scholarly journals A high-resolution and harmonized model approach for reconstructing and analysing historic land changes in Europe

2016 ◽  
Vol 1 (1) ◽  
Author(s):  
Richard Fuchs
Keyword(s):  
High Resolution ◽  
The Netherlands ◽  
Land Cover ◽  
Atmospheric Carbon Dioxide ◽  
Land Use Changes ◽  
Aerial Photographs ◽  
Land Change ◽  
Reforestation Program ◽  
Land Changes ◽  
Model Approach

<p><span class="pb_authors"><strong>R. Fuchs<sup>1</sup>, M. Herold<sup>1</sup>, P. H. Verburg<sup>2</sup>, and J. G. P. W. Clevers<sup>1</sup></strong></span><br /><span class="pb_affiliations"><sup>1</sup>Laboratory of Geoinformation Science and Remote Sensing, Wageningen University, Droevendaalsesteeg 3, 6708 PB Wageningen, the Netherlands<br /><sup>2</sup>Institute for Environmental Studies, VU University Amsterdam, De Boelelaan 1085, 1081 HV Amsterdam, the Netherlands</span></p><p>Human-induced land use changes are nowadays the second largest contributor to atmospheric carbon dioxide after fossil fuel combustion. Existing historic land change reconstructions on the European scale do not sufficiently meet the requirements of greenhouse gas (GHG) and climate assessments, due to insufficient spatial and thematic detail and the consideration of various land change types. This paper investigates if the combination of different data sources, more detailed modelling techniques, and the integration of land conversion types allow us to create accurate, high-resolution historic land change data for Europe suited for the needs of GHG and climate assessments. We validated our reconstruction with historic aerial photographs from 1950 and 1990 for 73 sample sites across Europe and compared it with other land reconstructions like Klein Goldewijk et al. (2010, 2011), Ramankutty and Foley (1999), Pongratz et al. (2008) and Hurtt et al. (2006). The results indicate that almost 700 000 km2 (15.5%) of land cover in Europe has changed over the period 1950–2010, an area similar to France. In Southern Europe the relative amount was almost 3.5% higher than average (19%). Based on the results the specific types of conversion, hot-spots of change and their relation to political decisions and socio-economic transitions were studied. The analysis indicates that the main drivers of land change over the studied period were urbanization, the reforestation program resulting from the timber shortage after the Second World War, the fall of the Iron Curtain, the Common Agricultural Policy and accompanying afforestation actions of the EU. Compared to existing land cover reconstructions, the new method considers the harmonization of different datasets by achieving a high spatial resolution and regional detail with a full coverage of different land categories. These characteristics allow the data to be used to support and improve ongoing GHG inventories and climate research.</p><p><strong>Citation:</strong><span> Fuchs, R., Herold, M., Verburg, P. H., and Clevers, J. G. P. W.: A high-resolution and harmonized model approach for reconstructing and analysing historic land changes in Europe, Biogeosciences, 10, 1543-1559, doi:10.5194/bg-10-1543-2013, 2013.</span></p>

scholarly journals A high-resolution and harmonized model approach for reconstructing and analysing historic land changes in Europe

2013 ◽  
Vol 10 (3) ◽  
pp. 1543-1559 ◽  
Author(s):  
R. Fuchs ◽  
M. Herold ◽  
P. H. Verburg ◽  
J. G. P. W. Clevers
Keyword(s):  
High Resolution ◽  
Land Cover ◽  
Atmospheric Carbon Dioxide ◽  
Land Use Changes ◽  
Aerial Photographs ◽  
Land Change ◽  
Modelling Techniques ◽  
Reforestation Program ◽  
Economic Transitions ◽  
Second World

Abstract. Human-induced land use changes are nowadays the second largest contributor to atmospheric carbon dioxide after fossil fuel combustion. Existing historic land change reconstructions on the European scale do not sufficiently meet the requirements of greenhouse gas (GHG) and climate assessments, due to insufficient spatial and thematic detail and the consideration of various land change types. This paper investigates if the combination of different data sources, more detailed modelling techniques, and the integration of land conversion types allow us to create accurate, high-resolution historic land change data for Europe suited for the needs of GHG and climate assessments. We validated our reconstruction with historic aerial photographs from 1950 and 1990 for 73 sample sites across Europe and compared it with other land reconstructions like Klein Goldewijk et al. (2010, 2011), Ramankutty and Foley (1999), Pongratz et al. (2008) and Hurtt et al. (2006). The results indicate that almost 700 000 km2 (15.5%) of land cover in Europe has changed over the period 1950–2010, an area similar to France. In Southern Europe the relative amount was almost 3.5% higher than average (19%). Based on the results the specific types of conversion, hot-spots of change and their relation to political decisions and socio-economic transitions were studied. The analysis indicates that the main drivers of land change over the studied period were urbanization, the reforestation program resulting from the timber shortage after the Second World War, the fall of the Iron Curtain, the Common Agricultural Policy and accompanying afforestation actions of the EU. Compared to existing land cover reconstructions, the new method considers the harmonization of different datasets by achieving a high spatial resolution and regional detail with a full coverage of different land categories. These characteristics allow the data to be used to support and improve ongoing GHG inventories and climate research.

scholarly journals A high-resolution and harmonized model approach for reconstructing and analyzing historic land changes in Europe

2012 ◽  
Vol 9 (10) ◽  
pp. 14823-14866 ◽  
Author(s):  
R. Fuchs ◽  
M. Herold ◽  
P. H. Verburg ◽  
J. G. P. W. Clevers
Keyword(s):  
High Resolution ◽  
Land Cover ◽  
Second World War ◽  
Aerial Photographs ◽  
Land Change ◽  
Reforestation Program ◽  
Economic Transitions ◽  
Second World ◽  
Global Carbon ◽  
Land Changes

Abstract. Currently, up to 30% of global carbon emission is estimated to originate from land use and land changes. Existing historic land change reconstructions on the European scale do not sufficiently meet the requirements of greenhouse gas (GHG) and climate assessments, due to insufficient spatial and thematic detail and the consideration of various land change types. This paper investigates if the combination of different data sources, more detailed modeling techniques and the integration of land conversion types allow us to create accurate, high resolution historic land change data for Europe suited for the needs of GHG and climate assessments. We validated our reconstruction with historic aerial photographs from 1950 and 1990 for 73 sample sites across Europe and compared it with other land reconstructions like Klein Goldewijk et al. (2010, 2011), Ramankutty and Foley (1999), Pongratz et al. (2008) and Hurtt et al. (2006). The results indicate that almost 700 000 km2 (15.5%) of land cover in Europe changes over the period 1950 to 2010, an area similar to France. In Southern Europe the relative amount was almost 3.5% higher than average (19%). Based on the results the specific types of conversion, hot-spots of change and their relation to political decisions and socio-economic transitions were studied. The analysis indicate that the main drivers of land change over the studied period were urbanization, the reforestation program after the timber shortage since the Second World War, the fall of the Iron Curtain, Common Agricultural Policy and accompanying afforestation actions of the EU. Compared to existing land cover reconstructions, the new method takes stock of the harmonization of different datasets by achieving a high spatial resolution and regional detail with a full coverage of different land categories. These characteristic allow the data to be used to support and improve ongoing GHG inventories and climate research.

Prediksi Perubahan Lahan Terbangun Dengan OBIA LCM Pada Citra Terfusi di Kota Kendari

2021 ◽  
Vol 5 (2) ◽  
pp. 170
Author(s):  
Adnan Adnan ◽  
Fitra Saleh ◽  
Iradat Salihin
Keyword(s):  
Land Use ◽  
Landsat Imagery ◽  
Land Use Changes ◽  
Landsat 8 ◽  
Land Change ◽  
Land Use Classification ◽  
Landsat 8 Oli ◽  
Land Change Modeler ◽  
Two Factors ◽  
Land Changes

Abstrak: Penggunaan lahan disetiap tahunnya akan mengalami perubahan. Perkembangan tersebut bisa jadi tidak terkendali, sehingga perencanaan prediksi perubahan lahan penting untuk dikaji. Dalam memprediksi dapat dilakukan dengan menggunakan citra, khususnya citra Landsat. Penelitian ini bertujuan untuk: (1) distribusi penggunaan lahan terbangun di Kota Kendari pada tahun 2014 dan 2019 dengan metode OBIA pada citra terfusi; (2) melihat arah perubahan penggunaan lahan terbangun di Kota Kendari pada tahun 2024 dan 2029 dengan metode Land Change Modeler (LCM). Metode yang digunakan dalam penelitian ini  yaitu metode klasifikasi penggunaan lahan berbasis piksel OBIA dan pemodelan prediksi perubahan penggunaan lahan Land Change Modeler (LCM). Hasil penelitian ini antara lain: (1) luas lahan terbangun pada tahun 2014 di Kota Kendari seluas 6.061,85 hektar dan luas penggunaan lahan terbangun di Kota Kendari pada tahun 2019 seluas 6.716,96 hektar dengan perubahan penggunaan lahan terbangun tahun 2014 sampai dengan tahun 2019 dengan pertambahan luas 2,43%; (2) Arah perubahan penggunaan lahan terbangun di Kota Kendari diprediksikan cenderung berkembang ke arah Kecamatan Baruga karena dipengaruhi oleh dua faktor yaitu kemiringan lereng dan jaringan jalan. Kata Kunci : Penggunaan Lahan, Landsat 8 OLI, Penajaman Citra, OBIA, LCM Abstract: Land use will change every year. The development may be uncontrollable, so predictive planning of land changes is important to review. In predicting  can be done using  imagery, especially Landsat imagery. This study aims to:(1)  the distribution of land  use  built  in Kendari City in 2014 and 2019 with OBIA method on diffusion imagery; (2) see the direction of land use changes built in Kendari City in  2024 and 2029 with land change modeler  (LCM) method. The methods used in this study are OBIA pixel-based land  use  classification method and land use change prediction modeling land change modeler (LCM).  The results of this study include: (1) land area  built in 2014 in Kendari City aswide as 6,061.85 hectars and land use area built in Kendari City in 2019 aswide as 6,716.96 hectars with land use changes built in 2014 to 2019 with an increase  of  2.43%; (2) The direction of land use changes built in Kendari City  is predicted   to tend to  develop  towards  Baruga Subdistrict because it is influenced by two factors, namely slope and road network. Keywords: Land Use,  Landsat 8 OLI,  Image Sharpening,  OBIA, LCM

scholarly journals Land Cover Changes in Open-Cast Mining Complexes Based on High-Resolution Remote Sensing Data

2019 ◽  
Author(s):  
Filipe Silveira Nascimento ◽  
Markus Gastauer ◽  
Pedro Walfir M. Souza-Filho ◽  
Wilson R. Nascimento Jr. ◽  
Diogo C. Santos ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Land Cover ◽  
Land Use Changes ◽  
Remote Sensing Data ◽  
Land Cover Changes ◽  
Special Focus ◽  
Open Cast Mining ◽  
High Resolution Satellite Images ◽  
Open Cast

Remote sensing technologies may play a fundamental role in the environmental assessment of open-cast mining and the accurate quantification of mine land rehabilitation efforts. Here, we developed a systematic geographic object-based image analysis (GEOBIA) approach to map the amount of revegetated area and to quantify the land-use changes in open-cast mines in the Caraj&aacute;s region situated in the eastern Amazon. Based on high-resolution satellite images from 2011 to 2015 from different sensors (GeoEye, WorldView-3 and Ikonos), we quantified forests, cangas (natural metalliferous savanna ecosystems), mine land, revegetated areas and water bodies. Based on the GEOBIA approach, threshold values were established to discriminate land cover classes using spectral bands, and the NDVI and NDWI indices and LiDAR digital ground and slope models. The overall accuracy was higher than 90%, and the Kappa indices varied between 0.82 and 0.88. During the observation period, the mining complex expanded; for that, canga and forest vegetation was converted to mine land. At the same time, the amount of revegetated area increased. Thus, we conclude that our approach is capable of providing consistent information regarding land cover changes in mines, with a special focus on the amount of revegetation necessary to fulfill environmental liabilities.

scholarly journals The Use of Small Format Air Photos for Mapping Land Cover Changes in Gumuk Pasir Parangtritis Core-Zone, 2015-2019

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Maulidini Fatimah Azahra ◽  
J Jumadi ◽  
Agus Anggoro Sigit
Keyword(s):  
Land Cover ◽  
Sand Dune ◽  
Land Use Changes ◽  
Mapping Method ◽  
Aerial Photographs ◽  
Land Cover Changes ◽  
Core Zone ◽  
The Core ◽  
Object Based ◽  
Tourism Economy

Gumuk Pasir Parangtritis is one of the potentials of the coastal area of ​​Parangtritis village in Yogyakarta, with several important roles for the coastal ecosystem and its surroundings, such as ecology, disaster, tourism, economy, and aquifer reserves. However, behind this important role, the existence of sandbanks is increasingly threatened from year to year because the area of ​​sand cover continues to decline, especially in the core zone. Therefore, regular and effective mapping and monitoring efforts are needed. This study aims to a) conduct land cover mapping using the Geographic Object Based Image Analysis (GEOBIA) method in the 2015-2019 timeframe; b) analyze changes in land cover in the core zone of sandbanks during 2015-2019; and c) evaluate the results of restoration of sand dune core zone in terms of land cover changes that have occurred until 2019. Small format aerial photographs (FUFK) are the data used in this study while the mapping method used is rule-based classification. The land cover of the sand dune core zone in 2015 included buildings, vegetation, sand, roads and ponds, while in 2019 it was in the form of buildings, vegetation, sand, and roads. Based on the classification results in the two years, it can be seen that there are changes in land cover (including area) through the cross-section of the two classification results. Some of the factors include the number of land use changes, the amount of vegetation, and sand mining. Furthermore, this change can be used as a basis for evaluating the success of the restoration efforts of the Gumuk Pasir Parangtritis core zone to date. The results of the evaluation show that the restoration carried out so far has not had much impact so it can be said that it has not been successful, because the area of ​​sand cover has actually decreased a lot (from 528,680 m2 to 344,347 m2), while the land cover in the form of vegetation and buildings has increased in size (from 869,341 m2 to 1,037,879 m2 for vegetation cover and an area of ​​4,674 m2 to 22,953 m2 for buildings).

scholarly journals Development of segmentation algorithm based region growing for software GIS GRASS

2010 ◽  
Vol 58 (1) ◽  
pp. 207-216
Author(s):  
Aleš Tippner
Keyword(s):  
Image Segmentation ◽  
High Resolution ◽  
Land Cover ◽  
Mathematical Morphology ◽  
Satellite Images ◽  
Satellite Image ◽  
Region Growing ◽  
Segmentation Algorithm ◽  
Aerial Photographs ◽  
High Resolution Satellite Image

Image segmentation is fundamental prerequisite for new satellite images interpretation methods. GIS GRASS provides segmentation tools enabling global image segmentation only. We designed procedure enabling local segmentation using existing GRASS tools and segmentation algorithm based on region growing that we developed with C++. This algorithm applies mathematical morphology operators to output segments, too. Principial aim of the project is creation of useful input for differentiation of base land cover classes in panchromatic high-resolution satellite image (or historical aerial photographs for example).

scholarly journals Land Cover Changes in Open-Cast Mining Complexes Based on High-Resolution Remote Sensing Data

2020 ◽  
Vol 12 (4) ◽  
pp. 611 ◽  
Author(s):  
Filipe Silveira Nascimento ◽  
Markus Gastauer ◽  
Pedro Walfir M. Souza-Filho ◽  
Wilson R. Nascimento ◽  
Diogo C. Santos ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Land Cover ◽  
Vegetation Index ◽  
Land Use Changes ◽  
Land Cover Changes ◽  
Special Focus ◽  
Open Cast Mining ◽  
High Resolution Satellite Images ◽  
Open Cast

Remote sensing technologies can play a fundamental role in the environmental assessment of open-cast mining and the accurate quantification of mine land rehabilitation efforts. Here, we developed a systematic geographic object-based image analysis (GEOBIA) approach to map the amount of revegetated area and quantify the land use changes in open-cast mines in the Carajás region in the eastern Amazon, Brazil. Based on high-resolution satellite images from 2011 to 2015 from different sensors (GeoEye, WorldView-3 and IKONOS), we quantified forests, cangas (natural metalliferous savanna ecosystems), mine land, revegetated areas and water bodies. Based on the GEOBIA approach, threshold values were established to discriminate land cover classes using spectral bands, the normalized difference vegetation index (NDVI), normalized difference water index (NDWI) and a light detection and range sensor (LiDAR) digital terrain model and slope map. The overall accuracy was higher than 90%, and the kappa indices varied between 0.82 and 0.88. During the observation period, the mining complex expanded, which led to the conversion of canga and forest vegetation to mine land. At the same time, the amount of revegetated area increased. Thus, we conclude that our approach is capable of providing consistent information regarding land cover changes in mines, with a special focus on the amount of revegetation necessary to fulfill environmental liabilities.

scholarly journals QUARTERLY MONITORING OF SUSPECTED ILLEGAL HUMAN ACTIVITIES IN NATIONAL NATURE RESERVES OF CHINA WITH SENTINEL-2 AND HIGH-RESOLUTION IMAGES ON THE CLOUD PLATFORM

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 1657-1662
Author(s):  
H. Wang ◽  
X. Ning ◽  
Q. Dong ◽  
Y. Liu ◽  
M. Hao ◽  
...  
Keyword(s):  
High Resolution ◽  
Land Cover ◽  
Human Activities ◽  
Google Earth ◽  
Nature Reserves ◽  
Land Change ◽  
High Resolution Images ◽  
National Nature Reserves ◽  
Sentinel 2 ◽  
Time Point

Abstract. Nature reserves play an important role in protecting biodiversity, preserving natural heritage, and maintaining national ecological security. Satellite remote sensing technology has become an essential way to capture the impact of human activities on nature reserves by monitoring the land cover change. However, current monitoring frequency and scale were inadequate to detect the land change related to illegal human activities rapidly and accurately. To solve the above problems, this study proposed an operational suspected illegal change detection method which combined the temporal advantage of Sentinel-2 double satellites with the spatial advantage of high-resolution images from SiweiEarth and Google Earth cloud platforms, together with high-precision high-resolution images from cloud platforms, historical land cover data from Geoinformation Survey Data of China, and the thematic information of study area. Eight typical national nature reserves were selected as study areas. January 1st, 2019 was taken as the time point of the base period. May 31st, August 31st, and November 30th were taken as the time point of the first period, the second period, and the third period respectively. Results showed that four national nature reserves had nine suspected illegal land change parcels, with a good ecological protection situation of the other four nature reserves. Deforestation and illegal construction were the two main suspected illegal types. In the next step, the study results will be provided to the Law Enforcement Administration of China to evaluate the applicability and generalization of this method, and a more rapid and intelligent method needs to be improved.

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