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Artykuły w czasopismach na temat „Land use change”

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Autor: Grafiati

Data publikacji: 4 czerwca 2021

Data aktualizacji: 1 czerwca 2024

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1

Ismail K, Bello, Sodiya Abiodun K i Solanke Peter A. "Public Land Acquisition and Land Use Change Problems in Ogun State". International Journal of Management Science and Business Administration 2, nr 8 (2015): 34–41. http://dx.doi.org/10.18775/ijmsba.1849-5664-5419.2014.28.1004.

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Human use of land has altered the structure and functioning of ecosystem. The most spatially and economically important human uses of land globally include cultivation in various forms; livestock grazing, settlement and construction, reserves and protected lands and timber extraction. The patterns of land use give us insight into the factors that have caused the land cover to change. A better understanding of the determining factors of land use changes is of crucial importance to the study of global environmental change. This paper theoretically strive to evaluate the contributions of government policies and programmes in transforming the various land uses in the urban centers of Ogun state with a view to provide better understanding among the stakeholders in real estate investment. The paper recommended that although landuse changes is an inevitable consequences in the developing nations, there is the need to consider the positive and negative aspect of the policies in order not to jeopardize the available environmental resources for sustainable development. The paper concluded by emphasized the need for government to carry the citizen along in the various policies and programs for even development.

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2

Dawson, A. H. "Land-use change". Land Use Policy 8, nr 1 (styczeń 1991): 83–84. http://dx.doi.org/10.1016/0264-8377(91)90061-m.

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Deshpande, Srinivas, i Rohan S. Gurav. "Change Detection of Land Use and Land Cover Over Ghataprabha River Basin". International Journal of Science and Research (IJSR) 12, nr 10 (5.10.2023): 71–78. http://dx.doi.org/10.21275/sr23930164256.

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Manca, Germana. "Introduction: Land Use and Land Change". Cartographica: The International Journal for Geographic Information and Geovisualization 47, nr 4 (grudzień 2012): 209–10. http://dx.doi.org/10.3138/carto.47.4.intro.

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5

Iacono, Michael J., i David M. Levinson. "Predicting Land Use Change". Transportation Research Record: Journal of the Transportation Research Board 2119, nr 1 (styczeń 2009): 130–36. http://dx.doi.org/10.3141/2119-16.

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Booth, Philip. "Managing land-use change". Land Use Policy 26 (grudzień 2009): S154—S159. http://dx.doi.org/10.1016/j.landusepol.2009.08.011.

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7

Veldkamp, A., i E. F. Lambin. "Predicting land-use change". Agriculture, Ecosystems & Environment 85, nr 1-3 (czerwiec 2001): 1–6. http://dx.doi.org/10.1016/s0167-8809(01)00199-2.

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Indrawan, I. N. P., Widiatmaka i B. H. Trisasongko. "Land use land cover change in Badung Regency, Bali". IOP Conference Series: Earth and Environmental Science 950, nr 1 (1.01.2022): 012096. http://dx.doi.org/10.1088/1755-1315/950/1/012096.

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Abstract Demand for land use can cause an undesirable impact. Bali Island has been exploited as the midpoint of tourism activities and altering land use over the last two decades. Badung regency is the hinterland area of Denpasar City, the capital city of Bali Province. Land conversion in Badung was caused by the construction infrastructures related to tourism development. Conversion occurred from agricultural lands to built-up lands. This research analyzed remote sensing data, taking the advantage of abundant, serial data acquisition. This study used Landsat 7 ETM and Sentinel 2 satellite images obtained from 2010 to 2020. Land cover types were identified by visual interpretation and LULC changes were analyzed by overlaying land use maps. Identified land-use types included eight categories, i.e. paddy fields, forests, mangroves, built-up areas, mixed gardens/plantations, upland fields, shrubs, and water bodies. Land use has changed significantly in the past 10 years especially in built-up areas, upland fields, and paddy fields. The trend showed that built-up areas persistently increased from 2010 to 2020. Paddy fields, shrubs, mixed gardens/plantations, and mangroves fluctuated in terms of the acreage; rose from 2010 to 2015, but were reduced in the rest of the period. Water bodies did not change throughout.

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9

Dero, Kambo, Wakshum Shiferaw i Biruk Zewde. "Urban induced land use land cover changes in upper Deme watershed, Southwest Ethiopia". Journal of Degraded and Mining Lands Management 9, nr 1 (1.10.2021): 3045–53. http://dx.doi.org/10.15243/jdmlm.2021.091.3045.

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The study was aimed to assess urban induced land use land cover changes in the upper Deme watershed. Three satellite images of 1986, 2002, and 2019 were analyzed by ArcGIS and processed by supervised classification. Land use land cover change in the watershed increased for settlement, bare land, and croplands in the period 1986-2019 by 56.6%, 53%, and 0.25%, respectively. However, the land use land cover change in the watershed decreased for a water body, forest, and grassland by 65%, 57.7%, and 7%, respectively. These enforced to change the work habit and social bases. Out of converted lands, during 1986-2002, 34.9%, 53%, 18%, 40.9%, and 10.6% of bare land, cropland, forest land, grassland, and water bodies, respectively, in the upper Deme watershed were changed into settlement areas. During 2002-2019, 30.7%, 36.8%, 26.9%, 66%, and 33.3% of bare land, cropland, forest land, grassland, and water bodies, respectively, were changed into settlement areas. This shows urbanization results in a different change in economic, social, land use land cover, and watershed management activities in the upper Deme watershed.

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10

van der Molen, P., i D. Mitchell. "Climate change, land use and land surveyors". Survey Review 48, nr 347 (23.02.2016): 148–55. http://dx.doi.org/10.1179/1752270615y.0000000029.

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Erickson, Donna L. "Rural land use and land cover change". Land Use Policy 12, nr 3 (lipiec 1995): 223–36. http://dx.doi.org/10.1016/0264-8377(95)00005-x.

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12

Smith, S. J., i A. Rothwell. "Carbon density and anthropogenic land-use influences on net land-use change emissions". Biogeosciences 10, nr 10 (8.10.2013): 6323–37. http://dx.doi.org/10.5194/bg-10-6323-2013.

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Abstract. We examine historical and future land-use emissions using a simple mechanistic carbon-cycle model with regional and ecosystem specific parameterizations. We use the latest gridded data for historical and future land-use changes, which includes estimates for the impact of forest harvesting and secondary forest regrowth. Our central estimate of net terrestrial land-use change emissions, exclusive of climate–carbon feedbacks, is 250 GtC over the last 300 yr. This estimate is most sensitive to assumptions for preindustrial forest and soil carbon densities. We also find that land-use change emissions estimates are sensitive to the treatment of crop and pasture lands. These sensitivities also translate into differences in future terrestrial uptake in the RCP (representative concentration pathway) 4.5 land-use scenario. The estimate of future uptake obtained here is smaller than the native values from the GCAM (Global Change Assessment Model) integrated assessment model result due to lower net reforestation in the RCP4.5 gridded land-use data product.

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13

Kalisz, Barbara, Krystyna Żuk-Gołaszewska, Wioleta Radawiec i Janusz Gołaszewski. "Land Use Indicators in the Context of Land Use Efficiency". Sustainability 15, nr 2 (6.01.2023): 1106. http://dx.doi.org/10.3390/su15021106.

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In recent decades, the land use changes induced by various economic activities in agricultural ecosystems have affected many aspects of human life. This is the reason why land use change is considered as one of the agriculture-related environmental impacts in a sustainability assessment of food and bio-based products. At the same time, the methodology applied for the quantification of land use change effects is still under intensive research, stimulating scientific discussions. The overall objective of this paper is to fill the gap in knowledge of responsible and sustainable land use management. Specifically, the research provides a comprehensive set of land use change indicators in the context of land use change and land use efficiency. The indicators can be measured based on publicly available databases with the applicability to agricultural sustainability assessment of land use change on a local, regional and global scale. The high share of artificial land and dominant agricultural use of land with low land use intensity were noted in Belgium, Luxemburg, Netherlands, Slovenia, Cyprus, Croatia, Finland, Germany, and United Kingdom. However, land use efficiency was also low. In turn, heterogeneous land cover (but less artificial areas than in other EU countries) and heterogeneous land uses with diverse land use intensity were noted in Austria, Bulgaria, Denmark, Estonia, France, Hungary, Ireland, Italy, Latvia, Lithuania, Malta, Poland, Portugal, Romania, Slovakia, Spain, and Sweden. The challenge in future research could be aggregation of different indicators in assessing the similarity of land use between countries.

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14

Wahyuni, Nurlita, Abdul Hasyim i Soemarno Soemarno. "Dynamic of the Land Use and Land Cover Change in Banyuwangi Regency From 1995-2019". Jurnal Wasian 8, nr 2 (30.12.2021): 121–32. http://dx.doi.org/10.20886/jwas.v8i2.6707.

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The land use and land cover change phenomenon has become one concern over many regions worldwide, including Indonesia. Land use and land cover change due to human activities triggered alteration terrestrial ecosystems and its services including climate control functions. The study aimed to analyze land use and land cover change in Banyuwangi regency during 1995 – 2019. Four satellite images from acquisition year 1995, 2000, 2014 and 2019 were used to analyze the spatial and temporal changes along with field observations. The classification processes of land use and land cover included determination of training areas, supervised classification, and accuracy assessment. There are 12 land use and land cover based on supervised classification as follow primary forest, secondary forest, plantation forest, mangrove forest, plantation, settlement, cropland, paddy field, shrubs, water, fishpond and barren land. The result showed during observation period of 1995 until 2019 land use and land cover which tends to decrease are secondary forest, mangrove forest, and rice fields. On the other hand, the area of settlements, shrubs and fishponds were increased significantly.

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15

Sewnet, Amare. "Land Use/Cover Change at Infraz Watershed, Northwestren Ethiopia". Journal of Landscape Ecology 8, nr 1 (1.01.2015): 69–83. http://dx.doi.org/10.1515/jlecol-2015-0005.

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Abstract Land cover is the physical and biological cover of the surface whereas land use covers the results of human activities for the exploitation of it. The land cover and landuse change is caused by both, natural and anthropogenic factors. The objective of this study was to detect land cover/use changes in Infraz Watershed. The study has used ArcGIS10 and ERDAS IMAGINE10, landsat images of 1973, 1986, 1995 and 2011 and socio-economic data to analyze land cover and landuse changes of Infraz watershed. The study has found that due to the population increase and improper agricultural activity bush and wetlands have declined where as farm and settlement lands expanded between the study years. About 1044 wetlands and 6338.7 ha of bush lands were lost and converted to cultivated and farm lands, grass lands and forest covers which were increased by 6685.3, 357.7 and 338.3 ha between the study periods respectively. There is an urgent need to limit the population growth rate and implementing land use policy in the Infraz watershed.

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16

van Asselen, Sanneke, i Peter H. Verburg. "Land cover change or land-use intensification: simulating land system change with a global-scale land change model". Global Change Biology 19, nr 12 (18.08.2013): 3648–67. http://dx.doi.org/10.1111/gcb.12331.

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17

Nganro, Sudirman, Slamet Trisutomo, Roland Barkey, Mukti Ali, Hidefumi Imura, Akio Onishi, Pei-I. Tsai i Mohd Amirul Mahamud. "Prediction of Future Land Use and Land Cover (LULC) in Makassar City". TATALOKA 23, nr 2 (31.05.2021): 183–89. http://dx.doi.org/10.14710/tataloka.23.2.183-189.

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Migration from rural area to urban area increases urban population. It increases and needs for settlements, leading to conversion of agricultural lands into settlement areas. Inconsistent land use compared with spatial planning causes change in land use. Spatial land use expansion can be monitored and predicted by modeling. NetLogo application is a software integrated with Agent-Based Modeling (ABM), which can be used to predict change of land use with various complex parameters. The present study used population growth as a parameter to predict change of land use of Makassar in 2050 based on 2017 land use classification map as the start of the prediction. The analysis result showed that the biggest change of land use happens to Settlement class which is 594.74 hectares and the smallest is Water Body class which is 8.76 hectares.

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18

Junkermann, W., J. Hacker, T. Lyons i U. Nair. "Land use change suppresses precipitation". Atmospheric Chemistry and Physics Discussions 9, nr 3 (8.05.2009): 11481–500. http://dx.doi.org/10.5194/acpd-9-11481-2009.

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Abstract. A feedback loop between regional scale deforestation and climate change was investigated in an experiment using novel, small size airborne platforms and instrument setups. Experiments were performed in a worldwide unique natural laboratory in Western Australia, characterized by two adjacent homogeneous observation areas with distinctly different land use characteristics. Conversion of several ten thousand square km of forests into agricultural land began more than a century ago. Changes in albedo and surface roughness and the water budget of soil and the planetary boundary layer evolved over decades. Besides different meteorology we found a significant up to now overseen source of aerosol over the agriculture. The enhanced number of cloud condensation nuclei is coupled through the hydrological groundwater cycle with deforestation. Modification of surface properties and aerosol number concentrations are key factors for the observed reduction of precipitation. The results document the importance of aerosol indirect effects on climate due to nanometer size biogenic aerosol and human impact on aerosol sources.

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Junkermann, W., J. Hacker, T. Lyons i U. Nair. "Land use change suppresses precipitation". Atmospheric Chemistry and Physics 9, nr 17 (10.09.2009): 6531–39. http://dx.doi.org/10.5194/acp-9-6531-2009.

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Abstract. A feedback loop between regional scale deforestation and climate change was investigated in an experiment using novel, small size airborne platforms and instrument setups. Experiments were performed in a worldwide unique natural laboratory in Western Australia, characterized by two adjacent homogeneous observation areas with distinctly different land use characteristics. Conversion of several ten thousand square km of forests into agricultural land began more than a century ago. Changes in albedo, surface roughness, the soil water budget and the planetary boundary layer evolved over decades. Besides different meteorology, we found a significant up to now overlooked source of aerosol over the agriculture area. The enhanced number of cloud condensation nuclei is coupled through the hydrological groundwater cycle with deforestation. Modification of surface properties and aerosol number concentrations are key factors for the observed reduction of precipitation. The results document the importance of aerosol indirect effects on climate due to nanometer size biogenic aerosol and human impact on aerosol sources.

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20

Bibby, Peter. "Land use change in Britain". Land Use Policy 26 (grudzień 2009): S2—S13. http://dx.doi.org/10.1016/j.landusepol.2009.09.019.

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Brazel, A. J. "Land Use and Cover Change". Landscape and Urban Planning 58, nr 1 (styczeń 2002): 71. http://dx.doi.org/10.1016/s0169-2046(01)00232-8.

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Charlton, W. A., i B. W. Beeley. "Land use change in Malta". Land Use Policy 4, nr 2 (kwiecień 1987): 96–101. http://dx.doi.org/10.1016/0264-8377(87)90043-3.

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Vorel, Jakub, i Stanislav Grill. "Land use change propensity maps". Journal of Maps 11, nr 2 (28.04.2014): 225–30. http://dx.doi.org/10.1080/17445647.2014.911709.

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24

Henderson-Sellers, A. "Land-use change and climate". Land Degradation and Development 5, nr 2 (lipiec 1994): 107–26. http://dx.doi.org/10.1002/ldr.3400050207.

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Chen, Jin, Peng Gong, Chunyang He, Ruiliang Pu i Peijun Shi. "Land-Use/Land-Cover Change Detection Using Improved Change-Vector Analysis". Photogrammetric Engineering & Remote Sensing 69, nr 4 (1.04.2003): 369–79. http://dx.doi.org/10.14358/pers.69.4.369.

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HUSSAINI, Fatema, Ebrahim FARHADI, Ali HOSSEINI i Ahmad POURAHMAD. "Investigating Land Use Change in Kabul, Afghanistan". Journal of Settlements and Spatial Planning 13, nr 2 (31.12.2022): 61–69. http://dx.doi.org/10.24193/jssp.2022.2.01.

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Land use change and land cover are considered as some of the important and effective factors of global environmental change. Therefore, understanding and predicting the causes, processes, and consequences of land use change has become a major global challenge. Kabul is the most populated city in Afghanistan. The face of Kabul has changed after a relatively peaceful period since 2001. The purpose of this study is to analyze land use change in Kabul from 2001 to 2019. We used the quantitative approach to analyse data provided by satellite images of Kabul in 2001 and 2019 from Landsat 8 and 7. Data was processed in ERDAS IMAGINE and Arc Map software to results in the final output. Urban land cover was classified into four classes, namely built-up area, green area, empty space, and mountain, and land cover changes were detected. The results of the image comparison between 2001 and 2019 show that the aggregated built-up area and empty space land cover increased by 69.1749 sq km and, correspondingly, 45.2538 sq km, whereas the green area decreased by 113.4216 sq km. We concluded that land cover has changed improperly. The rate of urban green space per individual is currently very low. These results indicate that the city is in a critical urban situation and the government should provide a comprehensive plan for controlling urban growth and fixing the problems caused by improper land use change in the city.

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Kumar, Dr Anil. "Spatio-Temporal Land use / Land cover Change Assessments;". International Journal for Research in Applied Science and Engineering Technology V, nr X (30.10.2017): 1669–72. http://dx.doi.org/10.22214/ijraset.2017.10242.

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Meyer, William B., i B. L. Turner. "Land-use/land-cover change: challenges for geographers". GeoJournal 39, nr 3 (lipiec 1996): 237–40. http://dx.doi.org/10.1007/bf00188373.

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Tol, Richard S. J. "Dynamic World: Land-Cover and Land-Use Change". Environmental Science & Policy 7, nr 1 (luty 2004): 77. http://dx.doi.org/10.1016/j.envsci.2003.10.001.

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Smith, S. J., i A. Rothwell. "Carbon density and anthropogenic land use influences on net land-use change emissions". Biogeosciences Discussions 10, nr 3 (5.03.2013): 4157–91. http://dx.doi.org/10.5194/bgd-10-4157-2013.

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Abstract. We examine historical and future land-use emissions using a simple mechanistic carbon-cycle model with regional and ecosystem specific parameterizations. Our central estimate of net terrestrial land-use change emissions, exclusive of climate feedbacks, is 250 Gt C over the last three hundred years. This estimate is most sensitive to assumptions for pre-industrial forest and soil carbon densities. We also find that estimates are sensitive to the treatment of crop and pasture lands. These sensitivities also translate into differences in future terrestrial uptake in the RCP4.5 land-use scenario. This estimate of future uptake is lower than the native values from the GCAM integrated assessment model result due to lower net reforestation in the RCP4.5 gridded land-use data product.

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Twisa, Sekela, i Manfred F. Buchroithner. "Land-Use and Land-Cover (LULC) Change Detection in Wami River Basin, Tanzania". Land 8, nr 9 (8.09.2019): 136. http://dx.doi.org/10.3390/land8090136.

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Anthropogenic activities have substantially changed natural landscapes, especially in regions which are extremely affected by population growth and climate change such as East African countries. Understanding the patterns of land-use and land-cover (LULC) change is important for efficient environmental management, including effective water management practice. Using remote sensing techniques and geographic information systems (GIS), this study focused on changes in LULC patterns of the upstream and downstream Wami River Basin over 16 years. Multitemporal satellite imagery of the Landsat series was used to map LULC changes and was divided into three stages (2000–2006, 2006–2011, and 2011–2016). The results for the change-detection analysis and the change matrix table from 2000 to 2016 show the extent of LULC changes occurring in different LULC classes, while most of the grassland, bushland, and woodland were intensively changed to cultivated land both upstream and downstream. These changes indicate that the increase of cultivated land was the result of population growth, especially downstream, while the primary socioeconomic activity remains agriculture both upstream and downstream. In general, net gain and net loss were observed downstream, which indicate that it was more affected compared to upstream. Hence, proper management of the basin, including land use planning, is required to avoid resources-use conflict between upstream and downstream users.

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Karandikar, Aarti, i Avinash Agrawal. "Performance analysis of change detection techniques for land use land cover". International Journal of Electrical and Computer Engineering (IJECE) 13, nr 4 (1.08.2023): 4339. http://dx.doi.org/10.11591/ijece.v13i4.pp4339-4346.

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<p><span lang="EN-US">Remotely sensed satellite images have become essential to observe the spatial and temporal changes occurring due to either natural phenomenon or man-induced changes on the earth’s surface. Real time monitoring of this data provides useful information related to changes in extent of urbanization, environmental changes, water bodies, and forest. Through the use of remote sensing technology and geographic information system tools, it has become easier to monitor changes from past to present. In the present scenario, choosing a suitable change detection method plays a pivotal role in any remote sensing project. Previously, digital change detection was a tedious task. With the advent of machine learning techniques, it has become comparatively easier to detect changes in the digital images. The study gives a brief account of the main techniques of change detection related to land use land cover information. An effort is made to compare widely used change detection methods used to identify changes and discuss the need for development of enhanced change detection methods.</span></p>

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Saleh Al-Zuhairi, Alaa Mahdi, i Tanzeeh Majeed Hameed. "Deterioration characterization of land cover and land use in Muqdadiya district center for the period 1995 to 2019". IOP Conference Series: Earth and Environmental Science 877, nr 1 (1.11.2021): 012017. http://dx.doi.org/10.1088/1755-1315/877/1/012017.

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Abstract The research dealt with the analysis of environmental changes in the types of land cover and land uses within the Muqdadiyah district center in Diyala governorate and revealed between 1995 and 2019 in order to determine the environmental deterioration of the land cover and land uses and the resulting environmental changes. For the American satellite (Landsat). It turned out that there were changes during the research period, as the amount of change in the area of agricultural land amounted to (-91,16) km2, and the area of pastures decreased as the amount of change reached (-39.89) km2, while the amount of change in the area of urbanization was (44, 38) km2, while the change amount was recorded (100,19) km2 for barren lands, which means a decrease in the area of agricultural and pasture lands in favor of built-up lands and barren lands, which negatively affected the biodiversity within the study area.

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Vranová, V., P. Formánek, K. Rejšek i M. Pavelka. "Impact of land-use change on proteolytic activity of mountain meadows". Soil and Water Research 4, No. 3 (22.09.2009): 122–25. http://dx.doi.org/10.17221/16/2009-swr.

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Casein-protease activity assessed at 50°C and with adjustment of optimum pH conditions (PA), and casein-protease activity near soil pH and at field soil temperature (LPA) were studied one vegetation period in mountain meadow soils covered with moderately mown vegetation, and over which vegetation had been abandoned for thirteen years. PA peaked in the first part of the vegetation season whereas LPA increased throughout the season; in addition, LPA was not linearly related to temperature (r = 0.127 resp. 0.312; P > 0.05). The combined effect of field soil temperature and pH decreased a casein-protease activity by > 98.4%. A management of meadows had no significant (P > 0.05) effect on PA and LPA.

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HAMILTON, CHRISTOPHER M., WAYNE E. THOGMARTIN, VOLKER C. RADELOFF, ANDREW J. PLANTINGA, PATRICIA J. HEGLUND, SEBASTIAN MARTINUZZI i ANNA M. PIDGEON. "Change in agricultural land use constrains adaptation of national wildlife refuges to climate change". Environmental Conservation 42, nr 1 (22.05.2014): 12–19. http://dx.doi.org/10.1017/s0376892914000174.

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SUMMARYLand-use change around protected areas limits their ability to conserve biodiversity by altering ecological processes such as natural hydrologic and disturbance regimes, facilitating species invasions, and interfering with dispersal of organisms. This paper informs USA National Wildlife Refuge System conservation planning by predicting future land-use change on lands within 25 km distance of 461 refuges in the USA using an econometric model. The model contained two differing policy scenarios, namely a ‘business-as-usual’ scenario and a ‘pro-agriculture’ scenario. Regardless of scenario, by 2051, forest cover and urban land use were predicted to increase around refuges, while the extent of range and pasture was predicted to decrease; cropland use decreased under the business-as-usual scenario, but increased under the pro-agriculture scenario. Increasing agricultural land value under the pro-agriculture scenario slowed an expected increase in forest around refuges, and doubled the rate of range and pasture loss. Intensity of land-use change on lands surrounding refuges differed by regions. Regional differences among scenarios revealed that an understanding of regional and local land-use dynamics and management options was an essential requirement to effectively manage these conserved lands. Such knowledge is particularly important given the predicted need to adapt to a changing global climate.

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Takayanagi, Seiya. "Relationship between population change and land use change used by land use subdivision mesh data". Journal of the City Planning Institute of Japan 52, nr 3 (25.10.2017): 459–66. http://dx.doi.org/10.11361/journalcpij.52.459.

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Wan, Lei, Huiyu Liu, Haibo Gong i Yujia Ren. "Effects of Climate and Land Use changes on Vegetation Dynamics in the Yangtze River Delta, China Based on Abrupt Change Analysis". Sustainability 12, nr 5 (4.03.2020): 1955. http://dx.doi.org/10.3390/su12051955.

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Vegetation dynamics is thought to be affected by climate and land use changes. However, how the effects vary after abrupt vegetation changes remains unclear. Based on the Mann-Kendall trend and abrupt change analysis, we monitored vegetation dynamics and its abrupt change in the Yangtze River delta during 1982–2016. With the correlation analysis, we revealed the relationship of vegetation dynamics with climate changes (temperature and precipitation) pixel-by-pixel and then with land use changes analysis we studied the effects of land use changes (unchanged or changed land use) on their relationship. Results showed that: (1) the Normalized Vegetation Index (NDVI) during growing season that is represented as GSN (growing season NDVI) showed an overall increasing trend and had an abrupt change in 2000. After then, the area percentages with decreasing GSN trend increased in cropland and built-up land, mainly located in the eastern, while those with increasing GSN trend increased in woodland and grassland, mainly located in the southern. Changed land use, except the land conversions from/to built-up land, is more favor for vegetation greening than unchanged land use (2) after abrupt change, the significant positive correlation between precipitation and GSN increased in all unchanged land use types, especially for woodland and grassland (natural land use) and changed land use except built-up land conversion. Meanwhile, the insignificant positive correlation between temperature and GSN increased in woodland, while decreased in the cropland and built-up land in the northwest (3) after abrupt change, precipitation became more important and favor, especially for natural land use. However, temperature became less important and favor for all land use types, especially for built-up land. This research indicates that abrupt change analysis will help to effectively monitor vegetation trend and to accurately assess the relationship of vegetation dynamics with climate and land use changes.

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Ning, Quanke, Shicheng Xie, Chen Zhong, Dan Yu i Xiaoman Tai. "Remote sensing analysis of land use/cover change". Journal of Geography and Cartography 5, nr 1 (28.01.2022): 24. http://dx.doi.org/10.24294/jgc.v5i1.1414.

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Based on Landsat–7ETM + images of 2007 and 2012 and Landsat–8 images of 2018, this study took Fuyang City, Anhui Province (Yingzhou District, Yingdong District, Yingquan District) as the research object, and made a quantitative analysis of land use/cover change in Fuyang City from 2007 to 2018 with the Environment for Visualizing Images (ENVI) software. According to the data of land use types in three phases, the article analyzes the development trend of various land use types and the main reasons for the changes of land use, which provides a certain basis for the urban planning and environmental construction of Fuyang City. The results show that with the rapid economic development and continuous improvement of the urbanization level in Fuyang City during 11 years, the area of various land types in the study area has changed greatly. The area of construction land area changed by 448.27 km2, with an increase of 543.57%; the area of arable land changed by 597.52 km2, with a decrease of 34.74%; the area of bare land changed by 26.00 km2, with a decrease of 80.68%. The changes were closely related to the rapid economic and social development in the study area. Under the influence of environmental protection policies and environmental awareness, the area of forest land changed by 85.00 km2, with an increase of 97.58%; the water area changed by 84.35 km2, with an increase of 201.39%.

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39

Bayer, Anita D., Mats Lindeskog, Thomas A. M. Pugh, Peter M. Anthoni, Richard Fuchs i Almut Arneth. "Uncertainties in the land-use flux resulting from land-use change reconstructions and gross land transitions". Earth System Dynamics 8, nr 1 (13.02.2017): 91–111. http://dx.doi.org/10.5194/esd-8-91-2017.

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Abstract. Land-use and land-cover (LUC) changes are a key uncertainty when attributing changes in measured atmospheric CO2 concentration to its sinks and sources and must also be much better understood to determine the possibilities for land-based climate change mitigation, especially in the light of human demand on other land-based resources. On the spatial scale typically used in terrestrial ecosystem models (0.5 or 1°) changes in LUC over time periods of a few years or more can include bidirectional changes on the sub-grid level, such as the parallel expansion and abandonment of agricultural land (e.g. in shifting cultivation) or cropland–grassland conversion (and vice versa). These complex changes between classes within a grid cell have often been neglected in previous studies, and only net changes of land between natural vegetation cover, cropland and pastures accounted for, mainly because of a lack of reliable high-resolution historical information on gross land transitions, in combination with technical limitations within the models themselves. In the present study we applied a state-of-the-art dynamic global vegetation model with a detailed representation of croplands and carbon–nitrogen dynamics to quantify the uncertainty in terrestrial ecosystem carbon stocks and fluxes arising from the choice between net and gross representations of LUC. We used three frequently applied global, one recent global and one recent European LUC datasets, two of which resolve gross land transitions, either in Europe or in certain tropical regions. When considering only net changes, land-use-transition uncertainties (expressed as 1 standard deviation around decadal means of four models) in global carbon emissions from LUC (ELUC) are ±0.19, ±0.66 and ±0.47 Pg C a−1 in the 1980s, 1990s and 2000s, respectively, or between 14 and 39 % of mean ELUC. Carbon stocks at the end of the 20th century vary by ±11 Pg C for vegetation and ±37 Pg C for soil C due to the choice of LUC reconstruction, i.e. around 3 % of the respective C pools. Accounting for sub-grid (gross) land conversions significantly increased the effect of LUC on global and European carbon stocks and fluxes, most noticeably enhancing global cumulative ELUC by 33 Pg C (1750–2014) and entailing a significant reduction in carbon stored in vegetation, although the effect on soil C stocks was limited. Simulations demonstrated that assessments of historical carbon stocks and fluxes are highly uncertain due to the choice of LUC reconstruction and that the consideration of different contrasting LUC reconstructions is needed to account for this uncertainty. The analysis of gross, in addition to net, land-use changes showed that the full complexity of gross land-use changes is required in order to accurately predict the magnitude of LUC change emissions. This introduces technical challenges to process-based models and relies on extensive information regarding historical land-use transitions.

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Polyakov, Maksym, i Daowei Zhang. "Population Growth and Land Use Dynamics along Urban–Rural Gradient". Journal of Agricultural and Applied Economics 40, nr 2 (sierpień 2008): 649–66. http://dx.doi.org/10.1017/s1074070800023919.

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In this study we apply a spatial conditional logit model to determine factors influencing land cover change in three contiguous counties in West Georgia between 1992 and 2001 using point (pixel) based observations of land characteristics. We found that accessibility to population and population growth affect not only development of rural lands and transition between agricultural and forestry uses, but also influence changes between forest types. The model could be used to project land use–land cover change at watershed or subwatershed level and thus serve as a valuable tool for county and city planners.

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Girma, Abel, Denghua Yan, Kun Wang, Hailu Birara, Mohammed Gedefaw, Dorjsuren Batsuren, Asaminew Abiyu, Tianlin Qin, Temesgen Mekonen i Amanuel Abate. "Climate Change, Land Use, and Vegetation Evolution in the Upper Huai River Basin". Atmosphere 14, nr 3 (7.03.2023): 512. http://dx.doi.org/10.3390/atmos14030512.

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Land-use/land-cover change and climate change have changed the spatial–temporal distribution of water resources. The Huai River Basin shows the spatial and temporal changes of climate from 1960 to 2016 and land-use/land-cover changes from 1995 to 2014. Thus, this study aims to investigate climate change, land use, and vegetation evolution in the Upper Huai River Basin. The Mann–Kendall test (MK), Innovative Trend Analysis Method (ITAM), and Sen’s slope estimator test were used to detect climate change trends. The land-use/land-cover change was also examined using a transformation matrix and Normalized Difference Vegetation Index (NDVI). The results of this study revealed that precipitation has shown a slightly decreasing trend during the past 56 years. However, the air temperature has increased by 1.2 °C. The artificial and natural vegetation and wetland were decreased by 12,097 km2, 3207 km2, and 641 km2, respectively. On the other hand, resident construction land and artificial water bodies increased by 2277 km2 and 3691 km2, respectively. This indicates that the land cover has significantly changed during the past 30 years. The findings of this study will have implications for predicting the water resources safety and eco-environment of The Huai River Basin. The spatial distribution showed an uneven change in the Huai River Basin. Together, we suggested that the variability of water resources availability in the Huai River Basin was mainly attributed to climate variability, while land use change plays a key role in the sub-basins, which experienced dramatic changes in land use.

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Arowolo, Aisha Olushola, i Xiangzheng Deng. "Land use/land cover change and statistical modelling of cultivated land change drivers in Nigeria". Regional Environmental Change 18, nr 1 (21.07.2017): 247–59. http://dx.doi.org/10.1007/s10113-017-1186-5.

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Arora, Gaurav, Peter T. Wolter, David A. Hennessy i Hongli Feng. "Land Use Change and Policy in Iowa’s Loess Hills". Sustainable Agriculture Research 5, nr 4 (11.09.2016): 30. http://dx.doi.org/10.5539/sar.v5n4p30.

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<p class="sar-body"><span lang="EN-US">Land use changes have important implications on ecosystems and society. Detailed identification of the nature of land use changes in any local region is critical for policy design. In this paper, we quantify land use change in Iowa’s Loess Hills ecoregion, which contains much of the state’s remaining prairie grasslands. We employ two distinct panel datasets, the National Resource Inventory data and multi-year Cropland Data Layers, that allow us to characterize spatially-explicit land use change in the region over the period 1982-2010. We analyze land use trends, land use transitions and crop rotations within the ecoregion, and contrast these with county and state-level changes. To better comprehend the underlying land use changes, we evaluate our land use characterizing metrics conditional on soil quality variables such as slope and erodibility. We also consider the role of contemporary agricultural policy and commodity markets to seek explanations for land use changes during the period of our study. Although crop production has expanded on the Loess Hills landform since 2005, much of the expansion in corn acres has been from reduced soybean acreage. We find that out of the total 258 km<sup>2</sup> increase in corn acreage during 2005-’10, about 100 km<sup>2</sup> transitioned from soybeans. Data also indicate intensifying monoculture with higher percentage of corn plantings for two to four consecutive years during 2000-’10. In addition, crop production is found to have moved away from more heavily sloped land. Cropping does not appear to have increased on lands with higher crop productivity.</span></p>

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Nedd, Ryan, i Aavudai Anandhi. "Land Use Changes in the Southeastern United States: Quantitative Changes, Drivers, and Expected Environmental Impacts". Land 11, nr 12 (9.12.2022): 2246. http://dx.doi.org/10.3390/land11122246.

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Land use change analysis provides valuable information for landscape monitoring, managing, and prioritizing large area conservation practices. There has been significant interest in the southeastern United States (SEUS) due to substantial land change from various economic activities since the 1940s. This study uses quantitative data from the Economic Research Service (ERS) for landscape change analysis, addressing land change among five major land types for twelve states in the SEUS from 1945 to 2012. The study also conducted a literature review using the PSALSAR framework to identify significant drivers related to land type changes from research articles within the region. The analysis showed how each land type changed over the period for each state in the time period and the percentage change for the primary drivers related to land use change. The literature review identified significant drivers of land use and land cover change (LULCC) within the SEUS. The associated drivers were categorized into natural and artificial drivers, then further subdivided into eight categories related to land type changes in the region. A schematic diagram was developed to show land type changes that impacted environmental changes from various studies in the SEUS. The results concluded that Forest land accounted for 12% change and agricultural land for 20%; population growth in the region is an average of 2.59% annually. It also concluded that the need for research to understand past land use trends, direction and magnitude of land cover changes is essential. Significant drivers such as urban expansion and agriculture are critical to the impending use of land in the region; their impacts are attributed to environmental changes in the region and must be monitored.

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45

Poyatos, Rafael, Jérôme Latron i Pilar Llorens. "Land Use and Land Cover Change After Agricultural Abandonment". Mountain Research and Development 23, nr 4 (listopad 2003): 362–68. http://dx.doi.org/10.1659/0276-4741(2003)023[0362:lualcc]2.0.co;2.

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Anurag, Ankita Saxena i Biswajeet Pradhan. "LAND USE/ LAND COVER CHANGE MODELLING: ISSUES AND CHALLENGES". Journal of Rural Development 37, nr 2 (2.04.2018): 413. http://dx.doi.org/10.25175/jrd/2018/v37/i2/129708.

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47

Mahmood, Rezaul, Roger A. Pielke i Clive A. McAlpine. "Climate-Relevant Land Use and Land Cover Change Policies". Bulletin of the American Meteorological Society 97, nr 2 (1.02.2016): 195–202. http://dx.doi.org/10.1175/bams-d-14-00221.1.

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Abstract Both observational and modeling studies clearly demonstrate that land-use and land-cover change (LULCC) play an important biogeophysical and biogeochemical role in the climate system from the landscape to regional and even continental scales. Without comprehensively considering these impacts, an adequate response to the threats posed by human intervention into the climate system will not be adequate. Public policy plays an important role in shaping local- to national-scale land-use practices. An array of national policies has been developed to influence the nature and spatial extent of LULCC. Observational evidence suggests that these policies, in addition to international trade treaties and protocols, have direct effects on LULCC and thus the climate system. However, these policies, agreements, and protocols fail to adequately recognize these impacts. To make these more effective and thus to minimize climatic impacts, we propose several recommendations: 1) translating international treaties and protocols into national policies and actions to ensure positive climate outcomes; 2) updating international protocols to reflect advancement in climate–LULCC science; 3) continuing to invest in the measurements, databases, reporting, and verification activities associated with LULCC and LULCC-relevant climate monitoring; and 4) reshaping Reducing Emissions from Deforestation and Forest Degradation+ (REDD+) to fully account for the multiscale biogeophysical and biogeochemical impacts of LULCC on the climate system.

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Houghton, R. A., J. I. House, J. Pongratz, G. R. van der Werf, R. S. DeFries, M. C. Hansen, C. Le Quéré i N. Ramankutty. "Carbon emissions from land use and land-cover change". Biogeosciences 9, nr 12 (13.12.2012): 5125–42. http://dx.doi.org/10.5194/bg-9-5125-2012.

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Abstract. The net flux of carbon from land use and land-cover change (LULCC) accounted for 12.5% of anthropogenic carbon emissions from 1990 to 2010. This net flux is the most uncertain term in the global carbon budget, not only because of uncertainties in rates of deforestation and forestation, but also because of uncertainties in the carbon density of the lands actually undergoing change. Furthermore, there are differences in approaches used to determine the flux that introduce variability into estimates in ways that are difficult to evaluate, and not all analyses consider the same types of management activities. Thirteen recent estimates of net carbon emissions from LULCC are summarized here. In addition to deforestation, all analyses considered changes in the area of agricultural lands (croplands and pastures). Some considered, also, forest management (wood harvest, shifting cultivation). None included emissions from the degradation of tropical peatlands. Means and standard deviations across the thirteen model estimates of annual emissions for the 1980s and 1990s, respectively, are 1.14 ± 0.23 and 1.12 ± 0.25 Pg C yr−1 (1 Pg = 1015 g carbon). Four studies also considered the period 2000–2009, and the mean and standard deviations across these four for the three decades are 1.14 ± 0.39, 1.17 ± 0.32, and 1.10 ± 0.11 Pg C yr−1. For the period 1990–2009 the mean global emissions from LULCC are 1.14 ± 0.18 Pg C yr−1. The standard deviations across model means shown here are smaller than previous estimates of uncertainty as they do not account for the errors that result from data uncertainty and from an incomplete understanding of all the processes affecting the net flux of carbon from LULCC. Although these errors have not been systematically evaluated, based on partial analyses available in the literature and expert opinion, they are estimated to be on the order of ± 0.5 Pg C yr−1.

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Morris, Joe. "Agricultural land drainage, land use change and economic performance". Land Use Policy 9, nr 3 (lipiec 1992): 185–98. http://dx.doi.org/10.1016/0264-8377(92)90042-u.

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Rakhmonov, Sherzod, Uktam Umurzakov, Kosimdjon Rakhmonov, Iqbol Bozarov i Ozodbek Karamatov. "Land Use and Land Cover Change in Khorezm, Uzbekistan". E3S Web of Conferences 227 (2021): 01002. http://dx.doi.org/10.1051/e3sconf/202122701002.

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This article depicts on discussions about land use and land cover change distribution in Khorezm province, Uzbekistan between 1987 and 2019. For the study Landsat 5 TM and Landsat 8 OLI respectively used to detect land use changes in the study area. Khorezm region affected by Aral Sea shrinkage having received salt wind from northeast of the region. Moreover, population increased within study period, making population density intense. Research is carried out to detect reflection of ecology and density in land use. RS techniques maximum likelihood employed to classify land use to generate land cover distribution map. In total seven class selected such as agricultural land, built up, bare land, lowland, saline land, sand and waterbody. The research of Khorezm region for 32 years has been thoroughly studied and found out that agricultural land, built up and saline land increased tremendously while lowland and bare soil are decreased accordingly. The result map can be used for decision makers and government bodies for future long term urban and regional planning.

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