Multitemporal Analysis of Sentinel‐1/2 Images for Land Use Monitoring at Regional Scale

2021 ◽  
pp. 201-222
Author(s):  
Andrea Garzelli ◽  
Claudia Zoppetti
Keyword(s):  
Land Use ◽  
Regional Scale ◽  
Multitemporal Analysis ◽  
Land Use Monitoring

Lessons learned from a VGI initiative for Land Use monitoring

2021 ◽  
Vol 3 ◽  
pp. 1-3
Author(s):  
Ana-Maria Olteanu-Raimond ◽  
Marie-Dominique Van Damme ◽  
Laurence Jolivet
Keyword(s):  
Land Use ◽  
Lessons Learned ◽  
Land Use Monitoring

Climate and land use change impacts on water resources in Sardinia (Italy)

2021 ◽  
Author(s):  
Dario Ruggiu ◽  
Salvatore Urru ◽  
Roberto Deidda ◽  
Francesco Viola
Keyword(s):  
Land Use ◽  
Water Resources ◽  
Land Use Change ◽  
Hydrological Cycle ◽  
Potential Evapotranspiration ◽  
Regional Scale ◽  
Annual Runoff ◽  
Annual Rainfall ◽  
Land Use Scenarios ◽  
Near Future

<p>The assessment of climate change and land use modifications effects on hydrological cycle is challenging. We propose an approach based on Budyko theory to investigate the relative importance of natural and anthropogenic drivers on water resources availability. As an example of application, the proposed approach is implemented in the island of Sardinia (Italy), which is affected by important processes of both climate and land use modifications. In details, the proposed methodology assumes the Fu’s equation to describe the mechanisms of water partitioning at regional scale and uses the probability distributions of annual runoff (Q) in a closed form. The latter is parametrized by considering simple long-term climatic info (namely first orders statistics of annual rainfall and potential evapotranspiration) and land use properties of basins.</p><p>In order to investigate the possible near future water availability of Sardinia, several climate and land use scenarios have been considered, referring to 2006-2050 and 2051-2100 periods. Climate scenarios have been generated considering fourteen bias corrected outputs of climatic models from EUROCORDEX’s project (RCP 8.5), while three land use scenarios have been created following the last century tendencies.</p><p>Results show that the distribution of annual runoff in Sardinia could be significantly affected by both climate and land use change. The near future distribution of Q generally displayed a decrease in mean and variance compared to the baseline.   </p><p>The reduction of  Q is more critical moving from 2006-2050 to 2051-2100 period, according with climatic trends, namely due to the reduction of annual rainfall and the increase of potential evapotranspiration. The effect of LU change on Q distribution is weaker than the climatic one, but not negligible.</p>

scholarly journals FOREST CERTIFICATION AS A TOOL TO ENSURE THE BALANCE OF FORESTRY LAND USE

2021 ◽  
Vol 71 (3) ◽  
Author(s):  
Stepan Dankevych
Keyword(s):  
Land Use ◽  
Regional Scale ◽  
Environmental Indicators ◽  
Statistical Characteristics ◽  
Forest Certification ◽  
Capital Investments ◽  
Forest Lands ◽  
The Impact ◽  
The Relationship ◽  
Over Time

The problem of ensuring the balanced use of forest lands determines the search for new economic and environmental tools that can influence this process. The need to improve the certification tool as part of the financial and economic mechanism for ensuring balanced forestry land use corresponds to the directions of state policy and European integration intentions of Ukraine, modern requirements of the ecological aspect of forestry land use. The work examines the practice in the field of forest certification in Ukraine from the point of view of balanced land use. Spatial-temporal analysis and assessment of the scale and dynamics of the spread of forest FSC certification in Ukraine has been carried out. The study was formed in three stages: (I) study of changes over time in the volume of forest certification on a national scale, (II) assessment of trends over time for indicators on a regional scale, (III) study of the relationship between individual indicators. The analysis of the impact of FSC-certification of forest management in Ukraine on the environmental indicators of forestry land use based on the results of the correlation between the statistical characteristics of certain economic and environmental indicators, such as the area of certified forests, capital investments, reforestation. Analysis of statistical data showed the relationship between environmental and economic performance over time and changes in specific characteristics on a regional scale. The study makes it possible, on the basis of an objectively existing causal relationship between phenomena and indicators, to identify the course of certain positive or negative processes in forestry land use. Forest certification can play a role in maintaining a balanced use of forest lands, preventing illegal logging, forest degradation and contributing to reforestation and capital investments. The study helps to identify certain key variables that limit the ability of forestry operators to ensure balanced use of forest lands and how forest certification can affect this. Foreign experience in stimulating forest certification has been investigated for the possibility of borrowing the experience of using management tools in order to motivate forest certification in Ukraine. It has been proven that certification is a significant environmental tool for ensuring a balanced level of land use and has the potential for further development.

Mapping Regional Landscape by Using OpenstreetMap (OSM)

2019 ◽  
pp. 771-790 ◽  
Author(s):  
Di Yang
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Forest Cover ◽  
Regional Scale ◽  
Google Earth ◽  
Computing Power ◽  
New Approach ◽  
Computation Cost ◽  
Regional Landscape ◽  
Google Earth Engine

A forest patterns map over a large extent at high spatial resolution is a heavily computation task but is critical to most regions. There are two major difficulties in generating the classification maps at regional scale: large training points sets and expensive computation cost in classifier modelling. As one of the most well-known Volunteered Geographic Information (VGI) initiatives, OpenstreetMap contributes not only on road network distributions, but the potential of justify land cover and land use. Google Earth Engine is a platform designed for cloud-based mapping with a strong computing power. In this study, we proposed a new approach to generating forest cover map and quantifying road-caused forest fragmentations by using OpenstreetMap in conjunction with remote sensing dataset stored in Google Earth Engine. Additionally, the landscape metrics produced after incorporating OpenStreetMap (OSM) with the forest spatial pattern layers from our output indicated significant levels of forest fragmentation in Yucatan peninsula.

Mapping Regional Landscape by Using OpenstreetMap (OSM)

2017 ◽  
pp. 138-157
Author(s):  
Di Yang
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Forest Cover ◽  
Regional Scale ◽  
Google Earth ◽  
Computing Power ◽  
New Approach ◽  
Computation Cost ◽  
Regional Landscape ◽  
Google Earth Engine

A forest patterns map over a large extent at high spatial resolution is a heavily computation task but is critical to most regions. There are two major difficulties in generating the classification maps at regional scale: large training points sets and expensive computation cost in classifier modelling. As one of the most well-known Volunteered Geographic Information (VGI) initiatives, OpenstreetMap contributes not only on road network distributions, but the potential of justify land cover and land use. Google Earth Engine is a platform designed for cloud-based mapping with a strong computing power. In this study, we proposed a new approach to generating forest cover map and quantifying road-caused forest fragmentations by using OpenstreetMap in conjunction with remote sensing dataset stored in Google Earth Engine. Additionally, the landscape metrics produced after incorporating OpenStreetMap (OSM) with the forest spatial pattern layers from our output indicated significant levels of forest fragmentation in Yucatan peninsula.

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