Urban Form Dynamics and Modelling towards Sustainable Hinterland Development in North Cianjur, Jakarta–Bandung Mega-Urban Region

The urban form is the physical configuration of a city, developed over time and space. Urban form can be considered at different scales, from region to neighborhood, each carrying a different focus. North Cianjur serves as the hinterland and one of the conurbation corridors of the Jakarta–Bandung Mega-Urban Region, meaning that the balance between its function as an environmental buffer area and the destination of urban growth needs to be planned carefully. This paper explores the dynamics in North Cianjur and employs several model scenarios as a planning intervention using landscape dynamic tools and land-change modeling, with three scenarios employed: Business as Usual (BAU), Spatial Planning Policy (SPP), and Urban Containment (UCT). The result show that North Cianjur has transformed into a polycentric region with two urban zones, a peri-urban zone, and a rural zone in the northernmost part of the region. Urban form trends show a sprawling built-up pattern outside urban zones, and a compacted trend in urban zones due to expansion from the Jakarta and Bandung Metropolitan Area. UCT models appear to be the most optimal for implementation in North Cianjur, representing a way to accommodate urban growth and expansion inside the urban center while still maintaining regional sustainability.

Long-Term Changes in Cork Oak and Holm Oak Patches Connectivity. The Algarve, Portugal, a Mediterranean Landscape Case Study

Structural connectivity can be inferred by several landscape metrics that appear to be relevant for characterizing how landscapes constrain or favor the presence and movement of animal species at the level of the regional landscape. Trends of change can be estimated trough spatial time-series analysis. The use of historical maps increases the time span of analysis of the landscape dynamic, relative to the use of remote sensing-related information. Supported by GIS, in this study, a framework for the analyses of the long-term trends of change in the connectivity of the Algarve regional landscape was used to seize the possibility of expanding the span of the spatial time series by integrating an unpublished agricultural and forest map from the turn of the 19th to the 20th century with another historical map and two recent maps. The total area covered by cork and holm oak-related community patches and their connectivity increased over the 20th century and stabilized in the 21st century. A reflection on Portuguese contemporary land-cover policies is urged, to face the sustainable planning and management challenges concerning biodiversity.

Landscape dynamic network biomarker analysis reveals the tipping point of transcriptome reprogramming to prevent skin photodamage

Skin, as the outmost layer of human body, is frequently exposed to environmental stressors including pollutants and ultraviolet (UV), which could lead to skin disorders. Generally, skin response process to ultraviolet B (UVB) irradiation is a nonlinear dynamic process, with unknown underlying molecular mechanism of critical transition. Here, the landscape dynamic network biomarker (l-DNB) analysis of time series transcriptome data on 3D skin model was conducted to reveal the complicated process of skin response to UV irradiation at both molecular and network levels. The advanced l-DNB analysis approach showed that: (i) there was a tipping point before critical transition state during pigmentation process, validated by 3D skin model; (ii) 13 core DNB genes were identified to detect the tipping point as a network biomarker, supported by computational assessment; (iii) core DNB genes such as COL7A1 and CTNNB1 can effectively predict skin lightening, validated by independent human skin data. Overall, this study provides new insights for skin response to repetitive UVB irradiation, including dynamic pathway pattern, bi-phasic response, and DNBs for skin lightening change, and enables us to further understand the skin resilience process after external stress.

Understanding Spatio-Temporal Patterns of Land Use/Land Cover Change under Urbanization in Wuhan, China, 2000–2019

Exploring land use structure and dynamics is critical for urban planning and management. This study attempts to understand the Wuhan development mode since the beginning of the 21st century by profoundly investigating the spatio-temporal patterns of land use/land cover (LULC) change under urbanization in Wuhan, China, from 2000 to 2019, based on continuous time series mapping using Landsat observations with a support vector machine. The results indicated rapid urbanization, with large LULC changes triggered. The built-up area increased by 982.66 km2 (228%) at the expense of a reduction of 717.14 km2 (12%) for cropland, which threatens food security to some degree. In addition, the natural habitat shrank to some extent, with reductions of 182.52 km2, 23.92 km2 and 64.95 km2 for water, forest and grassland, respectively. Generally, Wuhan experienced a typical urbanization course that first sped up, then slowed down and then accelerated again, with an obvious internal imbalance between the 13 administrative districts. Hanyang, Hongshan and Dongxihu specifically presented more significant land dynamicity, with Hanyang being the active center. Over the past 19 years, Wuhan mainly developed toward the east and south, with the urban gravity center transferred from the northwest to the southeast of Jiang’an district. Lastly, based on the predicted land allocation of Wuhan in 2029 by the patch-generating land use simulation (PLUS) model, the future landscape dynamic pattern was further explored, and the result shows a rise in the northern suburbs, which provides meaningful guidance for urban planners and managers to promote urban sustainability.

Modelling soil organic matter at long-time and landscape scales.

<p>Understanding and simulating the soil organic matter had become a key challenge to better predict the landscape dynamic and its evolution. Although numerical modelling developments already integrate soil organic matter to improve agricultural practices at field or plot scales, additional work needs to be carried out to describe the landscape evolution over hundreds to thousands of years.</p><p>We aim to identify and quantify the processes associated to organic matter cycle that take part in landscape long-term evolution. We complete a reference sediment transport model designed for large scale evolution by adding some physical considerations relative to organic matter behaviour. The main developments concern:</p><ul><li> Organic matter productivity and its export to soils</li> <li> Organic matter evolution and degradation along soil profile and during transport</li> <li> Rock and regolith compartments with different lithologies and compositions</li> <li> Weathering and erosion</li> </ul><p>In this presentation, we explore the strengths and limits of this model designed to address a wide variety of questions in various settings. We also discuss the results and assess the validity of this approach considering availability of long-term sedimentary records.</p>

Identifying pre-outbreak signals of hand, foot and mouth disease based on landscape dynamic network marker

Background The high incidence, seasonal pattern and frequent outbreaks of hand, foot and mouth disease (HFMD) represent a threat for billions of children around the world. Detecting pre-outbreak signals of HFMD facilitates the timely implementation of appropriate control measures. However, real-time prediction of HFMD outbreaks is usually challenging because of its complexity intertwining both biological systems and social systems. Results By mining the dynamical information from city networks and horizontal high-dimensional data, we developed the landscape dynamic network marker (L-DNM) method to detect pre-outbreak signals prior to the catastrophic transition into HFMD outbreaks. In addition, we set up multi-level early warnings to achieve the purpose of distinguishing the outbreak scale. Specifically, we collected the historical information of clinic visits caused by HFMD infection between years 2009 and 2018 respectively from public records of Tokyo, Hokkaido, and Osaka, Japan. When applied to the city networks we modelled, our method successfully identified pre-outbreak signals in an average 5 weeks ahead of the HFMD outbreak. Moreover, from the performance comparisons with other methods, it is seen that the L-DNM based system performs better when given only the records of clinic visits. Conclusions The study on the dynamical changes of clinic visits in local district networks reveals the dynamic or landscapes of HFMD spread at the network level. Moreover, the results of this study can be used as quantitative references for disease control during the HFMD outbreak seasons.

DINAMIKA LANSKAP KABUPATEN KETAPANG DAN KABUPATEN KAYONG UTARA TERHADAP PERUBAHAN INDEKS PEMBANGUNAN MANUSIA

The paper describes a landscape dynamic (Change Index-CI) of Ketapang and Kayong Utara Districs, West Kalimantan, in 1990-2018 and its correlation of peoples’ welfare condition and environmental condition change. Land-based investment has increased sharply in the past 20 years. This condition influences landscape dynamic and climate condition. CI is identified through spatial and temporal analysis by calculating human intervention level to land cover. Meanwhile, the condition of peoples’ welfare at sub-district level is measured from the district’s Human Development Index (HDI) which is analyzed from CI. In this analysis, the HDI is considered a dependent variable and CI level as the independent variable. Landscape environmental condition uses information on annual average temperature of landscape. The study applies simple regression method for the 2000, 2010 and 2018 HDIs with the CI of 1990-2000, 2000-2001 and 2010-2018 periods in 26 sub-districts. The results show that CI has positive correlation with the HDI of 0.086 regression coefficient value. It implies that there is significant correlation of the HDI and CI. The higher the CI value, the higher the HDI will increase. Thus, the regression result is the HDI = 60.103+0.086CI, with <0.05 value (significant). It means every growth by 1% at each sub-district, it will lead the rise of HDI by 0.086% at that sub-district. Meanwhile, the average of annual landscape temperature ascends along the growing CI. The temperature increases significantly by 0.95oC during 1990-2018 periods following the massive land-based investment. On the other hand, prior to the massive land-based investment during 1985-1990, the temperature increase was 0.32oC. Keywords: Change Index, Environmental Condition, Oil Palm, Spatial, Temperature, Welfare AbstrakJurnal ini menggambarkan dinamika lanskap (Change Index – CI) Kabupaten Ketapang dan Kabupaten Kayong Utara, Provinsi Kalimantan Barat pada periode 1990 – 2018 kaitannya dengan kesejahteraan masyarakat dan perubahan kondisi lingkungan. Investasi berbasis lahan mengalami peningkatan secara signifikan dalam 20 tahun terakhir. Kondisi ini mempengaruhi dinamika lanskap dan kondisi iklim. CI dapat diidentifikasi dengan memperhitungkan tekanan manusia terhadap tutupan lahan baik secara spasial dan temporal. Sementara itu, kondisi kesejahteraan masyarakat pada wilayah administrasi kecamatan dihitung dihitung dari Indeks Pembangunan Manusia (IPM) wilayah Kabupaten yang dihasilkan dari analisis menggunakan CI. Pada Analisis ini, IPM merupakan variabel terikat dan indek CI merupakan variabel bebas. Kondisi lingkungan landskap menggunakan informasi suhu rata-rata tahunan.Penelitian ini menggunakan metode regresi sederhana antara nilai IPM tahun 2000, 2010, dan 2018 dengan CI periode tahun 1990-2000, 2000-2001, dan 2010-2018 pada 26 wilayah kecamatan. Hasilnya menunjukkan korelasi positif dengan nilai koefisien regresi IPM sebesar 0.086. Ini berarti bahwa terdapat korelasi signifikan antara IPM dan CI. Kenaikan nilai CI akan meningkatkan nilai IPM. Sehingga, regresi yang dihasilkan adalah IPM = 60.103+0.086CI, dengan nilai <0.05 yang berarti bahwa korelasinya sangat signifikan. Hal ini berarti bahwa setiap kenaikan CI sebesar 1% pada setiap kecamatan, maka ini akan meningkatkan nilai IPM sebesar 0.086% pada kecamatan tersebut. Sementara itu, suhu rata-rata tahunan pada lanskap mengalami kenaikan selama adanya peningkatan CI. Suhu pada lanskap meningkat drastis sebesar 0.95oC selama periode 1990-2018, hal ini sejalan dengan investasi berbasis lahan mengalami peningkatan secara massif. Sementara itu, sebelum investasi berbasis lahan dilakukan secara massif pada periode 1985-1990, kenaikan suhu sebesar 0.31oCKata kunci: Change Index, Kelapa Sawit, Kesejahteraan, Kondisi lingkungan, Suhu, Spasial

Personalized Early-Warning Signals during Progression of Human Coronary Atherosclerosis by Landscape Dynamic Network Biomarker

Coronary atherosclerosis is one of the major factors causing cardiovascular diseases. However, identifying the tipping point (predisease state of disease) and detecting early-warning signals of human coronary atherosclerosis for individual patients are still great challenges. The landscape dynamic network biomarkers (l-DNB) methodology is based on the theory of dynamic network biomarkers (DNBs), and can use only one-sample omics data to identify the tipping point of complex diseases, such as coronary atherosclerosis. Based on the l-DNB methodology, by using the metabolomics data of plasma of patients with coronary atherosclerosis at different stages, we accurately detected the early-warning signals of each patient. Moreover, we also discovered a group of dynamic network biomarkers (DNBs) which play key roles in driving the progression of the disease. Our study provides a new insight into the individualized early diagnosis of coronary atherosclerosis and may contribute to the development of personalized medicine.