Land Use And Land Cover Change Change Research Articles

Climate change driven by LUCC reduced NPP in the Yellow River Basin, China

Anthropogenic activities and the resulting climate change affect the type, structure, and function of ecosystems. Understanding vegetation dynamics related to anthropogenic activities and climate change is critical to address the terrestrial carbon cycle in the context of global warming. The objective of this study is to quantify the effects of human-induced land use and land cover change (LUCC) and LUCC-induced climate change on terrestrial net primary productivity (NPP) in the Yellow River Basin (YRB) during 2000–2020 using Weather Research and Forecasting (WRF) model and Integrated Biosphere Simulator (IBIS) model through different experimental scenarios. Results indicated that LUCC can cause an increase in NPP of 1.2 ± 0.67 gC m−2 yr−1 in YRB. The increased precipitation and decreased temperature due to LUCC showed weak negative effect on annual mean NPP in YRB (−0.2 ± 0.74 gC m−2 yr−1). The coupling of LUCC and LUCC-induced climate change increased annual mean NPP approximately 0.6 ± 0.86 gC m−2 yr−1. The impacts of LUCC and LUCC-induced climate change and their coupling effects on NPP were greatest in spring, increasing NPP by 5.1 ± 0.51, 3.4 ± 0.41, and 6.1 ± 0.79 gC m−2 yr−1, respectively. These findings provide important guidance for the sustainable and adaptive management of terrestrial ecosystems in river basin in the context of global change.

Mapping land-use and land-cover changes through the integration of satellite and airborne remote sensing data.

An integrated, remotely sensed approach to assess land-use and land-cover change (LULCC) dynamics plays an important role in environmental monitoring, management, and policy development. In this study, we utilized the advantage of land-cover seasonality, canopy height, and spectral characteristics to develop a phenology-based classification model (PCM) for mapping the annual LULCC in our study areas. Monthly analysis of normalized difference vegetation index (NDVI) and near-infrared (NIR) values derived from SPOT images enabled the detection of temporal characteristics of each land type, serving as crucial indices for land type classification. The integration of normalized difference built-up index (NDBI) derived from Landsat images and airborne LiDAR canopy height into the PCM resulted in an overall performance of 0.85, slightly surpassing that of random forest analysis or principal component analysis. The development of PCM can reduce the time and effort required for manual classification and capture annual LULCC changes among five major land types: forests, built-up land, inland water, agriculture land, and grassland/shrubs. The gross change LULCC analysis for the Taoyuan Tableland demonstrated fluctuations in land types over the study period (2013 to 2022). A negative correlation (r = - 0.79) in area changes between grassland/shrubs and agricultural land and a positive correlation (r = 0.47) between irrigation ponds and agricultural land were found. Event-based LULCC analysis for Taipei City demonstrated a balance between urbanization and urban greening, with the number of urbanization events becoming comparable to urban greening events when the spatial extent of LULCC events exceeds 1000 m2. Besides, small-scale urban greening events are frequently discovered and distributed throughout the metropolitan area of Taipei City, emphasizing the localized nature of urban greening events.

EVALUATION AND PREDICTION OF LAND USE, AND LAND COVER CHANGES USING REMOTE SENSING AND CA-ANN MODEL IN HUONG HOA DISTRICT, QUANG TRI PROVINCE

Evaluation of land use and land cover change (LULC) is necessary for densely vegetated areas like Huong Hoa district, Quang Tri province. It is a basis for sustainable development strategies. Therefore, the study aims to evaluate the LULC change in the 10-year period of 2013–2023 by using Landsat 8 satellite image data with the Maximum Likelihood Classification method and to predict future LULC changes. The LULC maps for 2013, 2018, and 2023 are accurate, with Kappa coefficients of 0.82–0.85. In the period of 2013–2023, the dense vegetation area tended to decrease by 1.4%. The decrease was mainly due to the transition to sparse vegetation cover. Bare land increased by 0.5%, and the built-up area decreased by 0.6%. Meanwhile, the water bodies changed slightly. The prediction of LULC change with the CA-ANN model in the QGIS MOLUSCE plugin is based on the history of LULC change and two spatial variables: DEM and distance to the road. The accuracy of the CA-ANN model is satisfactory, with an overall accuracy of 86% and a Kappa coefficient of 0.76. In the simulated LULC of 2033, dense vegetation is predicted to keep a higher decrease (2%) in the area compared with the LULC of 2023. Sparse vegetation steadily increased by 1.3% over the subsequent 10 years. Similarly, the built-up area, water boddies, and bare land extended slightly by 0.5, 0.1, and 0.1%, respectively. The CA-ANN model in the QGIS MOLUSCE plugin is suitable for the simulated LULC changes for the studied area.

Assessing the potential impacts of LULC change on urban air quality in Dhaka city

Dhaka is among the top five metropolises with the most particulate pollution and polluted air alone, responsible for 17.6% of the risk of mortality and disability. As a result of recent global episodes of urban air pollution, policymakers and administration agencies are endeavoring to regulate urban land use and land cover change (LULC) and sustainably enhance air quality. This study aims to establish a relationship between alterations in PM2.5 concentration and LULC features. The Bangladesh Meteorological Department provided PM2.5 and meteorological data for 2012 and 2018, and RapidEye image data was used to classify land-use for 2012 and 2018. Between 2012 and 2018, waterbodies and vegetation fell by 2% and 5.3%, and construction and bare land increased by 4% and 3.4%, respectively. Reduced vegetation and waterbodies might result in an increase in barren land and built-up areas. Numerous industrial sites and the unlawful acquisition of canals may also contribute to the growth of barren land. In 2018, homogeneity of the landscape pattern is higher than 2011. The aggregation and contagion indices, landscape metrices, have inverse correlation of −0.01 and −0.158 respectively with PM2.5 concentrations. However, the landscape index has positive correlation of 0.06 with PM2.5 concentrations. On the other hand, the variability in PM2.5 concentrations is correlated with the altered characteristics of LULCs and related landscape indicators. According to the spatial correlation, PM2.5 levels have decreased as vegetation and waterbodies have increased, as the PM2.5 concentration is negatively correlated with vegetation and waterbodies by −0.212 and −0.028, respectively. Furthermore, meteorological indices are significantly correlated with PM2.5 concentration, which was used as an independent variable to estimate the annual average PM2.5 concentration levels for 2024 using an Artificial Neural Network, which range from 312 to 188 μg/m3. The government should take appropriate measures to curb polluting air emissions, ensuring a livable city in the future.

Using CORONA Imagery to Study Land Use and Land Cover Change—A Review of Applications

CORONA spy satellites offer high spatial resolution imagery acquired in the 1960s and early 1970s and declassified in 1995, and they have been used in various scientific fields, such as archaeology, geomorphology, geology, and land change research. The images are panchromatic but contain many details of objects on the land surface due to their high spatial resolution. This systematic review aims to study the use of CORONA imagery in land use and land cover change (LULC) research. Based on a set of queries conducted on the SCOPUS database, we identified and examined 54 research papers using such data in their study of LULC. Our analysis considered case-study area distributions, LULC classes and LULC changes, as well as the methods and types of geospatial data used alongside CORONA data. While the use of CORONA images has increased over time, their potential has not been fully explored due to difficulties in processing CORONA images. In most cases, study areas are small and below 5000 km2 because of the reported drawbacks related to data acquisition frequency, data quality and analysis. While CORONA imagery allows analyzing built-up areas, infrastructure and individual buildings due to its high spatial resolution and initial mission design, in LULC studies, researchers use the data mostly to study forests. In most case studies, CORONA imagery was used to extend the study period into the 1960s, with only some examples of using CORONA alongside older historical data. Our analysis proves that in order to detect LULC changes, CORONA can be compared with various contemporary geospatial data, particularly high and very high-resolution satellite imagery, as well as aerial imagery.

Assessment of land use and land cover change on Gum Talha (Acacia seyal var. seyal) forest in Bahar Alarab, Sudan

Abstract. Younis AYI, Jonathan BN, Togun AO, Yasin EHE, Omer SO, Hamad GAI, Aissata SD. 2022. Assessment of land use and land cover change on Gum Talha (Acacia seyal var. seyal) forest in Bahar Alarab, Sudan. Biodiversitas 23: 4549-4560. Evaluating land use and land cover change (LULC) is essential for the sustainable management of natural resources, biodiversity conservation, monitoring of food security, and research related to climate change and ecology. A better assessment of land-use changes is highly needed for further investigation due to increasingly rapid changes in LULC in response to human population growth. The emerging climatic change also has a significant effect on LULC. The objective of this study is to assess land use and land cover in Bahar Alarab, East Darfur State, Sudan, using remote sensing data obtained from satellite images. For assessing the LULC changes, Landsat images of the years 1988, 2002, and 2020 were downloaded and analyzed using QGIS 3.22.1 and ERDAS 2014 software, where supervised classification was applied with GPS point verification, change detection, matrix, and accuracy assessment. The analysis on LULC showed considerable changes during the two study periods, where 2020 had a considerable increase in forest cover in which on that year it occupied 26.44% of the area compared to 2002 and 1988 with 21.27% and 21.45%, respectively. Whereas 2002 the area was covered by a vast herbaceous vegetation (33.41%) compared to 1988 and 2002. Moreover, in 1988, shrubland decreased from 31.95% to 29.06% and 23.67% in 2020 and 2002, respectively. Sparse vegetation covered a considerable area in 2020 (23.61%) compared to 2002 and 1988 (21.65% and 17.71%, respectively). The results highlighted that there was statistically significant correlation between climate factors and LULC. Average temperature was highly positively correlated with sparse vegetation at 98.2%, while rainfall was highly negatively correlated with forest (-96.9%) and sparse vegetation (-88%), and highly positively correlated with herbaceous vegetation (83.5%). This study provides a unique understanding of LULC changes and their implications in management and conservation efforts, as well as a road map for decision makers for sustainable development of LULC in the Bahar Alarab.

Stability of soil organic carbon pools affected by land use and land cover changes in forests of eastern Himalayan region, India

Forests are among the largest terrestrial carbon pools that are most vulnerable to land use and land cover change (LULC). Therefore, it is essential to manage forest ecosystems to enhance soil organic carbon (SOC) pools and soil functionality. The present study was carried out to analyze C stability and change in SOC stock under different forest types in the eastern Himalayan region of India. Topsoil (0–15 and 15–30 cm) samples from six dominant forests i. e. tropical wet evergreen, montane subtropical, temperate, Quercus, bamboo, and shifting cultivation (Jhum) lands were collected and analyzed for selected soil properties and SOC stock. Active (very labile + labile), slow (less labile), and passive (non-labile) C fractions were also analyzed to determine the stability of the SOC pool under the LULC scenario. Results show that the percentage contribution of active C to total organic carbon in topsoil was highest in a temperate forest (74.1%) while lowest in a bamboo forest (48.1%). Unlike, slow C (18.4%) and passive C (26.6%) were highest in Quercus forest. Pearson correlation analysis shows significant positive relation of active and slow C pool with SOC and total nitrogen concentration. The estimates of SOC stock (0–30 cm) were significantly higher in temperate forests (132.7 Mg C ha−1). However, the conversion of natural forests to bamboo forest and jhum land reduced SOC stock by 29% and 68%, respectively. C lability index shows higher labile C in jhum land while recalcitrancy index was highest in a bamboo forest. Our study concluded that LULC change significantly altered the stability and stock of SOC in natural forests. Owing to a higher percentage of slow and passive C pools, Quercus forests play a major role in C sink management.

Assessment of Land Use and Land Cover Changes on Soil Erosion Using Remote Sensing, GIS and RUSLE Model: A Case Study of Battambang Province, Cambodia

Soil erosion causes land degradation which negatively impacts not only natural resources but also livelihoods of people due to low agricultural productivity. Cambodia is prone to soil erosion due to poor agricultural practices. In this research we use Battambang province as a case study to quantify impact of land use and land cover change (LULC) on soil erosion. This study assessed the impact from LULC changes to soil erosion. LULC change maps were analyzed based on Landsat satellite imagery of 1998, 2008, and 2018, computed in QGIS 6.2.9, while the soil erosion loss was estimated by the integration of remote sensing, GIS tools, and Revised Universal Soil Loss Equation (RUSLE) model. The results showed that the area of agricultural land of Battambang province significantly increased from 44.50% in 1998 to 61.11% in 2008 and 68.40% in 2018. The forest cover significantly decreased from 29.82% in 1998 to 6.18% in 2018. Various soil erosion factors were estimated using LULC and slope. Based on that, the mean soil loss was 2.92 t/ha.yr in 1998, 4.20 t/ha.yr in 2008, and 4.98 t/ha.yr in 2018. Whereas the total annual soil loss was 3.49 million tons in 1998, 5.03 million tons in 2008, and 5.93 million tons in 2018. The annual soil loss at the agricultural land dramatically increased from 190,9347.9 tons (54%) in 1998 to 3,543,659 tons (70.43%) in 2008 and to 4,267,439 tons (71.91%) in 2018 due to agricultural land expansion and agricultural practices. These losses were directly correlated with LULC, especially agricultural land expansion and forest cover decline. Our results highlight the need to develop appropriate land use and crop management practices to decrease land degradation and soil erosion. These data are useful to bring about public awareness of land degradation and alert local citizens, researchers, policy makers, and actors towards land rehabilitation to bring the area of land back to a state which is safe for increasing biodiversity and agricultural productivity. Measures to reduce or prevent soil erosion and the use of conservation agriculture practices, along with water and soil conservation, management, agroforestry practices, vegetation cover restoration, the creation of slope terraces, and the use of direct sowing mulch-based cropping systems should be considered.

Coastal land use and shoreline evolution along the Nador lagoon Coast in Morocco

The coastal zone, a highly dynamic and complex environment, has important ecological and jurisdictional implications for governments and coastal managers. Based on the CORINE Land Cover classification system, this paper examined the effects of land use and land cover change (LULC) on the coastlines' dynamics along the ∼24 km barrier island of Nador lagoon on the Mediterranean coast of Morocco during a period of 62 years (1954–2016). The study utilized high-resolution orthoimages in the geographic information system (GIS) environment to characterize coastline evolution and LULC changes. The evolution of the coastline was assessed using a GIS tool, in particular the Digital Shoreline Analysis System (DSAS). The net rates of coastline change were calculated by using statistical methods: the End Point Rate (EPR) and the Linear Regression Rate (LRR). Results concerning the LULC changes showed that agricultural area and beach/dune classes decreased over the entire study period (62 years) by 11.14% and 28.45%, respectively. Urban fabric, shrub, forest, and saltmarsh/peat bog classes increased during the 62 years of evaluation by 2.69%, 19.92%, 16.77%, and 0.19%, respectively. Results regarding coastal analysis indicated that the accretion and erosion processes along the barrier island of the Nador lagoon (∼24km) were observed at 45% (10.6 km) and 55% (12.8 km) of the coastline, respectively. The beaches of Oulad Zehra and Oulad Aissa were characterized by erosion (−0.58 m/yr to −0.57 m/yr respectively), while accretion was observed on the beaches of Boukana and Kariat Arkmane at rates of +2.15 m/yr and +0.82 m/yr, respectively. This study highlighted that natural and anthropogenic processes have a strong influence on the erosion/accretion trends identified along the barrier island of Nador lagoon. The changes in LULC have affected the barrier island of the lagoon in two different forms: (1) a significant spatial conversion due to dune reforestation and (2) a fundamental spatial modification that affects the sea-lagoon connection (inlet) and the construction of new hard engineering structures.

Assessment of the impact of LUCC on NPP and its influencing factors in the Yangtze River basin, China

Land use and land cover change (LUCC) will directly affect the types, structures and functions of ecosystems, and then have important impact on vegetation net primary productivity (NPP). The evaluation of the spatio-temporal dynamic changes of LUCC and regional NPP, and assessing the impact of LUCC on NPP can facilitate the corresponding management of different environmental types of regions and provide scientific guidance for scientific development of ecological resources, and better restore and control the ecological environment, thus promoting rapid economic development. Using MODIS normalized difference vegetation index (NDVI) data and meteorological data from 2001 to 2018, combined with Carnegie-Ames-Stanford model (CASA), the regional NPP was estimated, and the influence of LUCC on NPP in Yangtze River basin from 2001 to 2018 and its causes were analyzed. The results showed that the area with a land cover and land use change account for 10.98% of the total study area in the past 18 years, and the most important change is the transformation from grassland to forest and grassland to crop/natural vegetation mosaic (NVM). Forests, wetlands, crop/natural vegetation mosaic, low vegetation cover (LVC) land, urban, and water bodies are growing. The forest land area increased the most and that of grassland decreased the most. Total NPP has increased by 53887.51GgC in the past 18 years, which was due to the combination effect of LUCC change and climate change.

Population Growth and Land Use Land Cover Change Scenario in Ethiopia

Land use and land cover change (LULC) is widespread, accelerating, and significant processes driven by human actions but also producing changes that impact humans. These changes can alter the availability of different biophysical resources including soil, vegetation, water, animal feed and finally it leads to a decreased availability of different products and services for human, livestock, agricultural production and damage to the environment as well. Understanding land use land cover change with relation to population growth at various scales is vital for development of management strategies to tackle further decline of natural resources. In connection to this, a seminar paper was done to assess the relationship between population growth and land use land cover change in Ethiopia. Recently published articles, books, proceedings, dissertations and government reports were used as a secondary data source for this review paper. The result reveals that in Ethiopia there were considerable LULC changes in the second half of 20th century particularly in the highland part of the country. Forest and woodlands coverage of the country was declined from 40% in the early 20th century to 15%. Similarly, the population was rapidly growing from 41.2 million in 1985 to 63.5 million in 2000 and it was reached 96.6 million in 2015. Based on these results it can be concluded that, LULC change and population change have a strong relationship; as population increases the need for cultivated land, grazing land, fuel wood; settlement areas also increases to meet the growing demand for food and energy, and livestock population. Similarly, rapid population growth exerts pressure on the existing land resources through increasing the demand for food, wood for fuel and construction purposes, and other necessities.

LUCC及气候变化对澜沧江流域径流的影响

PDF HTML阅读 XML下载 导出引用 引用提醒 LUCC及气候变化对澜沧江流域径流的影响 DOI: 10.5846/stxb201811302610 作者: 作者单位: 云南省气象服务中心,云南省气候中心,云南大学,云南省气象服务中心,南京信息工程大学,云南省气候中心,南京信息工程大学 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目（41665005，41765003）；中国气象局气候变化专项（CCSF201736） Impacts of LUCC and climate change on runoff in Lancang River Basin Author: Affiliation: Yunnan Meteorological Service Center,Yunnan Provincial Climate Center,,,,, Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:运用SWAT模型，通过设置不同情景，定量分析了澜沧江流域土地利用与土地覆被变化（Land Use and Land Cover Change，LUCC）和气候变化对径流的影响，并结合RCP4.5、RCP8.5两种排放情景对流域未来径流的变化进行预估。结果表明：SWAT模型在澜沧江流域径流模拟中具有很好的适用性，率定期和验证期的模型参数R2分别达到0.80、0.74，Ens分别达到0.80、0.73；从土地利用变化方面考虑，流域内的农业用地转化为林地或草地，均会导致径流量的减少，而林地转化为草地则会引起径流量的增加，农业用地、林地、草地三者对径流增加贡献顺序为农业用地 > 草地 > 林地，从气候变化方面考虑，流域内的径流量与降雨量成正比，与气温成反比；2006-2015年间澜沧江流域气候变化引起的月均径流减少幅度强于LUCC引起的月均径流增加幅度，径流变化由气候变化主导；在RCP4.5和RCP8.5两种排放情景下，2021-2050年间澜沧江流域的径流均呈增加趋势，这与1971-2015年间流域实测径流的变化趋势相反。 Abstract:Using the SWAT (Soil and Water Assessment Tools) model, the impacts of LUCC (land use and land cover change) and climate change on runoff in Lancang River Basin were quantitatively analyzed by setting different scenarios. The future runoff changes were predicted with RCP4.5 and RCP8.5 emissions scenarios in Lancang River Basin. The results showed that the SWAT model had good applicability in runoff simulation of Lancang River Basin. The model parameters R2 of calibration and validation periods were 0.80 and 0.74, respectively. The model parameters Ens of calibration and validation periods were 0.80 and 0.73, respectively. Considering the land use change, the conversion of farmland into woodland or grassland would reduce basin runoff, but the conversion of woodland into grassland would increase basin runoff. The contribution to basin runoff from big to small was farmland, grassland, and woodland. Regarding climate change, the basin runoff was proportional to rainfall, but inversely proportional to temperature. The reduction of monthly runoff caused by climate change was stronger than the increment caused by LUCC in Lancang River Basin from 2006 to 2015. Therefore, runoff change was dominated by climate change. The runoff in Lancang River Basin in both RCP4.5 and RCP8.5 emissions scenarios would increase from 2021 to 2050, which is contrary to the measured basin runoff from 1971 to 2015. 参考文献 相似文献 引证文献

Land use/cover changes and prediction of Dodoma, Tanzania

The primary objective of this paper is to analyze the past and present changes of Dodoma region and also predict the future changes using the Landsat satellite images of 1998, 2008 and 2018. In this study, land use and land cover change (LULC) is examined using remote sensing and Markov chains analysis. The study first uses remote sensing to detect LULC changes and then based on the result of classification images, predicts the 2030 LULC using Markov chains analysis. The results of the net change between 1998 and 2018 show that built-up land increased by 2221 ha, bare land by 15,737 ha and vegetation declined by 17,958 ha. Markov prediction to 2030 based on land use and land cover maps of 2008 and 2018 show that bare land has a high probability (0.61) of maintaining its current status in 2030. However, vegetation only has a probability of 0.41 for maintaining its current state, and it could convert to bare land at a probability of 0.43 and to built-up land at a probability of 0.015. The transition probabilities illustrate that most of the LULC are oriented towards the increase of the bare land and built-up land.

Assessment of Land-use and Land-cover Change and its Impact on Groundwater Quality Using Remote Sensing and GIS Techniques in Raipur City, Chhattisgarh, India

Abstract Monitoring of land use and land cover change (LULC) is essential for water conservation and management. In this study, an attempt has been made to understand the impact of LULC change on groundwater quality. In the present study LULC map of the study area prepared using satellite image of year 1999 and 2016 which are visually interpreted with help of ERDAS IMAGINE and ArcGIS software. In this study different image interpretation elements like tone, texture, size, pattern and association were used and verified with field check and total eight LULC classes were recognized such as settlement, road, cultivation, industry, drainage, lake, open land and vegetation. Comparison of LULC of year 1999 and year 2016 indicates that the settlement (net increases 16.2%), road (net increases 0.8%), open land (net increases 14.8%) and industry (net increases 3.1%) area has expanded. In the study area groundwater pollution is mainly associated with LULC change and as well as poor waste management practices. Obtained result has been validated with nitrate concentration and found 73.33% accuracy reflecting that, applied techniques has produced significantly reliable results.

Assessment of ecological risks induced by land use and land cover changes in Xiamen City, China

ABSTRACTThe landscape ecological risk (LER) in Xiamen City, China, from 1990 to 2030 was studied using an urban land use and land cover change (LUCC) model and LER analysis. The LUCC model was used to predict the LUCC of Xiamen from 2020 to 2030. We analyzed the characteristics of LUCC and landscape pattern changes and, finally, evaluated the effect of rapid LUCC on LER. Of the six landscape types investigated, built-up land and farmland demonstrated the most significant changes. The area of built-up land increased by 1.5 times in 2010 and is predicted to increase by 2.7 times in 2030 than that in 1990. The area of farmland increased from 34.5% in 1990 to 24.5% in 2010 and is predicted to decrease to 15.1% in 2030. The number of patches (NP) of built-up land decreased with increasing area, which promoted the dominance of built-up land over other landscape types. Five landscape types, those other than built-up land, increased in NP, landscape fragmentation, segmentation, and disturbance but decreased in dominance. The LER of Xiamen in 2010 was slightly lower than that in 1990. However, with the acceleration of urbanization, the LER in 2020 and 2030 will increase by 7.6% and 12.5% than that in 2010. The LER will significantly increase in areas such as the Huandong sea area, the second urban core of Xiamen, and northern Xiang'an. For the areas, some measures (e.g. optimum urban spatial growth patterns and control of coastal reclamation) must inevitably increase to reduce the LER posed by rapid urbanization.

Hydrologic Impact Evaluation of Land Use and Land Cover Change in Palico Watershed, Batangas, Philippines Using the SWAT Model

Information on the relationship between hydrologic response and land use and land cover change (LULC) is vital for proper management of water resources and land use planning. This study aimed to evaluate the impact of LULC on the hydrologic characteristics of Palico watershed in Batangas, Philippines using the Soil and Water Assessment Tool (SWAT) model. Model inputs used were the 1989 and 2013 LULC maps and climatological and hydrologic data. Good agreement was obtained between simulated and observed streamflow values during model calibration (NSE=0.84 & R2=0.86), and validation (NSE=0.61 & R2=0.68). For the entire watershed, reduction in forest cover and rangeland resulted to an increase in surface runoff and decreases in baseflow or dry season flow and groundwater recharge. LULC changes affected the water quantity and timing of occurrence. Subbasin with 22% increase in forest cover and rangeland increased the baseflow by 1% to 15% and reduced the streamflow by 1% to 17% during the rainy months. Another subbasin with 54% forest loss resulted to more pronounced rainfall-runoff response with 11% to 17% decrease in baseflow and 4% to 24% increase in streamflow during rainy months. Finding the balance between these two opposite LULC change scenarios is crucial for the attainment of water security and sustainability in the watershed and in the areas it serves.

Linking long-term landscape dynamics to the multiple interactions among ecosystem services in the European Alps

Human driven land-use and land-cover change (LULC) is considered to be among the greatest ecological pressures in mountain regions. Over the past century, across the European Alps, extensive LULC changes have been observed, affecting ecosystem goods and services (ESs). For eight case study sites across the Alpine arc we aimed to provide a spatiotemporal explicit assessment of the impacts of LULC dynamics on ES provision and interactions, including cultivated crops, plant material, climate regulation, soil erosion control and aesthetics. We quantified ES provision in biophysical terms at four time periods (1850, 1955, 1985, 2005) using spatially explicit LULC based assessment models. ES interactions were identified by statistically analyzing the spatiotemporal pattern among ES capacities. Over the past century forested areas have increased mainly at the cost of grasslands, while on easily accessible sites and fertile valley floors agricultural intensification occurred. ES provision shifted between 1850 and 2005, from a predominance of production ESs in 1850 to a landscape characterized by regulating ESs in 2005. Spatiotemporal analyses of ES interactions revealed trade-offs between regulating and cultural ESs and within the provisioning ES bundle and allowed to derive three different ES trajectories: regions developing from single to multifunctional sites in terms of service provision, sites reducing their service capacities and sites with rather stationary patterns over broad time periods. We demonstrated that ES capacities in complex agro-ecological mountain regions are highly sensitive to long-term landscape dynamics. We conclude that assessing ES capacities and interactions in an explicitly spatiotemporal manner can help to guide evidence-based environmental measures.

Impact of Land-Use and Land-Cover Change on urban air quality in representative cities of China

The atmospheric particulate pollution in China is getting worse. Land-Use and Land-Cover Change (LUCC) is a key factor that affects atmospheric particulate pollution. Understanding the response of particulate pollution to LUCC is necessary for environmental protection. Eight representative cities in China, Qingdao, Jinan, Zhengzhou, Xi’an, Lanzhou, Zhangye, Jiuquan, and Urumqi were selected to analyze the relationship between particulate pollution and LUCC. The MODIS (MODerate-resolution Imaging Spectroradiometer) aerosol product (MOD04) was used to estimate atmospheric particulate pollution for nearly 10 years, from 2001 to 2010. Six land-use types, water, woodland, grassland, cultivated land, urban, and unused land, were obtained from the MODIS land cover product (MOD12), where the LUCC of each category was estimated. The response of particulate pollution to LUCC was analyzed from the above mentioned two types of data. Moreover, the impacts of time-lag and urban type changes on particulate pollution were also considered. Analysis results showed that due to natural factors, or human activities such as urban sprawl or deforestation, etc., the response of particulate pollution to LUCC shows obvious differences in different areas. The correlation between particulate pollution and LUCC is lower in coastal areas but higher in inland areas. The dominant factor affecting urban air quality in LUCC changes from ocean, to woodland, to urban land, and eventually into grassland or unused land when moving from the coast to inland China.

Land Use and Land Cover Change in Northeast Gadarif State: Case of El Rawashda Forest, Sudan

The main objectives of this study were to detecting the land use and land cover change (LULC), using remote sensing techniques, then identify the reasons for rangeland and tree cover degradation in El Rawashda Forest, Gadarif State, Sudan. The study has conducted field experiment developed on an area of 20 feddans that was affected by deterioration in the forest and to assess the best method for rehabilitation of the vegetation cover in the area of study. The experimental area was divided into 5 blocks; each block consisted of 4 treatments: grass seeds and Talih (Acacia seyal var. seyal); sowing seeds just before autumn, sowing seeds after disc ploughing, sowing seeds using water harvesting technique and control (no seeding). In the present study an attempt has been made to analyze and monitor the LULC changes using multi‐temporal Landsat data deterioration in the forest and to assess the best method for restoration of the vegetation. In the present study, an attempt has been made to analyze and monitor the LULC changes using multi‐temporal Landsat data for years 1984, 1994 and 2013. LULC grades in the classification scheme are: Trees, Mechanized Rain-fed Agriculture (MRA), Grasses and Bare land. Individual classifications based on maximum likelihood of algorithm were used and the results showed a significant that extensive change of LULC patterns has occurred in all decades in the study area. The results also show Trees class was decreased, while MRA, Grasses and Bare land were increased. The seeding of the forage and Talih seeds after disc plowing gave the best results compared to the other treatments, followed by forage and Talih seed sowing under the water harvesting technique and broadcasting of forage and Talih seeds and finally the control.

Exploring Land Use and Land Cover Effects on Air Quality in Central Alabama Using GIS and Remote Sensing

Air pollution has been a major topic of debate in highly developed areas over the last quarter century and therefore mitigation of poor air quality for health and environmental reasons has been a primary focus for local governments. Particulate matter, especially finer particles (PM2.5), is detrimental to human health, and urban expansion is thought to be a contributing factor to enhanced levels of PM2.5. However, there is limited research on the connection between land use and land cover change (LULC) and PM2.5 emissions. Using high resolution LANDSAT imagery from the past 12 years along with ground observations of PM2.5 mass concentrations in the Birmingham, AL region, we explore the links between the PM2.5 mass concentrations and LULC trends. Utilization of GIS allowed us to seamlessly analyze county-based patterns of LULC change and PM2.5 concentrations and display them in an easy to interpret manner. We found a moderate-to-strong correlation between PM2.5 observations and the urban area surrounding monitoring sites in 1998 and 2010. We also discuss factors such as local climate and topography and EPA imposed standards that can confound these comparisons. Finally, we determine the next steps that are required to fully quantify the cause and effect between LULC and air quality.