Past and future prediction of land cover land use change based on earth observation data by the CA–Markov model: a case study from Duhok governorate, Iraq

2021 ◽  
Vol 14 (15) ◽  
Author(s):  
Nabaz R. Khwarahm ◽  
Peshawa M. Najmaddin ◽  
Korsh Ararat ◽  
Sarchil Qader
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Land Cover ◽  
Markov Model ◽  
Earth Observation ◽  
Observation Data ◽  
Future Prediction ◽  
Earth Observation Data

Modelling of land use land cover change using earth observation data-sets of Tons River Basin, Madhya Pradesh, India

2017 ◽  
Vol 33 (11) ◽  
pp. 1202-1222 ◽  
Author(s):  
Sudhir Kumar Singh ◽  
Prosper Basommi Laari ◽  
Sk. Mustak ◽  
Prashant K. Srivastava ◽  
Szilárd Szabó
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
River Basin ◽  
Earth Observation ◽  
Data Sets ◽  
Observation Data ◽  
Land Use Land Cover ◽  
Earth Observation Data ◽  
Tons River Basin

Development of earth observation data cubes for monitoring land degradation processes in South Africa

2021 ◽  
Author(s):  
Insa Otte ◽  
Nosiseko Mashiyi ◽  
Pawel Kluter ◽  
Steven Hill ◽  
Andreas Hirner ◽  
...  
Keyword(s):  
South Africa ◽  
Land Use ◽  
Ecosystem Services ◽  
Land Use Change ◽  
South African ◽  
Land Degradation ◽  
Earth Observation ◽  
Observation Data ◽  
Data Cubes ◽  
Earth Observation Data

<p>Global biodiversity and ecosystem services are under high pressure of human impact. Although avoiding, reducing and reversing the impacts of human activities on ecosystems should be an urgent priority, the loss of biodiversity continues. One of the main drivers of biodiversity loss is land use change and land degradation. In South Africa land degradation has a long history and is of great concern. The SPACES II project SALDi (South African Land Degradation Monitor) aims for developing new, adaptive and sustainable tools for assessing land degradation by addressing the dynamics and functioning of multi-use landscapes with respect to land use change and ecosystem services. SPACES II is a German-South African “Science Partnerships for the Adaptation to Complex Earth System Processes”. Within SALDi ready-to-use earth observation (EO) data cubes are developed. EO data cubes are useful and effective tools using earth observations to deliver decision-ready products. By accessing, storing and processing of remote sensing products and time-series in data cubes, the efficient monitoring of land degradation can therefore be enabled. The SALDi data cubes from optical and radar satellite data include all necessary pre-processing steps and are generated to monitor vegetation dynamics of five years for six focus areas. Intra- and interannual variability in both, a high spatial and temporal resolution will be accounted to monitor land degradation. Therefore, spatial high resolution earth observation data from 2016 to 2021 from Sentinel-1 (C-Band radar) and Sentinel-2 (multispectral) will be integrated in the SALDi data cube for six research areas of 100 x 100 km. Additionally, a number of vegetation indices will be implemented to account for explicit land degradation and vegetation monitoring. Spatially explicit query tools will enable users of the system to focus on specific areas, like hydrological catchments or blocks of fields.</p>

scholarly journals EXPOSURE AND VULNERABILITY GEOSPATIAL ANALYSIS USING EARTH OBSERVATION DATA IN THE CITY OF LIEGE, BELGIUM

2017 ◽  
Vol IV-1/W1 ◽  
pp. 149-156
Author(s):  
N. Stephenne ◽  
B. Beaumont ◽  
E. Hallot ◽  
F. Lenartz ◽  
F. Lefebre ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Land Use ◽  
Air Pollution ◽  
Land Cover ◽  
Urban Heat Island ◽  
Earth Observation ◽  
Observation Data ◽  
Heat Island ◽  
Urban Heat ◽  
Earth Observation Data

Risk situation can be mitigated by prevention measures, early warning tools and adequate monitoring of past experiences where Earth Observation and geospatial analysis have an adding value. This paper discusses the potential use of Earth Observation data and especially Land Cover / Land Use map in addressing within the three aspects of the risk assessment: danger, exposure and vulnerability. Evidences of the harmful effects of air pollution or heat waves are widely admitted and should increase in the context of global warming. Moreover, urban areas are generally warmer than rural surroundings, the so-called urban heat island. Combined with in-situ measurements, this paper presents models of city or local climate (air pollution and urban heat island), with a resolution of less than one kilometer, developed by integrating several sources of information including Earth Observation data and in particular Land Cover / Land Use. This assessment of the danger is then be related to a map of exposure and vulnerable people. Using dasymetric method to disaggregate statistical information on Land Cover / Land Use data, the SmartPop project analyzes in parallel the map of danger with the maps of people exposure A special focus on some categories at risk such as the elderly has been proposed by Aubrecht and Ozceylan (2013). Perspectives of the project includes the integration of a new Land Cover / Land Use map in the danger, exposure and vulnerability models and proposition of several aspects of risk assessment with the stakeholders of Wallonia.

scholarly journals Land use/land cover in view of earth observation: data sources, input dimensions, and classifiers—a review of the state of the art

2019 ◽  
pp. 1-32 ◽  
Author(s):  
Prem Chandra Pandey ◽  
Nikos Koutsias ◽  
George P. Petropoulos ◽  
Prashant K. Srivastava ◽  
Eyal Ben Dor
Keyword(s):  
Land Use ◽  
Land Cover ◽  
State Of The Art ◽  
Earth Observation ◽  
The State ◽  
Data Sources ◽  
Observation Data ◽  
Land Use Land Cover ◽  
Earth Observation Data

scholarly journals Quantifying Tree Cover Loss in Urban Forests within Nairobi City Metropolitan Area from Earth Observation Data

2020 ◽  
Vol 3 (1) ◽  
pp. 78
Author(s):  
Francis Oloo ◽  
Godwin Murithi ◽  
Charlynne Jepkosgei
Keyword(s):  
Land Cover ◽  
Metropolitan Area ◽  
Land Surface ◽  
Urban Forest ◽  
Urban Forests ◽  
Earth Observation ◽  
Tree Cover ◽  
Observation Data ◽  
Vegetation Health ◽  
Earth Observation Data

Urban forests contribute significantly to the ecological integrity of urban areas and the quality of life of urban dwellers through air quality control, energy conservation, improving urban hydrology, and regulation of land surface temperatures (LST). However, urban forests are under threat due to human activities, natural calamities, and bioinvasion continually decimating forest cover. Few studies have used fine-scaled Earth observation data to understand the dynamics of tree cover loss in urban forests and the sustainability of such forests in the face of increasing urban population. The aim of this work was to quantify the spatial and temporal changes in urban forest characteristics and to assess the potential drivers of such changes. We used data on tree cover, normalized difference vegetation index (NDVI), and land cover change to quantify tree cover loss and changes in vegetation health in urban forests within the Nairobi metropolitan area in Kenya. We also used land cover data to visualize the potential link between tree cover loss and changes in land use characteristics. From approximately 6600 hectares (ha) of forest land, 720 ha have been lost between 2000 and 2019, representing about 11% loss in 20 years. In six of the urban forests, the trend of loss was positive, indicating a continuing disturbance of urban forests around Nairobi. Conversely, there was a negative trend in the annual mean NDVI values for each of the forests, indicating a potential deterioration of the vegetation health in the forests. A preliminary, visual inspection of high-resolution imagery in sample areas of tree cover loss showed that the main drivers of loss are the conversion of forest lands to residential areas and farmlands, implementation of big infrastructure projects that pass through the forests, and extraction of timber and other resources to support urban developments. The outcome of this study reveals the value of Earth observation data in monitoring urban forest resources.

Space Observatory for carbon budget monitoring in Russian forests using Earth observations and modelling

2020 ◽  
Author(s):  
Sergey Bartalev
Keyword(s):  
Land Cover ◽  
Carbon Budget ◽  
Earth Observation ◽  
Forest Carbon ◽  
Observation Data ◽  
Space Observatory ◽  
Russian Science ◽  
Land Cover Types ◽  
Russian Forests ◽  
Earth Observation Data

<p>Russian forest is a factor of global importance for implementation of international conventions on climate considering its potential for absorption and accumulation of the atmospheric carbon at an impressive scale. Considering recently adopted Paris agreement on climate the comprehensive and accurate estimation of Russian forests’ carbon budget became a top priority research and development issue on national agenda. However existing quantitative estimates of Russian forests’ carbon budget are of significant level of uncertainty. One of the most obvious reasons for such uncertainty is not sufficiently reliable and up-to-date information on characteristics of forests and their dynamics.</p><p>The Russian Science Foundation has supported an ambitious research megaproject titled “Space Observatory for Forest Carbon” (SOFC) started in year 2019 and aimed at the development of a new concept and comprehensive methods for forest carbon budget monitoring using Earth observation data and forest growth and dynamics models. The main SOFC project objectives are as follows:</p><p>- Development of a new concept and methodology for Russian forests and their carbon budget monitoring based on the integration of remote sensing and ground data along with improved models of forest structure and dynamics;</p><p>- Development of new annually updated GIS databases on the characteristics and multi-annual dynamics of Russian forests;</p><p>- Development of an informational system and technology for the continuous monitoring of Russian forests’ carbon budget.</p><p>Information necessary for carbon budget estimation includes data on various land cover types, forest characteristics (growing stock volume, species composition, age, site-index) and ecological parameters (Net Primary Production, heterotrophic respiration). Data on natural (fires, diseases and pests, windstorm, droughts) and anthropogenic (felling, pollution) forest disturbances causing deforestation, as well as information on subsequent reforestation processes are also vital.</p><p>The existing remote sensing methods can provide significant part of missing country-wide information about the land cover types and forest characteristics for the national-scale carbon budget estimation and monitoring. Multi-year time series of this data since the beginning of the century allow modelling the forest dynamics and its biophysical characteristics. The Earth observation data derived information on forest fires’ impact includes burnt area mapping over various land cover types as well as forest fire severity assessment allowing characterisation of fire induced carbon emissions. Furthermore, developed methods for processing and analysis of multi-year satellite data time series enable detection of forest cover changes caused by various destructive factors making it possible to substantially improve the accuracy of carbon budget estimation.</p><p>Obtained information on forest ecosystems’ parameters is used to improve existing and develop new approaches to forest carbon budget estimation, as well as to simulate various scenarios of Russian economy development depending on forest management practices and climate change trajectories.</p><p>This work was supported by the Russian Science Foundation [grant number 19-77-30015].</p>

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