Table of contents

The Geomatics International Conference (GeoICON) is an annual scientific meeting organized by the Department of Geomatics Engineering, Institut Teknologi Sepuluh Nopember Surabaya, Indonesia since 2016. Due to the outbreak of Covid-19, the 6th GeoICON 2021 was held virtually on July 27^st 2021. The conference had a theme of "Geospatial Technology for Mapping the Future: Solutions for Hazard and Disaster Mitigation. The 6^th GeoICON 2021 aims to bring together researchers, scientists, and scholar students to exchange and share their experiences, new ideas, and research results about all aspects of geospatial science and technology. The discussion about the practical challenges encountered is performed and the solutions are adopted.

During the conference, speakers of the event comes from many backgrounds such as government, industry, and academics. The participants presented their findings in eight main conference topic tracks, i.e. (A) flood modeling, (B) earthquake, (C) extreme weather and climate change, (D) tsunami simulation, (E) landslide and mass movement, (F) capacity strengthening, (G) sea-level rise, (H) temporal shelter model, as well as discussing potential joint research and collaborations among them. We would like to thank the committees for their strong commitment to organizing this event and the participants who have contributed to this volume.

We would also like to thank the editor for their time and valuable remarks as well as the reviewers for their suggestions on how to improve the paper. Our gratitude is also expressed to the publisher for the generous help in publishing this proceeding volume. Lastly, we would like to acknowledge all the contributing sponsors for their generous support of the conference.

October 28th, 2021

Dr. Eko Yuli Handoko ST., MT.

The 6^th GeoICON 2021

Chairman

List of Steering Committee, Organizing Committee are available in this pdf.

All conference organisers/editors are required to declare details about their peer review. Therefore, please provide the following information:

• Type of peer review: Single-blind

Single-anonymous: authors' identities are known to the reviewers, reviewers' identities are hidden from authors

Double-anonymous: author and reviewer identities are hidden to each other

Triple-blind: author and reviewer identities are hidden to each other, and from the Editor(s)

Open: author and reviewer identities are known to each other

• Describe criteria used by Reviewers when accepting/declining papers. Was there the opportunity to resubmit articles after revisions?

Some criteria when accepting/declining paper were including: (1). The depth of the research methods and results, (2). Whether the papers were written properly, (3). If the topics of the research matches our conference, (4). All the figures were correlated to the discussion.

Time given to authors in resubmitting after revisions was approximately 1 month.

• Conference submission management system:

We use Easychair.org platform in managing our conference submission. Submissions were available for 2.5 months prior to conference date. We generally accepted all the papers submitted for presentation in the conference as long as they suit the theme. After conference, the review process was conducted by Reviewers.

• Number of submissions received: 53 papers

• Number of submissions sent for review: 53 papers

• Number of submissions accepted: 43

• Acceptance Rate (Number of Submissions Accepted/Number of Submissions Received X 100): 85%

• Average number of reviews per paper: 2 reviews

• Total number of reviewers involved: 10 reviewers

• Any additional info on review process (ie plagiarism check system):

• Contact person for queries:

Mohammad Rohmaneo Darminto

rohmaneo@its.ac.id/geoicon@its.ac.id

Laboratory of Geoinformatics

Department of Geomatics Engineering

Institut Teknologi Sepuluh Nopember

Surabaya

Indonesia

Please submit this form along with the rest of your files on the submission date written in your publishing agreement.

The information you provide will be published as part of your proceedings.

The Global Navigation Satellite System is being developed as an atmospheric remote sensing system through the calculation of Zenith Total Delay. The development of the Continous Operating Reference Station encourages research investigations into Zenith Tropospheric Delay with continuous data and good spatial resolution. This research studies the characteristics of spatial and temporal variations of the Zenith Wet Delay in East Jawa. The case study in East Jawa Province uses 16 Continous Operating Reference Stations. As a comparison, meteorological data from the Badan Meteorologi, Klimatologi, and Geofisika stations are used.The Zenith Total Delay and Zenith Wet Delay values from the Continous Operating Reference Station data are calculated using GIPSY 6.4 Software. The Zenith Wet Delay values are gridded using the kriging method with the size of the grids being 0,25 x 0,25. The ZWD value comparison from the Continous Operating Reference Station and meteorology data has a strong correlation with a coefficient value of 0,712. The mean of Zenith Wet Delay's trend is increasing by about 0,712 mm/yr. The characteristics of the spatial and temporal variations of the ZWD value are influenced by the monsoon of Asia-Australian, which causes dry and rainy seasons, global phenomena such as El Nino and La Nina, rainfall, local meteorological conditions such as temperature and humidity, weather, and the topography of the stations.

Forest and land fires in Indonesia are one of the most common disasters. Over time, Indonesia's forests have experienced a decline, one of which is the result of forest and land fires. Forest and land fires can occur due to temperatures in the dry season that continue to increase. Utilization of remote sensing technology can be used for mapping forest and fire areas, and can also be used as a reference for the government to carry out reforestation or reforestation processes in fire areas. The use of Multispectral Sensors in Sentinel 2 satellite imagery can be used to produce this research. This research takes a case study on Mount Lawu, Magetan Regency. Mount Lawu is one of the climbing tourist destinations that almost every year experiences forest and land fires. And the use of the Google Earth Engine platform that supports cloud computing to facilitate this research in accessing high data sources to process large geospatial data sets. For processing satellite images using the Normalized Burned Ratio (NBR) vegetation index processing algorithm. This research was conducted in 2018 and 2019. By using the Random Forest method, which is one of the applications of Machine Learning, it will produce several accurate results from the calculation results. The results of the calculation of the area of fire in 2018 were 284.88 hectares with a total loss of Rp 42,732,000.00 and in 2019 it was 146.03 hectares with a total loss of Rp 21,904,500. The results of this study are displayed on GEE Apps so that users can directly access the resulting data.

Gresik is one of the areas with severe drought levels in East Java. This drought disaster caused by low rainfall and the high average surface temperature in an area. These two factors are currently difficult to predict due to uncertain climate change, this is also related to the global warming that is happening. This disaster cannot be completely avoided but can be minimized. This research was conducted to periodically check or time series of droughts by utilizing the Google Earth Engine platform. Drought identification obtained from multitemporal Landsat 8 satellite imagery with the TVDI (Temperature Vegetation Dryness Index) algorithm and field data retrieval in the form of aerial photos using a thermal camera from the DJI Mavic Enterprise Dual Thermal. From this study, it can be monitoring the distribution of drought in the 2015-2020 period in Gresik Regency occurred in 9 sub-districts, there are Wringinanom, Driyorejo, Kedamean, Balongpanggang, Benjeng, Menganti sub-districts as well as several areas in Duduksampeyan, Cerme and Panceng sub-districts. The identification of dry land also correlates well with the rainfall that occurs, namely?100 mm/month, which has low rainfall during drought events.

Condition assessment of the tank must be carried out since it is related to Health, Safety, and Environment (HSE). Assessment is carried out by referring to the applicable standards. This study aims to create a 3D (Dimension) model and assess the tank using Terrestrial Laser Scanner technology. This includes planning, data acquisition, data processing, and data visualization. The data processing process starts with the registration stage with the cloud-to-cloud method, georeferencing, 3D modeling using point cloud, and tank assessment filtered point cloud data. Assessment includes analysis of volume, verticality/slope (in terms of the difference between upper and lower tank), and roundness calculations. The 3D model of the tank was generated with a registration error of less than 1 cm. The volume of tank I and tank II were calculated to 134.108 m³ and 134.067 m³, respectively. The difference between the upper and lower radius for each tank ranges from 2 to 10 mm. Considering the results and recalling the API 650 standard (American Petroleum Institute), each tank is considered reliable and in a good condition.

Makassar city experiences many residential fire disasters during the last years. One of the causes of fires is difficult to overcome due to the firefighters' late response. The number of fires occurred due to the ineffectiveness of the fire fighting road, obstructed by traffic conditions, in its operation. Developing a geospatial route analysis can help firefighters quickly find the best route to a fire point to overcome this problem. Geospatial route analysis is currently a key role in emergency responses for urban fire disasters. A routing system can provide network analysis that allows users to navigate between source and destination points. In this case, the system can help firefighters to arrive as quickly as possible. On complicated road networks, some impedance factors would slow down drivers on a particular road. This study aims to provide firefighters from the base stations to residential fire disaster locations. The method used in the studies is Dijkstra's algorithms to calculate weights of the impedance factors to optimal routing based on length of the road, speed drive, and traffic conditions. Implementation of routing analysis using open source geospatial software, PostgreSQL as database management system with PostGIS, and pgrouting as extensions. The modeling results show that the optimal route selection with speed parameters based on road classification has a low weight value. Therefore, it can be used as a reference for selecting a firefighter's routing.

Monitoring the concentration of Total Suspended Solid (TSS) is one method to determine water quality, because a high TSS value indicates a high level of pollution. Remote sensing data can be used effectively in generating suspended sediment concentrations. Nowdays, Google Earth Engine platform has provided a large collection of remote sensing data. Therefore, this study uses Google Earth Engine which is processed for free and aims to calculate the TSS value in the Kali Porong area. This research was conducted multitemporal in the last ten years, namely from 2013-2021 using multitemporal satellite imagery landsat-8 and sentinel-2 by applying empirical algorithms for calculating TSS. The results of this study are the value of TSS concentration at each sample point and a multitemporal TSS concentration distribution map. The year 2016, 2017, and 2021, the distribution of TSS concentration values was higher than in other years. At the sample point, the lowest TSS concentration value was 16.55 mg/L in 2013. Meanwhile, the highest TSS concentration value of 266.33 mg/L occurred in 2014 precisely in the Porong River estuary area which is the border area between land and water. the sea so that a lot of TSS material is concentrated in the area due to waves and ocean currents.

The problem of environmental damages in the river area can transform the morphology and threaten the ecosystem in it with one of the causes being natural factors such as suspended sediment. Retracing the medium form is fluid, the common instrument to determine the condition of the area is a sound wave-based instrument such as a multibeam echosounder. Considering the improvement of multibeam echosounder which can acquire areas using many frequencies at one time, noted as multi-frequency multibeam echosounder, now its application can reach various fields including environmental monitoring. Factors that can be considered in its practice include time efficiency, cost, and notably the accuracy of the data result. By converting the results of the acquisition into an estimate of the concentration of suspended sediment and integrating the results from several frequencies, it will be established the applicable frequency usage. It was concluded that a multibeam echosounder with a frequency of 450 kHz was recommended in a case study to determine the concentration of suspended sediment. This is supported by a correlation value of 89.18% or a very high correlation.

The development in urban areas will continue to occur, such as the construction of settlements, offices, shops, educational and health facilities, and other supporting facilities. With the development that will always continue to occur in a nation, it will also increase the productivity in its city. The rapid development of urban activities will also followed by high demand for land. This can lead to land conversion. Therefore, it is necessary to use the land to its optimal capacity and manage it wisely in order to produce a quality space that is maintained for its sustainability. Rules and regulations are compiled into a plan in the Guidelines for the Preparation of Detailed Spatial Planning (RDTR). This research conducted in North Gandaria Urban Village because the buildings are divided into three environments, namely densely populated settlements, middle to upper settlements, offices and shops which based on geometrical aspects have various building forms from small to large ratios. Each building has different diverse land and building usages. In this study, land use suitability was identified by manual and digital classification, namely by image interpretation and classifying using the Object Based Image Analysis (OBIA) method on SPOT-7 images which were then superimposed to produce land use maps. In addition, this study utilizes altitude data from LiDAR to complement building spatial data and is processed to BIM. BIM dimensions are made in 3D with Level of Development 100 or equivalent to Level of Details 1 which has a flat roof if converted. From this research resulted suitability of land use and buildings to carry out an analysis related to sustainability and can be used as consideration and input by the policy makers on spatial planning policies. Based on the results of the analysis, it was found that the suitability of land use was 95% classified suitable to spatial detail plan. To determine the suitability of the building in this study, it was seen from the activities of the building and the height of the building. Based on building activities, 9.30% of building activities that are not allowed and another 90.70% are classified as conditionally allowed buildings, allowed, limited alowed and limited and conditional. Meanwhile, based on the height of the building, there are 82.7% of buildings that comply with the spatial detail plan.

Land is an important factor in human life. In addition of land use that continue to increase every year. Land use is an element of meeting needs. This situation often makes the condition of the land around it questionable the content and level of land productivity. Land whose productivity level is lost can cause critical land to occur. Coupled with the occurrence of uncontrolled development, land productivity has decreased. By using the application of remote sensing, it is able to monitor land conditions, one of which is by using Sentinel-2A data. Sentinel-2A image data was selected to identify the condition or distribution of critical land and critical land parameters that has the most influence on criticality level of the land with Sentinel-2A imagery with a spatial resolution of 10 meters for Red, Green, Blue, and Near-Infrared canals to perform NDVI classification processing. closely related to vegetation. Based on the Regulation of the Director General of Watershed Management and Social Forestry Number: P.4/V-SET/2013 concerning the Technical Guidelines for the Preparation of Spatial Data for Critical Lands, there are 5 parameters for determining the criticality of the processed land as indicators, including the level of erosion distribution, productivity land, land management, slope, and vegetation density. Based on the results of the study, the researchers found that the distribution of critical land in Lahat Regency was 19 hectares or 0.56%, the critical class was 36,090 hectares or 10.1%, the critical potential class was 142,140 hectares or 42.1%, the class which was slightly critical is 156,860 hectares or 46.5%, and non critical class is 3 hectares or 0.074%. for very critical class. These results can be seen with the parameter that most affects the criticality of the land is vegetation density.

Forest and land fires are a disaster that occurs almost every year on Sumatra Island. Ogan Komering Ilir is one of the regencies in South Sumatra Province with a high number of hotspots causing forest and land fires every year. Prevention efforts are important to reduce the impact caused by forest and land fires on various aspects of life. One of them is by building a web-based Geographic Information System (WebGIS) for the distribution of hotspots as a form of early warning and detection system by utilizing VIIRS Nightfire (VNF) data from the remote sensing technology of the Suomi-NPP satellite which has Visible Infrared Imaging Radiometer Suite (VIIRS) active sensors which have been processed with the Nightfire algorithm. The Leaflet JavaScript library plays an important role in adding to the functionality of WebGIS with a wide selection of available plugins and easy-to-read source code to make web-based spatial information more interactive. The prototype of WebGIS with the name OKIApi has been successfully developed and has several key features such as displaying information on the distribution of hotspots that have been classified by temperature; the priority level of firefighting areas and the vulnerability level of flammable areas based on the type of land cover; route to the hotspot or the fire department locations; a chart of the estimated burned area from the source footprint of hotspot; and a chart of the number of hotspots per day that have been classified by temperature. The percentage value of the web feasibility for the functionality test to 13 WebGIS features is 100% with a very good predicate, the usability test is 91.5% with a very good predicate, and the portability test on 18 web browsers applications is 100% with a very good predicate.

The hot mudflow released by Lapindo Mud Volcano periodically requires a large storage space. It is resulting the change in the main function of Kali Porong which is the channel for mud to the river mouth. This causes changes in water quality at Kali Porong estuary. The purpose of this study was to monitor water quality at Kali Porong estuary using Sentinel 2 image data with Total Suspended Solid (TSS) and chlorophyll-a analysis. Cloud computing technology can process image data into useful information. One of the open source cloud computing platforms is Google Earth Engine (GEE). In this platform, there is a database for storing satellite image data, including Sentinel-2. In addition to storing remote sensing data, GEE can process images quickly using the Java scripting language. In this study, monitoring was carried out in February-June 2021. The results show the average value of chlorophyll-a each month from February to June was 2.78 μg/m³, 2.76 μg/m³, 2.74 μg/m³, 2.98 μg/m3, and 3.2 mg/l. The average monthly TSS values from February to June were 16.11 μg/m³, 15.91 μg/m³, 15.76 μg/m³, 17.45 μg/m³, and 19.86 μg/m³, respectively. The correlation test result for chlorophyll-a estimation is 0.654. In the other hand, the correlation test result for the estimated TSS is 0.652. The trophic status of the waters at Kali Porong estuary is in the eutrophic class or has been polluted. The results show a tendency for the area with polluted trophic status to increase from February to June.

Surabaya is one of the metropolitan cities in Indonesia. The large population in Surabaya causes a lot of development and land conversion. This situation can affect the temperature in Surabaya to be higher than the surrounding area, thus affecting the comfort of people for outdoor activities. The level of comfort can be known when the microclimate conditions in the area have been identified. This paper aims to analyze outdoor thermal conditions using temperature, humidity, wind, and land use data which will be visualized in three dimensions to get a more comprehensive understanding. This research is located in Pakuwon Trade Center (PTC). Data acquisition was carried out on four different types of land cover, namely local residential, apartments, main parking lots, and real estate area. The results show that apartments have the lowest comfort index followed by real estate, local residential, and main parking lots. However, the four areas have comfort from warm to hot with a predicted percentage of the discomfort of around 75% - 100%. This number shows that mitigation that can reduce extreme heat and increase outdoor comfort in PTC is needed.

Indonesia is an archipelago located at the meeting point of 3 tectonic plates which constantly collide over time, the energy due to the collision will accumulate and be able to cause large earthquakes that can generate tsunamis. The island of Java is in the subduction zone of these plates, which causes the southern part of Java to have a high earthquake potential. On April 10, 2021, an earthquake measuring M 6.1 occurred in the south of Blitar and Malang. This earthquake was felt by most of the people of East Java, If the earthquake is large enough, it can cause a tsunami on the southern coast of East Java. Therefore, modeling was carried out using the FLOW module of Delft3D software while using earthquake parameters with a strength of M 9.1 which is the worst possible scenario on the southern coast of East Java. The results of this study indicate the fastest tsunami arrival time is 21 minutes, the highest maximum tsunami height is 20 meters, the highest run-up reaches 17,5 meters, and the furthest inundation reaches 765 meters along the southern coast of Blitar and Malang Regency.

The Lembang Fault is a major fault located at the northern Bandung. This fault has a high disaster risk, including ground shaking, surface rupture, and possible landslides or liquefaction. This fault can cause earthquakes of 6.5-7 magnitude, making 8 million people in four Regencies and Cities around West Bandung Regency, Cimahi City, Bandung City and Bandung Regency exposed to major disaster risk. This research focuses on assessing the Perception of Disaster Proneness of the Lembang Fault in the District of Cisarua, West Java, Indonesia. This research was conducted using a case study and deductive-qualitative approach. In addition, this research was carried out by combining engineering and social research methodologies. The survey location point is determined based on hazard data (Peak Ground Acceleration data), vulnerability data (covering building density, slope, curvature, soil character, distance from faults, etc.) and population density data. This study indicates that the public's perception of the disaster in the Lembang Fault is very subjective. How they act is based on experience or based on their beliefs. Therefore, an essential part of this research is assessing and measuring the community's perception of the Lembang Fault towards disasters that may arise. The government must make serious efforts to convey that the disaster in the Lembang fault is much bigger and can happen at any time. Therefore, building resilient communities that genuinely understand the dangers of living in disaster-prone areas is essential.

Landslide susceptibility mapping is an initial measure in the landslide hazard mitigation. This study aims to evaluate landslide susceptibility in the Cisangkuy Sub-watershed, a part of Bandung Basin. Twenty-seven landslide variables were involved in this modeling derived from various data sources. As a target, 25 landslide polygons obtained through a visual interpretation of Google Earth timeseries images and 33 landslide points obtained from a field survey and an official landslide report, were used as landslide inventory data. All spatial data were prepared in the same cell size referring to the highest spatial resolution of data involved in this modeling, i.e., 8.34 m. Fifty-eight (58) landslide locations covering an area of 0.87 Ha are equivalent to 1040 cells in the raster format. In total, 2040 samples consisting of landslides and non-landslides with the same ratio, were trained using random forest algorithm. Non-landslides were sampled randomly from landslide-free cells. This modeling was executed using R environment. In this study, the result was two labels, susceptible and non-susceptible. This model provided an excellent performance, its accuracy reached 98.56%. This research needs an improvement to provide a probability that has a range of 0 to 1 to show the level of landslide susceptibility.

PT. Hutama Karya (Persero), according to Presidential Regulation No. 100 of 2014 and No. 117 of 2015, obtained an assignment to construct and operate 24 sections of Trans Sumatera Toll Road along 2,789 km, including Padang - Pekanbaru Toll Road, where almost all of the segments are located in fault areas and in areas with diverse rock formation. In terms of the number of fault locations, the toll road has a greater risk of earthquakes. Whereas in terms of varying rock formations, construction planning and improper structure determination will cause a highly cost-enhancing effect. In the planning stage, the selection of route is one of the mitigations to minimize the risks and impacts of the earthquake disaster. Toll road trajectories are designed optimally by considering the movement of the earth's plates based on fault data on these locations and data on rock formations for the construction and structure plan of the Toll Road. Input data needed is Geological Secondary Data and Topographic Data containing information on fault areas and rock formations. Therefore, planning with Quantm Trimble software is the right solution. Determining the route with Quantm Trimble software is one of the effective and efficient methods. The main key in determining routes by Quantm Trimble is the software algorithm which can determine the route quickly by considering the main constraints such as avoiding fault areas, avoiding an area with certain rock formations also determining the construction methods on certain rock formation areas. Quantm Trimble software is able to generate several alternative routes based on user-defined constraints, including accommodating the automatic selected smoothing process according to the specified road geometry standard. The software greatly accommodates the determination of the plan by considering risk and disaster management, as well as being able to manage costs well by determining the construction method plan quickly and accurately.

This research was conducted to see the correlation between residual anomaly map, geological map, and isoseismal map and how they contribute to the determination of earthquake-prone areas. Moreover, the area studied is an area that is difficult to obtain geophysical data such as urban areas. The residual anomaly is obtained by calculating the bouguer anomaly from elevation data and free-air correction satellite, which then through the FFT process changes the spatial domain to the frequency domain in MATLAB. Thus, it can separate regional anomaly maps with residuals. Using the overlaying technique on two maps, namely residual anomaly maps with isoseismal, a clear correlation was found between the residual anomaly value and the impact of the earthquake as well as the validation of the geological map in the area

The purpose of this research is to analyze the geographical shape of the earth's face with the 472319 Hahslm patterns in geomorphology. Earth undergoes the process of forming water and soil so that it becomes a continent and an archipelago. The composition of the sea and land is 7:3. The object of this study is the shape of the sea and land on earth and the Quran 13.31. This research was conducted by studying literature from books, journals, electronic media, and earth globes, and world atlases. The methodology used is descriptive-analytical. The method used is reflexivity, similarity, and dynivity with the formula 472319 Hahslm. The result obtained is the process of changing the shape of the earth's surface towards a pattern of worship by the meaning of the holy book in the form of cutting the earth according to the meaning of the Quran. The Quran formula 13.31 forms an arrangement of 444 in the form of letter number 13, namely 1+3=4, and from 31, namely 3+1=4. The third pattern 4 is obtained from the number of letters hijaiyaj in the word for cutting the earth as many as 13 letters meaning 1 + 3 = 4. The geomorphological reflectivity of the earth resembles the pattern of 444. With the composition of the oceans and lands of 7:3 which has a difference of four from 7-3=4. In the formula, 472319 Hahslm derived from the Quran 15.87 means the Quran in the form of 6438 verses. The second meaning of 4 is obtained from the multiplication of 7 and 2, namely 7x2=14 by taking the first four words of the fourteenth phrase. And the third meaning of 4 from addition is 3+1+9=13 where the root of digit 13 is 1+3=4. The second geography of the earth is at number 4 from the geomorphology of the continents of Asia, Africa, Europe, and Australia which forms a hand pattern of 319. With the tips of small fingers located in parts of countries that have islands located in the eastern to southeastern Asian continents such as parts of Russia, Japan, Korea, China, and the Philippines. Meanwhile, the Southeast Asian region forms the index finger or pattern 1 which has a similarity to the shape of the Indonesian archipelago with the tip being large in Australia and New Zealand. Big finger thumb or pattern 9 has similarities with mainland India, Pakistan, Bangladesh in South Asia. While the Americas have similarities with pattern 7 or V for South America and pattern 2 for North America. Waters and islands are needed in a pandemic that has an economic effect. The conclusion is that the geography of the earth forms 472319 show the earth is worshiping even during the Covid economic era.

Slip rates on active faults derived from the interseismic velocity field are critical to understanding seismic hazards in metropolitan cities. This study integrated the data from the Global Navigation Satellite System (GNSS) and Interferometric Synthetic Aperture Radar (InSAR) to evaluate the interseismic velocities in the second-largest city in Indonesia, Surabaya, where branches of the Kendeng fault (the Surabaya and the Waru faults) pass through. Data from 16 campaign-mode GNSS stations collected between 2017 and 2020 from previous research are reprocessed to estimate the velocity field. Horizontal velocities under the ITRF frame range between -23.8 mm/yr and 47.9 mm/yr toward the southeast. Vertical velocities generally range between -1.3 mm/yr and -112.2 mm/yr. Sentinel-1A SAR data of both ascending and descending tracks acquired between November 2014 and July 2020 were used to generate the interferograms with the InSAR Scientific Computing Environment (ISCE) software. Furthermore, cumulative displacement time series were constructed using the Small BAseline Subset (SBAS) technique within the Generic InSAR Analysis Toolbox (GIAnT). This study also carried out the detection of outlier SAR epochs to improve the precision of Line-of-sight (LOS) velocity estimates. The LOS velocities range from -14.8 to 10.8 mm/yr in the ascending track and from -12.7 to 9.5 mm/yr in the descending track. These results will facilitate the detection of coupling behaviors on the Kendeng fault branches, which can improve our understanding of seismic risks in the Surabaya area.

Floods are one of the natural disasters that always occur in various regions in the Republic of Indonesia. Several flood points were recorded in Banjarasri Village and Kedungbanteng Village, Tanggulangin District, Sidoarjo Regency. There is an allegation that one of the factors causing the flooding in the two villages was caused by land subsidence. Therefore, it is necessary to conduct a study to monitor the magnitude of land subsidence in the area. In this study, the Global Positioning System (GPS) observation method was used. The research was carried out by collecting data from six points which were carried out over three periods of time, namely on 22 - 27 October 2020, 24 - 29 November 2020, and 24 - 29 March 2021. Based on the results of processing and analyzing GPS data, the observed values for shift and motion vectors are obtained. There were five points of land subsidence statistically, which included BM02, BM03, BM04, BM05, and BM06 with values of respectively 3.6 cm, 7.3 cm, 5.9 cm, 4.8 cm, and 5.2 cm. The horizontal position vector moves in various ways, where BM01 and BM04 move to the southwest as far as 2.5 cm and 1.9 cm, BM05 moves to the southeast with a shift of 3.3 cm, and BM06 moves to the northeast with a shift of 4.2 cmFloods are one of the natural disasters that always occur in various regions in the Republic of Indonesia. Several flood points were recorded in Banjarasri Village and Kedungbanteng Village, Tanggulangin District, Sidoarjo Regency. There is an allegation that one of the factors causing the flooding in the two villages was caused by land subsidence. Therefore, it is necessary to conduct a study to monitor the magnitude of land subsidence in the area. In this study, the Global Positioning System (GPS) observation method was used. The research was carried out by collecting data from six points which were carried out over three periods of time, namely on 22 - 27 October 2020, 24 - 29 November 2020, and 24 - 29 March 2021. Based on the results of processing and analyzing GPS data, the observed values for shift and motion vectors are obtained. There were five points of land subsidence statistically, which included BM02, BM03, BM04, BM05, and BM06 with values of respectively 3.6 cm, 7.3 cm, 5.9 cm, 4.8 cm, and 5.2 cm. The horizontal position vector moves in various ways, where BM01 and BM04 move to the southwest as far as 2.5 cm and 1.9 cm, BM05 moves to the southeast with a shift of 3.3 cm, and BM06 moves to the northeast with a shift of 4.2 cm.

There are many petroleum mining activities scattered in developing countries, such as Indonesia. Indonesia is one of the largest oil-producing countries in Southeast Asia with the 23rd ranking. Since the Dutch era, Indonesia has produced a very large amount of petroleum. One of the oil producing areas is "A" Village. There is an old well that produces petroleum oil which is still active with an age of more than 100 years, for now the oil well is still used by the local community as the main source of livelihood. With this activity, resulting in an oil pattern around the old oil refinery, which over time will absorb into the ground. This study aims to analyze and identify the oil pattern around the old oil refinery in the "A" area. The data used is in the form of High-Resolution Satellite Imagery (CSRT), namely Pleiades-1B with a spatial resolution of 1.5 meters. Data were identified using the Deep Learning Semantic method. For the limitation of this research is the administrative limit of XX Regency with a scale of 1: 25,000 as supporting data when cutting the image. The method used is the Deep Learning Convolutional Neural Network series. This research is based on how to wait for the method of the former oil spill which is the consideration of the consideration used. This study produced a land cover map that was classified into 3 categories, namely oil patterns area, area not affected by oil and vegetation. As a supporting value to show the accuracy of the classification results, an accuracy test method is used with the confusion matrix method. To show the accuracy of this study using thermal data taken from the field. Thermal data used in the form of numbers that show the temperature of each land cover. Based on the above reference, a research related to the analysis of very high-resolution image data (Pleiades-1B) will be conducted to examine the oil pattern. This research uses the deep learning series convolutional neural network (CNN) method. With this research, it is hoped that it can help agencies in knowing the right method to identify oil in mainland areas.

Global Navigation Satellite System (GNSS) is a navigation system that uses satellite signals to determine its position, which consists of several satellites arranged in a constellation system. GNSS transmits signals to receivers on Earth. The GNSS receiver determines the user's position, speed, and time by processing the signals transmitted by the satellites. The initial purpose of launching the GNSS was for navigation purposes, but along with its development, GNSS can be used for the purposes of observing deformation of the earth's crust and in studying the atmosphere. The delayed wave data when passing through the ionosphere can be used to obtain Total Electron Content (TEC) values which then used to study ionospheric disturbances. Ionospheric disturbances are caused by various phenomena, the most common one is the ionospheric disturbances caused by the induction of acoustic and gravitational waves excited by co seismic crustal motions from large earthquakes. Ionospheric disturbances that happened before an earthquake are called Pre-seismic Ionospheric Disturbances and those that occur after an earthquake are called Co-seismic Ionospheric Disturbances (CID). Most studies of ionospheric disturbances still provide information on the timing and value of TEC anomalies in 2D form. Therefore, in this study, a 3D ionosphere profile modelling using computed 3D tomography will be carried out. The 3D information provided is in the form of time, ionosphere altitude and TEC anomaly value by utilizing GNSS data. The TEC anomaly value is obtained from the calculation of linear combination of the ionosphere. This study aims to obtain a spatial and temporal analysis of the CID caused by the West Sumatra Earthquake on March 2, 2016.

Data containing information on the terrain elevation model is necessary for several uses related to human activities, such as development planning, spatial planning, disaster modeling, disaster mitigation planning, land productivity estimation, etc. Information about the ground elevation can be presented in a 3-dimensional topographical model such as Digital Terrain Model (DTM). There are several technologies used to form DTM data, including by using LiDAR and radar satellites (Sentinel-1). The hydro enforcement method is used to process DTM with LiDAR data by modifying the elevation value of LiDAR data in water areas during data processing. The height of this feature is modified digitally to achieve hydrological connectivity. This method aims to produce a DTM according to the principles of hydro enforcement and hydro flatten. While for processing DTM radar data, the InSAR method is used. InSAR is a remote sensing technique to extract three-dimensional information from the earth's surface with the phase of radar waves. Additional data of morphological information and break lines were added to provide more representative information on the actual situation. The result of this research is the value of vertical geometry accuracy (LE90) of DTM to RBI data with a scale of 1:25,000. In this research, 5 kinds of DTM have been successfully formed with LE90 vertical accuracy values are as follows: LiDAR DTM with LE90 of 4.614 m; InSAR DTM with LE90 of 9.583 m; InSAR breakline with LE90 of 9.433 m; InSAR RBI assimilation with LE90 of 2.532 m; and InSAR DTM-LiDAR assimilation with LE90 of 4.077 m. DTM with the highest accuracy based on Topographic Map (RBI) 1:25,000 is InSAR DTM RBI assimilation and the lowest accuracy is DTM InSAR without breakline and assimilation data.

One of the stages in the topographical mapping work is the measurement of the horizontal control framework, which is currently almost all done using GNSS satellite technology. The online post-processing services provided by the Indonesian Geospatial Information Agency (BIG) are called xpos-InaCORS. Using this service, measurements are possible using only 1 GNSS receiver can be used for measurement and obtained of the mapping control framework. This research was conducted to determine the accuracy of the online post-processing method by xpos-InaCORS BIG when used as a control point for the mapping of the route of the channel or road which tends to be elongated with a 3rd order (SNI 19-6724-2002). The coordinates of the results of the online processing calculation are compared with the results of the static differential method, which is calculated using commercial software (Leica Infinity). The results showed that at this location, observations for 15 minutes on each benchmark were able to produce an accuracy of 1 centimeter, and to comply with the qualifications of order 3rd SNI, observations must be a minimum duration of 75 minutes. The cost of observation on the online post-processing method requires 60% of the static differential. Observation at 75 minutes resulted in an average accuracy of northing (N) = 15mm and easting (E) = 8mm.

The Gravity Method based on TOPEX satellite data is a one of geophysical method which from satellite observations. The gravity method investigate the gravitational field from one to another observation point. The principle of this method has the ability to distinguish the mass material density from its environment, so that the subsurface structure can be identified. In this research, gravity method is used to identify subsurface structures that are suspected of Probolinggo Fault and identify the rock lithology. From TOPEX we get free air anomaly and then applied the correction process to obtain Complete Bouguer Anomaly (CBA) value. The CBA value is processed interpolation to create CBA map, and then the map is filtered by butterworth to obtain regional and residual maps. The value of high gravity acceleration is 0.076 - 19.74 mGal indicating compact rocks. Meanwhile, based on the residual anomaly map, the value of smaller gravity acceleration is -0.92 - 0.9 mGal indicates lower compacting rocks with smaller mass. The gravity acceleration contrast on the residual anomaly, on the north side of fault line (0.12 mGal to 0.45 mGal) and on the south side (-0.92 mGal to -0.043 mGal), is interpreted as normal fault. Furthermore, 3D modelling shows density value less than 2 gr/cm³ we can interpret as pyroclastic fall, in between 2 gr/cm³ until 2.4 gr/cm³ is sandstone and more than 2.4 gr/cm³ is igneous rock such as andesit. 2D slicing modelling show presence the shear fault, so we can suspect this area have oblique fault with west-east direction.

Earthquake can be caused by several things, one of which is due to an active fault. To mitigate earthquake disasters that can be caused by the Probolinggo Fault, measurement of the microtremor geophysical method is carried out to analyze seismic vulnerability. In this study, the microtremor measurements were carried out on 30 measurement points. The data obtained from measurements are then processed using EasyHVSR software to obtain natural frequency (f₀) and natural amplification (A₀) values. This value is then used to create a microtremor microzonation map, which is seismic vulnerability index, based on natural frequency and amplification . it founded that low natural frequency mostly founded on eastern of measurement area, caused by thick sedimentary from Lamongan volcanic. High amplification mostly founded from middle to western area, and high seismic vulnerability index founded on western of measurement area, include Maron and Krucil Sub-district. It means seismic wave can very destructive on those area.

Karst aquifers can be a source of water supply, especially for the community in Donorojo District, which is one of the areas with the worst drought crisis in Pacitan Regency and requires a sustainable solution to the problem of water needs. Therefore, the study and management of karst formations are very important because of their abundance and potential in forming subsurface aquifer karst aquifers. The recharge rate is one of the basic parameters in the management of the consumption and maintenance of this resource. In addition, the distribution of aquifer locations, aquifer characteristics, and the quality of groundwater forming the aquifer need to be known. This study aims to assess aquifers in the Karst area of Donorojo, Pacitan based on recharge rate and spatial distribution. The APLIS method can estimate surface recharge rates and present the results as a map of the spatial distribution of aquifer recharge rates by utilizing a Geographical Information System (GIS). The results of the analysis using the APLIS method, the groundwater recharge rate in the Donorojo Pacitan karst area is divided into 4 classes, namely very low, low, moderate, and high. Almost the entire Donorojo karst area has a high groundwater recharge rate, this means that the area needs to be used as a groundwater protection zone and it is important to carry out good groundwater management, especially to overcome the problem of drought.

Tidal data has a significant role in various fields in hydrographic surveys and navigation, port planning, and other coastal management. The number of fixed tide stations in Indonesia is minimal compared to the vast territorial waters in Indonesia. So that for areas that are not covered by tidal fixed stations, direct tidal observation with a certain length of observation is necessary, and of course, this requires quite expensive costs. Fortunately, there are regional and global tidal data predictions that can be used to determine tidal conditions in Indonesian waters. In this study, the regional (BIG) and the global (FES2014 and TPXO9) tidal data prediction models were validated with direct observation in the five locations such as Surabaya, Gresik1, Gresik2, Bangkalan, and Giligenting for 39 hours. The root means square error (rmse) calculation results show that in the five locations, the BIG tidal prediction has the smallest rmse value in three tidal stations at Gresik 1, Gresik 2, and Gili Genting with 0.303 m, 0.050 m, and 0.155 m respectively. At the same time, the TPXO9 tidal model shows the biggest rmse at Gresik 1, Gresik 2, and Bangkalan with 0.420 m, 0.195 m, and 0.630 m, respectively.

The availability of geoids, especially in survey and mapping activities, is useful for transforming the geometric heights obtained from observations of the Global Navigation Satellite System (GNSS) into orthometric heights that have real physical meanings such as those obtained from waterpass measurements. If a geoid is available, the orthometric heights of points on earth can be determined using the GNSS heighting method. The use of modern survey and mapping instruments based on satellite observations such as GNSS is more efficient in terms of time, effort, and cost compared to the accurate waterpass method. According to the Indonesian Geospatial Information Agency (BIG) it is stated that the application of geoid as a national Vertical Geospatial Reference System has an adequate and ideal category if the accuracy is higher than 15 cm. Recent studies have shown that it is possible to generate local geoid models with centimetre accuracy by utilizing airborne gravity data. We calculate free-air gravity anomaly data is calculated by processing airborne gravity and GNSS data using the Stokes Integral method on AGR software. Next a geoid model is created by calculating the contribution of three components, namely the long wave component represented by the EGM2008 global geoid data model, the shortwave component represented by the Shuttle Radar Topography Mission (SRTM) data and the medium wave component represented by the free-air gravity anomaly data. The geoid model validation was carried out using the geoid fitting method for geoid accuracy by calculating the difference between the gravimetric geoid and the geometric geoid and comparing it with the global geoid model EGM2008 degrees 2190. As a result, the total geoid model accuracy value was determined to be 49.4 cm on gravimetric geoid undulations with a standard deviation of 7.1 cm. Meanwhile, the results of the EGM2008 geoid undulation accuracy test at 2190 degrees resulted in an accuracy of 51.9 cm with a standard deviation of 9.9 cm. These results indicate that the local geoid model from airborne gravity measurement data produces a geoid model with a higher accuracy than the global geoid model EGM2008 degrees 2190. However, the accuracy of the resulting data is still below the BIG standard of 15 cm, so further research is needed to produce a geoid model which conforms to the standard.

Land use planning in an area will refer to the regulations that have been established by the City Planning Office of each region. This is because each region has the authority to plan spatial plans in their respective regions. The border area is an area whose land use can be influenced by two different regional regulations. This is because the border area is a special area located on the border between two regions, each of which has spatial planning regulations. Gayungan District is one of the sub-districts included in the Border Area between Surabaya City and Sidoarjo Regency. To prevent overlapping spatial regulations that may occur in Gayungan District, it is necessary to monitor the suitability of land use using geographic information system technology and remote sensing. The data used in this study are the 2019 Gayungan District RDTRK Map and very high resolution satellite imagery of Pleiades Surabaya City 2019. The method used is the Object Based Image Analysis (OBIA) method. The result of this research is the suitability of land use in Gayungan District. A land use can be said to be suitable if the existing land use is in accordance with the land use in the plan. Meanwhile, land use is said to be inappropriate if the existing land use is different from the planned spatial use. All land use classes in Gayungan District in 2019 had a higher percentage of unsuitable land than the percentage of suitable land. Each percentage of land is not suitable for each land use class, namely: water body class by 92.593%, road class by 78.035%, industrial class by 77.838%, defense class by 76.706%, green open space class by 69.736%, and residential class by 52,27%. So it can be said that the land use in Gayungan District in 2019 was not in accordance with the plans in the City Spatial Detail Plan Map for 2018-2038, but the land use could be appropriate in its designation for the future, because there is a possibility of development for residential class, industrial class, and defense class on open land that is still widely available.

Badan Informasi Geospasial (BIG) is a government agency engaged in the field of Geospatial Information (IG). BIG provides several services that can be accessed by the general public and related to IG. One of the services provided by BIG is the Indonesia Continuously Operating Reference System (InaCORS). InaCORS is divided into various services, as Rinex data services, Online Post-Processing, RTK NTrip, and Mobile InaCORS. This study aims to determine the effectiveness and accuracy of InaCORS services for GNSS surveys using the Rapid Static method and Network RTK. The rapid static survey data is processed using online post-processing services and Network RTK (iMax, Max, and Nearest) will use InaCORS points as a base reference. This study also uses the results of the Total Station tool as comparison data. The results showed that the average value of the difference between the rapid static coordinates and the TS observations was dN = 0.353 m dE = 0.180 m and dZ = 0.233 m, while the Network RTK and TS coordinates were dN = 0.408 m dE = 0.184 m and dZ = 0.176 m.

This study aims to determine the effect of physiography based on slope and land cover for water control in Kali Lamong watershed. The data used in this research are DEM data and Landsat 8 imagery data. The process of processing slope data is through conversion coordinates system, DEM clip, create slope, reclassify, dissolve shapefile, and slope classification analysis. Landsat 8 data processing goes through a process through conversion coordinates system, composite band, crop composite, extent shapefile, sharpen band, unsupervised classification, and land cover classification analysis. Slope classification maps and land cover classification maps are used for flow coefficient classification for physiographic analysis based on slope and land cover for water control in Kali Lamong watershed. On the land cover classification map, five land classifications were obtained, namely agriculture (158413000 m²), settlements (72701400 m²), industrial land (11571600 m²), plantations (46017800 m²), and waters (15268500 m²). On the slope classification map obtained 5 classifications, as flat with a slope of 0-8% (288469544 m²), as slope with a slope of 8-15% (7656738 m²), as rather steep with a slope of 15-25% (1905360 m²), as steep with a slope of 25-45 (526614 m²), and as very steep with a slope of more than 45% (32148 m²). From the combination of Landsat 8 image data and slope data, flow coefficient analysis was carried out. The flow coefficient is influenced by land cover and slope. From this research, the classification of low flow coefficient is less than 0.25, medium flow coefficient is 0.25-0.5, and high flow coefficient is more than 0.75. The average flow coefficient of Kali Lamong watershed is 0.49 with a moderate flow coefficient classification value. This shows that 49% of the runoff water is in Kali Lamong watershed. The higher the flow coefficient value, the water runs off the surface. So that it can be used as an initial study for the technical planning of Kali Lamong hydrology and the development, improvement, utilization, and control of water flow in Kali Lamong.

Atmospheric phase delay is one of the most significant errors limiting the accuracy of Interferometric Synthetic Aperture Radar (InSAR) results. In this research, we used the Generic Atmospheric Correction Online Service for InSAR (GACOS) data to correct the tropospheric delay modeling from the persistent scatterers' InSAR monitoring. Eighty-one (81) Sentinel-1A images and tropospheric delay maps from GACOS monitored land subsidence in Surabaya city between 2017 and 2019. InSAR processing was carried out using the GMTSAR software, continued with StaMPS and TRAIN, which were used to correct the tropospheric delay of PSInSAR-derived deformation measurements. The results before and after the atmospheric phase delay correction using GACOS were confirmed and analyzed in the main subsidence area. The findings of the experiments reveal that the atmospheric phase affects the mean LOS velocity results to some extent. The average difference between PS-InSAR before and after tropospheric correction is 1.734 mm/year with a standard deviation of 0.550 mm/year. The significance test of the two variables, 95%, showed that the tropospheric correction with GACOS data could affect the PS-InSAR results. Furthermore, GACOS correction may increase the error at some points, which could be due to its turbulence data's low accuracy.

Geoid model was chosen as a vertical reference in Indonesia based on the Head of the Geospatial Information Agency Regulation (Perka BIG) No. 15 of 2013 concerning the Indonesian Geospatial Reference System (SRGI2013). Therefore, the development of local geoid models continues to be carried out to obtain good accuracy. The geoid is formed through three main components: long wave, short wave, and medium wave. One of the longwave components is the global geopotential model obtained from topographic, terrestrial, altimetry, and gravity satellite data. Along with the development of technology and gravity observation methods, the global model has many variations, so it is necessary to determine the global model that is most suitable for the geographical conditions in Indonesia. EGM2008 is often used in local geoid modeling in Indonesia based on research that compares several global models. Still, it does not rule out the possibility of a new global model that is more suitable for Indonesia.

Nowadays, Global Geopotential Models (GGMs) can be used as a reference to develop more detailed regional/local geoids, or they can be used to provide geoid heights on their own. Since 2000, several GGMs have been released, and they are mainly derived from satellite gravity measurements, satellite-only models, terrestrial gravimetry, altimeter-derived gravity data in marine areas, and airborne gravity data. With a precise geoid model, ellipsoidal heights obtained from GPS can be converted to orthometric heights, which is reasonably quite needed in Geodesy, Civil Engineering, etc. These heights reflect changes in topography as well as local variations in gravity. This paper evaluates some of the latest releases of high degree reference models and the satellite-only global gravity field model over Sudan using 19 GPS/Leveling stations. We have been selected 6 GGMs based on Gravity field Goce and Grace, and they released in 2020, 2019, 2014, 2008, and 1996 as shown in the International Centre for Global Earth Models website (ICGEM). The accuracy evaluation of the GGM models have been discussed, the accurate GGMs over Sudan are XGM2019e_2159 and GOCO05s, which have indicated -0.019 and 0.046 meters, respectively. The evaluation results produce valuable information to academia and geoid modeling research topics in Sudan, which shows the precise model from the selected GGMs in Sudan by using the available GPS/Leveling data.

Flood is one of the hydrometeorological disasters that occur in Surabaya, especially during the rainy season. The occurrence of floods brings a huge impact on the economy, the environment, and humans' losses. Based on the National Disaster Management Agency in Indonesia (BNPB) records, the flood inundation height in Surabaya reach about 10 -70 cm for 6 hours. Some anticipation efforts are required to minimize the impact. Therefore, this study aims to provide a flood vulnerability level assessment using the GIS and Analytical Hierarchy Process (AHP) method as a priority recommendation in increasing capacity. This research uses 4 criteria in the assessment including social, economic, physical, and environmental. Each criterion is divided into several classes with adjusted scoring values. The results of the AHP rank the social criteria as the highest weighted value of 0.42322. Furthermore, the results of the flood vulnerability assessment yield some areas that have the highest vulnerability value including Trengilismejoyo District, Wonocolo District, Dukuhpakis District, Sukolilo District, Krembangan District, Semampir District, and Benowo District.

Landsat 8 Satellite Imagery (Landsat Data Continuity Mission, LDCM) is a satellite product made by Orbital Science Corporation, which launched with The Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) instruments as the latest features. One of the Thermal Infrared Sensor (TIRS) instruments is called Band 10, that provide temperature information on the earth's surface. As many research conduct the temperature comparison between satellite imagery analysis and land cover temperature has been come with positive correlation for both of the variable. As to prove the temperature relationship, it is necessary to validate the actual temperature values on the earth's surface by conduct the temperature survey in the area using the temperature measurement tools. One of the tools is DJI Mavic Enterprise Dual Thermal camera as the camera that capable to take samples data of particular objects categories that included urban areas, waters, vegetation, open land, settlements, and industrial factories. Using the satellite imagery's temperature data and the land cover temperature data survey, comparing and accuration assessment are needed to see how close the value of both variable. The data processing carried out that both of the data have a positive correlation as the relationship, which have a Pearson correlation value of 0.892 and sig. (2-tailed) at the number 0.000000068. This correlation value showed that the relationship between both data is acceptable as the both data can represent each other to conduct any research. However, as the satellite imagery contains 29,85% of cloud cover, the temperature obtained lower in the Landsat 8 satellite image rather than the actual temperature on the earth's surface.

Java is Indonesia's and the world's most populous island. The increase in population on the island of Java reduces the area of forest and other vegetation covers. Landslides, floods, and other natural disasters are caused by reduced vegetation cover. Furthermore, it has the potential to lead to the extinction of flora and fauna. The Normalized Difference Vegetation Index (NDVI) can be used to monitor the vegetation cover. This study analyzes the NDVI changes value from 2005 to 2020 using Terra and Aqua MODIS image data processed using Google Earth Engine. Processing was carried out in some stages: down-setting, performing NDVI processing, calculating monthly average NDVI, calculating annual average NDVI, and analyzing. From the study results, the NDVI value of Terra and Aqua MODIS data has a solid but imperfect correlation coefficient due to differences in orbital time which causes differences in solar zenith angle, sensor viewing angle, and azimuth angle. Then from this study, it was found that overall, changes in vegetation density cover on the island of Java decreased, which was indicated by the NDVI decline rate of -0.00047/year. The most significant decrease in NDVI value occurred in the period 2015–2016, covering an area of 13994.630 km², and the most significant increase in NDVI occurred in the period 2010–2011, covering an area of 2256.101 km².

COVID-19 is spreading into Indonesia and has reached tens of thousands of cases as of September 30, 2020. It was recommended by the American Public Health Association and the Centers for Disease Control and Prevention to remain physically active during COVID-19 quarantine by regularly visiting parks and green spaces as it can protect the body against the consequences of quarantine impacting physical and mental health. In this research, green space was monitored by using remotely sensed data. The green space distribution was obtained from the calculation of the Greenness Index from Landsat-8 Surface Reflectance Tier 1 satellite imagery processed through the Google Earth Engine platform. This study was conducted to determine the value of Greenness Index (GI), Case Fatality Rate (CFR) value due to COVID-19, and the relationship between them in 42 sub-districts in DKI Jakarta in the period of April to September 2020. Twenty-eight subdistricts (67%) showed negative correlation values that indicated that more green space in a region affects lower CFR growth.

Tropical peatlands make up almost ten percent of the land surface in Indonesia, making peat fires detrimental not only for global atmospheric carbon levels, but also to public health and socioeconomic activities in the region. Indonesian Fire Danger Rating System (FDRS) was developed based on the Canadian Forest Fire Weather Index System (CFFWIS), using three different fuel codes and three indices representing fire behaviour. Daily Fire Weather Index (FWI) calculation is done by the Meteorological Climatological and Geophysical Agency (BMKG) with data from its synoptic weather stations network. Distribution of such weather stations are sparse, therefore this paper reports on the development of Fire Weather Index calculator on Google Earth Engine, using high resolution weather data, provided by weather model and remote-sensing open datasets. The resulting application is capable of generating daily maps of FWI components to be used by the Indonesian Fire Danger Rating System.

Garbage or waste is basically a residual material resulting from human activities and natural processes that have no economic value anymore. The volume of waste in Malang City and Malang Regency every year always increases, so the existing waste final processing site will no longer be able to accommodate the pile of garbage. Therefore the Malang City Government plans to collaborate with the Malang Regency Government in making an integrated regional waste landfill and processing site. In this study, an analysis of the determination of the appropriate location for regional waste final processing for Malang City and Malang Regency was carried out using the Simple Additive Weighting (SAW) method. The SAW method is a weighted summation method, which can make a more precise assessment, based on the predetermined criteria and preference weights. Preference weights were determined by pairwise comparison method. The criteria used are geological hazardous areas, distance from drinking water sources, land slope level, distance from settlements, protected areas and distance from airports. The final result in this study is a map of the appropriate location for a regional waste final processing site and an analysis of the location for the best regional final processing site. The location map is classified into three, namely: not feasible with a total area of 54,774.33 ha, less feasible with a total area of 170,846.49 ha and feasible with a total area of 130,096.63 ha.

The Opak Fault is an active fault that can potentially cause earthquakes in Yogyakarta. Periodic monitoring of the Opak Fault activity was previously used more GNSS observation data from the measurement campaign by the Geodesi Geometri dan Geodesi Fisis (GGGF) Laboratory Team, Geodetic Engineering Department, Faculty of Engineering, Universitas Gadjah Mada. However, there are several CORS BIG stations located in Yogyakarta. The CORS BIG data is used to increase the precision of the Opak Fault monitoring station. Therefore, the addition of the CORS is evaluated to obtain a displacement in the monitoring station. The computation of the displacement velocity value of the Opak Fault monitoring station has been done before using the Linear Least Square Collocation and grid search methods. The other method, namely the kriging method, needs to be evaluated for producing a more precise displacement velocity value. The research data includes GNSS campaign and CORS BIG data for six years, 2013 to 2020. The CORS stations around DIY are JOGS and CBTL. The GNNS data were processed to determine the solution for the daily coordinate, displacement, and standard deviation values for each Opak Fault monitoring station. The displacement velocity value is generated by the Linear Least Square method then reduced from the influence of the Sunda Block. The velocity value is used in the strain value estimation around the Opak Fault area at each station using the kriging method combined with the gaussian sequential simulation technique. The estimated displacement velocities are examined for statistical significance compared to the research of Adam (2019) and Pinasti (2019). This research generates the value of the displacement velocity in the east and north components of 12.39 to 30.99 mm/year and 1.96 to -14.11 mm/year, respectively. The displacement direction of all monitoring stations is dominant to the southeast. The Sunda Block reduced the displacement velocity. The east and north components are -2.32 to 2.28 mm/year and -0.52 to 4.2 mm/year, respectively. The displacement direction is towards the northwest. The strain estimation using the kriging method combined with the gaussian sequential simulation technique obtained an average strain value of 0.05 microstrain/year. The result of the data processing at each station has different arrow lengths, meaning that each location has a different strain value.

According to information of areas at high risk of drought provided by Central Java disaster risk assessment in 2016 - 2020, Klaten Regency is in the top ten at high risk of drought in Central Java. Drought is an annual disaster in this region, which usually occurs during the dry season. The impact of the drought has caused some areas to experience a lack of clean water. For the purpose of disaster mitigation in anticipating and minimizing drought disasters losses, it is necessary to analyze the level of drought with a decision-making system by comparing two methods, namely the AHP with TOPSIS. Both methods are decision-making methods that are composed of various criteria to obtain an alternative sequence of choices. Both the AHP and TOPSIS methods produces weight values and a positive ideal solution value, respectively. These are used as input data in the mapping of drought vulnerability analysis with Geographical Information Systems (GIS). The results of the analysis are visualized with a map that shows the level of drought vulnerability. AHP and TOPSIS method decision making generates the order of the drought classes in predicting the distribution of areas experiencing drought. To validate the model, the authors compare the results of the analysis of drought vulnerability of the two methods with drought data from BPBD (Local Agency for Disaster Prevention) and DPUPR (Public Works and Public Housing Department). The results show that AHP provides better results than TOPSIS based on results validation with BPBD and DPUPR data. By comparing the two models with BPBD data, the results show that the percentage of AHP suitability is higher than TOPSIS at 47,619% and 19,048% respectively.