scholarly journals Predicting Land Cover Change in the Mamminasata Area, Indonesia, to Evaluate the Spatial Plan

2020 ◽  
Vol 9 (8) ◽  
pp. 481
Author(s):  
Andi Muhammad Yasser Hakim ◽  
Masayuki Matsuoka ◽  
Sumbangan Baja ◽  
Dorothea Agnes Rampisela ◽  
Samsu Arif
Keyword(s):  
Land Cover ◽  
Grid Cell ◽  
Support Vector ◽  
Land Cover Changes ◽  
Statistical Validation ◽  
Development Zone ◽  
Composite Support ◽  
The Government ◽  
Overlapping Method ◽  
Spatial Plan

The spatial plan program for Makassar City and the surrounding area called Mamminasata (Makassar, Maros, Sungguminasa, and Takalar) was created by the Indonesian Government. The program regulates the proportion of land cover, but predictions about land cover changes were not considered. Therefore, in this study, we predict what the land cover may be in 2031 using the multi-layer perceptron neural network and the Markov chain methods. For this purpose, image composite, support vector machine classifier, and change detection were applied to a time series of satellite data. Visual validation showed the hot-spots of land cover changes related to population density, and statistical validation scored 0.99 and 0.78 in no information kappa and grid-cell level location kappa, respectively. The model was performed to predict land cover in 2031, and the predicted result was then compared with the spatial plan using an overlapping method. The results showed that built-up area, dryland agriculture, and wetland agriculture occupied two, twenty, and eight percent of the protected zone, respectively. Meanwhile, fifteen percent of the development zone was covered by forest, mainly in the eastern part of Mamminasata. The result can be used to help the Government decide future plans for the Mamminasata area.

scholarly journals Applying a support vector model to assess land cover changes in the Uvs Lake Basin ecoregion in Mongolia

2019 ◽  
Vol 6 (1) ◽  
pp. 158-169 ◽  
Author(s):  
Buyan-Erdene Jamsran ◽  
Chinsu Lin ◽  
Ishgaldan Byambakhuu ◽  
Jamsran Raash ◽  
Khaulenbek Akhmadi
Keyword(s):  
Land Cover ◽  
Vector Model ◽  
Support Vector ◽  
Land Cover Changes ◽  
Lake Basin

scholarly journals Spatial near future modeling of land use and land cover changes in the temperate forests of Mexico

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6617 ◽  
Author(s):  
Jesús A. Prieto-Amparán ◽  
Federico Villarreal-Guerrero ◽  
Martin Martínez-Salvador ◽  
Carlos Manjarrez-Domínguez ◽  
Griselda Vázquez-Quintero ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Temperate Forests ◽  
Secondary Forest ◽  
Primary Forest ◽  
Support Vector ◽  
Land Cover Changes ◽  
Land Use Land Cover ◽  
Kappa Index

The loss of temperate forests of Mexico has continued in recent decades despite wide recognition of their importance to maintaining biodiversity. This study analyzes land use/land cover change scenarios, using satellite images from the Landsat sensor. Images corresponded to the years 1990, 2005 and 2017. The scenarios were applied for the temperate forests with the aim of getting a better understanding of the patterns in land use/land cover changes. The Support Vector Machine (SVM) multispectral classification technique served to determine the land use/land cover types, which were validated through the Kappa Index. For the simulation of land use/land cover dynamics, a model developed in Dinamica-EGO was used, which uses stochastic models of Markov Chains, Cellular Automata and Weight of Evidences. For the study, a stationary, an optimistic and a pessimistic scenario were proposed. The projections based on the three scenarios were simulated for the year 2050. Five types of land use/land cover were identified and evaluated. They were primary forest, secondary forest, human settlements, areas without vegetation and water bodies. Results from the land use/land cover change analysis show a substantial gain for the secondary forest. The surface area of the primary forest was reduced from 55.8% in 1990 to 37.7% in 2017. Moreover, the three projected scenarios estimate further losses of the surface are for the primary forest, especially under the stationary and pessimistic scenarios. This highlights the importance and probably urgent implementation of conservation and protection measures to preserve these ecosystems and their services. Based on the accuracy obtained and on the models generated, results from these methodologies can serve as a decision tool to contribute to the sustainable management of the natural resources of a region.

scholarly journals The fate of land evaporation – A global dataset

2020 ◽  
Author(s):  
Andreas Link ◽  
Ruud van der Ent ◽  
Markus Berger ◽  
Stephanie Eisner ◽  
Matthias Finkbeiner
Keyword(s):  
Land Cover ◽  
Hydrological Cycle ◽  
Grid Cell ◽  
Reanalysis Data ◽  
Land Cover Changes ◽  
Atmospheric Moisture ◽  
Grid Cells ◽  
Time Period ◽  
Tracking Model ◽  
Areas Of Interest

Abstract. Various studies investigated the fate of evaporation and the origin of precipitation. The more recent studies among them were often carried out with the help of numerical moisture tracking. Many research questions could be answered within this context such as dependencies of atmospheric moisture transfers between different regions, impacts of land cover changes on the hydrological cycle, sustainability related questions as well as questions regarding the seasonal and inter-annual variability of precipitation. In order to facilitate future applications, global datasets on the fate of evaporation and the sources of precipitation are needed. Since most studies are on a regional level and focus more on the sources of precipitation, the goal of this study is to provide a readily available global dataset on the fate of evaporation for a fine-meshed grid of source and receptor cells. The dataset was created through a global run of the numerical moisture tracking model WAM-2layers and focused on the fate of land evaporation. The tracking was conducted on a 1.5° × 1.5° grid and was based on reanalysis data from the ERA-Interim database. Climatic input data were incorporated in 3- respectively 6-hourly time steps and represent the time period from 2001 to 2018. Atmospheric moisture was tracked forward in time and the geographical borders of the model were located at +/- 79.5° latitude. As a result of the model run, the annual and monthly average as well as the inter-annual average fate of evaporation was determined for 8684 land grid cells (all land cells except those located within Greenland and Antarctica) and provided via source-receptor matrices. The gained dataset was complemented via an aggregation to country and basin scales in order to highlight possible usages for areas of interest larger than grid cells. This resulted in data for 265 countries and 8223 basins. Finally, five types of source-receptor matrices for average moisture transfers were chosen to build the core of the dataset: land grid cell to grid cell, country to grid cell, basin to grid cell, country to country, basin to basin. The dataset is, to our knowledge, the first ready-to-download dataset providing the overall fate of evaporation for land cells of a global fine-meshed grid in monthly resolution. At the same time, information on the sources of precipitation can be extracted from it. It could be used for investigations into average annual, seasonal and inter-annual sink and source regions of atmospheric moisture from land masses for most of the regions in the world and shows various application possibilities for studying interactions between people and water such as land cover changes or human water consumption patterns. The dataset is accessible under https://doi.pangaea.de/10.1594/PANGAEA.908705 (Link et al., 2019a) and comes along with example scripts for reading and plotting.

scholarly journals Dinamika dan Proyeksi Perubahan Tutupan Lahan serta Inkonsistensi Tata Ruang di Wilayah Pegunungan Kendeng

2020 ◽  
Vol 4 (2) ◽  
pp. 99-112
Author(s):  
Andrea Emma Pravitasari ◽  
Ernan Rustiadi ◽  
Soeryo Adiwibowo ◽  
Imelda Kusuma Wardani ◽  
Iwan Kurniawan ◽  
...  
Keyword(s):  
Land Cover ◽  
Mining Area ◽  
Karst Area ◽  
Land Cover Changes ◽  
Markov Analysis ◽  
Central Java ◽  
Inconsistency Analysis ◽  
Land Cover Maps ◽  
Central Java Province ◽  
Spatial Plan

Dynamics and Projections of Land Cover Changes and Spatial Plan Inconsistenciesin Kendeng Mountains Region Kendeng is limestone mountains that stretch across the northern part of Java Island. It is located in 7 regencies in 2 provinces (Pati, Grobogan, Blora, and Rembang Regenciy in Central Java Province; and Lamongan, Bojonegoro, and Tuban Regency in East Java Province). Kendeng Mountains is rich in natural resources and biodiversity. However, the development of mining activities and other cultivation activities has led to a dynamic land cover changes and threatens to damage the karst area of Kendeng Mountains. This research aims to: (1) identify the dynamics of land cover changes (LCC) in Kendeng Mountains (1996–2016); (2) conduct projections of the LCC in 2036; and (3) analyze spatial plan inconsistencies in the region. LCC analysis was conducted with ArcGIS 10.3 software using land cover maps of 1996, 2000, 2006, 2011, and 2016 from the Ministry of Environment and Forestry. Projections of LCC in 2036 was analyzed by CA-Markov using Idrisi Selva software. Spatial plan inconsistency analysis was carried out by overlaying land cover maps with Spatial Plan (RTRW) maps. Based on CA-Markov analysis, the mining area increased from 12 ha (1996) to 1,660 ha (2016), as well as built-up area from 83,543 ha (1996) to 96,761 ha (2016). The projection of land cover change predicts that mining area and built-up area in 2036 will increase to 3,646 ha and 110,843 ha. Existing area (in 2016) which is inconsistent with the Spatial Plan is 12.3%. Based on predicted LCC in 2036, it seems that the chances of spatial plan inconsistencies in this region will increase more in the future.

scholarly journals Land Cover Change and Deforestation Characteristics in The Management Section of National Park (MNSP) VI Besitang, Gunung Leuser National Park

2019 ◽  
Vol 2 (2) ◽  
pp. 91-100 ◽  
Author(s):  
Nurdin Sulistyono ◽  
Bastian Samuel P. Ginting ◽  
Pindi Patana ◽  
Arida Susilowati
Keyword(s):  
Land Cover ◽  
National Park ◽  
Close Correlation ◽  
Land Cover Changes ◽  
Dryland Agriculture ◽  
Maximum Likelihood Classification ◽  
The World ◽  
Open Land ◽  
The Government ◽  
Slope Class

Gunung Leuser National Park is one of the world heritage forest located in Indonesia where the Government of Indonesia and the International world give serious attention to the condition of the area. Unfortunately the forest area of Leuser Mountain National Park significantly decreasing by years due to deforestation.. This study aims to determine land cover changes, the rate of deforestation and spatial characteristics of deforestation in the National Park Management Section Region VI Besitang Gunung Leuser National Park. Classification method was maximum likelihood classification (MLC). The results of this study indicated land cover changes from 2008 to 2016 at SPTN Region VI Besitang TNGL that forest has increased from 104.741,15 ha to 107.336,03 ha, mixed dryland agriculture has decreased from 3.690,40 ha to 2.498,53 ha, Palm oil decreased from 526,96 ha to 88,40 ha, and open land increased from 3.116,80 ha to 3.572,93 ha. The rate of deforestation in this area during that period is 221,14 ha/year or 1.769,12 ha. Factors that have a close correlation with the area of deforestation are the number of population and the number of families farmer; distance from road, river, settlement and plantation; height class, and slope class.

scholarly journals The fate of land evaporation - A global dataset

2020 ◽  
Author(s):  
Andreas Link ◽  
Ruud van der Ent ◽  
Markus Berger ◽  
Stephanie Eisner ◽  
Matthias Finkbeiner
Keyword(s):  
Land Cover ◽  
Hydrological Cycle ◽  
Grid Cell ◽  
Reanalysis Data ◽  
Land Cover Changes ◽  
Atmospheric Moisture ◽  
Grid Cells ◽  
Time Period ◽  
Tracking Model ◽  
Areas Of Interest

<p><span>Various studies investigated the fate of evaporation and the origin of precipitation. The more recent studies among them were often carried out with the help of numerical moisture tracking. Many research questions could be answered within this context such as dependencies of atmospheric moisture transfers between different regions, impacts of land cover changes on the hydrological cycle, sustainability related questions as well as questions regarding the seasonal and inter-annual variability of precipitation. In order to facilitate future applications, global datasets on the fate of evaporation and the sources of precipitation are needed. Since most studies are on a regional level and focus more on the sources of precipitation, the goal of this study is to provide a readily available global dataset on the fate of evaporation for a fine-meshed grid of source and receptor cells. The dataset was created through a global run of the numerical moisture tracking model WAM-2layers and focused on the fate of land evaporation. The tracking was conducted on a 1.5° × 1.5° grid and was based on reanalysis data from the ERA-Interim database. Climatic input data were incorporated in 3- respectively 6-hourly time steps and represent the time period from 2001 to 2018. Atmospheric moisture was tracked forward in time and the geographical borders of the model were located at +/- 79.5° latitude. As a result of the model run, the annual and monthly average as well as the inter-annual average fate of evaporation was determined for 8684 land grid cells (all land cells except those located within Greenland and Antarctica) and provided via source-receptor matrices. The gained dataset was complemented via an aggregation to country and basin scales in order to highlight possible usages for areas of interest larger than grid cells. This resulted in data for 265 countries and 8223 basins. Finally, five types of source-receptor matrices for average moisture transfers were chosen to build the core of the dataset: land grid cell to grid cell, country to grid cell, basin to grid cell, country to country, basin to basin. The dataset is, to our knowledge, the first ready-to-download dataset providing the overall fate of evaporation for land cells of a global fine-meshed grid in monthly resolution. At the same time, information on the sources of precipitation can be extracted from it. It could be used for investigations into average annual, seasonal and inter-annual sink and source regions of atmospheric moisture from land masses for most of the regions in the world and shows various application possibilities for studying interactions between people and water such as land cover changes or human water consumption patterns. The dataset is accessible under <a href="https://doi.pangaea.de/10.1594/PANGAEA.908705%20">https://doi.pangaea.de/10.1594/PANGAEA.908705</a></span><span>  and comes along with example scripts for reading and plotting.   </span></p>

scholarly journals Spatial near future modeling of land use and land cover changes in the temperate forests of Mexico

2019 ◽  
Author(s):  
Jesús A Prieto-Amparán ◽  
Federico Villarreal-Guerrero ◽  
Martin Martínez-Salvador ◽  
Carlos Manjarrez-Domínguez ◽  
Griselda Vázquez-Quintero ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Temperate Forests ◽  
Secondary Forest ◽  
Primary Forest ◽  
Support Vector ◽  
Land Cover Changes ◽  
Land Use Land Cover ◽  
Kappa Index

The loss of temperate forests of Mexico has continued in recent decades despite wide recognition of their importance to maintaining biodiversity. This study analyzes land use/land cover change scenarios, using satellite images from the Landsat sensor. Images corresponded to the years 1990, 2005 and 2017. The scenarios were applied for the temperate forests with the aim of getting a better understanding of the patterns in land use/land cover changes. The Support Vector Machine (SVM) multispectral classification technique served to determine the land use/land cover types, which were validated through the Kappa Index. For the simulation of land use/land cover dynamics, a model developed in Dinamica-EGO was used, which uses stochastic models of Markov Chains, Cellular Automata and Weight of Evidences. For the study, a stationary, an optimistic and a pessimistic scenario were proposed. The projections based on the three scenarios were simulated for the year 2050. Five types of land use/land cover were identified and evaluated. They were primary forest, secondary forest, human settlements, areas without vegetation and water bodies. Results from the land use/land cover change analysis show a substantial gain for the secondary forest. The surface area of the primary forest was reduced from 55.8% in 1990 to 37.7% in 2017. Moreover, the three projected scenarios estimate further losses of the surface are for the primary forest, especially under the stationary and pessimistic scenarios. This highlights the importance and probably urgent implementation of conservation and protection measures to preserve these ecosystems and their services. Based on the accuracy obtained and, on the models generated, results from these methodologies can serve as a decision tool to contribute to the sustainable management of the natural resources of a region.

scholarly journals Spatial near future modeling of land use and land cover changes in the temperate forests of Mexico

2019 ◽  
Author(s):  
Jesús A Prieto-Amparán ◽  
Federico Villarreal-Guerrero ◽  
Martin Martínez-Salvador ◽  
Carlos Manjarrez-Domínguez ◽  
Griselda Vázquez-Quintero ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Temperate Forests ◽  
Secondary Forest ◽  
Primary Forest ◽  
Support Vector ◽  
Land Cover Changes ◽  
Land Use Land Cover ◽  
Kappa Index

The loss of temperate forests of Mexico has continued in recent decades despite wide recognition of their importance to maintaining biodiversity. This study analyzes land use/land cover change scenarios, using satellite images from the Landsat sensor. Images corresponded to the years 1990, 2005 and 2017. The scenarios were applied for the temperate forests with the aim of getting a better understanding of the patterns in land use/land cover changes. The Support Vector Machine (SVM) multispectral classification technique served to determine the land use/land cover types, which were validated through the Kappa Index. For the simulation of land use/land cover dynamics, a model developed in Dinamica-EGO was used, which uses stochastic models of Markov Chains, Cellular Automata and Weight of Evidences. For the study, a stationary, an optimistic and a pessimistic scenario were proposed. The projections based on the three scenarios were simulated for the year 2050. Five types of land use/land cover were identified and evaluated. They were primary forest, secondary forest, human settlements, areas without vegetation and water bodies. Results from the land use/land cover change analysis show a substantial gain for the secondary forest. The surface area of the primary forest was reduced from 55.8% in 1990 to 37.7% in 2017. Moreover, the three projected scenarios estimate further losses of the surface are for the primary forest, especially under the stationary and pessimistic scenarios. This highlights the importance and probably urgent implementation of conservation and protection measures to preserve these ecosystems and their services. Based on the accuracy obtained and, on the models generated, results from these methodologies can serve as a decision tool to contribute to the sustainable management of the natural resources of a region.

scholarly journals The fate of land evaporation – a global dataset

2020 ◽  
Vol 12 (3) ◽  
pp. 1897-1912
Author(s):  
Andreas Link ◽  
Ruud van der Ent ◽  
Markus Berger ◽  
Stephanie Eisner ◽  
Matthias Finkbeiner
Keyword(s):  
Land Cover ◽  
Hydrological Cycle ◽  
Grid Cell ◽  
Reanalysis Data ◽  
Land Cover Changes ◽  
Atmospheric Moisture ◽  
Grid Cells ◽  
Accounting Model ◽  
Tracking Model ◽  
Areas Of Interest

Abstract. Various studies investigated the fate of evaporation and the origin of precipitation. The more recent studies among them were often carried out with the help of numerical moisture tracking. Many research questions could be answered within this context, such as dependencies of atmospheric moisture transfers between different regions, impacts of land cover changes on the hydrological cycle, sustainability-related questions, and questions regarding the seasonal and interannual variability of precipitation. In order to facilitate future applications, global datasets on the fate of evaporation and the sources of precipitation are needed. Since most studies are on a regional level and focus more on the sources of precipitation, the goal of this study is to provide a readily available global dataset on the fate of evaporation for a fine-meshed grid of source and receptor cells. The dataset was created through a global run of the numerical moisture tracking model Water Accounting Model-2layers (WAM-2layers) and focused on the fate of land evaporation. The tracking was conducted on a 1.5∘×1.5∘ grid and was based on reanalysis data from the ERA-Interim database. Climatic input data were incorporated in 3- to 6-hourly time steps and represent the time period from 2001 to 2018. Atmospheric moisture was tracked forward in time and the geographical borders of the model were located at ±79.5∘ latitude. As a result of the model run, the annual, the monthly and the interannual average fate of evaporation were determined for 8684 land grid cells (all land cells except those located within Greenland and Antarctica) and provided via source–receptor matrices. The gained dataset was complemented via an aggregation to country and basin scales in order to highlight possible usages for areas of interest larger than grid cells. This resulted in data for 265 countries and 8223 basins. Finally, five types of source–receptor matrices for average moisture transfers were chosen to build the core of the dataset: land grid cell to grid cell, country to grid cell, basin to grid cell, country to country, basin to basin. The dataset is, to our knowledge, the first ready-to-download dataset providing the overall fate of evaporation for land cells of a global fine-meshed grid in monthly resolution. At the same time, information on the sources of precipitation can be extracted from it. It could be used for investigations into average annual, seasonal, and interannual sink and source regions of atmospheric moisture from land masses for most of the regions in the world and shows various application possibilities for studying interactions between people and water, such as land cover changes or human water consumption patterns. The dataset is accessible under https://doi.org/10.1594/PANGAEA.908705 (Link et al., 2019a) and comes along with example scripts for reading and plotting the data.

Sign in / Sign up

Export Citation Format

Share Document