Usability of VGI for validation of land cover maps

Volunteered Geographic Information (VGI) represents a growing source of potentially valuable data for many applications, including land cover map validation. It is still an emerging field and many different approaches can be used to take value from VGI, but also many pros and cons are related to its use. Therefore, since it is timely to get an overview of the subject, the aim of this article is to review the use of VGI as reference data for land cover map validation. The main platforms and types of VGI that are used and that are potentially useful are analysed. Since quality is a fundamental issue in map validation, the quality procedures used by the platforms that collect VGI to increase and control data quality are reviewed and a framework for addressing VGI quality assessment is proposed. A review of cases where VGI was used as an additional data source to assist in map validation is made, as well as cases where only VGI was used, indicating the procedures used to assess VGI quality and fitness for use. A discussion and some conclusions are drawn on best practices, future potential and the challenges of the use of VGI for land cover map validation.

Temporal analysis of land use and transportation investments with geographic information system

Land use and transportation interaction has been a research topic for several decades. There have been efforts to identify impacts of transportation on land use from several different perspectives. One focus has been the role of transportation improvements in encouraging new land developments or relocation of activities due to improved accessibility. The impacts studied have included property values and increased development. Another focus has been on the changes in travel behavior due to better mobility and accessibility. Most studies to date have been conducted in metropolitan level, thus unable to account for interactions spatially and temporally at smaller geographic scales. ^ In this study, a framework for studying the temporal interactions between transportation and land use was proposed and applied to three selected corridor areas in Miami-Dade County, Florida. The framework consists of two parts: one is developing of temporal data and the other is applying time series analysis to this temporal data to identify their dynamic interactions. Temporal GIS databases were constructed and used to compile building permit data and transportation improvement projects. Two types of time series analysis approaches were utilized: univariate models and multivariate models. Time series analysis is designed to describe the dynamic consequences of time series by developing models and forecasting the future of the system based on historical trends. Model estimation results from the selected corridors were then compared. ^ It was found that the time series models predicted residential development better than commercial development. It was also found that results from three study corridors varied in terms of the magnitude of impacts, length of lags, significance of the variables, and the model structure. Long-run effect or cumulated impact of transportation improvement on land developments was also measured with time series techniques. The study offered evidence that congestion negatively impacted development and transportation investments encouraged land development. ^

Modeling the Effect of Land Use and Climate Change Scenarios on the Water Flux of the Upper Mara River Flow, Kenya

Increasingly erratic flow in the upper reaches of the Mara River, has directed attention to land use change as the major cause of this problem. The semi-distributed hydrological model SWAT and Landsat imagery were utilized in order to 1) map existing land use practices, 2) determine the impacts of land use change on water flux; and 3) determine the impacts of climate change scenarios on the water flux of the upper Mara River. This study found that land use change scenarios resulted in more erratic discharge while climate change scenarios had a more predictable impact on the discharge and water balance components. The model results showed the flow was more sensitive to the rainfall changes than land use changes but land use changes reduce dry season flows which is a major problem in the basin. Deforestation increased the peak flows which translated to increased sediment loading in the Mara River.

A Modeling Approach to Determine the Impacts of Land Use and Climate Change Scenarios on the Water Flux of the Upper Mara River

With the flow of the Mara River becoming increasingly erratic especially in the upper reaches, attention has been directed to land use change as the major cause of this problem. The semi-distributed hydrological model Soil and Water Assessment Tool 5 (SWAT) and Landsat imagery were utilized in the upper Mara River Basin in order to 1) map existing field scale land use practices in order to determine their impact 2) determine the impacts of land use change on water flux; and 3) determine the impacts of rainfall (0%, ±10% and ±20%) and air temperature variations (0% and +5%) based on the Intergovernmental Panel on Climate Change projections on the water flux of the 10 upper Mara River. This study found that the different scenarios impacted on the water balance components differently. Land use changes resulted in a slightly more erratic discharge while rainfall and air temperature changes had a more predictable impact on the discharge and water balance components. These findings demonstrate that the model results 15 show the flow was more sensitive to the rainfall changes than land use changes. It was also shown that land use changes can reduce dry season flow which is the most important problem in the basin. The model shows also deforestation in the Mau Forest increased the peak flows which can also lead to high sediment loading in the Mara River. The effect of the land use and climate change scenarios on the sediment and 20 water quality of the river needs a thorough understanding of the sediment transport processes in addition to observed sediment and water quality data for validation of modeling results.

Land Use and Climate Change Impacts on the Hydrology of the Upper Mara River Basin, Kenya: Results of a Modeling Study to Support Better Resource Management

Some of the most valued natural and cultural landscapes on Earth lie in river basins that are poorly gauged and have incomplete historical climate and runoff records. The Mara River Basin of East Africa is such a basin. It hosts the internationally renowned Mara-Serengeti landscape as well as a rich mixture of indigenous cultures. The Mara River is the sole source of surface water to the landscape during the dry season and periods of drought. During recent years, the flow of the Mara River has become increasingly erratic, especially in the upper reaches, and resource managers are hampered by a lack of understanding of the relative influence of different sources of flow alteration. Uncertainties about the impacts of future climate change compound the challenges. We applied the Soil Water Assessment Tool (SWAT) to investigate the response of the headwater hydrology of the Mara River to scenarios of continued land use change and projected climate change. Under the data-scarce conditions of the basin, model performance was improved using satellite-based estimated rainfall data, which may also improve the usefulness of runoff models in other parts of East Africa. The results of the analysis indicate that any further conversion of forests to agriculture and grassland in the basin headwaters is likely to reduce dry season flows and increase peak flows, leading to greater water scarcity at critical times of the year and exacerbating erosion on hillslopes. Most climate change projections for the region call for modest and seasonally variable increases in precipitation (5–10 %) accompanied by increases in temperature (2.5–3.5 °C). Simulated runoff responses to climate change scenarios were non-linear and suggest the basin is highly vulnerable under low (−3 %) and high (+25 %) extremes of projected precipitation changes, but under median projections (+7 %) there is little impact on annual water yields or mean discharge. Modest increases in precipitation are partitioned largely to increased evapotranspiration. Overall, model results support the existing efforts of Mara water resource managers to protect headwater forests and indicate that additional emphasis should be placed on improving land management practices that enhance infiltration and aquifer recharge as part of a wider program of climate change adaptation.

The Lena River Delta - Land cover classification of tundra environments based on Landsat 7 ETM+ data and its application for upscaling of methane emissions

The Lena River Delta, situated in Northern Siberia (72.0 - 73.8° N, 122.0 - 129.5° E), is the largest Arctic delta and covers 29,000 km**2. Since natural deltas are characterised by complex geomorphological patterns and various types of ecosystems, high spatial resolution information on the distribution and extent of the delta environments is necessary for a spatial assessment and accurate quantification of biogeochemical processes as drivers for the emission of greenhouse gases from tundra soils. In this study, the first land cover classification for the entire Lena Delta based on Landsat 7 Enhanced Thematic Mapper (ETM+) images was conducted and used for the quantification of methane emissions from the delta ecosystems on the regional scale. The applied supervised minimum distance classification was very effective with the few ancillary data that were available for training site selection. Nine land cover classes of aquatic and terrestrial ecosystems in the wetland dominated (72%) Lena Delta could be defined by this classification approach. The mean daily methane emission of the entire Lena Delta was calculated with 10.35 mg CH4/m**2/d. Taking our multi-scale approach into account we find that the methane source strength of certain tundra wetland types is lower than calculated previously on coarser scales.

Global Change Pressures on Soils from Land Use and Management

This work contributed to The input of PS and PCW contributes to the Belmont Forum/FACCE-JPI funded DEVIL project (NE/M021327/1) and for PS also contributes to the EU FP7 SmartSoil project (Project number: 289694)

Global Change Pressures on Soils from Land Use and Management

This work contributed to The input of PS and PCW contributes to the Belmont Forum/FACCE-JPI funded DEVIL project (NE/M021327/1) and for PS also contributes to the EU FP7 SmartSoil project (Project number: 289694)

Land Use and Water Quality Correlations in Miami-Dade, Florida

South Florida continues to become increasingly developed and urbanized. My exploratory study examines connections between land use and water quality. The main objectives of the project were to develop an understanding of how land use has affected water quality in Miami-Dade canals, and an economic optimization model to estimate the costs of best management practices necessary to improve water quality. Results indicate Miami-Dade County land use and water quality are correlated. Through statistical factor and cluster analysis, it is apparent that agricultural areas are associated with higher concentrations of nitrogen, while urban areas commonly have higher levels of phosphorous than agricultural areas. The economic optimization model shows that urban areas can improve water quality by lowering fertilizer inputs. Agricultural areas can also implement methods to improve water quality although it may be more expensive than urban areas. It is important to keep solutions in mind when looking towards future water quality improvements in South Florida.

Baseline characteristics of climate, permafrost, and land cover from Samoylov Island, Lena River Delta, Siberia

Samoylov Island is centrally located within the Lena River Delta at 72° N, 126° E and lies within the Siberian zone of continuous permafrost. The landscape on Samoylov Island consists mainly of late Holocene river terraces with polygonal tundra, ponds and lakes, and an active floodplain. The island has been the focus of numerous multidisciplinary studies since 1993, which have focused on climate, land cover, ecology, hydrology, permafrost and limnology. This paper aims to provide a framework for future studies by describing the characteristics of the island's meteorological parameters (temperature, radiation and snow cover), soil temperature, and soil moisture. The land surface characteristics have been described using high resolution aerial images in combination with data from ground-based observations. Of note is that deeper permafrost temperatures have increased between 0.3 to 1.3 °C over the last five years. However, no clear warming of air and active layer temperatures is detected since 1998, though winter air temperatures during recent years have not been as cold as in earlier years.

Land cover classification of Samoylov Island and Landsat subpixel water cover of Lena River Delta, Siberia, with links to ESRI grid files

Ignoring small-scale heterogeneities in Arctic land cover may bias estimates of water, heat and carbon fluxes in large-scale climate and ecosystem models. We investigated subpixel-scale heterogeneity in CHRIS/PROBA and Landsat-7 ETM+ satellite imagery over ice-wedge polygonal tundra in the Lena Delta of Siberia, and the associated implications for evapotranspiration (ET) estimation. Field measurements were combined with aerial and satellite data to link fine-scale (0.3 m resolution) with coarse-scale (upto 30 m resolution) land cover data. A large portion of the total wet tundra (80%) and water body area (30%) appeared in the form of patches less than 0.1 ha in size, which could not be resolved with satellite data. Wet tundra and small water bodies represented about half of the total ET in summer. Their contribution was reduced to 20% in fall, during which ET rates from dry tundra were highest instead. Inclusion of subpixel-scale water bodies increased the total water surface area of the Lena Delta from 13% to 20%. The actual land/water proportions within each composite satellite pixel was best captured with Landsat data using a statistical downscaling approach, which is recommended for reliable large-scale modelling of water, heat and carbon exchange from permafrost landscapes.

Previous land use and climate influence differences in soil organic carbon following reforestation of agricultural land with mixed-species plantings

Reforestation of agricultural land with mixed-species environmental plantings (native trees and shrubs) can contribute to mitigation of climate change through sequestration of carbon. Although soil carbon sequestration following reforestation has been investigated at site- and regional-scales, there are few studies across regions where the impact of a broad range of site conditions and management practices can be assessed. We collated new and existing data on soil organic carbon (SOC, 0–30 cm depth, N = 117 sites) and litter (N = 106 sites) under mixed-species plantings and an agricultural pair or baseline across southern and eastern Australia. Sites covered a range of previous land uses, initial SOC stocks, climatic conditions and management types. Differences in total SOC stocks following reforestation were significant at 52% of sites, with a mean rate of increase of 0.57 ± 0.06 Mg C ha−1 y−1. Increases were largely in the particulate fraction, which increased significantly at 46% of sites compared with increases at 27% of sites for the humus fraction. Although relative increase was highest in the particulate fraction, the humus fraction was the largest proportion of total SOC and so absolute differences in both fractions were similar. Accumulation rates of carbon in litter were 0.39 ± 0.02 Mg C ha−1 y−1, increasing the total (soil + litter) annual rate of carbon sequestration by 68%. Previously-cropped sites accumulated more SOC than previously-grazed sites. The explained variance differed widely among empirical models of differences in SOC stocks following reforestation according to SOC fraction and depth for previously-grazed (R2 = 0.18–0.51) and previously-cropped (R2 = 0.14–0.60) sites. For previously-grazed sites, differences in SOC following reforestation were negatively related to total SOC in the pasture. By comparison, for previously-cropped sites, differences in SOC were positively related to mean annual rainfall. This improved broad-scale understanding of the magnitude and predictors of changes in stocks of soil and litter C following reforestation is valuable for the development of policy on carbon markets and the establishment of future mixed-species environmental plantings.

Land use and zoning map, Jackson Brook watershed, Morris County, New Jersey /

Shows "1988 land use."