The LUC Approach to Creating a Continental-Scale Land-Cover Database for Russia

Land cover is an essential surface characteristic of the Earth. Yet -- this may come as a surprise -- there is no generally accepted, complete and universal land-cover product for Russia, as is the problem in many other parts of the world. A review of global land-cover databases concluded that one of the most pressing problems in global climate and ecosystem studies is a lack of adequate land-cover data. This may explain why land-cover mapping often leads to debate over classification schemes, use of class descriptors and labels, and product specifications. Land-use and land-cover information is required in various forms and at different scales. A variety of techniques are in current use to collect the necessary data, ranging from census studies, ground observations, to remotely sensed data. The methodological plurality has also resulted in a widely diverse number of methods to store and present these data. In view of this unsatisfactory situation, FAO and UNEP, with the support of UNESCO and a number of other organizations, have launched an initiative on harmonizing and standardizing land-use and land-cover classification systems. Another major effort has been launched by the International Geosphere-Biosphere Programme (IGBP), to serve the needs of the global environmental change research community. The IGBP-DIS Global 1 km Land-cover Project is currently underway. The project is primarily relying on NOAA AVHRR data and aims to develop and distribute a global data-set representing land-cover in terms of seventeen broad classes. Being aware of these efforts, and aiming to be consistent with and useful to the international research community, the Land-Use Change (LUC) project at IIASA decided at an early stage to be in active contact with the research groups charged with harmonizing land-use and land-cover classifications, to use their methods and standards as they would emerge. Consequently, as regards land-cover database development, the main task of the LUC project was defined as: (i) producing a complete list of land-cover categories in Europe and Northern Asia based on available national-level data sources, and (ii) which would correspond to the diversity of land-use and land-cover of this huge territory. Charged with this task, it was necessary to develop a framework allowing to concentrate the project's efforts on these problems. The objective of this paper is to present an outline and rationale of the methodology for elaborating the project's land-cover database. Comprising the major portion of the study region, the approach has been developed on the basis of Russian experience

Land Use and Land Cover Change Detection Using Remote Geospatial Techniques: A Case Study of an Urban City in Southwestern, Nigeria

Many cities in developing countries are experiencing ecosystem modification and change. Today, about 10 million hectares of the world’s forest cover have been converted to other land uses. In Nigeria, there is an estimated increase of 8.75 million ha of cropland and decrease of about 1.71 million ha of forest cover between 1995 to 2020, indicating that Nigeria has been undergoing a wide range of land use and land cover changes. This paper analyses the changes in land use/cover in Ila Orangun, Southwestern, Nigeria from 1986 to 2018, with a view to providing adequate information on the pattern and trend of land use and land cover changes for proper monitoring and effective planning. The study utilized satellite images from Landsat 1986, 2002 and 2018. Remote sensing and Geographical Information System techniques as well as supervised image classification method were used to assess the magnitude of changes in the city over the study period. The results show that 26.36% of forest cover and 44.48% of waterbody were lost between the period of 1986 and 2018. There was a rapid increase in crop land by 365.7% and gradual increase in built-up areas by 103.85% at an annual rate of 3.25%. Forest was the only land cover type that recorded a constant reduction in areal extent. The study concluded that the changes in land use and land cover is a result of anthropogenic activities in the study area

From imagery to ecology: Leveraging time series of all available Landsat observations to map and monitor ecosystem state and dynamics

https://zslpublications.onlinelibrary.wiley.com/doi/full/10.1002/rse2.24Published versio

Seafloor characterization using airborne hyperspectral co-registration procedures independent from attitude and positioning sensors

The advance of remote-sensing technology and data-storage capabilities has progressed in the last decade to commercial multi-sensor data collection. There is a constant need to characterize, quantify and monitor the coastal areas for habitat research and coastal management. In this paper, we present work on seafloor characterization that uses hyperspectral imagery (HSI). The HSI data allows the operator to extend seafloor characterization from multibeam backscatter towards land and thus creates a seamless ocean-to-land characterization of the littoral zone

Relevance of intermittent rivers and streams in agricultural landscape and their impact on provided ecosystem services—a Mediterranean case study

Ecosystem services (ES), as an interconnection of the landscape mosaic pieces, along with temporal rivers (IRES) are an object of research for environmental planners and ecological economists, among other specialists. This study presents (i) a review on the importance of IRES and the services they can provide to agricultural landscapes; (ii) a classification tool to assess the impact of IRES to provide ES by agricultural landscapes; (iii) the application of the proposed classification to the Caia River in order to identify the importance of this intermittent river for its surrounding agricultural landscape. The classification of the ES follows the Common International Classification of Ecosystem (CICES) classification that was adapted for the purposes of this study. Firstly, the list of ES provided by agricultural landscape was elaborated. In the next step, we assessed the potential of IRES to provide ES. Next, IRES impacts to ES within the agricultural landscape were evaluated according to observations from the conducted field monitoring in the study area. This study focuses on the relevance of the intermittent Caia River-a transboundary river in Spain and Portugal-and its ephemeral tributaries in the agricultural landscape. Our study estimates that each hydrological phase of IRES increases the ES provided by the agricultural landscape. However, the dry phase can potentially have negative impacts on several services. The intensification of the agricultural sector is the main provision of the water resource within the Caia River basin, but we were able to identify several other ES that were positively impacted. The present study is in line with the conclusions of other authors who state that IRES constitute a valuable resource which should not be underestimated by society.Agência financiadora COST Action CA15113 Slovak Research and Development Agency APVV-16-0278 UID/SOC/04020/2013info:eu-repo/semantics/publishedVersio

Mapping and assessment of ecosystems and their services. Urban ecosystems

Action 5 of the EU Biodiversity Strategy to 2020 requires member states to Map and Assess the state of Ecosystems and their Services (MAES). This report provides guidance for mapping and assessment of urban ecosystems. The MAES urban pilot is a collaboration between the European Commission, the European Environment Agency, volunteering Member States and cities, and stakeholders. Its ultimate goal is to deliver a knowledge base for policy and management of urban ecosystems by analysing urban green infrastructure, condition of urban ecosystems and ecosystem services. This report presents guidance for mapping urban ecosystems and includes an indicator framework to assess the condition of urban ecosystems and urban ecosystem services. The scientific framework of mapping and assessment is designed to support in particular urban planning policy and policy on green infrastructure at urban, metropolitan and regional scales. The results are based on the following different sources of information: a literature survey of 54 scientific articles, an online-survey (on urban ecosystems, related policies and planning instruments and with participation of 42 cities), ten case studies (Portugal: Cascais, Oeiras, Lisbon; Italy: Padua, Trento, Rome; The Netherlands: Utrecht; Poland: Poznań; Spain: Barcelona; Norway: Oslo), and a two-day expert workshop. The case studies constituted the core of the MAES urban pilot. They provided real examples and applications of how mapping and assessment can be organized to support policy; on top, they provided the necessary expertise to select a set of final indicators for condition and ecosystem services. Urban ecosystems or cities are defined here as socio-ecological systems which are composed of green infrastructure and built infrastructure. Urban green infrastructure (GI) is understood in this report as the multi-functional network of urban green spaces situated within the boundary of the urban ecosystem. Urban green spaces are the structural components of urban GI. This study has shown that there is a large scope for urban ecosystem assessments. Firstly, urban policies increasingly use urban green infrastructure and nature-based solutions in their planning process. Secondly, an increasing amount of data at multiple spatial scales is becoming available to support these policies, to provide a baseline, and to compare or benchmark cities with respect to the extent and management of the urban ecosystem. Concrete examples are given on how to delineate urban ecosystems, how to choose an appropriate spatial scale, and how to map urban ecosystems based on a combination of national or European datasets (including Urban Atlas) and locally collected information (e.g., location of trees). Also examples of typologies for urban green spaces are presented. This report presents an indicator framework which is composed of indicators to assess for urban ecosystem condition and for urban ecosystem services. These are the result of a rigorous selection process and ensure consistent mapping and assessment across Europe. The MAES urban pilot will continue with work on the interface between research and policy. The framework presented in this report needs to be tested and validated across Europe, e.g. on its applicability at city scale, on how far the methodology for measuring ecosystem condition and ecosystem service delivery in urban areas can be used to assess urban green infrastructure and nature-based solutions

Characterizing degradation gradients through land cover change analysis in rural Eastern Cape, South Africa

CITATION: Munch, Z., et al. 2017. Characterizing degradation gradients through land cover change analysis in rural Eastern Cape, South Africa. Geosciences, 7(1):7, doi:10.3390/geosciences7010007.The original publication is available at http://www.mdpi.comLand cover change analysis was performed for three catchments in the rural Eastern Cape, South Africa, for two time steps (2000 and 2014), to characterize landscape conversion trajectories for sustained landscape health. Land cover maps were derived: (1) from existing data (2000); and (2) through object-based image analysis (2014) of Landsat 8 imagery. Land cover change analysis was facilitated using land cover labels developed to identify landscape change trajectories. Land cover labels assigned to each intersection of the land cover maps at the two time steps provide a thematic representation of the spatial distribution of change. While land use patterns are characterized by high persistence (77%), the expansion of urban areas and agriculture has occurred predominantly at the expense of grassland. The persistence and intensification of natural or invaded wooded areas were identified as a degradation gradient within the landscape, which amounted to almost 10% of the study area. The challenge remains to determine significant signals in the landscape that are not artefacts of error in the underlying input data or scale of analysis. Systematic change analysis and accurate uncertainty reporting can potentially address these issues to produce authentic output for further modelling.http://www.mdpi.com/2076-3263/7/1/7Publisher's versio

Vegetation Dynamics in Ecuador

Global forest cover has suffered a dramatic reduction during recent decades, especially in tropical regions, which is mainly due to human activities caused by enhanced population pressures. Nevertheless, forest ecosystems, especially tropical forests, play an important role in the carbon cycle functioning as carbon stocks and sinks, which is why conservation strategies are of utmost importance respective to ongoing global warming. In South America the highest deforestation rates are observed in Ecuador, but an operational surveillance system for continuous forest monitoring, along with the determination of deforestation rates and the estimation of actual carbon socks is still missing. Therefore, the present investigation provides a functional tool based on remote sensing data to monitor forest stands at local, regional and national scales. To evaluate forest cover and deforestation rates at country level satellite data was used, whereas LiDAR data was utilized to accurately estimate the Above Ground Biomass (AGB; carbon stocks) at catchment level. Furthermore, to provide a cost-effective tool for continuous forest monitoring of the most vulnerable parts, an Unmanned Aerial Vehicle (UAV) was deployed and equipped with various sensors (RBG and multispectral camera). The results showed that in Ecuador total forest cover was reduced by about 24% during the last three decades. Moreover, deforestation rates have increased with the beginning of the new century, especially in the Andean Highland and the Amazon Basin, due to enhanced population pressures and the government supported oil and mining industries, besides illegal timber extractions. The AGB stock estimations at catchment level indicated that most of the carbon is stored in natural ecosystems (forest and páramo; AGB ~98%), whereas areas affected by anthropogenic land use changes (mostly pastureland) lost nearly all their storage capacities (AGB ~2%). Furthermore, the LiDAR data permitted the detection of the forest structure, and therefore the identification of the most vulnerable parts. To monitor these areas, it could be shown that UAVs are useful, particularly when equipped with an RGB camera (AGB correlation: R² > 0.9), because multispectral images suffer saturation of the spectral bands over dense natural forest stands, which results in high overestimations. In summary, the developed operational surveillance systems respective to forest cover at different spatial scales can be implemented in Ecuador to promote conservation/ restoration strategies and to reduce the high deforestation rates. This may also mitigate future greenhouse gas emissions and guarantee functional ecosystem services for local and regional populations

Linking remote-sensing estimates of land cover and census statistics on land use to produce maps of land use of the conterminous United States

Human use of the land has a large effect on the structure of terrestrial ecosystems and the dynamics of biogeochemical cycles. For this reason, terrestrial ecosystem and biogeochemistry models require moderate resolution (e.g., ≤0.5°) information on land use in order to make realistic predictions. Few such data sets currently exist. To create a land use data set of sufficient resolution, we developed models relating land cover data derived from optical remote sensing and a census database on land use for the conterminous United States. The land cover product used was from the International Geosphere-Biosphere Programme DISCover global product, derived from 1 km advanced very high resolution radiometer imagery, with 16 land cover classes. Land use data at state-level resolution came from the U.S. Department of Agriculture\u27s Major Land Uses database, aggregated into four general land use categories: Cropland, Pasture/Range, Forest, and Other. We developed and applied models relating these data sets to generate maps of land use in 1992 for the conterminous United States at 0.5° spatial resolution