Analisis Potensi Daerah Rawan Longsor di Kecamatan Bawen dan Tuntang dengan Metode Simple Additive Weighting (SAW)

2021 ◽  
Vol 1 (2) ◽  
pp. 17-25
Author(s):  
Mira ◽  
Merryana Lestari ◽  
Candra Gudiato ◽  
Sri Yulianto Prasetyo ◽  
Charitas Fibriani
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Wetness Index ◽  
Simple Additive Weighting

Intensitas curah hujan yang tinggi pada penghujung tahun 2020 dan awal tahun 2021 tidak hanya menyebabkan beberapa daerah di Indonesia terendam banjir, namun juga tanah longsor. Tanah Longsor dapat terjadi karena adanya pergerakan tanah di musim penghujan serta dipengaruhi kondisi tektonik di Indonesia yang selalu berubah-ubah. Kecamatan Bawen dan Tuntang adalah dua Kecamatan yang berada di Kabupaten Semarang, Jawa Tengah. Kedua daerah tersebut dilanda bencana banjir dan tanah longsor pada April 2020 silam. Kerugian materiil dan moril dari penduduk setempat tentunya tidak dapat dihindari. Untuk melakukan pencegahan sedini mungkin agar dapat menekan kerugian di masa mendatang, perlu dilakukan penelitian mengenai potensi daerah-daerah yang rawan longsor di Kecamatan Bawen dan Tuntang. Analisis yang dilakukan menggunakan metode Simple Additive Weighting (SAW) untuk menghitung persentase suatu daerah terjadi longsor. Adapun parameter yang digunakan antara lain tutupan lahan, kemiringan kelerengan, curah hujan, Soil Adjusted Vegetation Index (SAVI), Normalized Difference Vegetation Index (NDVI), dan Normalized Difference Wetness Index (NDWI). Hasil dari penelitian ini menunjukkan bahwa  tingkat kerawanan bencana tanah longsor di Kecamatan Bawen dan Tuntang tergolong “kurang rawan”. Hasil dari penelitian ini diharapkan dapat menjadi dokumen perencanaan tata ruang berbasis mitigasi bencana tanah longsor di Kabupaten Semarang, khususnya pada Kecamatan Bawen dan Tuntang.

scholarly journals Identification of Surface Water Storing Sites Using Topographic Wetness Index (TWI) and Normalized Difference Vegetation Index (NDVI)

2018 ◽  
Vol 8 ◽  
pp. 91-100
Author(s):  
Belete Berhanu ◽  
Ethiopia Bisrat
Keyword(s):  
Surface Water ◽  
Water Resource ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Cost Effective ◽  
Water Shortage ◽  
Sample Volume ◽  
Runoff Generation ◽  
Topographic Wetness Index ◽  
Wetness Index

Ethiopia is endowed with water and has a high runoff generation area compared to many countries, but the total stored water only goes up to approximately 36BCM. The problem of water shortage in Ethiopia emanates from the seasonality of rainfall and the lack of infrastructure for storage to capture excess runoff during flood seasons. Based on this premise, a method for a syndicate use of topography, land use and vegetation was applied to locate potential surface water storing sites. The steady-state Topographic Wetness Index (TWI) was used to represent the spatial distribution of water flow and water stagnating across the study area and the Normalized Difference Vegetation Index (NDVI) was used to detect surface water through multispectral analysis. With this approach, a number of water storing sites were identified in three categories: primary sources (water bodies based), secondary sources (Swampy/wetland based) and tertiary sources (the land based). A sample volume analysis for the 120354 water storing sites in category two, gives a 44.92BCM potential storing capacity with average depth of 4 m that improves the annual storage capacity of the country to 81BCM (8.6 % of annual renewable water sources). Finally, the research confirmed the TWI and NDVI based approach for water storing sites works without huge and complicated earth work; it is cost effective and has the potential of solving complex water resource challenges through spatial representation of water resource systems. Furthermore, the application of remote sensing captures temporal diversity and includes repetitive archives of data, enabling the monitoring of areas, even those that are inaccessible, at regular intervals.

Pemetaan Pulau Kecil Gelasa Kabupaten Bangka Tengah

2019 ◽  
Vol 2 (1) ◽  
pp. 11-14
Author(s):  
Wahyu Adi
Keyword(s):  
Coral Reefs ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Image Interpretation ◽  
Vegetation Coverage ◽  
Small Island ◽  
Shallow Waters ◽  
Small Islands ◽  
Seagrass Beds ◽  
Cover Density

Pulau Kecil Gelasa merupakan daerah yang belum banyak diteliti. Pemetaan ekosistem di pulau kecil dilakukan dengan bantuan citra Advanced Land Observing Satellite (ALOS). Penelitian terdahulu diketahui bahwa ALOS memiliki kemampuan memetakan terumbu karang dan padang lamun di perairan dangkal serta mampu memetakan kerapatan penutupan vegetasi. Metode interpretasi citra menggunakan alogaritma indeks vegetasi pada citra ALOS yaitu NDVI (Normalized Difference Vegetation Index), serta pendekatan Lyzengga untuk mengkoreksi kolom perairan. Hasil penelitian didapatkan luasan Padang Lamun di perairan dangkal 41,99 Ha, luasan Terumbu Karang 125,57 Ha. Hasil NDVI di daratan/ pulau kecil Gelasa untuk Vegetasi Rapat seluas 47,62 Ha; luasan penutupan Vegetasi Sedang 105,86 Ha; dan penutupan Vegetasi Jarang adalah 34,24 Ha.   Small Island Gelasa rarely studied. Mapping ecosystems on small islands with the image of Advanced Land Observing Satellite (ALOS). Previous research has found that ALOS has the ability to map coral reefs and seagrass beds in shallow water, and is able to map vegetation cover density. The method of image interpretation uses the vegetation index algorithm in the ALOS image, NDVI (Normalized Difference Vegetation Index), and the Lyzengga approach to correct the water column. The results of the study were obtained in the area of Seagrass Padang in the shallow waters of 41.99 ha, the area of coral reefs was 125.57 ha. NDVI results on land / small islands Gelasa for dense vegetation of 47.62 ha; area of Medium Vegetation coverage 105.86 Ha; and the coverage of Rare Vegetation is 34.24 Ha.

HEALTHINESS OF OIL PALM PLANTATION TOWARDS SUSTAINABILITY OF ENVIRONMENT

2020 ◽  
Vol 7 (1) ◽  
pp. 21
Author(s):  
Faradina Marzukhi ◽  
Nur Nadhirah Rusyda Rosnan ◽  
Md Azlin Md Said
Keyword(s):  
Oil Palm ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Satellite Image ◽  
Vegetation Indices ◽  
Soil Nutrient ◽  
Oil Palm Plantation ◽  
Sustainable Environment ◽  
Moisture Analysis ◽  
The Relationship

The aim of this study is to analyse the relationship between vegetation indices of Normalized Difference Vegetation Index (NDVI) and soil nutrient of oil palm plantation at Felcra Nasaruddin Bota in Perak for future sustainable environment. The satellite image was used and processed in the research. By Using NDVI, the vegetation index was obtained which varies from -1 to +1. Then, the soil sample and soil moisture analysis were carried in order to identify the nutrient values of Nitrogen (N), Phosphorus (P) and Potassium (K). A total of seven soil samples were acquired within the oil palm plantation area. A regression model was then made between physical condition of the oil palms and soil nutrients for determining the strength of the relationship. It is hoped that the risk map of oil palm healthiness can be produced for various applications which are related to agricultural plantation.

ANALISIS SPEKTRAL CITRA SPOT 7 UNTUK IDENTIFIKASI KAWASAN MANGROVE DI PANTAI TIMUR KABUPATEN LAMPUNG SELATAN

2019 ◽  
Vol 3 ◽  
pp. 1213
Author(s):  
Nirmawana Simarmata ◽  
Fitralia Elyza ◽  
Rezalian Vatiady
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index

Konversi hutan manggrove merupakan sumber utama emisi CO dengan jumlah sebesar 1,7 ± 0,6 Pg karbon per tahun. Kegiatan konversi hutan mangrove menjadi lahan tambak melepaskan cadangan karbon ke atmosfir dalam jumlah yang cukup berarti. Ekspansi usaha pertambakan udang di kawasan pesisir Provinsi Lampung semakin meluas dari tahun ke tahun yang berdampak serius pada kondisi hutan mangrove. Kebijakan pembukaan tambak baru telah mengubah bentang hutan mangrove dan akan menimbulkan kerugian sosial yang jauh lebih besar. Menanggapi permasalahan tersebut, Indonesia menjadi salah satu negara yang mengikuti program Reduce Emission from Deforestation and Degradation atau REDD+ dalam melakukan inventarisasi karbon hutan. Indonesia memiliki potensi sumberdaya hutan mangrove yang sangat melimpah. Potensi hutan mangrove Indonesia cukup besar, Indonesia memiliki luas hutan mangrove terbesar di dunia. Salah satunya di Kabupaten Lampung Selatan merupakan kawasan dengan tutupan yang relatif luas di Provinsi Lampung. Karakteristik hutan mangrove dianalisis berdasarkan nilai spektral nya dengan menggunakan indeks vegetasi. Jenis data penginderaan jauh yang digunakan untuk penelitian ini adalah citra SPOT 7. Citra SPOT 7 dianalisis menggunakan Normalized Difference Vegetation Index (NDVI) sehingga diperoleh nilai kehijauan objek mangrove. Nilai indeks vegetasi pada kawasan penelitian mempunyai range antara 0.2 – 0.7. Nilai indeks vegetasi digunakan sebagai parameter untuk memetakan kawasan hutan mangrove di Kabupaten Lampung Selatan.

TEMPERATURA DE SUPERFÍCIE E A RELAÇÃO COM O ÍNDICE DE VEGETAÇÃO POR DIFERENÇA NORMALIZADA (NDVI) NA MICROBACIA DO RIO DA BATATEIRAS, CRATO-CE

2019 ◽  
Vol 21 (2) ◽  
pp. 1310-1320
Author(s):  
Cícera Celiane Januário da Silva ◽  
Vinicius Ferreira Luna ◽  
Joyce Ferreira Gomes ◽  
Juliana Maria Oliveira Silva
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Temperature Measurement ◽  
Rainy Season ◽  
Satellite Images ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Landsat 8 ◽  
Low Density ◽  
Difference Map

O objetivo do presente trabalho é fazer uma comparação entre a temperatura de superfície e o Índice de Vegetação por Diferença Normalizada (NDVI) na microbacia do rio da Batateiras/Crato-CE em dois períodos do ano de 2017, um chuvoso (abril) e um seco (setembro) como também analisar o mapa de diferença de temperatura nesses dois referidos períodos. Foram utilizadas imagens de satélite LANDSAT 8 (banda 10) para mensuração de temperatura e a banda 4 e 5 para geração do NDVI. As análises demonstram que no mês de abril a temperatura da superfície variou aproximadamente entre 23.2ºC e 31.06ºC, enquanto no mês correspondente a setembro, os valores variaram de 25°C e 40.5°C, sendo que as maiores temperaturas foram encontradas em locais com baixa densidade de vegetação, de acordo com a carta de NDVI desses dois meses. A maior diferença de temperatura desses dois meses foi de 14.2°C indicando que ocorre um aumento da temperatura proporcionado pelo período que corresponde a um dos mais secos da região, diferentemente de abril que está no período de chuvas e tem uma maior umidade, presença de vegetação e corpos d’água que amenizam a temperatura.Palavras-chave: Sensoriamento Remoto; Vegetação; Microbacia.                                                                                  ABSTRACTThe objective of the present work is to compare the surface temperature and the Normalized Difference Vegetation Index (NDVI) in the Batateiras / Crato-CE river basin in two periods of 2017, one rainy (April) and one (September) and to analyze the temperature difference map in these two periods. LANDSAT 8 (band 10) satellite images were used for temperature measurement and band 4 and 5 for NDVI generation. The analyzes show that in April the surface temperature varied approximately between 23.2ºC and 31.06ºC, while in the month corresponding to September, the values ranged from 25ºC and 40.5ºC, and the highest temperatures were found in locations with low density of vegetation, according to the NDVI letter of these two months. The highest difference in temperature for these two months was 14.2 ° C, indicating that there is an increase in temperature provided by the period that corresponds to one of the driest in the region, unlike April that is in the rainy season and has a higher humidity, presence of vegetation and water bodies that soften the temperature.Key-words: Remote sensing; Vegetation; Microbasin.RESUMENEl objetivo del presente trabajo es hacer una comparación entre la temperatura de la superficie y el Índice de Vegetación de Diferencia Normalizada (NDVI) en la cuenca Batateiras / Crato-CE en dos períodos de 2017, uno lluvioso (abril) y uno (Septiembre), así como analizar el mapa de diferencia de temperatura en estos dos períodos. Las imágenes de satélite LANDSAT 8 (banda 10) se utilizaron para la medición de temperatura y las bandas 4 y 5 para la generación de NDVI. Los análisis muestran que en abril la temperatura de la superficie varió aproximadamente entre 23.2ºC y 31.06ºC, mientras que en el mes correspondiente a septiembre, los valores oscilaron entre 25 ° C y 40.5 ° C, y las temperaturas más altas se encontraron en lugares con baja densidad de vegetación, según el gráfico NDVI de estos dos meses. La mayor diferencia de temperatura de estos dos meses fue de 14.2 ° C, lo que indica que hay un aumento en la temperatura proporcionada por el período que corresponde a uno de los más secos de la región, a diferencia de abril que está en la temporada de lluvias y tiene una mayor humedad, presencia de vegetación y cuerpos de agua que suavizan la temperatura.Palabras clave: Detección remota; vegetación; Cuenca.

Developing land-state maps of Tram Chim National Park in Vietnam based on monitoring results

2020 ◽  
Vol 963 (9) ◽  
pp. 53-64
Author(s):  
V.F. Kovyazin ◽  
Thi Lan Anh Dang ◽  
Viet Hung Dang
Keyword(s):  
National Park ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Likelihood Method ◽  
Wetland Area ◽  
Water Index ◽  
Effi Ciency ◽  
Normalized Difference Water Index ◽  
Specially Protected Natural Areas ◽  
Protected Natural Areas

Tram Chim National Park in Southern Vietnam is a wetland area included in the system of specially protected natural areas (SPNA). For the purposes of land monitoring, we studied Landsat-5 and Sentinel-2B images obtained in 1991, 2006 and 2019. The methods of normalized difference vegetation index (NDVI) and water objects – normalized difference water index (NDWI) were used to estimate the vegetation in National Park. The allocated land is classifi ed by the maximum likelihood method in ENVI 5.3 into categories. For each image, a statistical analysis of the land after classifi cation was performed. Between 1991 and 2019, land changes occurred in about 57 % of the Tram Chim National Park total area. As a result, the wetland area has signifi cantly reduced there due to climate change. However, the area of Melaleuca forests in Tram Chim National Park has increased due to the effi ciency of reforestation in protected areas. Melaleuca forests are also being restored.

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