Geographia Technica最新文献_第5页

A NEAR FUTURE CLIMATE CHANGE IMPACTS ON WATER RESOURCES IN THE UPPER CHAO PHRAYA RIVER BASIN IN THAILAND 近期气候变化对泰国湄南河上游流域水资源的影响

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Geographia Technica Pub Date : 2022-10-17 DOI: 10.21163/gt_2022.172.16

N. Yoobanpot, Weerayuth Pratoomchai

引用次数: 0

NIGHTTIME AND DAYTIME POPULATION ESTIMATION FROM OPEN DATA 从公开数据估计夜间和白天的人口

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Geographia Technica Pub Date : 2022-10-17 DOI: 10.21163/gt_2022.172.15

Nelson Mileu, M. Queirós

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DAILY STREAMFLOW FORECASTING USING EXTREME LEARNING MACHINE AND OPTIMIZATION ALGORITHM. CASE STUDY: TRA KHUC RIVER IN VIETNAM 使用极值学习机和优化算法进行日流量预测。越南屈克河个案研究

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Geographia Technica Pub Date : 2022-10-14 DOI: 10.21163/gt_2022.172.13

H. Nguyen

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ALGORITHMS DEVELOPMENT OF THE FIELD MANGROVE CHLOROPHYLL-a BIOMASS, CARBON BASED ON SENTINEL-2A DATA AT CAWAN ISLAND, SUMATERA, INDONESIA 基于SENTINEL-2A数据的印尼苏门答腊加万岛红树林叶绿素-a生物量、碳计算算法的发展

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Geographia Technica Pub Date : 2022-10-06 DOI: 10.21163/gt_2022.172.11

Agus Hartoko, Aulia Rahim, N. Latifah

{"title":"ALGORITHMS DEVELOPMENT OF THE FIELD MANGROVE CHLOROPHYLL-a BIOMASS, CARBON BASED ON SENTINEL-2A DATA AT CAWAN ISLAND, SUMATERA, INDONESIA","authors":"Agus Hartoko, Aulia Rahim, N. Latifah","doi":"10.21163/gt_2022.172.11","DOIUrl":"https://doi.org/10.21163/gt_2022.172.11","url":null,"abstract":": The study develop of algorithms for the tropical mangrove chlorophyll-a, biomass and carbon based on the field data measurements at Cawan Island Sumatera Indonesia and Sentinel-2A satellite data. Samples of mangrove leaf were used for chlorophylla-a measurements using spectrometry method. Field sampling data using purposive sampling method. Data of mangrove tree diameter at breast height (DBH) was processed using allometric equation to estimate the mangrove biomass and carbon content. Algorithms were developed after performing a series of polynomial regressions of field and Sentinel-2A satellite data and then select the highest correlation coefficient. The dominant mangrove is Rhizophora apiculata . The field mangrove leaf chlorophyll-a content ranged from 14.03-15.77 mg.ml - 3 , while the estimated chlorophyll-a from algorithm is in the range of 13.714-16 mg.ml -3 . Calculated field mangrove biomass is in the range of 66.31-85.05 tons.ha -1 , while the value from algorithms is in the range of 51-90 tons.ha -1 . The highest biomass and carbon storage is in the trunks. This study produces the algorithm of mangrove leaf chlorophylll-a = 0.0002((B 4 + B 2 )/2) 2 – 0.057((B 4 + B 2 )/2) + 16.79, with RMSE of 0.072 mg.m -3 . Algorithm for mangrove biomass = 24.69(B 4 /Band 2 ) 2 - 47.41(B 4 /B 2 ) + 36.06, with RMSE of 0.337 tons/0.2ha and algorithm for mangrove carbon = 10.071(B 4 /B 2 ) 2 – 23.159(B 4 /B 2 ) + 44.233; with RMSE of 0.235 tonsC/0.2ha. The new insight in this study is that the algorithm developments can be applied for mangrove chlorophyll-a content, biomass and carbon content estimation using any optical satellite data based on its relevant spectral range. This algorithm development is an open approach method based on highest correlation coefficient on regression equation of the field and the satellite spectral value. The algorithms resulted from this study can be applied over wide and in any area in the tropics.","PeriodicalId":45100,"journal":{"name":"Geographia Technica","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2022-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45349147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

TIDAL FLOOD MODEL PROJECTION USING LAND SUBSIDENCE PARAMETER IN PONTIANAK, INDONESIA 基于地面沉降参数的印尼蓬蒂亚纳克潮汐洪水模型投影

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Geographia Technica Pub Date : 2022-10-06 DOI: 10.21163/gt_2022.172.12

Randy Ardianto, A. Ismanto, J. Sampurno, S. Widada

引用次数: 0

JOINT DISTRIBUTION AND COINCIDENCE PROBABILITY OF THE NUMBER OF DRY DAYS AND THE TOTAL AMOUNT OF PRECIPITATION IN SOUTHERN SUMATRA FIRE-PRONE AREA 苏门答腊岛南部火灾易发区干旱日数与降水总量的联合分布及其重合概率

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Geographia Technica Pub Date : 2022-09-30 DOI: 10.21163/gt_2022.172.10

S. Nurdiati, M. Najib, Achmad Syarief Thalib

{"title":"JOINT DISTRIBUTION AND COINCIDENCE PROBABILITY OF THE NUMBER OF DRY DAYS AND THE TOTAL AMOUNT OF PRECIPITATION IN SOUTHERN SUMATRA FIRE-PRONE AREA","authors":"S. Nurdiati, M. Najib, Achmad Syarief Thalib","doi":"10.21163/gt_2022.172.10","DOIUrl":"https://doi.org/10.21163/gt_2022.172.10","url":null,"abstract":": El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) can affect the increase in rainfall intensity and the number of dry days, also known as dry spells that can cause drought and increase the potential for forest fires. This study examines the effect of ENSO and IOD conditions on the joint distribution of the number of dry days and total precipitation in a fire-prone area in southern Sumatra, Indonesia. The joint distribution is constructed using rotated copulas from several families, including Gaussian, student’s t, Clayton, Gumbel, Frank, Joe, Galambos, BB1, BB6, BB7, and BB8. Fire-prone areas are defined using k-mean clustering, while the copula parameters are estimated using the inference of function for margins (IFM) method. Based on the peak of joint probability density functions (PDFs), ENSO and IOD conditions had a significant effect in the dry season but had no significant effect in the rainy season. The peak of joint PDFs is getting to the dry-dry conditions when the ENSO and IOD indexes increase in the dry season. However, based on coincidence probability, ENSO conditions still influence the joint distribution between the number of dry days and total precipitation during the rainy season but not with IOD conditions. The lower the ENSO index, the higher the probability of wet conditions co-occurring in the number of dry days and total precipitation. Meanwhile, ENSO and IOD conditions significantly affect the coincidence probability between the number of dry days and total precipitation. Moderate-Strong El Niño has the most considerable coincidence probability of 68.5%, followed by Positive IOD with 62.6%. The two conditions had similar effects on the joint distribution of the number of dry days and total precipitation. Moreover, the association between the number of dry days and the total precipitation was stronger in the dry season than in the rainy","PeriodicalId":45100,"journal":{"name":"Geographia Technica","volume":" ","pages":""},"PeriodicalIF":0.7,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44225543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

HOW THE CLIMATE MIGRATES. CASE STUDY FOR FOUR LOCATIONS IN THE CARPATHIAN-BASIN 气候是如何迁移的。喀尔巴阡盆地四个地点的案例研究

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Geographia Technica Pub Date : 2022-09-08 DOI: 10.21163/gt_2022.172.09

Zsolt Magyari-Saska

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GIS-BASED ASSESSMENT OF COASTAL VULNERABILITY IN THE JATABEK (JAKARTA, TANGERANG, AND BEKASI) REGION, INDONESIA 基于GIS的印尼雅加达、唐格朗和贝卡西地区海岸脆弱性评估

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Geographia Technica Pub Date : 2022-09-01 DOI: 10.21163/gt_2022.172.08

G. A. Rahmawan, R. Dhiauddin, U. J. Wisha, W. A. Gemilang, A. Syetiawan, W. Ambarwulan, A. Rahadiati

引用次数: 0

ACCURACY PERFORMANCE OF SATELLITE-DERIVED SEA SURFACE TEMPERATURE PRODUCTS FOR THE INDONESIAN SEAS 印度尼西亚海域卫星海面温度产品的精度性能