scholarly journals OBSERVING THE INUNDATED AREA USING LANDSAT-8 MULTITEMPORAL IMAGES AND DETERMINATION OF FLOOD-PRONE AREA IN BANDUNG BASIN

2019 ◽  
Vol 15 (2) ◽  
pp. 131
Author(s):  
Fajar Yulianto ◽  
NFn Suwarsono ◽  
Sayidah Sulma ◽  
Muhammad Rokhis Khomarudin
Keyword(s):  
Land Surface ◽  
Land Use Changes ◽  
Image Data ◽  
Landsat 8 ◽  
Flood Events ◽  
Water Index ◽  
The Past ◽  
Prone Area ◽  
Flood Prone Area ◽  
Flood Prone Areas

Flood is the most frequent hydro-meteorological disaster in Indonesia. Flood disasters in the Bandung basin result from increasing population density, especially in the Citarum riverbank area, accompanied by land use changes in upstream of the Citarum catchment area which has disrupted the river’s function. One of the basic issues that need to be investigated is which areas of the Bandung basin are prone to flooding. This study offers an effective and efficient method of mapping flood-prone areas based on flood events that have occurred in the past through the use of historical remote sensing image data. In this research, Landsat-8 imagery was used to observe the inundated area in the Bandung basin in the past (2014–2018) using an improved algorithm, the modified normalized water index (MNDWI). The results of the study show that MNDWI is the appropriate parameter to be used to detect flooded areas in the Bandung basin area that have heterogeneous land surface conditions. The flood-prone area was determined based on flood events for 2014 to 2018, identified as inundated areas in the images. The estimation of the flood-prone area in the Bandung basin is 11,886.87 ha. Most of the flood-prone areas are in the subdistricts of Rancaekek, Bojongsoang, Solokan Jeruk, Ciparay, Cileunyi, Bale Endah and Cikancung. This area geographically or naturally is a water habitat area. Therefore, if the area will be used for residential, this will have consequences that flood will always be a threat to the area. 

scholarly journals Predicting Land Use/Land Cover Changes Using a CA-Markov Model under Two Different Scenarios

2018 ◽  
Vol 10 (10) ◽  
pp. 3421 ◽  
Author(s):  
Rahel Hamad ◽  
Heiko Balzter ◽  
Kamal Kolo
Keyword(s):  
Land Use ◽  
Markov Chain ◽  
Land Cover ◽  
Land Use Changes ◽  
Landsat 8 ◽  
Chain Model ◽  
Land Use Land Cover ◽  
Kurdistan Region ◽  
The Past ◽  
Past Trend

Multi-temporal Landsat images from Landsat 5 Thematic Mapper (TM) acquired in 1993, 1998, 2003 and 2008 and Landsat 8 Operational Land Imager (OLI) from 2017, are used for analysing and predicting the spatio-temporal distributions of land use/land cover (LULC) categories in the Halgurd-Sakran Core Zone (HSCZ) of the National Park in the Kurdistan region of Iraq. The aim of this article was to explore the LULC dynamics in the HSCZ to assess where LULC changes are expected to occur under two different business-as-usual (BAU) assumptions. Two scenarios have been assumed in the present study. The first scenario, addresses the BAU assumption to show what would happen if the past trend in 1993–1998–2003 has continued until 2023 under continuing the United Nations (UN) sanctions against Iraq and particularly Kurdistan region, which extended from 1990 to 2003. Whereas, the second scenario represents the BAU assumption to show what would happen if the past trend in 2003–2008–2017 has to continue until 2023, viz. after the end of UN sanctions. Future land use changes are simulated to the year 2023 using a Cellular Automata (CA)-Markov chain model under two different scenarios (Iraq under siege and Iraq after siege). Four LULC classes were classified from Landsat using Random Forest (RF). Their accuracy was evaluated using κ and overall accuracy. The CA-Markov chain method in TerrSet is applied based on the past trends of the land use changes from 1993 to 1998 for the first scenario and from 2003 to 2008 for the second scenario. Based on this model, predicted land use maps for the 2023 are generated. Changes between two BAU scenarios under two different conditions have been quantitatively as well as spatially analysed. Overall, the results suggest a trend towards stable and homogeneous areas in the next 6 years as shown in the second scenario. This situation will have positive implication on the park.

SISTEM INFORMASI GEOGRAFIS (SIG) DAERAH RAWAN BANJIR DI KOTA BENGKULU MENGGUNAKAN ARCVIEW

2016 ◽  
Vol 12 (1) ◽  
Author(s):  
Rahma Wayan Lestari ◽  
Indra Kanedi ◽  
Yode Arliando
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Geographic Information ◽  
The Body ◽  
Microsoft Excel ◽  
Microsoft Word ◽  
Prone Area ◽  
Flood Prone Area ◽  
The City ◽  
Flood Prone Areas

The purpose of this research is to create a geographic information system Bengkulu city flood-prone areas using ArcView. Apply the knowledge obtained during the lecture, especially relating to the development of Geographic Information Systems. To be able to produce a system that is accurate and useful information for the community. Where the research was conducted in the city of Bengkulu BASARNAS. Bengkulu BASARNAS office specializing in Search and Rescue (SAR), is the body that manage the flood of data that is still done manually, using Microsoft Word and Microsoft Excel. Thus experiencing problems in delivering information directly to the office because the SAR agencies require a long time.Keywords: Geographic Information System, Flood Prone Area

scholarly journals KERUSAKAN LAHAN AKIBAT KEGIATAN PENAMBANGAN EMAS TANPA IZIN DISEKITAR SUNGAI SINGINGI KABUPATEN KUANTAN SINGINGI

2019 ◽  
Vol 15 (3) ◽  
Author(s):  
Mailendra Mailendra ◽  
Imam Buchori
Keyword(s):  
Gold Mining ◽  
Image Data ◽  
Google Earth ◽  
Landsat 8 ◽  
Mining Activities ◽  
Vegetation Density ◽  
The Past ◽  
High Level ◽  
Damage Map

Indonesia is one of the countries that has the potential of natural resources other than agriculture, namely mining, especially gold. Gold mining without permits is one of the mining activities which results in a decrease in the quality of the surrounding environment, especially land. The purpose of this study was to look at the land damage that occurred as a result of unlicensed gold mining activities around the Singingi River in the massive Kuantan Singingi Regency in the past two decades. The method used in the analysis is the scoring and overlay method, the data used are Landsat 5 TM and Landsat 8 OLI which are processed using the supervised cllasification method and digitized on screen. Furthermore, as comparative data, surveys and interviews are carried out and utilizing high resolution image data from SPOT images and google earth. The results of this study were found that there was a change in land use from other land uses into unlicensed gold mining land covering an area of 2,680.03 Ha from 2006 to 2018. Then a land damage map with three parameters was produced, namely vegetation density, mine life and type of tailings . Land with a high level of damage covering 699.34 ha, moderate damage 1,501.04 and low damage 479.65. The largest area of land damage occurs in Sungai Paku Village and the smallest village is Pulau Padang.

scholarly journals Pemetaan Tingkat Kerawananan Banjir Di Kota Jambi Menggunakan Metode Scoring Dan Overlay Berbasis Sistem Informasi Geografis

2021 ◽  
Vol 5 (2) ◽  
pp. 132-141
Author(s):  
Lusiani Pryastuti ◽  
Keyword(s):  
Land Use ◽  
Information System ◽  
Spatial Distribution ◽  
Geographic Information System ◽  
Soil Type ◽  
Flood Vulnerability ◽  
Overlay Method ◽  
Prone Area ◽  
Flood Prone Area ◽  
Flood Prone Areas

This research is about flood vulnerability mapping in Jambi City based on Geographic Information System (GIS). This study is aiming to find out the flood vulnerability level, spatial distribution of flood, and flood prone areas in Jambi City. We used five parameters that affect flood vulnerability, including land slope, land level, land use, soil type, and rainfall during 2019. The method used is the scoring and overlay method with the help of ArcGis software. Flood vulnerability level was divided into three categories, namely quite vulnerable, vulnerable, and very vulnerable. The results obtained in this study are that most of Jambi City has a level of flood vulnerability in the vulnerable category, which is an area of 9254.82 ha (58%), while for the area that is dominated quite safe from flooding, Jambi Selatan sub-district, is 2849.14 ha (18%). This shows that more than half of the Jambi city area is a flood-prone area so it is very important to carry out structural and non-structural mitigation actions

scholarly journals STUDY OF LAND USE CHANGES AND ITS RELATIONSHIP WITH TEMPERATURE AND DENGUE FEVER IN 2003 AND 2016 OVER JAKARTA PROVINCE USING LANDSAT 7+ETM AND LANDSAT 8 OLI

2018 ◽  
Vol 12 (1) ◽  
pp. 18
Author(s):  
Risya Lailarahma ◽  
I Wayan Sandi Adnyana
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Surface Temperature ◽  
Dengue Fever ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Land Use Changes ◽  
Water Infiltration ◽  
Landsat 8 ◽  
Temperature Changes

Land use changes over Jakarta caused by urbanization affected the increasing of infrastructure and decreasing vegetation from 2003 to 2016. This condition reduced water infiltration and caused inundation when heavy rainfall coming. Then Aedes aegypti would breed.and increased which brought dengue fever desease. This study was about analyzing the land use change in Jakarta Province using Landsat image, and its relationship with land surface temperature and dengue fever distribution. The effects of land use change also analysed by this study which including the effects from temperature and dengue fever that analysed by indices of land use in Jakarta at 2003 and 2016. The temperature analysis could be obtained by TIR band in Landsat and using some algortitma which calculated in band math of ENVI software. Vegetation index value’s average decreased from 0.652 in 2003 to 0.647 2016 in 2016. Built up index value’s average increased from -0.03 in 2003 to -0.02 in 2016. While Bareland index value’s average decreased from 0.16 in 2003 to -0.46 in 2016. Land surface temperature increased 3?C from 2003 to 2016. Vegetation area decreased 27.929 ha, bare land area decreased 6.012 ha, while built up area increased 34.278 ha from 2003 to 2016. Increasing of land surface temperature proportional to increasing dengue fever patients 1.187 patients. Increasing of land surface temperature increasing dengue fever cases 1.187 patients. To review and monitor more about the relationship between landuse changes and temperature changes required image with high resolution so that the results obtained more accurate. Complete data of dengue fever per subdistricts also required to analyse further more about relationship between landuse changes, temperature changes, and dengue fever.

scholarly journals Assessment of the Hail Damage on Agricultural Crops from North of Baragan Plain, Romania, Using Remote Sensing Data

2021 ◽  
Author(s):  
Claudiu Valeriu Angearu ◽  
Irina Ontel ◽  
Anisoara Irimescu ◽  
Burcea Sorin
Keyword(s):  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Remote Sensing Data ◽  
Weather Radar ◽  
Radar Data ◽  
Landsat 8 ◽  
Water Index ◽  
Hail Damage ◽  
Sentinel 2A

Abstract Hail is one of the dangerous meteorological phenomena facing society. The present study aims to analyze the hail event from 20 July 2020, which affected the villages of Urleasca, Traian, Silistraru and Căldăruşa from the Traian commune, Baragan Plain. The analysis was performed on agricultural lands, using satellite images in the optical domain: Sentinel-2A, Landsat-8, Terra MODIS, as well as the satellite product in the radar domain: Soil Water Index (SWI), and weather radar data. Based on Sentinel-2A images, a threshold of 0.05 of the Normalized Difference Vegetation Index (NDVI) difference was established between the two moments of time analyzed (14 and 21 July), thus it was found that about 4000 ha were affected. The results show that the intensity of the hail damage was directly proportional to the Land Surface Temperature (LST) difference values in Landsat-8, from 15 and 31 July. Thus, the LST difference values higher than 12° C were in the areas where NDVI suffered a decrease of 0.4-0.5. The overlap of the hail mask extracted from NDVI with the SWI difference situation at a depth of 2 cm from 14 and 21 July confirms that the phenomenon recorded especially in the west of the analyzed area, highlighted by the large values (greater than 55 dBZ) of weather radar reflectivity as well, indicating medium–large hail size. This research also reveals that satellite data is useful for cross validation of surface-based weather reports and weather radar derived products.

scholarly journals Machine-Learning blends of geomorphic descriptors: value and limitations for flood hazard assessment across large floodplains

2021 ◽  
Author(s):  
Andrea Magnini ◽  
Michele Lombardi ◽  
Simone Persiano ◽  
Antonio Tirri ◽  
Francesco Lo Conti ◽  
...  
Keyword(s):  
Machine Learning ◽  
Decision Tree ◽  
Recent Literature ◽  
Flood Hazard ◽  
Open Problems ◽  
Prone Area ◽  
Tree Models ◽  
Multivariate Approaches ◽  
Flood Prone Area ◽  
Flood Prone Areas

Abstract. Recent literature shows several examples of simplified approaches that perform flood hazard (FH) assessment and mapping across large geographical areas on the basis of fast-computing geomorphic descriptors. These approaches may consider a single index (univariate) or use a set of indices simultaneously (multivariate). What is the potential and accuracy of multivariate approaches relative to univariate ones? Can we effectively use these methods for extrapolation purposes, i.e. FH assessment outside the region used for setting up the model? Our study addresses these open problems by considering two separate issues: (1) mapping flood-prone areas, and (2) predicting the expected water depth for a given inundation scenario. We blend seven geomorphic descriptors through Decision Tree models trained on target FH maps, referring to a large study area (≈105 km2). We discuss the potential of multivariate approaches relative to the performance of a selected univariate model and on the basis of multiple extrapolation experiments, where models are tested outside their training region. Our results show that multivariate approaches may (a) significantly enhance flood-prone area delineation (overall accuracy: 93 %) relative to univariate ones (overall accuracy: 84 %), (b) provide accurate predictions of expected inundation depths (determination coefficient ≈0.7), and (c) produce encouraging results in extrapolation.

scholarly journals SPATIAL AND TEMPORAL VARIABILITY OF SURFACE TEMPERATURE, LAND USE AND LAND COVER CHANGE: A CASE STUDY IN CAMPINAS, BRAZIL

2021 ◽  
Vol 28 ◽  
Author(s):  
Luiza Marchezan Bezerra ◽  
Ana Maria Heuminski de Avila
Keyword(s):  
Land Use ◽  
Surface Temperature ◽  
Land Surface ◽  
Land Use Changes ◽  
Thermal Infrared ◽  
Climatic Conditions ◽  
Spatial And Temporal Variability ◽  
Landsat 8 ◽  
Climatic Data ◽  
Infrared Sensor

deteriorating climatic conditions in urban centers of Brazil is a real concern for human security and urban livelihood sustainability.  The city of Campinas in São Paulo state/Brazil is highly vulnerable to climatic disasters. The present paper analyses the relationship between land use changes and temperature in Campinas between 1989 and 2016. The 28-year period was chosen due to the variability of climatic data in three meteorological stations (University of Campinas, Agronomic Institute of Campinas and International Airport of Viracopos). Data from five sources were used for land use land changes (LULC), and land surface temperature (LST) analysis. The data sources were: i) Landsat 5 Thermometer Mapper (TM), ii) Landsat 5 Thermal Infrared Sensor (TIRS), iii) Thermal Infrared Sensor (ETM +) sensors from Landsat 5, iv) Landsat 8 Operational Land Imager (OLI), and v) Thermal Infrared Sensor (TIRS). The results indicate consistent relations between urbanized increase area and the elevation of air and surface temperature in Campinas. In the studied period, there was an increase of 23% in urbanized areas in Campinas and around the meteorological stations. Cepagri presented the highest growth, about 22%, as well as the station with the highest air temperature

scholarly journals Analysis of the changes and driving force of the water area in the Ulungur Lake over the past 40 years

2020 ◽  
Vol 69 (5) ◽  
pp. 500-511
Author(s):  
Fan Gao ◽  
Bing He ◽  
Zhenglon Yan ◽  
Songsong Xue ◽  
Yizhen Li
Keyword(s):  
Lake Water ◽  
Human Activities ◽  
Image Data ◽  
Water Area ◽  
Climate Trends ◽  
Humid Climate ◽  
Index Method ◽  
Water Index ◽  
The Past ◽  
Terminal Lakes

Abstract The inland lakes in arid regions, especially the terminal lakes, are highly sensitive to the influence of human activities and climate change. In order to analyze the evolution of the area of water in Ulungur Lake (Buluntuohai Lake, Jili Lake) and the main causes of those changes, 3S technology, satellite data preprocessing, water extraction and database construction methods are combined with consideration of climatic changes and human activity in this study. The data in this study include 11 phases of remote sensing image data, field mapping data and relevant attribute data of the study area from 1977 to 2017. The results demonstrated the following. (1) Over the past 40 years, the change in Ulungur Lake's area was characterized by natural expansion, fluctuation stability, and recovery increase. Significant changes were mainly concentrated in the waters of Zhonghaizi, Xiaohaizi, Camel's Neck, and the waters near Akekule. (2) The period from 1977 to 1995 was the expansion period of the lake water area, and human activities were the main driving factors. The period from 2000–2017 was a smaller period of expansion of the lake water area, with warmer and more humid climate trends combined with human activities driving the change. (3) The water area that was extracted based on the MNDWI water index method can increase the contrast between bodies of water and buildings, which can aid in interpreting and extracting water element information from flat terrain and single types of surface features. This can provide an effective technical means for quantitative and dynamic analysis of the temporal and spatial changes in lake water area.

scholarly journals AUTOMATIC PADDY RICE MAPPING INTERFACE USING ARCENGINE AND LANDSAT8 IMAGERY (CASE STUDY IN NORTH PART OF IRAN)

2014 ◽  
Vol XL-2/W3 ◽  
pp. 79-83 ◽  
Author(s):  
Sh. Bahramvash Shams
Keyword(s):  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Initial Period ◽  
Rice Paddy ◽  
Paddy Rice ◽  
Landsat 8 ◽  
Water Index ◽  
The North ◽  
North Part

Recognition of paddy rice boundaries is an essential step for many agricultural processes such as yield estimation, cadastre and water management. In this study, an automatic rice paddy mapping is proposed. The algorithm is based on two temporal images: an initial period of flooding and after harvesting. The proposed method has several steps include: finding flooded pixels and masking unwanted pixels which contain water bodies, clouds, forests, and swamps. In order to achieve final paddy map, indexes such as Normalized Difference Vegetation Index (NDVI) and Land Surface Water Index (LSWI) are used. Validation is performed by rice paddy boundaries, which were drawn by an expert operator in Google maps. Due to this appraisal good agreement (close to 90%) is reached. The algorithm is applied to Gilan province located in the north part of Iran using Landsat 8 date 2013. Automatic Interface is designed based on proposed algorithm using Arc Engine and visual studio. In the Interface, inputs are Landsat bands of two time periods including: red (0.66 μm), blue (0.48 μm), NIR (0.87 μm), and SWIR (2.20 μm), which should be defined by user. The whole process will run automatically and the final result will provide paddy map of desire year.

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