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  • 1
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    Modeling the Impact of Investment and National Planning Policies on Future Land Use Development: A Case Study for Myanmar
    MDPI AG ; 2023
    In:  ISPRS International Journal of Geo-Information Vol. 12, No. 1 ( 2023-01-13), p. 22-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 12, No. 1 ( 2023-01-13), p. 22-
    Abstract: Land use change (LUC) can be affected by investment growth and planning policies under the context of regional economic cooperation and development. Previous studies on land use simulation mostly emphasized the effects of local socioeconomic factors and planning constraint areas that prevent land conversions. However, investment and national planning policies that trigger regional LUC were often ignored. This study aims to couple the economic theory-based Computable General Equilibrium of Land Use Change (CGELUC) model and the cellular automata-based Future Land Use Simulation (FLUS) model to incorporate macroscopic impacts of investment into land use simulation, while proposing an updated mechanism that integrates into the FLUS model to consider the local impacts of planning policies. Taking Myanmar as a case, the method was applied to project the land use patterns (LUPs) during 2017–2050 under three scenarios: baseline, fast, and harmonious development. Specifically, the simulated land use structure (LUS) in 2018 acquired by the CGELUC model was verified by the existing data, and the future LUSs under different scenarios were projected later. Simultaneously, the consistencies between the results simulated by the FLUS model and land use maps in 2013, 2015, and 2017 were represented by the kappa coefficient. The updated mechanism was applied to update the Probability-of-Occurrence (PoO) surfaces based on the planning railway networks and special economic zone. Lastly, the LUPs under different scenarios were projected based on the future LUSs and updated PoO surfaces. Results reveal that the validation accuracy reaches 96.87% for the simulated LUS, and satisfactory accuracies of the simulated LUPs are obtained (kappa coefficients 〉 0.83). The updated mechanism increases the mean PoO values of built-up land in areas affected by planning policies (increasing by 0.01 to 0.21), indicating the importance of the planning policies in simulation. The cultivated land and built-up land increase with investment increasing under all three scenarios. The harmonious development scenario, showing the least forest encroachment and the highest diversity of LUP, is the optimal approach to achieve land sustainability. This study highlights the impacts of investment and planning policies on future LUCs of Myanmar, and a dynamic simulation process is expected to minimize the uncertainties of the input data and model in the future work.
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi12010022
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2655790-3
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  • 2
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    Land Cover Mapping in Southwestern China Using the HC-MMK Approach
    MDPI AG ; 2016
    In:  Remote Sensing Vol. 8, No. 4 ( 2016-04-07), p. 305-
    Details
    In: Remote Sensing, MDPI AG, Vol. 8, No. 4 ( 2016-04-07), p. 305-
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs8040305
    Language: English
    Publisher: MDPI AG
    Publication Date: 2016
    detail.hit.zdb_id: 2513863-7
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  • 3
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    Estimation of Vegetation Leaf-Area-Index Dynamics from Multiple Satellite Products through Deep-Learning Method
    MDPI AG ; 2022
    In:  Remote Sensing Vol. 14, No. 19 ( 2022-09-22), p. 4733-
    Details
    In: Remote Sensing, MDPI AG, Vol. 14, No. 19 ( 2022-09-22), p. 4733-
    Abstract: A high-quality leaf-area index (LAI) is important for land surface process modeling and vegetation growth monitoring. Although multiple satellite LAI products have been generated, they usually show spatio-temporal discontinuities and are sometimes inconsistent with vegetation growth patterns. A deep-learning model was proposed to retrieve time-series LAIs from multiple satellite data in this paper. The fusion of three global LAI products (i.e., VIIRS, GLASS, and MODIS LAI) was first carried out through a double logistic function (DLF). Then, the DLF LAI, together with MODIS reflectance (MOD09A1) data, served as the training samples of the deep-learning long short-term memory (LSTM) model for the sequential LAI estimations. In addition, the LSTM models trained by a single LAI product were considered as indirect references for the further evaluation of our proposed approach. The validation results showed that our proposed LSTMfusion LAI provided the best performance (R2 = 0.83, RMSE = 0.82) when compared to LSTMGLASS (R2 = 0.79, RMSE = 0.93), LSTMMODIS (R2 = 0.78, RMSE = 1.25), LSTMVIIRS (R2 = 0.70, RMSE = 0.94), GLASS (R2 = 0.68, RMSE = 1.05), MODIS (R2 = 0.26, RMSE = 1.75), VIIRS (R2 = 0.44, RMSE = 1.37) and DLF LAI (R2 = 0.67, RMSE = 0.98). A temporal comparison among LSTMfusion and three LAI products demonstrated that the LSTMfusion model efficiently generated a time-series LAI that was smoother and more continuous than the VIIRS and MODIS LAIs. At the crop peak growth stage, the LSTMfusion LAI values were closer to the reference maps than the GLASS LAI. Furthermore, our proposed method was proved to be effective and robust in maintaining the spatio-temporal continuity of the LAI when noisy reflectance data were used as the LSTM input. These findings highlighted that the DLF method helped to enhance the quality of the original satellite products, and the LSTM model trained by the coupled satellite products can provide reliable and robust estimations of the time-series LAI.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs14194733
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
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  • 4
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    A Cost-Constrained Sampling Strategy in Support of LAI Product Validation in Mountainous Areas
    MDPI AG ; 2016
    In:  Remote Sensing Vol. 8, No. 9 ( 2016-08-26), p. 704-
    Details
    In: Remote Sensing, MDPI AG, Vol. 8, No. 9 ( 2016-08-26), p. 704-
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs8090704
    Language: English
    Publisher: MDPI AG
    Publication Date: 2016
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  • 5
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    Comprehensive Assessment of Performances of Long Time-Series LAI, FVC and GPP Products over Mountainous Areas: A Case Study in the Three-River Source Region, China
    MDPI AG ; 2021
    In:  Remote Sensing Vol. 14, No. 1 ( 2021-12-23), p. 61-
    Details
    In: Remote Sensing, MDPI AG, Vol. 14, No. 1 ( 2021-12-23), p. 61-
    Abstract: Vegetation biophysical products offer unique opportunities to examine long-term vegetation dynamics and land surface phenology (LSP). It is important to understand the time-series performances of various global biophysical products for global change research. However, few endeavors have been dedicated to assessing the performances of long-term change characteristics or LSP extraction derived from different satellite products, especially in mountainous areas with highly fragmented and rugged surfaces. In this paper, we assessed the time-series characteristics and LSP detections of Global LAnd Surface Satellite (GLASS) leaf area index (LAI), fractional vegetation cover (FVC), and gross primary production (GPP) products across the Three-River Source Region (TRSR). The performances of products’ temporal agreements and their statistical relationship as a function of topographic indices and heterogeneous pixels, respectively, were investigated through intercomparison among three products during the period 2000 to 2018. The results show that the phenological differences between FVC and two other products are beyond 10 days over more than 35% of the pixels in TRSR. The long-term trend of FVC diverges significantly from GPP and LAI for 13.96% of the total pixels, and the percentages of mismatched pixels between FVC and two other products are 33.24% in the correlation comparison. Moreover, good agreements are observed between GPP and LAI, both in terms of LSP and interannual variations. Finally, the LSP and long-term dynamics of the three products exhibit poor performances on heterogeneous surfaces and complex topographic areas, which reflects the potential impacts of environmental factors and algorithmic imperfections on the quality and performances of different products. Our study highlights the spatiotemporal disparities in detections of surface vegetation activity in mountainous areas by using different biophysical products. Future global change studies may require multiple high-quality satellite products with long-term stability as data support.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs14010061
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
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  • 6
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    Investigating Eco-Environmental Vulnerability for China–Pakistan Economic Corridor Key Sector Punjab Using Multi-Sources Geo-Information
    MDPI AG ; 2021
    In:  ISPRS International Journal of Geo-Information Vol. 10, No. 9 ( 2021-09-17), p. 625-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 10, No. 9 ( 2021-09-17), p. 625-
    Abstract: China-Pakistan economic corridor (CPEC), a critical part of the Belt and Road initiative (BRI), is subjected to rapid infrastructure development, which may lead to potential eco-environmental vulnerability. This study uses multi-source geo-information, and the multi-criteria decision-making (MCDM)-based best–worst method (BWM) to quantify the baseline eco-environmental vulnerability of one key CPEC sector—the Punjab province. The Punjab province is an important connection between northern and southern CPEC routes in Pakistan. In this study, we have established an indicator system consisting of twenty-two influential factors in a geospatial database to conduct eco-environmental vulnerability analysis. The overall setup is supported by a geographic information system (GIS) to perform spatial analysis. The resulting map was categorized into five vulnerability levels: very low, low, medium, high, and very high. The results revealed that the overall eco-environmental health of the Punjab province is reasonably good as 4.64% and 59.45% area of the key sector lies in ‘very low’ and ‘low’ vulnerability categories; however, there also exist highly vulnerable areas, particularly in the proximity of CPEC projects. Although high vulnerability areas constitute a very small percentage, only 0.08% of the Punjab province, still, decision-makers need to be aware of those regions and make corresponding protection strategies. Our study demonstrated that the MCDM-BWM-based EVA model could be effectively used to quantify vulnerability in other areas of CPEC. The findings of the study emphasize that management policies should be aligned with research-based recommendations for ecological protection, natural resource utilization, and sustainable development in regions participating in BRI.
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi10090625
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2655790-3
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  • 7
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    Comparing Three Remotely Sensed Approaches for Simulating Gross Primary Productivity over Mountainous Watersheds: A Case Study in the Wanglang National Nature Reserve, China
    MDPI AG ; 2021
    In:  Remote Sensing Vol. 13, No. 18 ( 2021-09-08), p. 3567-
    Details
    In: Remote Sensing, MDPI AG, Vol. 13, No. 18 ( 2021-09-08), p. 3567-
    Abstract: Light Use Efficiency (LUE), Vegetation Index (VI)-based, and process-based models are the main approaches for spatially continuous gross primary productivity (GPP) estimation. However, most current GPP models overlook the effects of topography on the vegetation photosynthesis process. Based on the structures of a two-leaf LUE model (TL-LUE), a VI-based model (temperature and greenness, TG), and a process-based model (Boreal Ecosystem Productivity Simulator, BEPS), three models, named mountain TL-LUE (MTL-LUE), mountain TG (MTG), and BEPS-TerrainLab, have been proposed to improve GPP estimation over mountainous areas. The GPP estimates from the three mountain models have been proven to align more closely with tower-based GPP than those from the original models at the site scale, but their abilities to characterize the spatial variation of GPP at the watershed scale are not yet known. In this work, the GPP estimates from three LUE models (i.e., MOD17, TL-LUE, and MTL-LUE), two VI-based models (i.e., TG and MTG), and two process-based models (i.e., BEPS and BEPS-TerrainLab) were compared for a mountainous watershed. At the watershed scale, the annual GPP estimates from MTL-LUE, MTG, and BTL were found to have a higher spatial variation than those from the original models (increasing the spatial coefficient of variation by 6%, 8%, and 22%), highlighting that incorporating topographic information into GPP models might improve understanding of the high spatial heterogeneity of the vegetation photosynthesis process over mountainous areas. Obvious discrepancies were also observed in the GPP estimates from MTL-LUE, MTG, and BTL, with determination coefficients ranging from 0.02–0.29 and root mean square errors ranging from 399–821 gC m−2yr−1. These GPP discrepancies mainly stem from the different (1) structures of original LUE, VI, and process models, (2) assumptions associated with the effects of topography on photosynthesis, (3) input data, and (4) values of sensitive parameters. Our study highlights the importance of considering surface topography when modeling GPP over mountainous areas, and suggests that more attention should be given to the discrepancy of GPP estimates from different models.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs13183567
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
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  • 8
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    Seamless Upscaling of the Field-Measured Grassland Aboveground Biomass Based on Gaussian Process Regression and Gap-Filled Landsat 8 OLI Reflectance
    MDPI AG ; 2018
    In:  ISPRS International Journal of Geo-Information Vol. 7, No. 7 ( 2018-06-22), p. 242-
    Details
    In: ISPRS International Journal of Geo-Information, MDPI AG, Vol. 7, No. 7 ( 2018-06-22), p. 242-
    Type of Medium: Online Resource
    ISSN: 2220-9964
    URL: Article
    DOI: 10.3390/ijgi7070242
    Language: English
    Publisher: MDPI AG
    Publication Date: 2018
    detail.hit.zdb_id: 2655790-3
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  • 9
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    Highly Oxygenated Triterpenoids and Diterpenoids from Fructus Rubi (Rubus chingii Hu) and Their NF-kappa B Inhibitory Effects
    MDPI AG ; 2021
    In:  Molecules Vol. 26, No. 7 ( 2021-03-29), p. 1911-
    Details
    In: Molecules, MDPI AG, Vol. 26, No. 7 ( 2021-03-29), p. 1911-
    Abstract: During a phytochemical investigation of the unripe fruits of Rubus chingii Hu (i.e., Fructus Rubi, a traditional Chinese medicine named “Fu-Pen-Zi”), a number of highly oxygenated terpenoids were isolated and characterized. These included nine ursane-type (1, 2, and 4–10), five oleanane-type (3, 11–14), and six cucurbitane-type (15–20) triterpenoids, together with five ent-kaurane-type diterpenoids (21–25). Among them, (4R,5R,8R,9R,10R,14S,17S,18S,19R,20R)-2,19α,23-trihydroxy-3-oxo-urs-1,12-dien-28-oic acid (rubusacid A, 1), (2R*,4S*,5R*,8R*,9R*,10R*,14S*,17S*, 18S*,19R*,20R*)-2α,19α,24-trihydroxy-3-oxo-urs-12-en-28-oic acid (rubusacid B, 2), (5R,8R,9R,10R, 14S,17R,18S,19S)-2,19α-dihydroxy-olean-1,12-dien-28-oic acid (rubusacid C, 3), and (3S,5S,8S,9R, 10S,13R,16R)-3α,16α,17-trihydroxy-ent-kaur-2-one (rubusone, 21) were previously undescribed. Their chemical structures and absolute configurations were elucidated on the basis of spectroscopic data and electronic circular dichroism (ECD) analyses. Compounds 1 and 3 are rare naturally occurring pentacyclic triterpenoids featuring a special α,β-unsaturated keto-enol (diosphenol) unit in ring A. Cucurbitacin B (15), cucurbitacin D (16), and 3α,16α,20(R),25-tetrahydroxy-cucurbita-5,23- dien-2,11,22-trione (17) were found to have remarkable inhibitory effects against NF-κB, with IC50 values of 0.08, 0.61, and 1.60 μM, respectively.
    Type of Medium: Online Resource
    ISSN: 1420-3049
    URL: Article
    DOI: 10.3390/molecules26071911
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2008644-1
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  • 10
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    The Proliferative Role of Immune Checkpoints in Tumors: Double Regulation
    MDPI AG ; 2022
    In:  Cancers Vol. 14, No. 21 ( 2022-10-31), p. 5374-
    Details
    In: Cancers, MDPI AG, Vol. 14, No. 21 ( 2022-10-31), p. 5374-
    Abstract: Cancer remains a serious social health problem, and immunotherapy has become the major treatments in tumor treatment. Additionally, improving the efficiency and safety of treatment is necessary. Further, more therapy targets are warranted for future tumor treatments. In this review, in addition to examining the currently recognized role of immune regulation, we focus on the proliferative role of 15 immune checkpoints in various tumors, including PD1, PD-L1, FGL1, CD155, CD47, SIRPα, CD276, IDO1, SIGLEC-15, TIM3, Galectin-9, CD70, CD27, 4-1BBL, and HVEM. We managed to conclude that various immune checkpoints such as PD1/PD-L1, FGL1, CD155, CD47/SIRPα, CD276, and SIGLEC-15 all regulate the cell cycle, and specifically through Cyclin D1 regulation. Furthermore, a variety of signal pathways engage in proliferation regulation, such as P13K, AKT, mTOR, and NK-κB, which are also the most common pathways involved in the regulation of immune checkpoint proliferation. Currently, only PD1/PD-L1, CD47/SIRPα, TIM3/Galectin-9, and CD70/CD27 checkpoints have been shown to interact with each other to regulate tumor proliferation in pairs. However, for other immune checkpoints, the role of their receptors or ligands in tumor proliferation regulation is still unknown, and we consider the enormous potential in this area. An increasing number of studies have validated the various role of immune checkpoints in tumors, and based on this literature review, we found that most of the immune checkpoints play a dual regulatory role in immunity and proliferation. Therefore, the related pathways in proliferation regulation can served the role of therapy targets in tumor therapy. Further, great potential is displayed by IDO1, SIGLEC-15, 4-1BBL, and HVEM in tumor proliferation regulation, which may become novel therapy targets in tumor treatment.
    Type of Medium: Online Resource
    ISSN: 2072-6694
    URL: Article
    DOI: 10.3390/cancers14215374
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2527080-1
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