Simulated event‐scale flow and sediment generation responses to agricultural land cover change in lowland UK catchments

he availability of land for fulfillment of space in the Sarbagita coastal area is increasingly limited. This iscaused by the rapid development of tourism in the Sarbagita coastal region, which can eliminate a large portion ofproductive agricultural land. This study specifically examines the probability value of land cover change, especially fromnon-built up area to built up area, in the Sarbagita coastal area until 2030. Calculation of the probability of land coverchange is done through fuzzy set logic which is assessed based on 1 main parameter, namely tourist location and 2supporting parameters, namely accessibility and service facilities, and also limiting factors. The value of the fuzzymembership is taken from Landsat images from 1995 to 2015. The results show the probability of changes in land coverhas values from 0 (very low) to 0.97 (very high). This means that there is no one land that must change (value 1) fromnon-built land to being built. The probability of a high land cover change tends to follow the road network pattern.

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Land-Use/Land-Cover Change and Anthropogenic Causes Around Koupa Matapit Gallery Forest, West-Cameroon

Journal of Geography and Geology ◽

10.5539/jgg.v10n2p56 ◽

2018 ◽

Vol 10 (2) ◽

pp. 56 ◽

Cited By ~ 2

Author(s):

Marie Caroline Solefack Momo ◽

Andre Ledoux Njouonkou ◽

Lucie Felicite Temgoua ◽

Romuald Djouda Zangmene ◽

Junior Baudoin Wouokoue Taffo ◽

...

Keyword(s):

Land Use ◽

Land Cover ◽

Land Cover Change ◽

Satellite Images ◽

Agricultural Land ◽

Local Population ◽

Forest Products ◽

Anthropogenic Factors ◽

Significant Implication ◽

Gallery Forest

This study assesses land cover change of the Koupa Matapit forest gallery, West Cameroon, in relation to anthropogenic factors. Ethnobotanical surveys were conducted to investigate the relationships between the local population and the gallery forest; the spatio-temporal dynamics of the landscapes around the gallery forest were studied from the diachronic analysis of three Landsat TM satellite images of 1984, Landsat ETM + 1999 and Landsat OLI_TIRS of 2016, supplemented by verification missions on field. The satellite images were processed using ArcGIS and Erdas Imagine software. According to surveys, it should be noted that agriculture and livestock are the main economic activities of the population of Koupa Matapit, agriculture and fuel wood collection for energy were the main anthropogenic activities responsible for deforestation and degradation of the forest gallery. The collection of non-timber forest products (NTFPs) would have a significant implication in land use and cover changes. The results indicate that the extension of savannah/agricultural land (from 6989 ha in 1984 to 7604 ha in 2016) and bare soil/built up area (from 71 ha in 1984 to 342 ha in 2016) would have led to the disappearance of much of the forest area (1465 ha in 1984 to 580 ha in 2016). The rapid population growth of Koupa Matapit would be responsible for these pressures. There is an urgent need to implement appropriate land use policy in this area.

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Analysis Transfer of the Function Cover of Agricultural Land Become a Housing Area and Industry in the Semarang City with Approach of Remote Sensing and Geographic Information System

Journal of Applied Geospatial Information ◽

10.30871/jagi.v3i2.1264 ◽

2019 ◽

Vol 3 (2) ◽

pp. 204-210

Author(s):

Harnawan Nurul Asna ◽

Frederik Samuel Papilaya

Keyword(s):

Remote Sensing ◽

Information System ◽

Geographic Information System ◽

Land Cover ◽

Land Cover Change ◽

Agricultural Land ◽

Unsupervised Classification ◽

Geographic Information ◽

Classification Technique ◽

Housing Area

The purpose of this study was to find out how much area of agricultural land was converted because of the high property business activities in Semarang City, the data used for this study were taken from 1999 to 2018. The classification method used in this study was the remote sensing method using the unsupervised classification technique. Output of this study is the extensive data of agricultural land cover change obtained from 1999 to 2018. The results of this study can prove that the Geographic Information System can be used to find out how much agricultural land cover change in Semarang City from 1999 to 2018. The area of agricultural land that has been converted is from 1999 to 2009 around 3072 ha and from 2009 to 2018 around 1071.4 ha.

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Farmers’ Income and Land Cover Change at Lore Lindu National Park in Indonesia

Modern Applied Science ◽

10.5539/mas.v12n12p41 ◽

2018 ◽

Vol 12 (12) ◽

pp. 41

Author(s):

Rustam Abdul Rauf ◽

Adam Malik ◽

Isrun . ◽

Golar . ◽

Alimudin Laapo ◽

...

Keyword(s):

Land Cover ◽

Land Cover Change ◽

National Park ◽

Agricultural Land ◽

Secondary Forest ◽

Forest Area ◽

Farm Income ◽

Primary Forest ◽

Secondary Forests ◽

Lore Lindu National Park

Lore Lindu National Park in Central Sulawesi is one of the protected areas. Although it is protected, many of its areas are experiencing pressure and disruption by human activities. The purpose of this research was to know the relationship between farmers’ income and land cover change at Lore Lindu National Park. The research method was a participatory survey. Variables of incomes were sourced from farming and outside farming (forests). Data of land cover change were obtained using imagery in 2012, 2014 and 2016. The result of research is the average of farming income of IDR 1,387,077 (cocoa farming) and non-farm income of IDR 854,819 (forest honey, resin). In the last five years (2012-2016), the primary forest area decreased by 902.37 ha, while the secondary forest has shown an increase of 2,233.61 ha. The trend of land cover change was drastic, with change in the secondary dry land forest area from 6.9 ha (in 2012) to 2,240.5 ha (in 2016). The increased secondary forest area and the secondary forests have been converted into agricultural land and mixed gardens.

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Retrieval of Land-Use/Land Cover Change (LUCC) Maps and Urban Expansion Dynamics of Hyderabad, Pakistan via Landsat Datasets and Support Vector Machine Framework

Remote Sensing ◽

10.3390/rs13163337 ◽

2021 ◽

Vol 13 (16) ◽

pp. 3337

Author(s):

Shaker Ul Din ◽

Hugo Wai Leung Mak

Keyword(s):

Land Use ◽

Support Vector Machine ◽

Land Cover ◽

Land Cover Change ◽

Agricultural Land ◽

Urban Expansion ◽

Support Vector ◽

Land Use Land Cover ◽

Landsat Images ◽

Barren Land

Land-use/land cover change (LUCC) is an important problem in developing and under-developing countries with regard to global climatic changes and urban morphological distribution. Since the 1900s, urbanization has become an underlying cause of LUCC, and more than 55% of the world’s population resides in cities. The speedy growth, development and expansion of urban centers, rapid inhabitant’s growth, land insufficiency, the necessity for more manufacture, advancement of technologies remain among the several drivers of LUCC around the globe at present. In this study, the urban expansion or sprawl, together with spatial dynamics of Hyderabad, Pakistan over the last four decades were investigated and reviewed, based on remotely sensed Landsat images from 1979 to 2020. In particular, radiometric and atmospheric corrections were applied to these raw images, then the Gaussian-based Radial Basis Function (RBF) kernel was used for training, within the 10-fold support vector machine (SVM) supervised classification framework. After spatial LUCC maps were retrieved, different metrics like Producer’s Accuracy (PA), User’s Accuracy (UA) and KAPPA coefficient (KC) were adopted for spatial accuracy assessment to ensure the reliability of the proposed satellite-based retrieval mechanism. Landsat-derived results showed that there was an increase in the amount of built-up area and a decrease in vegetation and agricultural lands. Built-up area in 1979 only covered 30.69% of the total area, while it has increased and reached 65.04% after four decades. In contrast, continuous reduction of agricultural land, vegetation, waterbody, and barren land was observed. Overall, throughout the four-decade period, the portions of agricultural land, vegetation, waterbody, and barren land have decreased by 13.74%, 46.41%, 49.64% and 85.27%, respectively. These remotely observed changes highlight and symbolize the spatial characteristics of “rural to urban transition” and socioeconomic development within a modernized city, Hyderabad, which open new windows for detecting potential land-use changes and laying down feasible future urban development and planning strategies.

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Quantifying Land Cover Change Due to Petroleum Exploration and Production in the Haynesville Shale Region Using Remote Sensing

Natural Resources Management ◽

10.4018/978-1-5225-0803-8.ch038 ◽

2017 ◽

pp. 813-830

Author(s):

Daniel Unger ◽

I-Kuai Hung ◽

Kenneth Farrish ◽

Darinda Dans

Keyword(s):

Land Cover ◽

Land Cover Change ◽

Classification Accuracy ◽

Oil And Gas ◽

Agricultural Land ◽

Landscape Fragmentation ◽

Petroleum Exploration ◽

Landsat Thematic Mapper ◽

Exploration And Production ◽

The U.S

The Haynesville Shale lies under areas of Louisiana and Texas and is one of the largest gas plays in the U.S. Encompassing approximately 2.9 million ha, this area has been subject to intensive exploration for oil and gas, while over 90% of it has traditionally been used for forestry and agriculture. In order to detect the landscape change in the past few decades, Landsat Thematic Mapper (TM) imagery for six years (1984, 1989, 1994, 2000, 2006, and 2011) was acquired. Unsupervised classifications were performed to classify each image into four cover types: agriculture, forest, well pad, and other. Change detection was then conducted between two classified maps of different years for a time series analysis. Finally, landscape metrics were calculated to assess landscape fragmentation. The overall classification accuracy ranged from 84.7% to 88.3%. The total amount of land cover change from 1984 to 2011 was 24%, with 0.9% of agricultural land and 0.4% of forest land changed to well pads. The results of Patch-Per-Unit area (PPU) index indicated that the well pad class was highly fragmented, while agriculture (4.4-8.6 per sq km) consistently showed a higher magnitude of fragmentation than forest (0.8-1.4 per sq km).

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Quantifying Land Cover Change Due to Petroleum Exploration and Production in the Haynesville Shale Region Using Remote Sensing

International Journal of Applied Geospatial Research ◽

10.4018/ijagr.2015040101 ◽

2015 ◽

Vol 6 (2) ◽

pp. 1-17 ◽

Cited By ~ 4

Author(s):

Daniel Unger ◽

I-Kuai Hung ◽

Kenneth Farrish ◽

Darinda Dans

Keyword(s):

Land Cover ◽

Land Cover Change ◽

Landscape Change ◽

Oil And Gas ◽

Agricultural Land ◽

Landscape Fragmentation ◽

Petroleum Exploration ◽

Forest Land ◽

The Past ◽

Exploration And Production

The Haynesville Shale lies under areas of Louisiana and Texas and is one of the largest gas plays in the U.S. Encompassing approximately 2.9 million ha, this area has been subject to intensive exploration for oil and gas, while over 90% of it has traditionally been used for forestry and agriculture. In order to detect the landscape change in the past few decades, Landsat Thematic Mapper (TM) imagery for six years (1984, 1989, 1994, 2000, 2006, and 2011) was acquired. Unsupervised classifications were performed to classify each image into four cover types: agriculture, forest, well pad, and other. Change detection was then conducted between two classified maps of different years for a time series analysis. Finally, landscape metrics were calculated to assess landscape fragmentation. The overall classification accuracy ranged from 84.7% to 88.3%. The total amount of land cover change from 1984 to 2011 was 24%, with 0.9% of agricultural land and 0.4% of forest land changed to well pads. The results of Patch-Per-Unit area (PPU) index indicated that the well pad class was highly fragmented, while agriculture (4.4-8.6 per sq km) consistently showed a higher magnitude of fragmentation than forest (0.8-1.4 per sq km).

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Land Use Land Cover Change and its Pathways in Sidin VDC, Panchthar District, Nepal

Geographical Journal of Nepal ◽

10.3126/gjn.v11i0.19550 ◽

2018 ◽

Vol 11 ◽

pp. 77-94 ◽

Cited By ~ 1

Author(s):

Prem Sagar Chapagain ◽

Mohan Kumar Rai ◽

Basanta Paudel

Keyword(s):

Land Use ◽

Land Cover ◽

Land Cover Change ◽

Agricultural Land ◽

Time Series Data ◽

Household Survey ◽

Human Interaction ◽

Series Data ◽

Land Use Land Cover ◽

Important Indicator

Land use/land cover situation is an important indicator of human interaction with environment. It reflects both environmental situation and the livelihood strategies of the people in space over time. This paper has attempted to study the land use/ land cover change of Sidin VDC, in the Koshi River basin in Nepal, based on maps and Remote sensing imageries (RS) data and household survey using structured questionnaires, focus group discussion and key informant interview. The study has focused on analysis the trend and pathways of land use change by dividing the study area into three elevation zones – upper, middle and lower. The time series data analysis from 1994-2004-2014 show major changes in forest and agricultural land. The dominant pathways of change is from forest to agriculture and forest to shrub during 1994-2004 and agriculture to forest during 2004-2014. The development of community forest, labor migration and labor shortage are found the major causes of land use change.The Geographical Journal of NepalVol. 11: 77-94, 2018

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Land Use and Land Cover Change Detection and Prediction in the Kathmandu District of Nepal Using Remote Sensing and GIS

Sustainability ◽

10.3390/su12093925 ◽

2020 ◽

Vol 12 (9) ◽

pp. 3925 ◽

Cited By ~ 2

Author(s):

Sonam Wangyel Wang ◽

Belay Manjur Gebru ◽

Munkhnasan Lamchin ◽

Rijan Bhakta Kayastha ◽

Woo-Kyun Lee

Keyword(s):

Remote Sensing ◽

Land Use ◽

Land Cover ◽

Land Cover Change ◽

Agricultural Land ◽

Water Bodies ◽

Geographical Information ◽

Land Cover Changes ◽

Rapid Urbanization ◽

Urbanized Areas

Understanding land use and land cover changes has become a necessity in managing and monitoring natural resources and development especially urban planning. Remote sensing and geographical information systems are proven tools for assessing land use and land cover changes that help planners to advance sustainability. Our study used remote sensing and geographical information system to detect and predict land use and land cover changes in one of the world’s most vulnerable and rapidly growing city of Kathmandu in Nepal. We found that over a period of 20 years (from 1990 to 2010), the Kathmandu district has lost 9.28% of its forests, 9.80% of its agricultural land and 77% of its water bodies. Significant amounts of these losses have been absorbed by the expanding urbanized areas, which has gained 52.47% of land. Predictions of land use and land cover change trends for 2030 show worsening trends with forest, agriculture and water bodies to decrease by an additional 14.43%, 16.67% and 25.83%, respectively. The highest gain in 2030 is predicted for urbanized areas at 18.55%. Rapid urbanization—coupled with lack of proper planning and high rural-urban migration—is the key driver of these changes. These changes are associated with loss of ecosystem services which will negatively impact human wellbeing in the city. We recommend city planners to mainstream ecosystem-based adaptation and mitigation into urban plans supported by strong policy and funds.

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