Precision Measurements from Very-Large Scale Aerial Digital Imagery

Managers need measurements and resource managers need the length/width of a variety of items including that of animals, logs, streams, plant canopies, man-made objects, riparian habitat, vegetation patches and other things important in resource monitoring and land inspection. These types of measurements can now be easily and accurately obtained from very large scale aerial (VLSA) imagery having spatial resolutions as fine as 1 millimeter per pixel by using the three new software programs described here. VLSA images have small fields of view and are used for intermittent sampling across extensive landscapes. Pixel-coverage among images is influenced by small changes in airplane altitude above ground level (AGL) and orientation relative to the ground, as well as by changes in topography. These factors affect the object-to-camera distance used for image-resolution calculations. ‘ImageMeasurement’ offers a user-friendly interface for accounting for pixel-coverage variation among images by utilizing a database. ‘LaserLOG’ records and displays airplane altitude AGL measured from a high frequency laser rangefinder, and displays the vertical velocity. ‘Merge’ sorts through large amounts of data generated by LaserLOG and matches precise airplane altitudes with camera trigger times for input to the ImageMeasurement database. We discuss application of these tools, including error estimates. We found measurements from aerial images (collection resolution: 5–26 mm/pixel as projected on the ground) using ImageMeasurement, LaserLOG, and Merge, were accurate to centimeters with an error less than 10%. We recommend these software packages as a means for expanding the utility of aerial image data.     

Sensitizing Land Uses to Control Motor Vehicular Air Pollution: a Case Study of Lahore in Connection with Paris

Several factors influence air pollution, but effect of land uses is pivotal and has direct consequences on growth and development of a city. In order to assess consequent effects of land uses on air pollution, it is important to transform a set of variables into significant components by using principal component analysis. These components help to develop an effective model between air pollution and land uses by application of regression analysis. Lahore, titled as “Paris of the East,” has some featured commonalities with Paris and was jointly selected for research to adopt common policies and measures to combat air pollution. A two-step cluster analysis has been applied to testify resemblance of Paris to towns of Lahore as a cluster. This paper is trying to develop a calibrated model which helps to estimate about air pollution at a significant level with only one independent variable. Furthermore, it helps to control air pollution through sensitization of land uses in Lahore.     

Land Cover Changes as a Result of Environmental Restrictions on Nitrate Leaching in Dairy Farming

Nitrate leaching forms an important environmental problem because it causes pollution of groundwater and surface water, and adds to already problematic eutrophication. This study analyses the impact of reductions in nitrate leaching on land cover decisions of dairy farms, of which the activities make an important contribution to nitrate leaching. As the level of nitrate leaching depends on groundwater depth as well as on the supply of nitrogen, spatial variation in groundwater levels will cause a spatial variation in land cover under restrictions on nitrate leaching. A non-linear partial optimisation model for the economic and ecological aspects of the problem were used to show how land cover and dairy farms' financial balances change when nitrate losses are reduced. The model is spatially explicit, and describes nitrate leakage and yields of maize and grass as a function of groundwater depth, including the effects of various grazing systems. The model analyses the decisions of a risk neutral agent who minimises costs under the following constraints: (i) production, feed requirements and mass balances for fodder; (ii) constraints for nitrate leaching. Economic costs are attributed to increased costs of fodder and processing of manure when nitrate restrictions are tightened. An important result of the study is the variation in compliance costs and land cover for maize and grass production brought about by spatial variation in groundwater depth. While the effects are negligible for some shallow groundwater classes, it is extremely difficult in other classes – if not impossible – to obtain the EU standard of maximum admissible losses of 34 kg N ha^–1 at low costs. The study shows an important reduction in land cover by maize.     

A web application to support the quantification and valuation of ecosystem services

Assessing the impacts of policies on a wide range of ecosystem services can support the development of cost-effective policies that establish win–win situations across different environmental domains. To explore the quantity and value of ecosystem services, the web-based application “nature value explorer” was developed. The application allows to estimate the impact of land use and land cover change on regulating and cultural ecosystem services in Flanders, Belgium. To ensure the applicability in day-to-day decision making as part of environmental impact assessments, user requirements were investigated prior to tool development. Finding the optimal balance between accuracy and complexity on the one hand and flexibility and user-friendliness on the other hand was an important challenge. To date, the nature value explorer has been successful in drawing the interest of policy makers and has been used several times to support decisions in infrastructure projects as well as in nature restoration projects in Flanders. This paper discusses the user requirements, the main tool characteristics, potential policy applications and future improvements. Three case studies illustrate the functionalities of the tool in day-to-day decision making. The tool can be consulted on http://www.natuurwaardeverkenner.be.     

Using exploratory regression to identify optimal driving factors for cellular automaton modeling of land use change

Defining transition rules is an important issue in cellular automaton (CA)-based land use modeling because these models incorporate highly correlated driving factors. Multicollinearity among correlated driving factors may produce negative effects that must be eliminated from the modeling. Using exploratory regression under pre-defined criteria, we identified all possible combinations of factors from the candidate factors affecting land use change. Three combinations that incorporate five driving factors meeting pre-defined criteria were assessed. With the selected combinations of factors, three logistic regression-based CA models were built to simulate dynamic land use change in Shanghai, China, from 2000 to 2015. For comparative purposes, a CA model with all candidate factors was also applied to simulate the land use change. Simulations using three CA models with multicollinearity eliminated performed better (with accuracy improvements about 3.6%) than the model incorporating all candidate factors. Our results showed that not all candidate factors are necessary for accurate CA modeling and the simulations were not sensitive to changes in statistically non-significant driving factors. We conclude that exploratory regression is an effective method to search for the optimal combinations of driving factors, leading to better land use change models that are devoid of multicollinearity. We suggest identification of dominant factors and elimination of multicollinearity before building land change models, making it possible to simulate more realistic outcomes.     

Sub-hourly changes in biogeochemical properties in surface waters of Zuari estuary, Goa

Processes in natural waters are highly variable in time and space. Although changes are expected in short-time scales, how short one could get to measure reliably is subjective to sampling strategies and methodologies. Here, we show that sub-hourly changes in surface waters dissolved oxygen, nutrients, and pigments are measurable and significant in an estuarine system. Tidal circulation has been found to strongly influence the observed changes and has implications to material fluxes in and out of estuaries.     

Trends in land use and land cover change in the protected and communal areas of the Zambezi Region,Namibia

Land management decisions have extensively modified land use and land cover in the Zambezi Region. These decisions are influenced by land tenure classifications, legislation, and livelihoods. Land use and land cover change is an important indicator for quantifying the effectiveness of different land management strategies. However, there has been no evidence on whether protected or communal land tenure is more affected by land use and land cover changes in southern Africa and particularly Namibia. Our study attempted to fill this gap by analyzing the relationship between land use and land cover change and land tenure regimes stratified according to protected and communal area in the Zambezi Region. Multi-temporal Landsat TM and ETM+ imagery were used to determine the temporal dynamics of land use and land cover change from 1984 to 2010. The landscape showed distinctive modifications over the study period; broad trends include the increase in forest land after 1991. However, changes were not uniform across the study areas. Two landscape development stages were deduced: (1) 1984–1991 represented high deforestation and gradual increase in shrub land; (2) 1991–2000 and 2000–2010 represented lower deforestation and slower agropastoral expansion. The results further show clear patterns of the dynamics, magnitude, and direction of land use and land cover change by tenure regime. The study concluded that land tenure has a direct impact on land use and land cover, since it may restrict some activities carried out on the land in the Zambezi Region.     

Land cover change of watersheds in Southern Guam from 1973 to 2001

Land cover change can be caused by human-induced activities and natural forces. Land cover change in watershed level has been a main concern for a long time in the world since watersheds play an important role in our life and environment. This paper is focused on how to apply Landsat Multi-Spectral Scanner (MSS) satellite image of 1973 and Landsat Thematic Mapper (TM) satellite image of 2001 to determine the land cover changes of coastal watersheds from 1973 to 2001. GIS and remote sensing are integrated to derive land cover information from Landsat satellite images of 1973 and 2001. The land cover classification is based on supervised classification method in remote sensing software ERDAS IMAGINE. Historical GIS data is used to replace the areas covered by clouds or shadows in the image of 1973 to improve classification accuracy. Then, temporal land cover is utilized to determine land cover change of coastal watersheds in southern Guam. The overall classification accuracies for Landsat MSS image of 1973 and Landsat TM image of 2001 are 82.74% and 90.42%, respectively. The overall classification of Landsat MSS image is particularly satisfactory considering its coarse spatial resolution and relatively bad data quality because of lots of clouds and shadows in the image. Watershed land cover change in southern Guam is affected greatly by anthropogenic activities. However, natural forces also affect land cover in space and time. Land cover information and change in watersheds can be applied for watershed management and planning, and environmental modeling and assessment. Based on spatio-temporal land cover information, the interaction behavior between human and environment may be evaluated. The findings in this research will be useful to similar research in other tropical islands.     

丹江湿地国家级自然保护区及其内外区域2000—2015年土地覆被变化分析

为研究2000—2015年丹江湿地国家级自然保护区及其内外生态状况变化和保护成效,基于高分1号数据生产的2m高分辨率遥感影像数据对丹江湿地国家级自然保护区2015年人类活动状况进行分析,基于30 m分辨率的4期TM遥感影像生产的土地覆被数据和基于Modis遥感影像生产的植被覆盖度数据,对淅川县、丹江湿地国家级自然保护区及其核心区的土地覆被状况、土地覆被转类指数及其土地覆被转类途径的主导程度和3个相关区域范围内的生态系统质量以及不同区域土地覆被变化的主要变化原因进行分析。结果表明,保护区核心区的格局和质量在该区域处于最优,且土地覆被变化状况也以核心区转类指数最高;丹江湿地国家级自然保护区内的主要人类活动影响为耕地,其次包括居民点、采石场、养殖场; 15年间,保护区内外土地覆被均呈现转好趋势,但是保护区内变化优于保护区外,保护区核心区优于整个保护区,且转好的主导因素均是耕地变为湿地; 15年间植被覆盖度变化较小。     

The role of environmental and socio-demographic indicators in the analysis of land use changes in a protected area of the Natura 2000 Network: the case study of Lake Trasimeno,Umbria, Central Italy

This article sets out to analyse how and to what degree land use is linked to the physical characteristics of the territory itself, and the way in which changes in land use are determined by agricultural and socio-demographic dynamics. The study was conducted within the territorial boundaries of five municipalities surrounding Lake Trasimeno and refers to the periods 1977–2000 for land use and 1971–2001 for socio-demography data. The use of environmental, social, economic and agricultural indicators demonstrates how a mix of various indicators are useful for monitoring the changes which took place. It also shows the powerful influence that socio-demographic factors exert upon land use and landscape change.     

Application of geographically weighted regression model to analysis of spatiotemporal varying relationships between groundwater quantity and land use changes (case study: Khanmirza Plain,Iran)

Understanding the spatiotemporal relationships between land use/cover changes (LUCC) and groundwater resources is necessary for effective and efficient land use management. In this paper, geographically weighted regression (GWR) and ordinary least squares (OLS) models have been expanded to analyze varying spatial relationships between groundwater quantity changes and LUCC for three periods: 1987–2000, 2000–2010, and 1987–2010 in the Khanmirza Plain of southwestern Iran. For this purpose, TM images were used to generate LUCC (rainfed, irrigated, meadow, and bare lands). Groundwater quantity variables, including groundwater level changes (GLC) and groundwater withdrawal differences (GWD), were gathered from piezometric and agricultural wells data. The analysis of spatial autocorrelation (Moran’s I and local indicators of spatial association ) demonstrated that GWR has a better ability to model spatially varying data with very minimal clustering of residuals. The results R ² and corrected Akaike’s Information Criterion parameters revealed that the GWR has the lowest similarity in space and time in neighboring situations and it has the high ability to explain more variance in the LUCC as a function of the groundwater quantity changes. All results of the distribution of local R ² values from GWR confirm our assertion that there is a spatiotemporal relationship between types of land use and each of groundwater quantity variables within the region. According to the t test results from GWR, there are significant differences between the GLC and GWD and the land use types in different places of region in each of the three time series. The GWR results can help decision-makers to make appropriate decisions for future planning.     

Spatial Validation of Land Use Change Models Using Multiple Assessment Techniques: A Case Study of Transition Potential Models

Using land use and cover change (LUCC) models for the urban growth planning, environmental assessment, and decision-making needs the establishment of an appropriate level of confidence in their performance. The objective of this research is to explore the importance of using multiple assessment techniques in order to fairly evaluate the performance of land use models. An application is conducted by using the Land Change Modeler for Ecological Sustainability (LCM) which is an empirical and transition potential model. LCM is applied to model the agricultural to developed areas transition in Rennes metropolitan area (France). The land demand is estimated using the Markov Chain model; whereas, the transition potential map is implemented using the Multi-Layer Perceptron Neural Network (MLP) method based on historical changes and driving variables. The model performance is assessed based on a variety of the most commonly used validation techniques. At the study area level, the correctness and disagreement analysis shows that LCM performs better at predicting the amount than the allocation of developed areas. Additionally, landscape metrics reveal that LCM tends to predict a fragmented urban form, which seems evident because of the large number of the individual urban patches. At the municipality level, the error budget analysis shows that the model performance, which varies highly between different subareas, needs to be improved. Moreover, the cross-tabulation between the transition potential map and both the observed and the predicted agricultural to developed areas transitions reveals that the order of the transition potential values does not perfectly fit the observed change; whereas, the predicted change is not solely limited to areas with high potential.     

Climate impact of surface albedo change in Life Cycle Assessment: Implications of site and time dependence

Land use affects the global climate through greenhouse gas and aerosol emissions, as well as through changes in biophysical properties of the surface. Anthropogenic land use change over time has caused substantial climate forcing related to albedo, i.e. the share of solar radiation reflected back off the ground. There is growing concern that albedo change may offset climate benefits provided by afforestation, bioenergy or other emission reduction measures that affect land cover. Conversely, land could be managed actively to increase albedo as a strategy to combat global warming.Albedo change can be directly linked to radiative forcing, which allows its climate impact to be compared with that of greenhouse gases in Life Cycle Assessment (LCA). However, the most common LCA methods are static and linear and thus fail to account for the spatial and temporal dependence of albedo change and its strength as a climate forcer. This study sought to develop analytical methods that better estimate radiative forcing from albedo change by accounting for spatial and temporal variations in albedo, solar irradiance and transmission through the atmosphere. Simplifications concerning the temporal resolution and aggregation procedures of input data were evaluated.The results highlight the importance of spatial and temporal variations in determining the climate impact of albedo change in LCA. Irradiance and atmospheric transmittance depend on season, latitude and climate zone, and they co-vary with instantaneous albedo. Ignoring these dependencies led to case-specific errors in radiative forcing. Extreme errors doubled the climate cooling of albedo change or resulted in warming rather than cooling in two Swedish cases considered. Further research is needed to understand how different land use strategies affect the climate due to albedo, and how this compares to the effect of greenhouse gases. Given that albedo change and greenhouse gases act on different time scales, LCAs can provide better information in relation to climate targets if the timing of flows is considered in life cycle inventory analysis and impact assessment.     

The potential of remote sensing for monitoring land cover changes and effects on physical geography in the area of Kayisdagi Mountain and its surroundings (Istanbul)

The effect of land cover change, from natural to anthropogenic, on physical geography conditions has been studied in Kayisdagi Mountain. Land degradation is the most important environmental issue involved in this study. Most forms of land degradation are natural processes accelerated by human activity. Land degradation is a human induced or natural process that negatively affects the ability of land to function effectively within an ecosystem. Environmental degradation from human pressure and land use has become a major problem in the study area because of high population growth, urbanization rate, and the associated rapid depletion of natural resources. When studying the cost of land degradation, it is not possible to ignore the role of urbanization. In particular, a major cause of deforestation is conversion to urban land. The paper reviews the principles of current remote sensing techniques considered particularly suitable for monitoring Kayisdagi Mountain and its surrounding land cover changes and their effects on physical geography conditions. In addition, this paper addresses the problem of how spatially explicit information about degradation processes in the study area rangelands can be derived from different time series of satellite data. The monitoring approach comprises the time period between 1990 and 2005. Satellite remote sensing techniques have proven to be cost effective in widespread land cover changes. Physical geography and particularly natural geomorphologic processes like erosion, mass movement, physical weathering, and chemical weathering features etc. have faced significant unnatural variation.     

Evaluating exposure to land degradation in association with repetitive armed conflicts in North Lebanon using multi-temporal satellite data

Repetitive armed conflicts may be directly and indirectly responsible for severe biophysical modification to the environment. This, in turn, makes land more susceptible to degradation. Mapping and monitoring land degradation are essential for designing and implementing post-conflict recovery plans and informed policy decisions. The aim of this work was to evaluate the effect of repetitive armed conflicts on land degradation along the coastal zone of North Lebanon using multi-temporal satellite data. The specific objectives were to (1) identify a list of indicators for use in conjunction with satellite remote sensing, (2) monitor land cover change throughout repetitive events of armed conflicts and (3) model the effect of repetitive armed conflicts on land degradation. The methodology of work comprised the use of multi-temporal Landsat images and literature review data in GEographic Object-Based Image Analysis (GEOBIA) approach. The work resulted in the development of (1) a list of indicators to be employed, (2) land cover change detection maps with the use of multi-temporal Landsat images and, consequently, a fire risk associated with changes in vegetation cover throughout repetitive armed conflict events, and (3) an integrated approach for modelling the effect of repetitive armed conflicts on land degradation with the use of a composite land degradation index (CLDI). The final synthetic map showed four classes of exposure to land degradation associated with repetitive armed conflicts. Data collected from field visits showed that the final classification results highly reflected (average of 90 %) the effect of repetitive armed conflicts on the different classes of exposure to land degradation.     

Assessing Development Pressure in the Chesapeake Bay Watershed: An Evaluation of Two Land-Use Change Models

Natural resource lands in the Chesapeake Bay watershed are increasingly susceptible to conversion into developed land uses, particularly as the demand for residential development grows. We assessed development pressure in the Baltimore-Washington, DC region, one of the major urban and suburban centers in the watershed. We explored the utility of two modeling approaches for forecasting future development trends and patterns by comparing results from a cellular automata model, SLEUTH (slope, land use, excluded land, urban extent, transportation), and a supply/demand/allocation model, the Western Futures Model. SLEUTH can be classified as a land-cover change model and produces projections on the basis of historic trends of changes in the extent and patterns of developed land and future land protection scenarios. The Western Futures Model derives forecasts from historic trends in housing units, a U.S. Census variable, and exogenously supplied future population projections. Each approach has strengths and weaknesses, and combining the two has advantages and limitations.     

Evaluating Spatio-temporal Complexities of Forest Management: An Integrated Agent-based Modeling and GIS Approach

The objective of this study is to integrate agent-based modeling and geographic information systems (GIS) for examining how interactions within forest management lead to patterns of land-cover change. Specifically, this study evaluates how management agents behave in the presence of variable timber prices, harvesting costs, and accessibility to timber and how their actions influence the spatial characteristics of the forest landscape over time. The GIS calculates the average harvested patch size, number of patches, and total harvested area as measures of emergent patterns resulting from agent actions. The results from the agent-based GIS model reveal that good economic conditions lead to few but large harvested patches, while deteriorating conditions will see more patches of smaller size if forest companies have access to high-quality timber. This study emphasizes the need for a complex systems approach to forest management as the model illustrates how system elements interact in a manner to produce emergent spatial patterns over time.     

Monitoring landscape metrics by point sampling: accuracy in estimating Shannon’s diversity and edge density

Environmental monitoring of landscapes is of increasing interest. To quantify landscape patterns, a number of metrics are used, of which Shannon’s diversity, edge length, and density are studied here. As an alternative to complete mapping, point sampling was applied to estimate the metrics for already mapped landscapes selected from the National Inventory of Landscapes in Sweden (NILS). Monte-Carlo simulation was applied to study the performance of different designs. Random and systematic samplings were applied for four sample sizes and five buffer widths. The latter feature was relevant for edge length, since length was estimated through the number of points falling in buffer areas around edges. In addition, two landscape complexities were tested by applying two classification schemes with seven or 20 land cover classes to the NILS data. As expected, the root mean square error (RMSE) of the estimators decreased with increasing sample size. The estimators of both metrics were slightly biased, but the bias of Shannon’s diversity estimator was shown to decrease when sample size increased. In the edge length case, an increasing buffer width resulted in larger bias due to the increased impact of boundary conditions; this effect was shown to be independent of sample size. However, we also developed adjusted estimators that eliminate the bias of the edge length estimator. The rates of decrease of RMSE with increasing sample size and buffer width were quantified by a regression model. Finally, indicative cost–accuracy relationships were derived showing that point sampling could be a competitive alternative to complete wall-to-wall mapping.     

Effect of DEM mesh size on AnnAGNPS simulation and slope correction

The objective of this paper is to study the impact of the mesh size of the digital elevation model (DEM) on terrain attributes within an Annualized AGricultural NonPoint Source pollution (AnnAGNPS) Model simulation at watershed scale and provide a correction of slope gradient for low resolution DEMs. The effect of different grid sizes of DEMs on terrain attributes was examined by comparing eight DEMs (30, 40, 50, 60, 70, 80, 90, and 100 m). The accuracy of the AnnAGNPS stimulation on runoff, sediments, and nutrient loads is evaluated. The results are as follows: (1) Rnoff does not vary much with decrease of DEM resolution whereas soil erosion and total nitrogen (TN) load change prominently. There is little effect on runoff simulation of AnnAGNPS modeling by the amended slope using an adjusted 50 m DEM. (2) A decrease of sediment yield and TN load is observed with an increase of DEM mesh size from 30 to 60 m; a slight decrease of sediment and TN load with the DEM mesh size bigger than 60 m. There is similar trend for total phosphorus (TP) variation, but with less range of variation, the simulation of sediment, TN, and TP increase, in which sediment increase up to 1.75 times compared to the model using unadjusted 50 m DEM. In all, the amended simulation still has a large difference relative to the results using 30 m DEM. AnnAGNPS is less reliable for sediment loading prediction in a small hilly watershed. (3) Resolution of DEM has significant impact on slope gradient. The average, minimum, maximum of slope from the various DEMs reduced obviously with the decrease of DEM precision. For the grade of 0～15°, the slopes at lower resolution DEM are generally bigger than those at higher resolution DEM. But for the grade bigger than 15°, the slopes at lower resolution DEM are generally smaller than those at higher resolution DEM. So it is necessary to adjust the slope with a fitting equation. A cubic model is used for correction of slope gradient from lower resolution to that from higher resolution. Results for Dage watershed showed that fine meshes are desired to avoid large underestimates of sediment and total nitrogen loads and moderate underestimates of total phosphorus loads even with the slopes for the 50 m DEM adjusted to be more similar to the slopes from the 30 m DEM. Decreasing the mesh size beyond this threshold does not substantially affect the computed runoff flux but generated prediction errors for nitrogen and sediment yields. So the appropriate DEM will control error and make simulation at acceptable level.     

Uncertainties of forest area estimates caused by the minimum crown cover criterion

Defining “forest land” is a complex issue and has been discussed for decades. Today, a confusing multitude of definitions of forest land are in use making comparison of forest area figures difficult. But currently, comparability is receiving much attention when it comes to install market mechanisms for ecosystem services. Minimum crown cover is among the most frequently employed criteria of forest definitions. However, the size of the reference area on which the crown cover percent is to be measured is usually not defined. But how does a change of the size of the reference area affect the derived forest cover? In this study, we analyze the interactions of the crown cover threshold and the size of the reference area. We start with analyzing the interactions using a simple geometric model of the forest edge. Then, we extend the analysis by simulating artificial landscapes where we study how the interaction is affected by different degrees of forest fragmentation, crown cover proportion, and spatial resolution of the data source used. The simulation showed that large differences in forest cover (>50 %) may result for a fixed crown cover threshold value, just by changing the size of the reference area, where the magnitude of this effect is a function of the chosen threshold value and the spatial configuration of the crowns. As a consequence of the findings, we see an urgent need to complete forest definitions by defining a reference area in order to reduce uncertainties of forest cover estimates.