Agricultural Land Evaluation Using GIS-Based Matching Method in Highland Areas for Oil Palm Cultivation

Oil palm (Elaeis guineensis) is one of the commodity crops and mostly found in tropical lands. This study aimed to analyze the current and potential land suitability for oil palm using the geographic information system (GIS) technique. The study was conducted in the Ranau area, State of Sabah, Malaysia. Field activity was carried out to collect soil samples and land information in the study area. Land suitability was then assessed using the matching method and GIS software was employed to produce a land suitability map for oil palm. The results indicated that the current land suitability classes in the study area were highly suitable (S1) with a total area of 99,118 ha (27.4%), moderately suitable (S2) with 110,108 ha (30.4%), marginally suitable (S3) with 109,533 ha (30.2%), currently not suitable (N1) with 2,728 ha (0.7%), and permanently not suitable (N2) with 40,693 ha (11.3%). While the potential land suitability classes showed highly suitable (S1) was 198,206 ha (54.7%), moderately suitable class (S2) was 123,281 ha (34%) and permanently not suitable (N2) was 40,693 ha (11.3%). Suitable areas that could be planted with oil palm included the gently sloping flank and the low gradient slope margin. Availability of nutrients and work capability were the dominant limiting factors in the study area. The output of this study recommends that the Ranau area had the potential for oil palm although it still needs land improvements for sustainable oil palm cultivation

Imputing Rainfall Data for Flood Simulation in Citarum River, West Java

The central role of the Citarum River as a buffer to meet the needs of agricultural irrigation, industrial activities, and raw water in the six surrounding districts, including 80% of the population of Jakarta, has experienced a decline in conditions from up-downstream. That way, a lot of data is available regarding the adaptation of floods, drought, and other water source functions for an integrated concept for Citarum. The focus of the study is in the Central Citarum Zone by using 5 and 10 years of rainfall intensity (time series), actualizing the runoff coefficient, Intensity Duration Frequency (IDF) modeling to the formulation of the peak runoff discharge. This achievement is realized by applying Gumbel's Method and Mononobe's Equation and optimizing the 2D HEC-RAS software. Experimental data from 2010 to 2019 indicated that November was the highest rainfall of 448.07 mm/hour, while the lowest was in July with a value of 52.50 mm/hour. The simulation results show an increase in flow rate up to 11%, which means it affects the river's capacity to accommodate the overflow load. Furthermore, this simulation is equipped with a map of the flood-affected areas with a peak discharge scenario in November

PEMANFAATAN SISTEM INFORMASI GEOGRAFIS UNTUK KAJIAN LINGKUNGAN HIDUP SEBAGAI PEMBELAJARAN DI ERA PENDIDIKAN 4.0 BAGI GURU GEOGRAFI DI DAERAH SUMATERA SELATAN

In education 4.0, digital technology and information systems need to be implemente in the education sector from the school to the university level. Specifically, the Geographic Information System (GIS) application needs to be mastered for the geography teachers to develop creativity related to their learning material. Based on this reason, the community dedication activity aims to improve the competency of geography teachers in the South Sumatera Province in the application of GIS for environmental studies. The method used in this activity is the GIS webinar activity and the evaluation of the action using a questionnaire. The results found that all participating teachers have well understood the webinar material. It indicates the output of the comprehension index polls before and after joining the webinar, which increased from 35% to 86%. Besides, another result also showed that the majority of teachers gave high assessments of the percentage satisfaction index that related to some aspects such as webinar activity (91.9%), speaker (87.9%), and the relevance of webinar materials to their job (96.8%). In conclusion, this webinar activity has a tremendous positive impact in improving the competency of geography teachers, especially for the application of GIS for environmental studies. --- Pada era pendidikan 4.0 ini, penggunaan teknologi digital dan sistem informasi perlu diimplementasikan dalam bidang pendidikan dari tingkat sekolah hingga universitas. Untuk guru geografi khususnya, aplikasi Sistem Informasi Geografis (SIG) sangat perlu dikuasai sehingga guru bisa mengembangkan kreativitas terkait materi ajar kepada siswa. Berdasarkan hal tersebut, tujuan kegiatan pengabdian kepada masyarakat ini adalah untuk meningkatkan kompetensi guru-guru geografi di daerah Provinsi Sumatera Selatan dalam pemanfaatan SIG untuk kajian lingkungan hidup. Metode yang digunakan yaitu kegiatan webinar SIG dan evaluasi kegiatan menggunakan kuesioner. Hasil kegiatan mendapatkan bahwa semua guru mampu memahami materi webinar yang disampaikan oleh narasumber dengan baik, ini ditunjukkan dengan hasil polling tingkat pemahaman peserta pada sebelum dan setelah pembekalan materi yang mengalami peningkatan dari 35% kepada 86%. Hasil evaluasi kegiatan juga menunjukkan bahwa mayoritas guru memberikan persentase indeks kepuasan yang tinggi terkait kegiatan webinar (91,9%), narasumber (87,9%), dan relevansi materi dengan pekerjaan (96,8%). Secara keseluruhan, kegiatan webinar ini memberikan dampak positif yang besar dalam peningkatan kompetensi guru-guru geografi terutama untuk penerapan SIG untuk kajian lingkungan hidup

Effect of COVID-19 movement control order policy on water quality changes in Sungai Langat, Selangor, Malaysia within distinct land use areas

For the first time in the 21st century, many nations have been forced to conduct a lockdown that restricts their industrial, transportation, and social activities to avoid the extensive COVID-19 spread. Therefore, our study aimed to analyze the status of water quality that was measured by suspended particulate matter (SPM) in Sungai Langat, Selangor, Malaysia using the remote sensing technique. The study was concerned with rivers located in distinct land-use areas such as high-density urban, low-density urban, and agricultural areas. The study period included before and after movement control order (MCO) periods that occurred in February 2020 and February 2021, respectively. The SPM levels in each period were calculated using the remote sensing technique through Landsat-8 OLI images then they were analyzed using statistical analysis. The results of the remote sensing technique showed the highest decrease of SPM levels during the MCO period was observed in Sungai Langat within a high-density urban area (34.1%). Then, the SPM levels in all Sungai Langat raised significantly after the MCO period with the highest change at 31.6%. Rainfall and erosion factors had a significant impact on the SPM level through natural processes but the COVID-19 restriction had a direct impact on the SPM level due to the restriction of industrial and social activities. The suspended activities have made the lower emission compared with before the COVID-19 period in 2019

Soil erosion assessment in Tasik Chini Catchment using remote sensing and gis techniques

Over many years, forested land transformation into urban, agriculture and mining areas within Tasik Chini Catchment become more intense. These activities have negatively affected the catchment through soil erosion and increased the amount of sediments that deposited into the lake. Hence, the present study aimed to estimate soil erosion risk within Tasik Chini Catchment integrating the Revised Universal Soil Loss Equation (RUSLE) model and remotely sensed geospatial data. The multispectral imagery from LANDSAT 8 was used to provide up to date information on land cover within the catchment. The result shows the majority of Tasik Chini Catchment is classified at very low class ( 150 ton ha−1 yr−1) with total area of 120.04 ha (2.30%). Tasik Chini Catchment is very susceptible to soil erosion especially on northwest and southeast regions, where the main sources of soil loss come from the agricultural, new settlements and mining activities. To conclude, the estimation of soil erosion model using remotely sensed data can be used to build sustainable development strategy within Tasik Chini Catchment in the future

Agricultural Land Evaluation Using GIS-Based Matching Method in Highland Areas for Oil Palm Cultivation

Oil palm (Elaeis guineensis) is one of the commodity crops and is mostly found in tropical lands. This study aimed to analyze the current and potential land suitability for oil palm using the geographic information system (GIS) technique. The study was conducted in the Ranau District, Sabah State, Malaysia. Field activity was carried out to collect soil samples and land information in the study area. Land suitability was then assessed using the matching method and GIS software was employed to produce a land suitability map for oil palm. The results indicated that the current land suitability classes in the study area were highly suitable (S1) with a total area of 99,118 ha (27.4%); moderately suitable (S2) with 110,108 ha (30.4%); marginally suitable (S3) with 109,533 ha (30.2%); currently not suitable (N1) with 2,728 ha (0.7%) and permanently not suitable (N2) with 40,693 ha (11.3%). Meanwhile, the potential land suitability classes showed 198,206 ha (54.7%) for S1; 123,281 ha (34%) for S2 and 40,693 ha (11.3%) for N2. Suitable areas that could be planted with oil palm included the gently sloping flank and the low gradient slope margin. Availability of nutrients and work capability were the dominant limiting factors in the study area. The outputs of this study recommend that the Ranau District has the potential for oil palm although it still needs land improvements for sustainable oil palm cultivation

Changes in air quality during and after large scale social restriction periods in Jakarta city, Indonesia

COVID-19 outbreak has constrained human activities in Jakarta, Indonesia during the large-scale social restriction (LSSR) period. The objective of this study was to evaluate the changes in the spatial variation of air pollutants over Jakarta during and after the LSSR periods. This study used satellite retrievals such as OMI, AIRS, and MERRA-2 satellite data to assess spatial variations of NO2, CO, O3, SO2, and PM2.5 from May to June 2020 (during the LSSR period) and from July to August 2020 (after the LSSR period) over Jakarta. The satellite images were processed using GIS software to increase the clarity of the images. The relationship between air pollutants and meteorological data was analyzed using Pearson correlation. The results showed the levels of NO2, PM2.5, O3, and CO increased by 59.4%, 21.2%, 16.2%, and 1.0%, respectively, while SO2 decreased by 19.1% after the LSSR period. The temperature value was inversely correlated with PM2.5, NO2, and SO2 concentrations. Furthermore, the backward trajectory analysis revealed that air pollutants from outland areas such as the east and southeast carried more particulate matter and gases pollutants, which contributed to the air pollution during and after the LSSR periods. As a whole, the COVID-19 outbreak had bad impacts on human health, but the increase in air pollutants levels after loosening the LSSR policy could also lead to a higher risk of severe respiratory diseases. This study provides new insight into air pollutant distribution during and after LSSR periods and recommends an effective method of mitigating the air pollution issues in Jakarta

Potential of Normalized Difference Vegetation Index for Mapping of Soft Clay Area in Paddy Fields of Kedah, Malaysia

Mapping of soft clay area in paddy fields uses remote sensing and GIS technique is the fastest way to obtain an accurate location of soft clay in a large scale area. It can be an alternative way to change conventional method like in-situ observation that is expensive and labor intensive. Therefore, this study aimed to investigate the normalized difference vegetation index (NDVI) to map soft clay area in paddy fields Kedah, Malaysia. To analyze soft clay area comprehensively, the study was carried out in three different periods; before paddy planting, after paddy planting and harvest. Ground-truth data of soft clay area was collected from study area during fieldwork activity and compared with NDVI values that produced from Landsat 8 image. Result of study showed NDVI map in period of before paddy planting could be a good indicator for mapping soft clay area because it gave a higher accuracy value than the other periods, with overall accuracy (85%) and kappa coefficient (0,84). Total area of soft clay from the highest value was showed in period of before paddy planting (1.856,97 ha), followed by after paddy planting (656,73 ha) and harvest (401,85 ha) periods, respectively

Clustering analysis of pm2.5 concentrations in the South Sumatra Province, Indonesia, using the merra-2 satellite application and hierarchical cluster method

The air quality monitoring system is the most prominent tool for monitoring air pollution levels, especially in areas where forest fires often occur. The South Sumatra Province of Indonesia is one of the greatest contributors to haze events in Indonesia due to peatlands fires. It does not sufficiently possess a ground monitoring system to cover rural areas, and thus, delayed actions can result in severe air pollution within this region. Therefore, the aim of this current study is to analyze the distribution and classification of PM2.5 observed from 2019 to 2021 within the South Sumatra Province, Indonesia. The acquisition of PM2.5 data was from the Merra-2 Satellite with a spatial resolution of 0.5˚ × 0.625˚ and an hourly interval. The hierarchical cluster analysis (HCA) was applied in this study for the clustering method. The result of the study revealed that the daily mean of PM2.5 levels varied from 5.9±0.01 to 21.3±0.03 μg/m3. The study area was classified into three classes: high pollution areas (HPA), moderate pollution areas (MPA) and low pollution areas (LPA), based on the HCA method. The average level of PM2.5 observed in HPA was notably higher, at 16.8±0.02 μg/m3, followed by MPA and LPA. Furthermore, this study indicated that the highest level of PM2.5 was found during 2019, with a severe haze event in the study area due to the intensive burning of forests, bush and peatlands. As a whole, the output of this study can be used by authorities for air quality management due to forest fire events in a certain area

Effect of COVID-19 Movement Control Order Policy on water quality changes in Sungai Langat, Selangor, Malaysia within distinct land use areas

For the first time in the 21st century, many nations have been forced to conduct a lockdown that restricts their industrial, transportation, and social activities to avoid the extensive COVID-19 spread. Therefore, our study aimed to analyze the status of water quality that was measured by suspended particulate matter (SPM) in Sungai Langat, Selangor, Malaysia using the remote sensing technique. The study was concerned with rivers located in distinct land-use areas such as high-density urban, low-density urban, and agricultural areas. The study period included before and after movement control order (MCO) periods that occurred in February 2020 and February 2021, respectively. The SPM levels in each period were calculated using the remote sensing technique through Landsat-8 OLI images then they were analyzed using statistical analysis. The results of the remote sensing technique showed the highest decrease of SPM levels during the MCO period was observed in Sungai Langat within a high-density urban area (34.1%). Then, the SPM levels in all Sungai Langat raised significantly after the MCO period with the highest change at 31.6%. Rainfall and erosion factors had a significant impact on the SPM level through natural processes but the COVID-19 restriction had a direct impact on the SPM level due to the restriction of industrial and social activities. The suspended activities have made the lower emission compared with before the COVID-19 period in 2019