Land Patterns Research Articles

Kajian Sistem Agroforestry untuk Mendukung Ketahanan Pangan di KPH Yogyakarta dan di Lahan Masyarakat Desa Sriharjo Bantul

Through the agroforestry farming system, which is able to overcome food problems due to land use change for communities or farmers living in areas around the forest, KPH Yogyakarta provides space for the community to be involved in KPH land management by allocating land to be managed together. The purpose of this study was to determine the same types of plants in the dry season and rainy season, to determine the planting pattern of agroforestry, and to determine the income of the community from agroforestry land. This research was conducted at KPH Yogyakarta and communal forest in Sriharjo Bantul village. The method is purposive sampling which has primary data by structure and composition of vegetation then use SEXI FS program and questionnaires in interviews and secondary data. The research was conducted in February-March 2023. The results showed that three types of crops in RPH Kepek and Pengkol, Bantul. The pattern of agroforestry land in KPH Yogyakarta (RPH Kepek) is alley cropping while the planting pattern in Pengkol, Bantul is random mixture. The income of RPH Kepek’s farmer is Rp 135,046, 729 with a total 10.7 ha and in Pengkol Bantul is Rp 2,382.22 with a total 1.35 ha area.

Direct public engagement of the disaster management agency in Meranti Islands Regency in responding to peatland disasters

Disaster studies are interesting studies that will always require dynamic changes, but local governments must be able to provide good policies. With system replication, disasters are downstream but must be accompanied by upstream problems which become the basis for being resolved early. With the policy of separating government affairs in responding to public problems, between the central government and regional governments, the public administration system will be better. The locus of analysis in this article is the Meranti Islands Regency in Riau Province, where almost more than 70% of its territory is peat area. From 1998 until its peak in 2015, the supporting factors were the climate which caused long droughts, and also the habitual pattern of burning land which caused forest and land fires in peat areas that were difficult to extinguish, resulting in a haze disaster that spread to neighboring countries, namely Malaysia and Singapore. Based on this experience, the regional government replicated the application-based satellite system public service innovation to detect disaster points, with the hope of being more responsive so that it can respond earlier to disasters in Meranti Islands Regency. The Regional Disaster Management Agency (BPBD) of Meranti Islands Regency realizes that geographically it is difficult to reach disaster points in this region because this district consists of several islands and access to reach these areas takes quite a long time.

Hard Landing Pattern Recognition and Precaution With QAR Data by Functional Data Analysis

Hard Landing Pattern Recognition and Precaution With QAR Data by Functional Data Analysis

A Novel Predictive Analysis and Classification of Land Subsidence Vulnerability Mapping based on GIS using Hybrid Optimized Machine Learning Techniques and Computer Vision

Land subsidence is a natural disaster caused by the extraction of the earth's material strength on the surface that causes the earth's surface to settle and sink. Land subsidence can also result in significant financial losses since it causes structural damage and expensive maintenance costs for roads, trains, barriers, pipelines, ground water, oil, natural gas, mines, and buildings. The Geographic Information System (GIS) and Google Earth Platform (GEP) can be used to map this land subsidence. This provides a comprehensive view of land pattern subsidence and its interactions with other geographical elements. It applies to both progressive subsidence caused by fluid extraction (groundwater, oil, or natural gas) and rapid surface subsidence caused by the collapse of an underground mine. Risk mitigation is the most effective way to deal with the experimental model. This research study focuses on the use of Predictive Data Analysis (PDA), a powerful environment in data analytics that provides a set of tools that make it easier to evaluate optimal models. The proposed model makes use of a dataset that includes specific land subsidence circumstances as input. The prediction result is achieved using a hybrid machine learning technique that combines Stochastic Gradient Descent (SGD) with Long Short-Term Memory (LSTM) and is compared to K-Nearest Neighbor (KNN), Generative Adversarial Network (GAN), and Artificial Neural Network (ANN). The proposed system employs LSTM and SGD as optimizers, resulting in a hybrid model that improves accuracy. Among the four algorithms investigated the LSTM-SGD network has the highest accuracy (97%), followed by KNN (96%), GAN (90%), and ANN (89%). Due to their ability to capture complicated nonlinear correlations in data and manage temporal dependencies, optimized hybrid ML models LSTM-SGD and KNN models appear to be particularly well-suited for land subsidence prediction.

Assessment of Soil Fertility Status Using Soil Nutrient Index (SNI) With Special Reference to pH, SOC, Ec, N, P, K and S of Jabalpur Block in Jabalpur District, M.P, India

Soil nutrients are the key factors that influence crop productivity and plant growth. The present study gives information about the soil nutrient status of Jabalpur Block in Jabalpur District, Madhya Pradesh. 30 soil samples were collected from the field at a depth of 0-15 cm. Soil samples were collected using grid sampling techniques and the location of soil sampling sites was determined using GPS. Soil samples were further analysed to determine the soil nutrient index (SNI) using the soil chemical properties such as pH, OC, EC, and soil macronutrients i.e. N, P, K and Sulphur (S), etc. The nutrients are further categorized as low, medium, and high as per the soil nutrient index (NI). The spatial variation of soil nutrient parameters was represented by using the interpolation method in the ArcGIS environment. Based on the fertility measurement, the pH of the Jabalpur block ranges from 7.1 to 7.9, which is indicative of Neutral to alkaline nature, and organic carbon content ranges from 0.7 % to 1.78 %, indicating that the amount of SOC is medium to high along with available N ranging from (90kg/ha to 320kg/ha), available P with (20.16kg/ha to 47.04kg/ha) and available K of (29.12 kg/ha to 118kg/ha). The fertility status of Jabalpur block in this study is primarily constrained by soil pH, as well as N, P, K and S. Therefore, to enrich the soil fertility status of Jabalpur block, proper nutrient management practices, application of different organic manures, suitable cropping pattern and sustainable use of agricultural land are very essential.

Delineating urban growth boundaries by coupling urban interactions and ecological conservation

Urban growth boundaries (UGBs) are efficient tools for controlling disorderly urban expansion/sprawl and ensuring sustainable urban development. Previous studies have delineated UGBs from the perspective of ecological conservation or efficiency improvement and have widely applied them to spatial planning. However, few studies have investigated the role of urban interactions and connections in delineating UGBs, especially in rapidly developing urban agglomerations. Our study proposed a novel framework for UGBs delineation in urban agglomerations by coupling urban interactions and ecological conservation, with two innovative points. First, interurban interactions and connections were quantified to elucidate the transition rules of cellular automata (CA), and ecological conservation was configured as a constraint of the CA model. Second, the hierarchical generalized linear model (HGLM)-CA model was used to simulate the urban land pattern in 2035, and the dilation-erosion algorithm realized the final UGBs. The proposed framework was applied to UGBs delineation in the Changsha-Zhuzhou-Xiangtan (CZX) urban agglomeration, a rapidly developing urban agglomeration in China. Furthermore, a comparison among multi-scenario UGBs shows that urban interactions and connections can accelerate the clustering of urban development, and the delineated UGBs are more practical. Our study highlighted the importance of urban interactions for UGBs delineation in urban agglomerations and evaluated a case of UGBs delineation to validate our appeal.

Phylogeographic characterization of Burkholderia pseudomallei isolated from Bangladesh.

Burkholderia pseudomallei possesses a diverse set of genes which encode a vast array of biological functions reflecting its clinical, ecological and phenotypic diversity. Strain variation is linked to geographic location as well as pattern of land uses. This soil-dwelling Gram-negative pathogen causes melioidosis, a tropical disease endemic in northern Australia and Southeast Asian regions including Bangladesh. Phylogeographic analyses of B. pseudomallei isolates by molecular typing techniques could be used to examine the diversity of this organism as well as to track melioidosis epidemics. In this study, 22 B. pseudomallei isolates, of which 20 clinical and two soil isolates were analyzed, utilizing Real-time PCR assay and multilocus sequence typing (MLST). The sequences were then submitted to PubMLST database for analysis and construction of phylogenetic tree. A total of 12 different sequence types (STs) that includes four novel STs were identified for the first time. Strains having STs 1005, 1007 and 56 were the most widespread STs frequently isolated in Bangladesh. ST 1005, ST 56, ST 1007 and ST 211 have been detected not only in Bangladesh but are also present in many Southeast Asian countries. ST 1005 was detected in both soil and clinical samples of Gazipur. Most prevalent, ST 56 has been previously reported from Myanmar, Thailand, Cambodia and Vietnam, confirming the persistence of the genotype over the entire continent. Further large-scale study is necessary to find out the magnitude of the infection and its different reservoirs in the environment along with phylogeographic association.

An innovative method for measuring the hysteresis effects of soil moisture on meteorological variables at various time scales and climate conditions

ABSTRACTUnderstanding the feedback and reactions of soil moisture to meteorological factors in meteorological-hydrological processes is essential due to the growing importance of soil moisture in energy and water cycles in critical zones. Using soil moisture and meteorological data from 1984 to 2018, based on Mann-Kendall and Sen slope trend, two possible patterns of land–atmosphere interaction were discovered in the Yangtze River Basin (YRB), low soil moisture model with less precipitation and higher evapotranspiration, and high-temperature mode with less soil moisture and less evapotranspiration. To measure the hysteresis between soil moisture and precipitation, temperature, and evapotranspiration, a novel method named Three-Step Method was put out. The lag times were measured at ground stations spread across various climatic zones and timescales. The findings demonstrated that the lag times are generally controlled by the regional climate, with shorter lag times in drier regions. Both long-term and short-term responses were seen in soil moisture to meteorological variables. On a monthly scale, soil moisture correlated positively with precipitation but negatively with temperature and evapotranspiration. On an annual scale, precipitation (temperature, evapotranspiration) lagged by roughly 0 to 2 months in the upper and middle regions and by －2 to －6 months in the lower region of the YRB. The contribution rates of meteorological elements on soil moisture were enhanced by taking lag time into account. This study provides a unique perspective for better understanding climate process forecasts and related drought management by considering the hysteresis of soil moisture on the feedback and responses of climate variables.

EU Outlook for Biomass Flows and Bio‐based Products

SummaryThe Bioeconomy Strategy Action Plan calls for sustainable extraction, processing, and use of biological resources in Europe as a pathway to achieve environmental, social and economic goals. However, the transition towards sustainable food systems within and across countries is diverse due to the existing heterogeneous land patterns and agricultural production structures, the variety of potential industries competing for specific biomass feedstocks, and the national policy frameworks in place. Therefore, it is key for policymakers to understand how biomass is supplied, and how it flows through the economy and is used for alternative purposes. This calls for tools that can monitor and quantitatively analyse these aspects. BioMAT has projected the annual growth rate of the EU bio‐based chemical production from 2018 to 2030 to be four times higher than its fossil‐based counterpart. The associated net‐availability of industrial sugars in 2030 is quite balanced, but excess demands for starch and plant oils will increase to fulfil requirements of a growing bio‐based chemical sector. As a vast amount of biological feedstock for material use originates from non‐EU regions (e.g. palm oil), sustainable sourcing and a better use of biological residues should be emphasised. Scenario analyses are helpful to consider consequences of assessing different technical pathways or policies.

Hume Village and Castle

A three-year community archaeology project was completed on behalf of the Hume Castle Preservation Trust at the village of Hume in the Scottish Borders. The project engaged with over 300 members of the public, providing training and volunteering opportunities in a suite of archaeological skills. The project work focused on Hume Village and its surrounding landscape; in particular Hume Castle and the remains of the former medieval village immediately surrounding it, and the associated kirkyard which housed the former Hume Parish Church. Extensive survey work was completed in the kirkyard and adjacent Glebe, in the grounds of Hume Castle, and at the castle itself. Excavations were completed in the castle grounds, the Glebe, and in the garden of West End Cottage in Hume Village. The results of the survey and excavation works portray the changing settlement pattern and use of land in the village area, particularly highlighting occupation and use of the former buildings surrounding the castle up to 200 years after its destruction. A similar pattern was found in the kirkyard, with continual use of the cemetery over 300 years after the abandonment, and probable destruction, of the former kirk. The results indicate that despite the destruction of its castle and kirk, the village of Hume has persevered, maintaining an important sense of place and memory in the landscape.

Analysis of spatial and temporal changes and driving forces of arable land in the Weibei dry plateau region in China

Arable land is the lifeblood of food production, it is of great significance to promote the protection of arable land and ensure national food security by accurately understanding the change law of cultivated land and its driving mechanism. This study takes the Weibei dry plateau region of China as an example, explores its spatial and temporal change characteristics through the center of gravity shift and land use shift matrix, and couples the geographic probe model to reveal the driving mechanisms affecting arable land change. The results show that in the past 25 years, the total arable land area in the Weibei Dry Plateau Region of China has decreased by 5.58%, and the stability of arable land resources in the whole region has weakened. The center of gravity of arable land shifts to the northeast, and the standard deviation ellipse of arable land mainly undergoes the change process of "increase (1995–2015)-decrease (2015–2020)", and the spatial distribution of arable land tends to be dispersed. In the LISA frequency mapping, the proportion of stable constant and low-frequency areas is as high as 89.58%, and the spatial pattern of cultivated land is relatively stable. Medium and high frequency areas. The transformation mode is mainly "low-low" aggregation, "low–high" aggregation is not significant, and the decline of cultivated land in the study area is more obvious. In the past 25 years, a total of 1017.26 km2 of arable land was converted to construction land. The explanatory power of the influencing factors varies in each period (0.299 to 0.731), with total agricultural machinery power has the strongest explanatory power of 0.694, 0.592, and 0.731, respectively. The interaction between slope and annual average temperature and other factors being the highest, both greater than 0.8. Through the construction of LISA frequency mapping, combined with the center of gravity model and standard deviation ellipse, the spatial evolution trend of regional arable land is more comprehensively and dynamically grasped. By using the geodetector model, the driving mechanism of the changes of arable land is revealed comprehensively, which provides a theoretical basis for the scientific management and effective protection of arable land resources and a basis for decision-making.

Which land cover product provides the most accurate land use land cover map of the Yellow River Basin?

Precise land use land cover (LULC) data are essential for understanding the landscape structure and spatial pattern of land use/cover in the Yellow River Basin (YRB) to regulate scientific and rational territorial spatial planning and support sustainable development. However, differences in the multiple sets of LULC products in portraying the land composition of the YRB limit our understanding of the land cover composition in this region. To address this issue, this study chose five sets of open and high spatiotemporal LULC data in 2020, namely, CLCD, LSV10, ESRI10, CLC_FCS30, and Globeland30, to evaluate the accuracy and consistency of classification in the YRB. Our results show that: (1) The LULC composition of the YRB in 2020 was mapped consistently by the five datasets. Grasslands, croplands, and woodlands constitute the major LULC types, accounting for 96% of the total area of the study area. (2) The correlation coefficients of the LULC types of any two of the five datasets ranged from 0.926 to 0.998, showing high land compositional consistency. However, among the five datasets, there were considerable differences in the areas of a single LULC type. (3) The classification consistencies of croplands, woodlands, grasslands, and water bodies were higher than 60% in any two datasets. The spatial consistencies of grasslands, croplands, and woodlands were higher than those of other LULC types. An area with better consistency can reach more than 50% of the average area of the corresponding land types, but grasslands were mixed with other LULC types in ESRI10 and GLC_FCS30. (4) According to the accuracy assessments, LSV10 data have the highest overall classification accuracy, 79.32%, and the classification accuracy of major land types is also higher than 70%; GLC_FCS30 data have the lowest overall accuracy, 70.14%. Based on these results, LSV10 can more accurately demonstrate LULC than the other four datasets. This study can be used as a reference for selecting land cover data, and it also highlights that the necessary assessments of consistency and accuracy are essential when conducting land use/cover change studies in a specific region.

Spatial Pattern of Large-Scale Agricultural Land and Spatial Heterogeneity of Influencing Factors in the Mountainous Areas of Western China—Wuling Mountains as an Example

The scaling of agricultural land is a trend in land use transformation and is important for modernizing agriculture. Therefore, the reasons for large-scale agricultural land formation should be explored. The spatial distribution of large-scale agricultural land and the factors for its formation vary between different regions. Currently, the exploration of the formation mechanism of large-scale agricultural land from the perspective of heterogeneity is not yet sufficient. Therefore, the main objectives of this article are as follows: first, analyze the spatial pattern characteristics of large-scale agricultural land; second, explore the spatial heterogeneity characteristics of influencing factors from both global and local perspectives; third, explore the mechanism of the formation of large-scale agricultural land from the perspective of heterogeneity. The results indicate the following: (1) The large-scale agricultural land distribution pattern in the Wuling Mountains area was high in the east and low in the west. (2) Natural conditions, production factors, and location conditions all significantly impacted large-scale agricultural land, but with differences in their degree of influence. From a local perspective, the influences of various factors in different regions also exhibited spatial heterogeneity. These two types of heterogeneity can be attributed to the differences in regional development stages. (3) Natural conditions, location conditions, and production factors had negative, positive, and positive effects on the agricultural land scale, respectively, but the influence of the first two decreased with the improvement in the regional development stages. The influence of different factors on production factors was related to the regional development stage, and production factors that were suitable for the regional development stage had a greater impact. The conclusion can provide differentiated policy support for regional land use in practice.

The super-environmental effect of the westward shift of China’s cultivated land patterns

The super-environmental effect of the westward shift of China’s cultivated land patterns

Combining spatiotemporal interactions of ecosystem services with land patterns and processes can benefit sensible landscape management in dryland regions

The study of land-use patterns and transitions has extended its influence into multiple ecosystem services (ESs) and their relationships, the integration of which can offer an opportunity to enhance the credibility of ES assessments in spatial landscape planning and management. However, it is not clear whether actual trade-offs/synergies are consistent at different spatial and temporal scales and have similar responses to land use/land cover (LULC). In this study, based on ecological zoning, we simulated three typical ESs (soil retention, water yield and carbon sequestration) and their correlations in the Loess Plateau of China. Furthermore, the spatial relationships among ESs and LULC patterns and the temporal relationships among ESs and LULC transfer were discussed to identify possible implications for future land-use management. The results showed that there were obvious trade-offs or synergies at the spatial scale, and most synergetic relationships among the three ESs weakened during 2000–2020. However, unstable values are approximately 0 at the temporal scale, so the relationship using “space-for-time” approach exaggerates the temporal coupling among ESs. Most spatial ES interactions decreased with increasing ratio of forest and grassland, which deserves more attention in ecological restoration. It is indispensable to consider both spatial and temporal variations in ES relationships as LULC changes to achieve sustainable development in multiscale landscape planning.

Coupling coordination analysis of industrial mining land, landscape pattern and carbon storage in a mining city: a case study of Ordos, China

Analyzing and optimizing the spatio-temporal characteristics of terrestrial ecosystem carbon storage, as well as examining their coupling and coordination relationships with industrial mining land and landscape pattern, can become a reference in the pursuit of carbon peaking and carbon neutrality for mining cities. This research takes the typical mining city of Ordos as the study target. Based on the LULC, the Multi-objective Planning (MOP) and Patch-generating Land Use Simulation (PLUS) model are used to predict the LULC under the natural development (Q1), ecological protection (Q2) and economic development (Q3) scenarios of 2030, and the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model is used to analyze the dynamics of carbon storage, finally a coupling coordination of industrial mining land, landscape pattern and carbon storage is constructed to investigate the interrelationship between them. The results show: (1) From 2000 to 2020, carbon storage shows an inverted ‘V’ shape of rising and then falling; (2) Compared to carbon storage in 2020, the Q1 demonstrates a decrease, while the Q2 and Q3 demonstrate increases; (3) From 2000 to 2020, the coupling coordination degree decreases, and in the future, Q2 and Q3 show an increase in it relative to the Q1.

Patterns of infringement, risk, and impact driven by coal mining permits in Indonesia

Coal mining is known for its contributions to climate change, but its impacts on the environment and human lives near mine sites are less widely recognised. This study integrates remote sensing, GIS, stakeholder interviews and extensive review of provincial data and documents to identify patterns of infringement, risk and impact driven by coal mining expansion across East Kalimantan, Indonesia. Specifically, we map and analyse patterns of mining concessions, land clearing, water cover, human settlement, and safety risks, and link them with mining governance and regulatory infractions related to coal mining permits. We show that excessive, improper permit granting and insufficient monitoring and oversight have led to deforestation, widespread overlaps of concessions with settlements, extensive boundary and regulatory violations, lacking reclamation, and numerous deaths. As the world’s largest thermal coal exporter, Indonesia’s elevated coal infringements, risks, and impacts translate to supply chain, sustainability, and human rights concerns for global coal markets.

Pengaruh Kearifan Lokal dalam Penilaian Risiko Konstruksi

One of the obstacles to construction work in Papua is delays in implementation due to obstruction byindigenous communities at the project site. Understanding the implementation of construction work in atraditional area, especially those related to local wisdom, is one of the risk knowledge which is the first step inrisk conceptualization and is the aim of this research. A qualitative approach, which will elaborate on socialand cultural meanings to explain one of the phenomena that occurs in the world of construction in Papua, anddescriptive methods, are used in analyzing research data. The characteristics of the traditional territory wherethe project location is located also influence the construction risk value of a project. Based on the topographiccharacteristics of the region, there are four large groups of Papuan indigenous people, so there are differencesin the construction risk values faced according to the socio-cultural characteristics of each traditionalcommunity. Urban areas have a high construction risk and rural areas have a lower risk. The risk value ofconstruction projects in Papua is also influenced by the type of construction project which will be related tothe required land pattern.

The Spatio-Temporal Patterns of Regional Development in Shandong Province of China from 2012 to 2021 Based on Nighttime Light Remote Sensing.

As a major coastal economic province in the east of China, it is of great significance to clarify the temporal and spatial patterns of regional development in Shandong Province in recent years to support regional high-quality development. Nightlight remote sensing data can reveal the spatio-temporal patterns of social and economic activities on a fine pixel scale. We based the nighttime light patterns at three spatial scales in three geographical regions on monthly nighttime light remote sensing data and social statistics. Different cities and different counties in Shandong Province in the last 10 years were studied by using the methods of trend analysis, stability analysis and correlation analysis. The results show that: (1) The nighttime light pattern was generally consistent with the spatial pattern of construction land. The nighttime light intensity of most urban, built-up areas showed an increasing trend, while the old urban areas of Qingdao and Yantai showed a weakening trend. (2) At the geographical unit scale, the total nighttime light in south-central Shandong was significantly higher than that in eastern and northwest Shandong, while the nighttime light growth rate in northwest Shandong was significantly highest. At the urban scale, Liaocheng had the highest nighttime light growth rate. At the county scale, the nighttime light growth rate of counties with a better economy was lower, while that of counties with a backward economy was higher. (3) The nighttime light growth was significantly correlated with Gross Domestic Product (GDP) and population growth, indicating that regional economic development and population growth were the main causes of nighttime light change.

Urban land patterns can moderate population exposures to climate extremes over the 21st century

Climate change and global urbanization have often been anticipated to increase future population exposure (frequency and intensity) to extreme weather over the coming decades. Here we examine how changes in urban land extent, population, and climate will respectively and collectively affect spatial patterns of future population exposures to climate extremes (including hot days, cold days, heavy rainfalls, and severe thunderstorm environments) across the continental U.S. at the end of the 21st century. Different from common impressions, we find that urban land patterns can sometimes reduce rather than increase population exposures to climate extremes, even heat extremes, and that spatial patterns instead of total quantities of urban land are more influential to population exposures. Our findings lead to preliminary suggestions for embedding long-term climate resilience in urban and regional land-use system designs, and strongly motivate searches for optimal spatial urban land patterns that can robustly moderate population exposures to climate extremes throughout the 21st century.