1 grid = 1 × 1 km) have undergone large-scale changes in forest cover (>75 ha) during 1930–1975, while only 3 grids have shown >75 ha loss during 1975–1990. Annual net rate of deforestation was 0.58 during 1930–1975, which has been reduced substantially during 1975–1990 (0.04). Annual gross rate of deforestation in 2006–2012 is indeed low (0.01) as compared to the national and global average. This study highlights the impact and effectiveness of conservation practices in minimizing the rate of deforestation and protecting the Similipal Biosphere Reserve.     

Monitoring and prediction of land use/land cover changes using CA-Markov model: a case study of Ravansar County in Iran

Human‐induced land use/land cover (LULC) changes are among the most important processes that shape the dynamics of the earth’s surface. This phenomenon, which is occurring at an astonishing rate, and its consequential environmental impacts have become an important area of research for scientists.Therefore, a wide range of methods and models have been developed to detect and predict these alterations, among which cellular automata (CA) models such as the CA‐Markov model, due to their affinity to geographic information system (GIS) and remote sensing (RS), are appropriate for detailed resolution modelling and simulating dynamic spatial processes. In Iran, the district of Ravansar has undergone severe LULC changes recently, thus to take the necessary precautions, decision‐makers need to predict and determine the extent of these changes. In this study, using spatial analysis methods the LULC changes in Ravansar were investigated from 1992 to 2015. Subsequently, the CA‐Markov model was applied to simulate the spatial pattern changes of LULC until 2030. Our results indicated that from 1992 to 2015, this region has witnessed a noticeable increase in the areas of the built‐up and agricultural lands (both aquatic and non‐aquatic), resulting in the decrease of the gardens, range, and bare lands. The simulated LULC map showed that this trend will continue due to more urbanization and development of agricultural areas.     

整合陆地表面温度与植被指数信息进行地表覆盖变化研究

利用植被指数(NDVI)的多时相或时序资料进行地表覆盖研究已取得了大量成果。随着陆地表面温度(LST)遥感反演精度的不断提高,将LST与NDVI结合起来进行地表植被动态变化的监测已成为可能。选择我国北方草地及其东南部毗邻的农牧交错带(farmingpastoralzone)为研究区。该区位于内蒙古高原东南边缘和黄土高原北部,半干旱气候,经纬度范围为:35°～50°N,100°～125°E。     

Dynamics of land surface temperature (LST) in response to land use and land cover (LULC) changes in the Weigan and Kuqa river oasis,Xinjiang, China

Land use and land cover (LULC) changes caused by human activities have strong influences on regional environment. Land surface temperate plays an important role in studying the impact of LULC changes on regional environment. In this paper, remotely sensed thermal infrared data were used to assess land surface temperature (LST) in the Weigan and Kuqa river oasis, Xingjiang, one of the important agricultural areas in the northwestern China. The present study deals with the extraction of LST and the relationship between LULC changes using Landsat 5 TM acquired on September 25, 1989, and September 6, 2011. The results indicate that the surface temperature of water body, bare land, and desert changed significantly between 1989 and 2011. In general, the LST was lower in 1989 than in 2011. There were no lower, higher, and highest temperature zones in 1989. However, the minimum temperature was 10.7 °C in 1989 and 15.8 °C in 2011. The maximum temperature was 29.3 °C in 1989 and 41.8 °C in 2011. Regarding the LULC types, the desert features in the Gobi Desert warmed more quickly than the oasis. So, the temperature of the oasis was lower than the surrounded areas, resulting in a so-called “cold island” phenomenon. Oasis cold island effect index (OCIEI) shows that stability of oasis had rising trend from 1989 to 2011. In addition, the impact of LULC changes on LST was analyzed and the driving forces were also analyzed from 1977 to 2011. This study is significant for further understanding of the energy exchange status of soil-plant-atmospheric system and the regional heat distribution in arid and semi-arid areas of the northwest China.     

Effects of land use/cover change on atmospheric humidity in three urban agglomerations in the Yangtze River Economic Belt,China

Natural Hazards - Land use/cover change (LUCC) affects regional climate not only through its direct changes of land surface properties, but also through its further modifications of...     

Changing land use/land cover patterns and growing human population in Wular catchment of Kashmir Valley,India

GeoJournal - The profound increase in human activities and the degrading scenario in fragile ecosystems of the western Himalayas like that of Wular Lake have highlighted the need to analyze the...     

Delineation of landslide hazard areas on Penang Island, Malaysia, by using frequency ratio, logistic regression, and artificial neural network models

This paper summarizes findings of landslide hazard analysis on Penang Island, Malaysia, using frequency ratio, logistic regression, and artificial neural network models with the aid of GIS tools and remote sensing data. Landslide locations were identified and an inventory map was constructed by trained geomorphologists using photo-interpretation from archived aerial photographs supported by field surveys. A SPOT 5 satellite pan sharpened image acquired in January 2005 was used for land-cover classification supported by a topographic map. The above digitally processed images were subsequently combined in a GIS with ancillary data, for example topographical (slope, aspect, curvature, drainage), geological (litho types and lineaments), soil types, and normalized difference vegetation index (NDVI) data, and used to construct a spatial database using GIS and image processing. Three landslide hazard maps were constructed on the basis of landslide inventories and thematic layers, using frequency ratio, logistic regression, and artificial neural network models. Further, each thematic layer’s weight was determined by the back-propagation training method and landslide hazard indices were calculated using the trained back-propagation weights. The results of the analysis were verified and compared using the landslide location data and the accuracy observed was 86.41, 89.59, and 83.55% for frequency ratio, logistic regression, and artificial neural network models, respectively. On the basis of the higher percentages of landslide bodies predicted in very highly hazardous and highly hazardous zones, the results obtained by use of the logistic regression model were slightly more accurate than those from the other models used for landslide hazard analysis. The results from the neural network model suggest the effect of topographic slope is the highest and most important factor with weightage value (1.0), which is more than twice that of the other factors, followed by the NDVI (0.52), and then precipitation (0.42). Further, the results revealed that distance from lineament has the lowest weightage, with a value of 0. This shows that in the study area, fault lines and structural features do not contribute much to landslide triggering.     

Urban land use transformation and determinants of urban land use size in China

Astract Recent economic reforms and shifts in land use planning in China have greatly changed the size and structure of urban land use. In this paper, an overview of the problems in urban land use and the impacts of economic reforms and planning policies on rapid urban land expansion and structural transformation is outlined. This is followed by statistical analyses to reveal determinants of urban land size. The study shows that urban land use in China has been improved, and urban land use size is related to urban reforms, urban land use adjustment, as well as to population growth and economic development.