Hasil untuk "Land use"

S. Rwanga, J. Ndambuki

Remote sensing is one of the tool which is very important for the production of Land use and land cover maps through a process called image classification. For the image classification process to be successfully, several factors should be considered including availability of quality Landsat imagery and secondary data, a precise classification process and user’s experiences and expertise of the procedures. The objective of this research was to classify and map land-use/land-cover of the study area using remote sensing and Geospatial Information System (GIS) techniques. This research includes two sections (1) Landuse/Landcover (LULC) classification and (2) accuracy assessment. In this study supervised classification was performed using Non Parametric Rule. The major LULC classified were agriculture (65.0%), water body (4.0%), and built up areas (18.3%), mixed forest (5.2%), shrubs (7.0%), and Barren/bare land (0.5%). The study had an overall classification accuracy of 81.7% and kappa coefficient (K) of 0.722. The kappa coefficient is rated as substantial and hence the classified image found to be fit for further research. This study present essential source of information whereby planners and decision makers can use to sustainably plan the environment.

A. Malik, J. Puissant, Kate M. Buckeridge et al.

Soil microorganisms act as gatekeepers for soil–atmosphere carbon exchange by balancing the accumulation and release of soil organic matter. However, poor understanding of the mechanisms responsible hinders the development of effective land management strategies to enhance soil carbon storage. Here we empirically test the link between microbial ecophysiological traits and topsoil carbon content across geographically distributed soils and land use contrasts. We discovered distinct pH controls on microbial mechanisms of carbon accumulation. Land use intensification in low-pH soils that increased the pH above a threshold (~6.2) leads to carbon loss through increased decomposition, following alleviation of acid retardation of microbial growth. However, loss of carbon with intensification in near-neutral pH soils was linked to decreased microbial biomass and reduced growth efficiency that was, in turn, related to trade-offs with stress alleviation and resource acquisition. Thus, less-intensive management practices in near-neutral pH soils have more potential for carbon storage through increased microbial growth efficiency, whereas in acidic soils, microbial growth is a bigger constraint on decomposition rates. Land use intensification could modify microbial activity and thus ecosystem function. Here, Malik et al. sample microbes and carbon-related functions across a land use gradient, demonstrating that microbial biomass and carbon use efficiency are reduced in human-impacted near-neutral pH soils.

J. Ning, Jiyuan Liu, W. Kuang et al.

Yan-sui Liu

K. Geurs, B. Wee

Yan-sui Liu, Jintao Li, Yuanyuan Yang

Bo Huang, Bei Zhao, Yimeng Song

Abstract Urban land-use mapping is a significant yet challenging task in the field of remote sensing. Although numerous classification methods have been developed for obtaining land-use information in urban areas, the accuracy and efficiency of these methods are insufficient to meet the requirements of real-world applications such as urban planning and land management. In recent years, deep learning techniques, especially deep convolutional neural networks (DCNN), have achieved an astonishing level of performance in image classification. However, the traditional DCNN methods do not focus on multispectral remote sensing images with more than three channels, and they are limited by their training samples. In addition, these methods uniformly decompose large images into small processing units, which chop up the land-use patterns and produce land-use maps with obvious “blocks”. In this study, a semi-transfer deep convolutional neural network (STDCNN) approach is proposed to overcome these weaknesses. The proposed STDCNN has three parts: one part involves a transferred DCNN with deep architecture; another part is designed to analyze multispectral images; and the final part fuses the first two parts into a classification layer. Moreover, a skeleton-based decomposing method using street block data is devised to maintain the integrity of the land-use patterns. In two case studies, the proposed method is used to generate urban land-use maps from a WorldView-3 image of a 143 km2 area of Hong Kong and a WorldView-2 image of a 25 km2 area of Shenzhen. The results show that the proposed STDCNN obtains an overall accuracy (OA) of 91.25% and a Kappa coefficient (Kappa) of 0.903 for Hong Kong land-use classification, and an OA of 80% and a Kappa of 0.780 for Shenzhen land-use classification. In addition, due to the proposed skeleton-based decomposition method, the proposed method can produce better land-use maps for real-world urban applications.

Yang Bai, T. Ochuodho, Jian Yang

Abstract Policy-makers are interested in knowing the relative importance and combined effects of land use and climate change on ecosystem services. However, knowledge of how to identify these relationships is still lacking. This study aims to provide a comprehensive assessment of water-related ecosystem services and to improve understanding of how they are impacted by land use and climate change in Kentucky, USA. By using InVEST models and environmental setting scenarios, this study first quantifies water-related ecosystem services in a spatially explicit manner. The effects of land use and climate change on these ecosystem services are assessed using two indicators developed in this study. The results show that at the state scale, climate change has a greater impact than land use on water retention, but land use change has a greater impact on soil retention, nitrogen export, and phosphorus export. Climate and land use change have a significant inhibitory effect on water retention, nitrogen export, and phosphorus export. The relative importance and combined influences of land use and climate change also depend on the scale and landscape composition. Unraveling the drivers of ecosystem services in the context of global change can provide critical knowledge for developing practical policy and land management applications.

Wei Liu, J. Zhan, Fen Zhao et al.

Abstract Ecosystem services value has decreased rapidly caused by land use/land cover changes driven by urbanization during the past decades. Expanding urbanization not only changes the spatial distribution of areas of ecosystem service demand but it also changes the potential functions of ecosystem services. It is necessary to undertake a quantitative analysis of historical changes in land use/land cover in the context of the urban land sprawl to better understand existing relationships between ecological services and land use/land cover change. The methodology for this study was derived from an established knowledge base on the importance of land use/land cover types for the supply of each of nine identified ecosystem services extracted from a review of the literature. We selected the Pearl River Delta as the object of our study and used a land-use dataset entailing a resolution of 100 m to analyze the land use/land cover change trends and the values of ecosystem services in this region from 1990 to 2015. Furthermore, we compiled a summary of changes in the values of ecosystem services caused by changes in land use/land cover. We found that the change trend of land use/land cover in the Pearl River Delta, which is dominated by forests, reflected a highly dynamic context. Construction land increased from 2909.77 km2 to 7486.89 km2 over the study period. The total value of ecosystem services increased by 4.5 × 1021 seJ during the period 1990–2015. Individual ecosystem services that contributed the greatest value were hydrological regulation, climate regulation, and soil formation and retention. In light of our findings, we developed a matrix of ecosystem service values in relation to land use transitions and explored its policy implications for ecosystem management. This matrix can help decision makers to better understand tradeoffs between ecosystem services caused by land use/land cover changes.

Yu Junqing, Kaile Zhou, Shanlin Yang

Abstract The rapid urbanization in China has a huge impact on land use. The scarcity of land resources has become a constraint for sustainable urban development. Recently, urban agglomeration (UA) has become a new type of complex urban system. The aim of this paper is to investigate the relationship of land use and UAs’ socio-economic development, and figure out effective land strategies. There are 12 evaluated UAs in our paper, which includes 184 cities. We analyze the land use performance of China’s UAs from different perspectives. We first analyze the decoupling relationship between economic growth and urban land use, and then evaluate land use efficiency of China’s 12 typical UAs. The k-means clustering is used to clarify evaluated UAs into different groups according to their characteristics. Furthermore, the efficiency decomposition, changing trend and comparison of core cities are also described. At last, the tobit regression model is built to verify the main driving factors of land use efficiency from three aspects, including economic level, economic structure and government regulation. The results show that most UAs showed weak decoupling relationship. Average urban land use efficiency of UAs in China was not very high. Furthermore, the average efficiency showed an evident fluctuation in 2008 and 2015. Yangtze River Delta and Pearl River Delta have been on the effective frontier. Based on group analysis, the UAs in central China have more room for efficiency improvement. The significant factors influencing UAs’ land use efficiency included per capita GDP, population density and the degree of market openness. Finally, several targeted strategies are proposed to improve urban land use performance of China’s UAs.

A. Alam, M. S. Bhat, M. Maheen

Land use and land cover (LULC) change has been one of the most immense and perceptible transformations of the earth’s surface. Evaluating LULC change at varied spatial scales is imperative in wide range of perspectives such as environmental conservation, resource management, land use planning, and sustainable development. This work aims to examine the land use and land cover changes in the Kashmir valley between the time periods from 1992–2001–2015 using a set of compatible moderate resolution Landsat satellite imageries. Supervised approach with maximum likelihood classifier was adopted for the classification and generation of LULC maps for the selected time periods. Results reveal that there have been substantial changes in the land use and cover during the chosen time periods. In general, three land use and land cover change patterns were observed in the study area: (1) consistent increase of the area under marshy, built-up, barren, plantation, and shrubs; (2) continuous decrease in agriculture and water; (3) decrease (1992–2001) and increase (2001–2015) in forest and pasture classes. In terms of the area under each LULC category, most significant changes have been observed in agriculture (−), plantation (+), built-up (+), and water (−); however, with reference to percent change within each class, the maximum variability was recorded in built-up (198.45%), plantation (87.98%), pasture (− 71%), water (− 48%) and agriculture (− 28.85%). The massive land transformation is largely driven by anthropogenic actions and has been mostly adverse in nature, giving rise to multiple environmental issues in the ecologically sensitive Kashmir valley.

M. Berihun, A. Tsunekawa, Nigussie Haregeweyn et al.

Abstract This study examined the trends, driving factors, and implications of land use/land cover (LULC) dynamics over the past 35 years (1982–2017) in three watersheds of the drought-prone areas that represent different agro-ecologies of Upper Blue Nile basin, Ethiopia: Guder (highland), Aba Gerima (midland), and Debatie (lowland). The changes in LULC were analyzed by integrating field observations, remote-sensing data (aerial photographs [1: 50,000 scale] and very high resolution [0.5–3.2 m] satellite images), and geographic information systems. The drivers of LULC were explored using key informant interviews and relevant literature reviews. The implications of LULC change on soil erosion and surface runoff responses were also evaluated. A minimum of four and maximum of six LULC classes were identified in each watershed over the study period. The study revealed that forest land was the dominant LULC class accounting for 40.9% and 32.0% in Guder and Aba Gerima, respectively in 1982. While in the same period, bush land (36.6%) was the dominant LULC class in Debatie watershed. From 1982 to 2016/2017, forest land, bush land, and grazing land respectively decreased by about 70%, 50%, and 27% in Guder; 65%, 49%, and 63% in Aba Gerima; and 63%, 59%, and 38% in Debatie. During the same period, cultivated land increased by approximately 40%, 129%, and 704% in Guder, Aba Gerima and Debatie, respectively. In contrast, between 2012 and 2017, plantation cover increased by about 400% in the Guder, mainly at the expense of cultivated land, which decreased by 40% for the same period. Population growth and associated changes in the farming practices were the major driving forces for the observed LULC changes in the study watersheds. The traditionally deleterious impacts of human activities on the environment have been recently reversed at an unprecedented rate, particularly at Guder and to a lesser extent at Aba Gerima, following the shift from the traditional annual cropping to more economically attractive tree-based farming practices such as Acacia decurrens plantation in Guder and khat (Catha edulis) cultivation in Aba Gerima. The continued expansion of cultivated land combined with population growth positively linked to the increase of gully erosion and surface runoff potential in the study watersheds particularly, in Aba Gerima and Debatie watersheds. The Upper Blue Nile basin is currently experiencing both positive and negative socio-economic and environmental consequences of LULC dynamics. Hence, the present study can help form a basis for the appropriate development of land management policies and strategies in this and other basins experiencing similar problems.

T. Gasser, Léa Crepin, Y. Quilcaille et al.

Abstract. Emissions from land use and land cover change are a key component of the global carbon cycle. However, models are required to disentangle these emissions from the land carbon sink, as only the sum of both can be physically observed. Their assessment within the yearly community-wide effort known as the “Global Carbon Budget” remains a major difficulty, because it combines two lines of evidence that are inherently inconsistent: bookkeeping models and dynamic global vegetation models. Here, we propose a unifying approach that relies on a bookkeeping model, which embeds processes and parameters calibrated on dynamic global vegetation models, and the use of an empirical constraint. We estimate that the global CO2 emissions from land use and land cover change were 1.36±0.42 PgC yr−1 (1σ range) on average over the 2009–2018 period and reached a cumulative total of 206±57 PgC over the 1750–2018 period. We also estimate that land cover change induced a global loss of additional sink capacity – that is, a foregone carbon removal, not part of the emissions – of 0.68±0.57 PgC yr−1 and 32±23 PgC over the same periods, respectively. Additionally, we provide a breakdown of our results' uncertainty, including aspects such as the land use and land cover change data sets used as input and the model's biogeochemical parameters. We find that the biogeochemical uncertainty dominates our global and regional estimates with the exception of tropical regions in which the input data dominates. Our analysis further identifies key sources of uncertainty and suggests ways to strengthen the robustness of future Global Carbon Budget estimates.

S. Wang, Belay Manjur Gebru, Munkhnasan Lamchin et al.

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.

Hail Jung, Daejin Kim

We study the effectiveness of textual information in predicting the returns of crude oil futures and understanding the behavior of market participants. Using a machine learning method to extract oil market sentiment from news articles, we find that the computed sentiment is significantly effective in explaining the crude oil futures returns, while existing textual analyses based on pre-defined dictionaries may mislead the contexts in the oil market. Consistent with previous findings that returns help explain the change in traders’ positions, the sentiment scores based on the machine learning method are also useful in explaining the behavior of different types of traders. Our empirical findings underscore the fact that accurately identifying textual information can increase the accuracy of oil price predictions and explain divergent behaviors of oil traders.

Dires Tewabe, Temesgen Fentahun Adametie

Abstract Land use land cover (LULC) change detection based on remote sensing data is an important source of information for various decision support systems. Information derived from land use and land cover change detection is important to land conservation, sustainable development, and management of water resources. This purpose of this study is therefore concerned with identifying the change in land use and land cover detection of the Tana basin. To identify land cover changes detection; remote sensing data, satellite imagery and image processing techniques had done within three dates of 1986, 2002 and 2018 using Land sat TM 30 m resolution images. ENVI and Arc GIS soft wares had used to identify the changes. The classification had done using six land cover (water body, bushland, grassland, forestland, cultivated, and residential land) class. Preprocessing and classification of the images had analyzed carefully and accuracy assessment was tested separately using the kappa coefficient. The results showed that overall accuracy in the basin was 84.21%, 83.32% and 91.40% and kappa coefficient of 79.02%, 83.32%, 89.66% for the years 1986, 2002 and 2018 respectively. This study indicated that in the last 32 years period, agricultural land and residential areas had significantly increased by 15.61% and 8.05% respectively in the basin. Therefore, proper land management practices, integrated watershed management, and active participation of the local community should be advance to protect undesirable LULC change in the basin.

S. B. Asabere, R. Acheampong, George Ashiagbor et al.

Abstract Urbanization induces spatial and environmental changes. Monitoring and understanding the nature of these changes is crucial to achieving sustainable urban development imperatives. To this end, this paper examines the evolution and spatio-environmental impacts of rapid urbanization in two major metropolitan regions of Ghana—Accra-City Region and the Greater Kumasi Sub-Region. The analysis uses Landsat satellite data and landscape metrics to examine land use transitions and to characterize the emergent landscapes over the last three decades. The results show that built-up land has increased significantly in these metropolitan regions largely at the expense of environmental land cover classes. The expansion process follows a general trend where the historical-core zones were initially sites of rapid land cover conversion to built-up, with settlements in the suburban and peripheral zones expanding in recent years and becoming integrated into the conterminous urban areas of the metropolitan regions. The analysis also uncovered a unique, dynamic and complex process whereby the urban-open-space class, being in a permanent state of flux, mediates transitions between built-up land and vegetation and vice versa. The metric-based land use transformation analysis shows that the landscape of the metropolitan regions has fragmented because of an increased expansion and aggregation of patches of built-up land in the core areas and leapfrog, sprawling expansion in the outlying suburban and peripheral zones. The paper concludes on the need for integrative urban growth management strategies that brings together spatial planning and environmental resource governance to avert the negative consequences on the natural environment of unfettered urban expansion.

Caterina Conigliani, Martina Iorio, Salvatore Monni

According to the UN's Sustainable Development Agenda, to effectively achieve sustainable development, strategies for building economic growth should also address social needs, including access to essential services. Sustainable integrated management of water resources for both primary use and energy production is crucial, especially in territories such as the Amazonian State of Pará, where a primary good like fresh water is also the main source of electricity. However, the territorial transformations occurring in Pará over installing new hydroelectric plants have jeopardised local development. This was mainly caused by the top-down approach underlying national strategic projects that have paid little attention to local needs, thus paving the way for detrimental conditions for implementing the UN's 2030 Agenda. This paper aims to analyse the relationship between a municipality's level of development and quality of life and the most relevant key determinants of sustainable development in Pará. To this end, we consider a spatial regression analysis, with particular attention devoted to the role of access to both energy and water. The presence of significant spillover effects implies that providing public services on a geographically broad basis could induce self-reinforcing benefits.

Maria Shams Khakwani, Anam Zafar, Gohar Mahmood et al.

Purpose: The objective of this research is to determine the impact of green manufacturing practices and digital transformation on firm performance, with a particular focus on the mediating role of green product innovation. Design/Methodology/Approach: The study conducted a survey of 212 employees from various businesses using a questionnaire-based method. The data is analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM) to examine the connections between digital transformation, green manufacturing practices, and company performance. The study also investigated the intermediary function of green product innovation in these connections and offered valuable insights into how sustainable practices might enhance corporate performance. Findings: This research indicates that green product innovation plays a vital role in connecting these practices to improved company success. The results suggests that organisations that have used digital transformation technologies are more inclined to foster innovation in environmental friendly goods, so enhancing sustainability and subsequently improving performance. Implications/Originality/Value: The present research contributes to the existing understanding of the impact of digital transformation and green manufacturing techniques on enhancing company performance with a specific emphasis on sustainability. The importance of digital transformation and environmentally-conscious manufacturing methods in improving the sustainability of enterprises is emphasised.

Hualin Xie, Yanwei Zhang, Xiaoji Zeng et al.