Land Use And Land Cover Types Research Articles

Modeling the Spatio-temporal dynamics and evolution of land use and land cover (1984–2015) using remote sensing and GIS in Raya, Northern Ethiopia

This study models the spatio-temporal dynamics, patterns, and evolution of land use and land cover (LULC) (1984–2015) using remote sensing and GIS supported by in-suit measurements in Raya, Northern Ethiopia. Landsat thematic mapper (TM), and operational land imager (OLI) path 168/169 and row 051/52 were acquired from the United States Geological Survey Landsat archive. All necessary image pre-processing techniques were applied to remove the distortions due to sensors. Eight major LULC types based on a supervised image classification and maximum likelihood decision rule were identified. Post-classification change detection method was also applied to detect the dynamics in LULC. Significant change in forestland, shrub/bush land, built-up area, grassland, cropland, barren land, and floodplain areas were observed over the period 1984–2015. Considerable losses were observed in grasslands (36.9%), water body (8.7%), and floodplain areas (74.4%), while other LULC types increased. This explains why the study area is frequently affected by drought and other related disasters. An overall accuracy of 88.5, 86.5 and 90.5% were observed for the 1984, 1995 and 2015 LULC, respectively. The overall Kappa coefficient of 0.87, 0.85, and 0.90 were also observed for the same periods. Besides, the Pearson pairwise correlation matrix among the 1984–1995, 1995–2015 and 1984–2015 LULC shows positive and strong correlation (r = 0.916, r = 0.908, r = 0.914) at p < 0.005 significance level. Therefore, there is no much difference in identifying LULC types using TM and OLI products. This study is crucial to implement scientific land use policies and strategies in the study area.

Classificação do Uso da Terra e Cobertura Vegetal Utilizando Técnicas de Mineração de Dados

O objetivo deste estudo é apresentar o mapeamento do uso da Terra e cobertura vegetal utilizando técnicas de mineração de dados. A área teste selecionada corresponde à bacia do Rio São Tomé, localizada na região de Alfenas, sul do estado de Minas Gerais. Para a realização deste estudo, foram utilizadas imagens multiespectrais geradas pelo sensor Linear Imaging Self-Scanner (LISS III) a bordo do satélite Indian Resource Satellite (IRS). A classificação das imagens foi feita utilizando o aplicativo Geographic Data Mining Analyst (GeoDMA) que possui algoritmos para segmentação de imagens, extração de atributos, seleção de feições e classificação. A análise dos resultados foi feita de maneira visual e quantitativa por meio de uma matriz de confusão. Para a geração desta matriz, 3000 pontos de referência foram coletados de maneira totalmente aleatória. Os resultados desta pesquisa mostraram o grande potencial da técnica de mineração de dados na classificação do uso da Terra e cobertura vegetal. As principais vantagens observadas de sua utilização foram: (1) permitiu incorporar no processo de classificação um grande número de variáveis tanto espectrais, espaciais quanto atributos do relevo; (2) simplificou a interpretação das regras de classificação por meio dos resultados das árvores de decisão; (3) gerou uma classificação consistente.

Land Surface Temperature Extracts for Peri-Urban Heat and Rural Cool Troughs in Ghana

The objective of this paper is to analyze the land surface temperatures (LST) derived from three satellite images as a proxy for urban heat island potential, through a peri-urban heat troughs (PuHT) to rural cool troughs (RuCT) continuum, concepts largely overlooked in the literature, in the Bosomtwe district of the Ashanti region of Ghana. Four Landsat satellite images from 2002, 2008 Enhanced Thematic Mapper+ (ETM+) and 2014 Landsat 8 Operational Land Imager and Thermal Infrared Sensor (OLI/TIRS) were geo-referenced and processed for classification using the maximum likelihood classifier algorithm in ERDAS Imagine 13. Land Use and Land Cover (LULC) transition analysis was performed in ArcMap for ArcGIS 10.2. Results indicate that, in order of importance, recent fallows and grasslands along with built up/bare land and concrete surfaces have been increasing in terms of coverage. A corresponding surface reflectance translated into LST values ranging between a minimum of 24oC (297K) to a maximum of 53oC (326K). Changing LULC types correlated with the land surface temperature fluxes, creating the RuCT and PuHT. This result explains the relatively substantial peri-urban land use dynamics in the district. Future studies should develop threshold values for RuCT and PuHT temperatures.

Utilization of Landsat data to quantify land-use and land-cover changes related to oil and gas activities in West-Central Alberta from 2005 to 2013

Land use and land cover (LULC) change detection associated with oil and gas activities plays an important role in effective sustainable management practices, compliance monitoring, and reclamation assessment. In this study, a mapping methodology is presented for quantifying pre- and post-disturbance LULC types with annual Landsat Best-Available-Pixel multispectral data from 2005 to 2013. Annual LULC and land disturbance maps were produced for one of the major conventional oil and gas production areas in West-Central Alberta with an accuracy of 78% and 87%, respectively. The highest rate of vegetation loss (178 km2/year) was observed in coniferous forest compared to broadleaf forest, mixed forest, and native vegetation. Integration of ancillary oil and gas geospatial data with annual land disturbances indicated that less than 20% of the total land disturbances were attributable to oil and gas activities. In 2013, approximately 44% of oil and gas disturbances from 2005 to 2013 showed evidence of vegetation recovery. In the future, geospatial data related to wildfire, logging activities, insect defoliation, and other natural and anthropogenic factors can be integrated to quantify other causes of land disturbances.

Linking major shifts in land surface temperatures to long term land use and land cover changes: A case of Harare, Zimbabwe

Rapid urban development is known to increase a landscape's thermal values, exposing residents to among others adverse heat related health impacts, discomfort as well as energy and water demand. Therefore, there is need to determine the implication of the transforming urban landscapes on urban micro-climate to optimise urban land uses and to effectively mitigate adverse impacts. In this study, we aimed at assessing micro-climate forcing of Land Use and Land Cover (LULC) changes in the heterogeneous Harare Metropolitan City, Zimbabwe, between 1984 and 2015. To achieve this objective, the transformation of major LULCs within the city was determined and relative brightness temperature used to assess long-term thermal changes in the city. Results show that coverage of high density residential areas increased by 92% between 1984 and 2016 at the expense of cooler green-spaces, which decreased by 75.5%. This translated to a 0.98°C and 1.98°C temperature increase, attributed to LULC changes alone and to all factors that include greenhouse effect and ozone depletion respectively. Results also show that converting bare areas to water bodies reduced surface temperatures by 4.5°C, while the construction of low-to-medium density residential areas reduced bare surface temperatures by 3.78°C. Conversion of green-spaces to low-medium residential areas increased temperatures by 0.16°C. Overall, conversion of LULC types contributed more than 0.5°C thermal elevation within the city, largely attributed to increases in built-up areas and reduction in heat mitigating green-spaces. These findings offer insight into landscape surface energy balance changes arising from urbanization, critical for urban planning, environmental governance as well and climate change management in cities.

Discrimination of Settlement and Industrial Area Using Landscape Metrics in Rural Region

Detailed and precise information of land-use and land-cover (LULC) in rural area is essential for land-use planning, environment and energy management. The confusion in mapping residential and industrial areas brings problems in energy management, environmental management and sustainable land use development. However, they remain ambiguous in the former rural LULC mapping, and this insufficient supervision leads to inefficient land exploitation and a great waste of land resources. Hence, the extent and area of residential and industrial cover need to be revealed urgently. However, spectral and textural information is not sufficient for classification heterogeneity due to the similarity between different LULC types. Meanwhile, the contextual information about the relationship between a LULC feature and its surroundings still has potential in classification application. This paper attempts to discriminate settlement and industry area using landscape metrics. A feasible classification scheme integrating landscape metrics, chessboard segmentation and object-based image analysis (OBIA) is proposed. First LULC map is generated from GeoEye-1 image, which delineated distribution of different land-cover materials using traditional OBIA method with spectrum and texture information. Then, a chessboard segmentation of the whole LULC map is conducted to create landscape units in a uniform spatial area. Landscape characteristics in each square of chessboard are adopted in the classification algorithm subsequently. To analyze landscape unit scale effect, a variety of chessboard scales are tested, with overall accuracy ranging from 75% to 88%, and Kappa coefficient from 0.51 to 0.76. Optimal chessboard scale is obtained through accuracy assessment comparison. This classification scheme is then compared to two other approaches: a top-down hierarchical classification network using only spectral, textural and shape properties, and lacunarity based hierarchical classification. The distinction approach proposed is overwhelming by achieving the highest value in overall accuracy, Kappa coefficient and McNemar test. The results show that landscape properties from chessboard segment squares could provide valuable information in classification.

Mapping coffee crops in southeastern Brazil using spectral mixture analysis and data mining classification

ABSTRACTThe task of mapping coffee crops using multispectral data sets is not yet a trivial routine. This is because coffee fields are extremely heterogeneous in terms of spectral reflectance. This study therefore aims to contribute to the mapping of coffee crops using multispectral imagery with 23.5 m spatial resolution taken by the Linear Imaging Self Scanner (LISS III) instrument on board the Indian Remote Sensing (IRS) satellite system. The section of land covered by this study is a traditional coffee-producing province located in the south of the State of Minas Gerais, southeastern Brazil. Whereas the pixel mixture effect was managed using spectral mixture analysis (SMA), the classification was carried out using data mining (DM) techniques. The decision tree (DT) outcomes were evaluated using a simple and qualitative method based on the elements of photointerpretation. In total, eight land-use and land-cover (LULC) types were mapped, including three classes of coffee-growing land expressing different phenological conditions and management. These were named ‘Production Coffee’, ‘Mixed Coffee’, and ‘Old/Pruned Coffee’. The results showed that the methodology was effective for mapping LULC types, as the workflow adopted simplified image interpretation and offered improvements in the classification performance. Despite the coffee-cultivation classes having a large spectral variability, which increases the chances of classification errors, not many confusions were observed involving the three coffee classes mapped with other categories of use. This therefore shows that the method was efficient in isolating the coffee classes (with an accuracy greater than 70%) from other categories of use. Comparing the results obtained in this work with a conventional maximum-likelihood (ML) classification, the results revealed that when using the methodology described, the confusions between classes were less dispersed and an improvement of approximately 10% was observed in the mapping of the Production Coffee class.

Hotspots of uncertainty in land-use and land-cover change projections: a global-scale model comparison.

Model‐based global projections of future land‐use and land‐cover (LULC) change are frequently used in environmental assessments to study the impact of LULC change on environmental services and to provide decision support for policy. These projections are characterized by a high uncertainty in terms of quantity and allocation of projected changes, which can severely impact the results of environmental assessments. In this study, we identify hotspots of uncertainty, based on 43 simulations from 11 global‐scale LULC change models representing a wide range of assumptions of future biophysical and socioeconomic conditions. We attribute components of uncertainty to input data, model structure, scenario storyline and a residual term, based on a regression analysis and analysis of variance. From this diverse set of models and scenarios, we find that the uncertainty varies, depending on the region and the LULC type under consideration. Hotspots of uncertainty appear mainly at the edges of globally important biomes (e.g., boreal and tropical forests). Our results indicate that an important source of uncertainty in forest and pasture areas originates from different input data applied in the models. Cropland, in contrast, is more consistent among the starting conditions, while variation in the projections gradually increases over time due to diverse scenario assumptions and different modeling approaches. Comparisons at the grid cell level indicate that disagreement is mainly related to LULC type definitions and the individual model allocation schemes. We conclude that improving the quality and consistency of observational data utilized in the modeling process and improving the allocation mechanisms of LULC change models remain important challenges. Current LULC representation in environmental assessments might miss the uncertainty arising from the diversity of LULC change modeling approaches, and many studies ignore the uncertainty in LULC projections in assessments of LULC change impacts on climate, water resources or biodiversity.

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.

Scale-dependent variability of soil organic carbon coupled to land use and land cover

Understanding the field-scale spatial variability of soil organic carbon (SOC) is critical to assess its spatial distribution at very fine scale (several meters) which is valuable for precision agriculture and natural resource management. The aim of this study was to investigate the field-scale spatial variability of SOC under five prevalent land use and land cover (LULC) types in Florida, U.S. with a uniform sampling scheme. Five scales, 2, 7, 22, 67 and>200m, were targeted and 108 soil samples at 0–20cm depth were collected and analyzed for SOC and bulk densities within each LULC type in 2012. Results indicate that SOC variability was scale dependent. Hardwood Hammock and Forest and Improved Pasture demonstrated large variation at both coarse scale (67 and>200m) and very fine scale (2m). Sandhill, Pineland and Dry Prairie were dominated by variation at very fine scales (2 and 7m). All five sites showed large variability at very fine scales, indicating the close coupling of SOC stock variation to structure and composition of vegetation. This study also identified that log-transformed SOC showed variance-invariant behavior, which had an approximately constant overall variance (sill) of 0.067±0.012 (log(kgm−2))2at field scale (∼500m) irrespective of LULC. These findings serve to explain field-scale variability of SOC relevant for precision agriculture and land management, but also facilitate better understanding of the scale-dependent fine-scale variability of SOC across larger soilscapes.

Effects of land use and land cover on selected soil quality indicators in the headwater area of the Blue Nile basin of Ethiopia.

Understanding changes in soil quality resulting from land use and land management changes is important to design sustainable land management plans or interventions. This study evaluated the influence of land use and land cover (LULC) on key soil quality indicators (SQIs) within a small watershed (Jedeb) in the Blue Nile Basin of Ethiopia. Factor analysis based on principal component analysis (PCA) was used to determine different SQIs. Surface (0-15 cm) soil samples with four replications were collected from five main LULC types in the watershed (i.e., natural woody vegetation, plantation forest, grassland, cultivated land, and barren land) and at two elevation classes (upland and midland), and 13 soil properties were measured for each replicate. A factorial (2 × 5) multivariate analysis of variance (MANOVA) showed that LULC and altitude together significantly affected organic matter (OM) levels. However, LULC alone significantly affected bulk density and altitude alone significantly affected bulk density, soil acidity, and silt content. Afforestation of barren land with eucalypt trees can significantly increase the soil OM in the midland part but not in the upland part. Soils under grassland had a significantly higher bulk density than did soils under natural woody vegetation indicating that de-vegetation and conversion to grassland could lead to soil compaction. Thus, the historical LULC change in the Jedeb watershed has resulted in the loss of soil OM and increased soil compaction. The study shows that a land use and management system can be monitored if it degrades or maintains or improves the soil using key soil quality indicators.

Soil Erosion Assessment of the Poyang Lake Basin, China: Using USLE, GIS and Remote Sensing

Soil erosion is one of the most critical eco-environmental issues in the Poyang Lake basin, China. The purpose of this study is to discover the spatial pattern of soil erosion, and predict soil loss and sediment yield, and evaluate soil loss impacts on main reservoirs by using Universal Soil Loss Equation (USLE), GIS and Remote Sensing (RS). Firstly, five erosion factors including rainfall erosivity (R), soil erodibility (K), topographic factor (LS), cover and management factor(C), and conservation supporting practice factor (P) were calculated and analyzed, respectively. Secondly, annual soil erosion and its spatial distribution were evaluated, and sediment yield was subsequently predicted. Next, soil erosion was classified into five erosion categories according to Industry Standard of Water Resources of China. Then, the relationship among soil erosion, landform and land use and land cover (LULC) were analyzed. Finally, the influence of soil erosion on main reservoirs in the basin were assessed. The result showed that: 28.3% of the total watershed area appears soil loss; the average annual soil loss amount is approximate 2.7 × 107 t; soil erosion modulus ranged from 0 to 394.8 t/ha/y, with a mean value of 1.82 t/ha/y. 71.7% of the watershed area are undergoing minimal erosion, primarily appear in surrounding the lake area, both sides of river valley and plains of five main rivers; 24.1% of the watershed area are undergoing low erosion, mainly found in the west, east, central hilly and mountain areas; 3.4% of the watershed area was observed moderate soil erosion; 0.83% of the watershed area are undergoing high, very high and extreme soil erosion, which located in the northeastern and northwestern corner, and the upstream of the Ganjiang river and Fuhe river sub-watershed. Low and moderate soil erosion most frequently occurred at the plains and hills zone in this basin. Soil loss happens on needleleaved forest, rainfed croplands and shrub land use type are greater than that of other LULC types; soil erosion modulus descends on the different land use types, orderly by bare lands, grass lands, shrub lands, rainfed croplands, needleleaved forest, spares vegetation, broadleaved deciduous forest, artificial surface, irrigated croplands and water bodies. Present main reservoirs are undergoing a big threat from the upstream sediment load, especially as the Qiyi, Da’ao, Qixing and Tuolin reservoir.

Land use and land cover in critical source areas on small dairy farms in the eastern United States

Rotational grazing (RG) is a livestock management practice that moves grazing cattle among small temporary pastures called paddocks. In dairy farming, RG has potential to improve soil and water conservation by situating well-managed perennial vegetation on erosion-prone parts of farm landscapes. Recently, geospatial technologies have enabled precise identification of “critical source areas” (CSAs). CSAs are sites where slope, soil, and water flow factors coincide to create the largest potential impacts on surface water quality from erosion within the landscape of a farm. Examination of land-use and land-cover (LULC) practices on CSAs allows nuanced comparisons of effects on water resources among agricultural production systems, enabling us to test the hypothesis that RG dairy farms manage CSAs so as to have lesser effects on water resources than comparable-sized nongrazing dairy farms. We assessed LULC on CSAs in 53 small dairy farms in New York, Pennsylvania, and Wisconsin, United States, using satellite imagery and other spatial data. Among these farms, 22 used some form of RG, while the remainder did not use grazing. We also did on-farm observations of most CSAs to assess the frequency of features that may particularly affect water resources, such as unvegetated areas within pastures. RG dairy farms differed significantly from nongrazing dairy farms in the total allocation of CSA area to hayfields and rotational pastures—two LULC types that are likely to reduce runoff and emissions of sediment and nutrients into waterways—but this difference varied across the states and was pronounced only in the Pennsylvania farms, where high-intensity grazing farms allocated these perennial LULC types to over 60% of CSA lands, while nongrazing farms allocated these LULC types to about 20% of CSAs. In New York and Pennsylvania, RG farms allocated significantly less erosion-prone annual cropland to CSA sites than nongrazing farms, and allocated less of the total farm area to LULC practices that are relatively vulnerable to soil erosion. However, these differences between farm types were pronounced only in Pennsylvania farms. Our results do not support the hypothesis that RG dairy farms are generally superior to comparably sized nongrazing dairy farms in their management of CSAs. It is likely that targeted technical and cost-share support could improve management of CSAs in RG farms, allowing them to more fully realize the potential of RG systems to improve soil and water conservation.

Assessing the Impacts of Urbanization-Associated Land Use/Cover Change on Land Surface Temperature and Surface Moisture: A Case Study in the Midwestern United States

Urbanization-associated land use and land cover (LULC) changes lead to modifications of surface microclimatic and hydrological conditions, including the formation of urban heat islands and changes in surface runoff pattern. The goal of the paper is to investigate the changes of biophysical variables due to urbanization induced LULC changes in Indianapolis, USA, from 2001 to 2006. The biophysical parameters analyzed included Land Surface Temperature (LST), fractional vegetation cover, Normalized Difference Water Index (NDWI), impervious fractions evaporative fraction, and soil moisture. Land cover classification and changes and impervious fractions were obtained from the National Land Cover Database of 2001 and 2006. The Temperature-Vegetation Index (TVX) space was created to analyze how these satellite-derived biophysical parameters change during urbanization. The results showed that the general trend of pixel migration in response to the LULC changes was from the areas of low temperature, dense vegetation cover, and high surface moisture conditions to the areas of high temperature, sparse vegetation cover, and low surface moisture condition in the TVX space. Analyses of the T-soil moisture and T-NDWI spaces revealed similar changed patterns. The rate of change in LST, vegetation cover, and moisture varied with LULC type and percent imperviousness. Compared to conversion from cultivated to residential land, the change from forest to commercial land altered LST and moisture more intensively. Compared to the area changed from cultivated to residential, the area changed from forest to commercial altered 48% more in fractional vegetation cover, 71% more in LST, and 15% more in soil moisture Soil moisture and NDWI were both tested as measures of surface moisture in the urban areas. NDWI was proven to be a useful measure of vegetation liquid water and was more sensitive to the land cover changes comparing to soil moisture. From a change forest to commercial land, the mean soil moisture changed 17%, while the mean NDWI changed 90%.

Changes in landscape fire-hazard during the second half of the 20th century: Agriculture abandonment and the changing role of driving factors

Past the middle of the 20th century, forest fires started to increase markedly in the Mediterranean countries of southern Europe. Hazardous land-use and land-cover (LULC) changes are considered major drivers of increased fire-hazard and fire risk. However, the contribution of various LULC changes to increased fire-hazard, as well as the role of environmental or socioeconomic factors in driving them, including its changing role over time, are poorly known. Understanding how changes in socio-economics in interaction with other factors modify landscape fire-hazard and risk is a major priority in fire-prone areas. Here we determined changes in fire-hazard through time, focusing on the contribution of agriculture abandonment to it, and on the changing role of its driving factors, in a large (56,000km2) rural area in West-Central Spain. The study period covers from 1950s to 2000. LULC maps at different time steps (1950s, 1978, 1986 and 2000) were available, as well as environmental and socioeconomic information at various scales. We analyzed trends in LULC change, focusing on those altering fire-hazard, and used general linear models (GLM) with generalized linear mixed models (GLMM) to account for the effects of variables at different spatial scales in determining changes leading to shifts in fire-hazard. We found that the proportion of hazardous LULC types increased twofold (26–42%) from 1950s to 2000. Until 1986, agriculture abandonment was the dominant LULC change leading to increased fire-hazard. Post-1986, LULC changes were mainly driven by deforestation due to fires and densification caused by natural vegetation dynamics. Models showed that the first abandoned lands were driven by local environmental and socioeconomic constraints (small farms, in distant locations, in municipalities with low population), whereas later abandonments were driven by non-local ones (large farms, in more productive soils, closer to towns, populations with high unemployment, and higher employment in the services sector). Throughout the entire period, high proportion of wildland vegetation, low mechanization level, and large number of land-holders older than 55 years favored abandonment. This implies that as the population ages, larger, more accessible and productive areas are abandoned, fire-hazard will increase closer to human settlements, increasing the wild-land urban interface and fire risk.

Evaluation of Carbon and Oxygen Balances in Urban Ecosystems Using Land Use/Land Cover and Statistical Data

Urban areas play an important role in the global carbon cycle, and human-induced carbon emissions from urban areas urgently need to be reduced. Therefore, understanding the relationship between carbon sources and sinks is the first step toward mitigating the effect of urban areas on climate change. Combined with the land use and land cover (LULC) empirical coefficients and statistical methods, urban carbon and oxygen balances in Beijing were evaluated. In this study, the carbon sequestration and oxygen emission capabilities of various LULC types were calculated, and the partitioning of carbon emissions and oxygen consumption in Beijing were estimated. The evaluation results indicated that the ecosystem services from the LULC in an area were not adequate to offset the urban carbon emissions and oxygen consumption. The areas with a high capacity for carbon sequestration and oxygen emissions were primarily distributed in the exurban districts of Beijing, and the carbon and oxygen balances in the exurban districts were superior to those of core urban areas. Industrial fossil fuel consumption dominated all of the human-induced carbon sources. The methods developed in this research were shown to be viable for the quantitative evaluation of urban ecosystem carbon and oxygen balances.

Interrelationships of Land Use/Cover Change and Topography with Soil Acidity and Salinity as Indicators of Land Degradation

As soil is the basis of all terrestrial ecosystems, degraded soil means lower fertility, reduced biodiversity and reduced human welfare. Therefore the focus of this paper is on elucidating the influence of land use and land cover (LULC) change on two important soil quality indicators that are fundamental to effective measures for ameliorating soil degradation; namely soil acidity and soil salinity in the Lower Hunter Valley of New South Wales, Australia. First, Analysis of Variance was used to elucidate the effects of LULC categories on soil acidity and salinity. The results indicate that soils under Vineyard have significantly higher pH. In contrast there is no significant effect of LULC or its change on soil salinity. To further elucidate the complex interactions of these soil quality indicators with landscape attributes over 20 years and other terrain attributes, multivariate ordination techniques (correspondence analysis and canonical correspondence analysis) were used. The results show that elevation exerted a more dominant influence on pH than the LULC types and their dynamics. In comparison, salinity of the soil appears to be higher in subsoil layers under woodland than under other LULC categories. The environmental implications of these interactions, as evidenced by this study, provide some insights for future land use planning in the region.

Digital soil mapping of soil organic carbon stocks under different land use and land cover types in montane ecosystems, Eastern Himalayas

Quantification of soil organic carbon (SOC) stocks is quite useful for accurate monitoring of C sequestration. However, there are still substantial gaps in our knowledge of SOC stocks in many parts of the world, including the Himalayas. We investigated the total SOC stocks and its spatial distribution under different land use and land cover (LULC) types in montane ecosystems of Bhutan. 186 Soil profiles were described and sampled by genetic horizons at sites located using conditioned Latin hypercube sampling. SOC concentrations at the standard depths designated for the GlobalSoilMap.Net were estimated with an equal-area spline profile function. SOC concentrations at these depth intervals were digitally mapped to a fine resolution matrix of 90m grid using regression kriging. We found significant influence of LULC categories on SOC concentration, SOC density, SOC stocks and their spatial distributions, although this influence decreased with increasing soil depth. The estimated mean SOC density in the top 1m were highest in fir forest soils (41.4kgm−2) and lowest in paddy land (12.0kgm−2). Allowing for LULC relative areas, mixed conifer forest had the highest SOC stocks in the upper meter (12.4Mt) with orchards the lowest (0.1Mt). The total SOC stocks for the whole study area for the 0–5, 5–15, 15–30, 30–60 and 60–100cm depths were 2.6, 5.0, 6.5, 7.5 and 5.4Mt, respectively. The overall SOC stock of the study area for the upper meter was approximately 27.1Mt. The combined forests accounted for more than 77.5% of the total SOC stocks of the study area. This and the relative SOC densities indicate that the conversion of even a fraction of forests to other LULC types could lead to substantial loss of SOC stocks. This loss of SOC stock is even greater when the decrease in aboveground biomass is also taken into consideration. However, appropriate management of the agricultural lands could increase their sequestration of atmospheric CO2.

Land Use and Land Cover Change, and Woody Vegetation Diversity in Human Driven Landscape of Gilgel Tekeze Catchment, Northern Ethiopia

Land use and land cover (LULC) change through inappropriate agricultural practices and high human and livestock population pressure have led to severe land degradation in the Ethiopian highlands. This has led to further degradation such as biodiversity loss, deforestation, and soil erosion. The study examined woody vegetation diversity status and the impact of drivers of change across different LULC types and agroecological zones in Gilgel Tekeze catchment, northern Ethiopian highlands. LULC dynamics were assessed using GIS techniques on 1976, 1986, and 2008 satellite images. Vegetation data were collected from 135 sample plots (20 m × 20 m) from five LULC types, namely, forest, shrub-bush, grazing, settlement, and cultivated land, in the three agroecological zones; Kolla, Weyna-Dega, and Dega. Differences in vegetation structure and composition and their relationship to agroecological zones were tested using two-way ANOVA and PCA technique. The results show that vegetation structure and composition significantly differed across all LULC types in different agroecological zones particularly in sapling density, tree height, and shrub height and in each agroecological zone between forest land, shrub-bush land, and settlement area. Overall, Weyna-Dega agroecological zone and the shrub-bush land had more structural and compositional diversity than the other agroecological zones and LULC types.

1990-2011年三峡库区生态系统服务价值演变及驱动力

作为我国西南部重要的生态屏障和生态走廊，三峡库区具有重要的战略意义，其生态问题非常值得关注。研究以覆盖三峡库区的4期Landsat TM遥感影像为数据源，通过人机交互解译分别获得1990、1998、2006、2011年的土地利用/覆盖，参照中国陆地生态系统单位面积生态服务价值当量表，采用研究区单位面积产量与全国农田粮食单位面积产量的比值作为地区修订系数，计算库区生态系统单位面积生态服务价值当量表，同时利用生物量对林地的生态系统服务价值作进一步的修订。然后结合土地利用结构和生态敏感性指数，定量分析土地利用变化引起的生态服系统务价值变化及其驱动因子。结果显示：1990-2011年间，三峡库区生态系统服务价值主要由林地支撑（占76.75%），其次是水域、耕地（共23.19%），草地的贡献率最小（0.22%），总生态系统服务价值从1990年的479.55 亿元增加到2011年的680.83 亿元；各项服务功能价值中，食物生产功能价值下降，其他各项功能价值上升，以土壤形成与保护功能上升幅度最大，达36.61 亿元，其次是气体调节（33.10 亿元）；驱动力分析表明，库区生态系统服务价值变化的主要原因是人类活动，特别是自1998年实施退耕还林工程以来 ，各自然生态系统的面积发生较大变化，同时，自然生态系统的健康程度和社会政策对生态系统服务价值变化的影响也不忽可视。研究表明，加强林地、草地和水域等生态系统服价值高的土地利用/覆盖类型保护，是维持库区生态系统稳定性的有效措施。;As the most important ecological barrier and ecological corridor in Southwestern China, the Three Gorges Reservoir region was strategically important and significant. Since the 1990s, in company with the accomplishment of the Three Gorges hydro-junction project, a series of key national ecological and forestry projects have been initiated, including the protective forests along the Yangtze River, the natural forests and Resources conservation, the conversion of cropland to forest, the afforestation of the reservoir surrounding area and the afforestation of both banks of the Yangtze River. These have led to significant changes of land use and land cover (LULC) types and their spatial distribution. More than twenty years has been gone. However, it is unknown that how the accomplishment of the ecological projects affected the change of ecosystem service values and what were the effects of these projects on the protection of the Three Gorges Reservoir region. There is a strong need to assess the effectiveness of the projects, including the dynamics of LULC types and the induced changes of ecological service values. The objective of this study was to analyze the spatiotemporal characteristics of ecological service changes and investigate the factors that have driven the dynamics in the Three Gorges Reservoir region. In this study, the Landsat Thematic Mapper^TM images that cover the Three Gorges Reservoir region were acquired for years of 1990, 1998, 2006 and 2011, respectively, and visually interpreted for LULC types. The per unit ecosystem service equivalent value of the ecosystems within the region was calculated by using the corresponding value of the terrestrial ecosystems for the whole country as a reference and the ratio of the per unit grain productivity of the study area to the corresponding value of the country as a revised coefficient. The obtained per unit ecosystem service equivalent value was further modified based on the value of biomass from forested land related to ecological service value. The changes of ecological service values induced by LULC dynamics and corresponding driving factors were quantitatively analyzed by combining land use structure index and ecological sensitivity index. The results showed that (1) during the past twenty one years, the ecological service values of the Three Gorges Reservoir region were mainly supported by the forested land with a percentage of 76.75%, followed by the water and cropland land (23.19%), and the contribution of the grassland was the least (0.22%). The total ecological service value increased from 47.96 billion yuan in 1990 to 68.08 billion yuan in 2011; (2) All the ecological service values increased except food production. The value from soil formation and protection had the greatest increase with an increment of 3.66 billion yuan, followed by the gas regulation (3.31 billion yuan); (3) The analysis of driving factors showed that the changes of the ecological service values were mainly due to human activities, especially the great change of the area for each of the natural ecosystems since the conversion of cropland to forest started in 1998. Moreover, the effects of both the health of the nature ecological systems and the social policy on the changes of the ecological service values could not be ignored. The findings implied that enhancing the protection of LULC types that have higher ecosystem service values, including forested land, grassland, water bodies and so on, is an effective way to stabilize the ecosystems of the Three Gorges Reservoir region.