Research on application of intelligent computation based LUCC model in urbanization process

AN ASSESSMENT OF SPATIAL VARIATION OF LAND SURFACE CHARACTERISTICS OF MINNA, NIGER STATE NIGERIA FOR SUSTAINABLE URBANIZATION USING GEOSPATIAL TECHNIQUES

As one of the last agricultural frontiers of the humid tropics, Amazonia is the largest area of the world currently undergoing frontier settlement. Although the earliest intrusions of foreign populations into Amazonia date from pre-Hispanic times, the large-scale entrance of peasant colonists into the vast region is a recent phenomenon. Much of this movement represents the spontaneous migration of peoples, but governments in the region have also become increasingly interested in opening up and integrating Amazonia to national and international economies. These actions are frequently seen as potential solutions to a number of national problems, including the need to increase agricultural production, correct spatial imbalances in the distribution of population, exploit frontier lands for reasons of national security, and defuse potentially serious political problems resulting from the existing agrarian structure, landlessness, and unemployment. The upper basin of the Amazon in Ecuador, bordering on the eastern slopes of the Andes, is one such area of frontier settlement. Recent decades have witnessed the rapid conversion of these Amazonian forests to agricultural uses through a series of schemes bearing such labels as land development and colonization. Most forest intervention in the region has come at the hands of colonist farmers attempting to establish land claims along transport routes originally constructed to aid in petroleum exploration and exploitation. These are farmers who formerly have made a living in long-established farmlands and who, for various reasons (population pressures, pervasive poverty, maldistribution of farmland, lack of inputs for intensive cultivation, lack of nonagrarian livelihood opportunities, and generally inadequate rural development) have been increasingly squeezed out of their homelands. A marginal person by virtue of his low socioeconomic and political status, the farmer often perceives

Land use, land cover, and climate change impacts are current global challenges that are affecting many sectors, like agricultural production, socio-economic development, water quality, and causing land fragmentation. In developing countries like Uganda, rural areas with high populations dependent on agriculture are the most affected. The development of sustainable management measures requires proper identification of drivers and impacts on the environment and livelihoods of the affected communities. This study applied drivers, pressure, state, impact, and response model in the L. Kyoga basin to determine the drivers and impacts of land use, land cover, and climate change on livelihoods and the environment. The objective of this study was to determine the drivers and impacts of land use, land cover, and climate changes on the environment and livelihoods in the L. Kyoga basin and suggest sustainable mitigation measures. Focus group discussions, key informant interviews, field observations, and literature reviews were used to collect data. Population increase and climate change were the leading drivers, while agriculture and urbanization were the primary pressures, leading to degraded land, wetlands, and forests; loss of soil fertility, hunger, poverty, poor water quality, which are getting worse. The local communities, government, and non-government institutions had responses to impacts, including agrochemicals, restoration, and conservation approaches. Although most responses were at a small/pilot scale level, most responses had promising results. The application of policies and regulations to manage impacts was also found to be weak. Land use, land cover changes, and climate change occur in the L. Kyoga basin with major impacts on land, water, and community livelihoods. With the observed increase in climate change and population growth, drivers and impacts are potentially getting worse. Therefore, it is essential to expand interventions, provide relief, review policies and regulations, and enforce them. The findings are helpful for decisions and policy-makers to design appropriate management options.

The pace of change in land use and cover in Ethiopia depends on three main factors that cause pressure on agriculture land: resettlement programmes, population growth and increasing agricultural investments. Gambella is one of the regions of Ethiopia that attracts large-scale agricultural investments that extensively drive land use and cover changes in the region. The aim of this study is to examine the rate, extent and distribution of various land use and cover changes in Gambella Regional State, Ethiopia, from 1987 to 2017. The analysis is mainly based on Landsat 5 and Sentinel 2A satellite images and fieldwork. Two Landsat Thematic Mapper and a Sentinel 2A image were used for determining the maximum likelihood of land use/cover classification. The results show that farmland decreased by 26 km2 from 1987 to 2000; however, during the last two decades, agricultural land area increased by 599 km2, mainly at the cost of tropical grasslands and forests. We found that areas cultivated by smallholder farmers increased by 9.17% from 1987 to 2000. However, small-scale farm activities decreased by 7% from 2000 to 2017. Areas cultivated by large-scale state farms totalled 202 km2 in 1987; but by 2000, this large-scale state farming had been completely abandoned by the state, and as a result, its land use has decreased to zero. Despite this, in 2017 large-scale farming increased to 746 km2. In addition, Gambella National Park, which is the nation's largest national park and ecosystem, was also largely affected by Land Use and Land Cover changes. The conversion of savannah/tropical grasslands to agricultural farmland has caused varied and extensive environmental degradation to the park. The Land Use and Land Cover changes in the Gambella region are discussed on the basis of underlying socioeconomic factors.

The relationship of land tenure, land use and land cover changes in Lake Victoria basin

Land use and land cover changes (LULCC) as a part of ecosystems has a significant impact on carbon budget. According to IPCC, approximately 23% of carbon was emitted from the human activities in agriculture, forestry and other land use (AFOLU) from 2007 to 2016. However, land cover includes crucial sector for carbon stock, as well. The land cover consists of five categories which are used area, agricultural land, forest, grass, wet land, and barren. Among these categories, forest counts because of its capacity of carbon sequestration. It is essential to manage the land use and land cover changes effectively since it has lots of influences on carbon cycles. Also, the sustainable management of land use and land cover changes could contribute to reducing the carbon emissions such as preventing deforestation and revegetation. Therefore, this study aims at analyzing the frequent land use change region using hot spot analysis in South Korea and North Korea and estimating the carbon emission and removals from land cover changes. First of all, we tracked the land cover changes at 10 years interval from 1980s to 2010s and identified the general trends. The changed area and ratio of each land cover were varied in both countries, but they had similar characteristics which is land cover changes from forest to cropland and from cropland to forest. It occurred for last four decades. To define the which region has been changed, the hot spot analysis was utilized. The change from forest to cropland appeared in southwest region of North Korea, major agriculture land. On the other hand, the transition from agriculture land to forest seemed to be minor, but the distinguished figure was created during the 2000s to 2010s change. The carbon emission was estimated at the hot spot area and these repeated changes led to additional carbon emission. This study would contribute to preventing the land cover changes frequent by defining the region to be managed.

Land use and land cover changes and their driving forces in selected forest reserves in Central Tanzania

Spatial analysis of land use and cover changes: Implications of green legacy initiative on climate action in Upper Awash Basin, Ethiopia

This study was conducted to estimate the land use and land cover (LULC) changes from 1986 to 2016 at Zamora municipality in Venezuela. Landsat 5 TM, Landsat 7 ETM+, and Landsat 8 (OLI/TIRS) images were obtained to evaluate the shoreline dynamics of the Valencia lake and the magnitude of LULC changes. The images were processed and classified through the object-oriented approach in eCognition Developer 8, for collecting ground-truth data was used Google Earth Engine Python API and Excel software for accuracy assessment. ArcGIS 10.4 and QGIS 2.18 were employed for spatial analysis. It was found that scrublands and farmlands experienced important reductions in area, 13029 ha, and 818 ha respectively, whereas forest, built-up, and water bodies classes showed remarkable increments in area, 11792 ha, 1482 ha, and 634 ha correspondingly. The Valencia lake shoreline underwent an upward trend wherein more than 50% of its raising occurred during the last two study years (2003-2016). It was also observed that land use and land cover changes prompted conflicts with other land uses, 337 ha of lands with high potential for crop yields were affected by the lake shoreline increment and built-up areas grow at a rate of 81 ha /yr. for the last two study years (2003-2016) mainly on lands with high potential for agricultural use.

A study coordinated by the MapBiomas project highlighted changes in land use and cover in the Caatinga in the period 1985-2020. To carry out the study, around 150,000 images from Landsat satellites were analyzed , with a resolution of 30 meters, available over a period of 35 years. Annual information was collected on twenty-five land use and land cover classes in the biome. In this post, we will highlight the main results of the study, which mapped the changes in the land cover of the Caatinga , in the last decades.

<p>Land use and landcover change (LU/LC) are important in global change studies because they can transform the local and global environment by developing the biochemical, biochemical and biogeographic properties of the Earth's structure. This paper is intended to develop Hybrid Convolutional Neural Network (HCNN) for land use and land cover changes prediction in Tiruppur Tamilnadu. Initially, the databases are collected from the open-source system. And the image dataset has been pre-processed using the image augmentation technique. Through which the image has been resized and processed for training it with the proposed mode. The resized images are sent to the HCNN for prediction of land cover and land use changes in Tiruppur Tamilnadu. The proposed classifier is a combination of Convolutional Neural Network (CNN) and Remora Optimization Algorithm (ROA). In the CNN, the ROA is utilized to select the hyper parameters to enable efficient prediction in land use and land cover changes. The proposed classifier is implemented in MATLAB and performances is evaluated by performance metrices such as accuracy, precision, recall, sensitivity, F_Measure and Kappa. The proposed methodology is compared with the conventional techniques such as CNN, Markov chain model and Recurrent Neural Network (RNN) respectively.</p>

The Amazon and the Atlantic Forest are Brazilian biomes that have undergone intense land use and cover changes, marked by the loss of native forest and the expansion of agriculture and livestock. These are areas with potential use for intensification based on low-carbon technologies, but this change is still taking place slowly. Some factors need to be identified to guide promising solutions for this issue. Aiming at this, this study aimed to identify the land use and land cover in a historical series of 35 years in the Amazon and Atlantic Forest and describe the patterns of sustainable land use by producers who use this technique in the Amazon, identifying their characteristics and perceptions regarding the change developed in the farm. The statistics of the platform from the Annual Mapping Project for Land Use and Land Cover in Brazil (MapBiomas) were used in an annual historical series from 1985 to 2020. The analysis of land use and land cover changes indicates that the native forest of the Amazon was reduced by 44.53 million hectares (Mha), while pastures, agriculture and planted forest increased by 38.10, 6.06 and 0.26 Mha, respectively, over the 35 years. In the Atlantic Forest, for the same period, forest and pasture reduced by 0.99 and 11.53 Mha, respectively, while agriculture expanded by 8.06 Mha and planted forest by 2.99 Mha. Sustainable land use strategies, such as Integrated Crop-Livestock-Forest (ICLF) or Agroforestry Systems (AFS), can support increased agricultural production while recovering and preserving the environment. In view of this, we identified in the Amazon, the pattern of land use by farmers who adopt sustainable technologies, considering AFS and managed pasture monoculture (MP). The results were generated through interviews and analysis of qualitative and quantitative research that allowed the evaluation of producers in three states in the Amazon (Mato Grosso, Pará and Rondônia). In general, farmers in the Amazon are still risk averse and mainly implement MP. But when assessing the states in isolation, we realize that the producers in Pará and Rondônia are more approachable when it comes to moving to a diversified system. We did not find many differences in the profile of these producers, but we noticed that pasture adopters always have areas of larger properties and generally develop livestock as their main economic activity. On the other hand, AFS producers have smaller areas of property, conserve more forest and may have agriculture as the main activity of the property. Regional and local fitness, producer tradition and technology transfer can influence the decision of the adopted technology. There are great opportunities to improve agricultural and livestock practices with MP systems and AFS, demonstrated through improvements in farm income, productivity and environment. This evidence can be extrapolated to land use in the Atlantic Forest biome. However, we emphasize the need to consider regional characteristics, socioeconomic conditions and the perspectives of producers in the development of public policies and programs to encourage sustainable agriculture. Keywords: Sustainable Development. Agroforestry System. Crop-Livestock-Forestry Integration. Rural Producer.

Kubu Raya Regency is one of the areas that has a peat ecosystem in it. The peat ecosystem has a role and function in mitigating climate change because it has the ability to store quite high carbon reserves. However, peat ecosystems often experience degradation and changes in land cover which can contribute carbon emissions to the atmosphere. Remote sensing is a technology that can be used to detect changes in land cover and use in Kubu Raya Regency. Therefore, this research aims to detect changes in land cover and using remote sensing technology and assess the level of accuracy of the detection results. Analysis of changes in land cover and use from 2000 - 2023 was obtained by guided classification using the Random Forest (RF) algorithm which involves various vegetation, water and built-up land indices. The research results show that there is a decrease in forest land area from 2000 to 2023 amounting to 106,542 ha. The forest area in 2000 was 524,359 ha, while in 2023 it will be 417,817 ha. The results of accuracy measurements show an overall accuracy (OA) value of 98.84% with a kappa statistic of 0.98. It is hoped that the results of these findings will provide an initial picture of the condition of the ecosystem in Kubu Raya Regency, most of which is a peat ecosystem, as a consideration in formulating peat ecosystem conservation policies.

Current estimates of land cover and land use are important aspects in understanding the flux of material and energy from terrestrial ecosystems into hydrological and atmospheric components of the earth system. These land use characteristics define the various dimensions of human impacts on ecosystem processes and resource use. The recent availability of global remote sensing data and agricultural census data from various regions of the world, including portions of Asia such as China and Mongolia, now makes it feasible to evaluate differences in the physical environment and land use patterns affecting land cover and land use changes. In addition, recent research involving transects studies along gradients of climate, soil, and land use intensity has been carried out during the past decade to allow more careful regional comparisons. Using the analysis of the Mongolian-North East China Transect (NECT), we can estimate the effect of land cover differences on ecosystem dynamics. The 30 m-Thematic Mapper data provides a way to identify fine scale features of the regional landscape patterns which are not captured by the 1-km AVHRR data. The focus of this paper is to evaluate the scale of land use and cover changes in the Asian region and the biogeochemical implications of these changes. The estimates of land cover and land use can vary depending on the spatial scale of the features represented across the land surface. Both physical and social factors influence the spatial extent these features represent. Therefore, the scale of land use intensification can affect the accuracy of land use area estimations. In particular, those regions of the world where land use practices are implemented via small individual holdings may be underestimated when using coarse scale remote sensing data such as AVHRR, where as the Thematic Mapper satellite data at 30 to 50 m resolution can provide a better estimate of land cover and land use area. The accuracy of the extrapolated fluxes of ecosystem dynamics and biogeochemical cycles are directly proportional to the accuracy associated with the land estimates. We will evaluate the land cover estimates in this region of Asia using these data sources. This region encompasses a broad set of precipitation and temperature regimes and includes characteristics of regional land cover and land use related to grazing systems and grain cultivation.

The usage of land use and land cover change information has significantly risen as a result of the requirement for relevant data for environmental monitoring, modeling, and planning. The main objective of the study is to analyze the trend of land use and land cover dynamics in Sheka biosphere reserve: A Case of Shato Core Area, Southwest Ethiopia. To map the land use and land cover, supervised classifications were used, and an accuracy evaluation was conducted. Information on the trend of land use and land cover change was obtained using the IDRISI software’s land change modeler. Results showed that about 308.29ha (56.7%) of wetland and 3,215.6ha (19.6%) of natural forest were converted to other land use types in the last 30 years. Plantation and rural settlement increased by 2,234.3ha (10.2%) and 1289.6ha (6.6%) respectively from 1991–2021. Sheka biosphere reserve was registered with UNESCO in 2012 and Shato is one of the core areas. It covers 5023.3ha (25.5%) of the study area. However, 1482ha (7.5%) were given to coffee plantations, and currently, only 3,541ha (18%) are left. The main drivers of land cover changes were attributed to large-scale agricultural intensification and its induced expansions of rural settlements in and around the Shato core area. The overall accuracy and kappa statistics for 1991, 2006, and 2021 were 74% (0.74), 81% (0.81), and 81.2% (0.812), respectively. Thus, land use and land cover change trend mapping and analysis play a crucial role in conservation planning and habitat monitoring. The study concluded that wetland and forestland conversions in the study area are decreasing overwhelmingly and need serious intervention mechanisms to tackle the loss of biodiversity in the Shato core area.