scholarly journals Monitoring Urban Expansion and Loss of Agriculture on the North Coast of West Java Province, Indonesia, Using Google Earth Engine and Intensity Analysis

2022 ◽  
Vol 2022 ◽  
pp. 1-16
Author(s):  
Laju Gandharum ◽  
Djoko Mulyo Hartono ◽  
Asep Karsidi ◽  
Mubariq Ahmad
Keyword(s):  
Agricultural Land ◽  
Urban Expansion ◽  
Google Earth ◽  
North Coast ◽  
Land Conversion ◽  
Intensity Analysis ◽  
West Java ◽  
Lulc Change ◽  
The North ◽  
Google Earth Engine

Uncontrolled urban expansion resulting from urbanization has a disastrous impact on agricultural land. This situation is being experienced by the densely populated and fertile island Java in Indonesia. Remote sensing technologies have developed rapidly in recent years, including the creation of Google Earth Engine (GEE). Intensity analysis (IA) is increasingly being used to systematically and substantially analyze land-use/land-cover (LULC) change. As yet, however, no study of land conversion from agriculture to urban areas in Indonesia has adopted GEE and IA approaches simultaneously. Therefore, this study aims to monitor urban penetration to agricultural land in the north coastal region of West Java Province by applying both methods to two time intervals: 2003–2013 and 2013–2020. Landsat data and a robust random forest (RF) classifier available in GEE were chosen for producing LULC maps. Monitoring LULC change using GEE and IA has demonstrated reliable findings. The overall accuracy of Landsat image classification results for 2003, 2013, and 2020 were 88%, 87%, and 88%, respectively. IA outputs at interval levels for all categories showed that the annual change-of-area rate was higher during 2013–2020 than during 2003–2013. At the category level, IA results showed that the area of agricultural land experienced net losses in both periods, with net loss in 2013–2020 being 2.3 times greater than that in 2003–2013 (∼1,850 ha per year). In contrast, the built-up area made net gains in both periods, reaching almost twice as much in the second period as in the first (∼2,030 ha per year). The transition-level IA performed proved that agricultural land had been the primary target for the expansion of built-up areas. The most extensive spatial distribution of land conversion from agriculture to built-up area was concentrated in the regencies of Bekasi, Karawang, and Cirebon. These findings are intended to provide stakeholders with enrichment in terms of available literature and with valuable inputs useful for identifying better urban and regional planning policies in Indonesia and similar regions.

scholarly journals MONITORING AND ASSESSMENT OF AGRI-URBAN LAND CONVERSION USING MULTI-SENSOR REMOTE SENSING AND GIS TECHNIQUES

2021 ◽  
Vol V-3-2021 ◽  
pp. 117-124
Author(s):  
D. C. Fargas Jr. ◽  
G. A. M. Narciso ◽  
A. C. Blanco
Keyword(s):  
Remote Sensing ◽  
Agricultural Land ◽  
Google Earth ◽  
High Rate ◽  
Landsat 8 ◽  
Land Conversion ◽  
Lulc Change ◽  
Random Forest Classification ◽  
Forest Classification ◽  
Single Sensor

Abstract. Continuous agricultural land conversion poses threat to food security but this has not been monitored due to ineffectual policies. One of the Philippine provinces with a high rate of conversion is the rice-producing province of Cavite. To assess the spatiotemporal dynamics of agricultural land conversion in Cavite, this study aims to develop an operational methodology to produce Land Use and Land Cover (LULC) change maps using a multi-sensor remote sensing approach for decision making and planning. LULC maps were generated using Random Forest Classification of Landsat 8 and Sentinel-1 image collections. Spectral indices, combinations of radar polarizations (VV, VH), and their principal components were included to improve its accuracy. Conversion maps were generated by taking the bi-annual difference of LULC maps from 2016 to 2019. Accuracy was assessed using visual inspection with Google Earth Pro. Classification was carried out using single-sensor (optical or radar) and multi-sensor (optical and radar) approach in combination with three feature selection algorithms, namely, Sandri and Zuccolotto (2006), Liaw and Wiener (2015), Kursa and Rudnicki (2010). Multi-sensor and single sensor yielded similarly high overall accuracies (OA = 96%) with the exception of single-sensor radar approach (OA = 53%). Multi-sensor approaches exhibit high accuracies (Cumulative Accuracy = 91%) in detecting agricultural to built-up LULC change up to 5,000 square meters unlike single-sensor optical approach (Cumulative Accuracy = 76%). Among the multi-sensor approaches, the method of Liaw and Wiener (2015) remains to be superior as it only uses eight (8) variables.

scholarly journals Watershed Health Changes based on Vegetated Land Cover in the Upper Citarum Watershed, West Java, Province, Indonesia

2021 ◽  
Vol 940 (1) ◽  
pp. 012045
Author(s):  
K Marko ◽  
D Sutjiningsih ◽  
E Kusratmoko
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Supervised Classification ◽  
Agricultural Land ◽  
Landsat Imagery ◽  
West Java ◽  
Health Changes ◽  
The North ◽  
Health Level ◽  
Watershed Health

Abstract The increase in built-up land and the decrease in vegetated land due to human activities have worsened watershed health from time to time. This study aims to assess the watershed’s health and changes every ten years based on the percentage of vegetated land cover except agricultural land in the Upper Citarum watershed, West Java. Land cover information was obtained from the processing of Landsat imagery in 1990, 2000, 2010, and 2020 based on remote sensing using the supervised classification method. The watershed health level is determined by calculating the percentage of vegetated land cover of 173 catchments. The results show that the area of the vegetated land cover decreased from 1990 to 2000, then increased from 2000 to 2010, and decreased again from 2010 to 2020. Changes in the area of vegetated land in each period of the year affect the health level of the watershed in a spatiotemporal manner. Although these changes occur in a fluctuating manner, the number of unhealthy catchments in the Upper Citarum watershed is increasing, especially in the Ci Kapundung sub-watershed in the north and Ci Sangkuy in the south.

scholarly journals Coastal Inundation and Land Subsidence in North Coast of West Java: A New Hazard?

2021 ◽  
Vol 925 (1) ◽  
pp. 012015
Author(s):  
T Solihuddin ◽  
S Husrin ◽  
E Mustikasari ◽  
A Heriati ◽  
T L Kepel ◽  
...  
Keyword(s):  
Land Subsidence ◽  
Satellite Image ◽  
Measurement Data ◽  
North Coast ◽  
Fish Ponds ◽  
West Java ◽  
Coastal Inundation ◽  
Industrial Estates ◽  
The North ◽  
Settlement Areas

Abstract The North Coasts of West Java are increasingly affected by human activities. The area has been utilized as settlement areas, industrial estates, and associated infrastructures including roads, school, hospital, market, etc. Consequently, this massive landuse and uncontrolled natural resources extraction have contributed to environmental degradation such as coastal erosion, accretion, pollution, inundation, and land subsidence. To date, we have so far very few field measurement data of land subsidence to support its importance. However, satellite image and on-ground observations used to determine spatio-temporal changes in the shoreline and area of inundation indicated the existence of land subsidence. Groundtruth data on selected areas also indicated the indicators of land subsidence such as damages of infrastructures including houses, roads, and sea dikes. The most noticeable shoreline changes in the North Coast of West Java are situated in Muara Gembong Bekasi and Legon Kulon Subang constituting maximum rates of shoreline retreat up to 200 and 150 m/year respectively for the last two decades (from 2000 to 2020). Whilst, the total areas of inundation in Muara Gembong and Legon Kulon based on recent satellite studies are 10.2 km2 and 7.4 km2 respectively. Coastal inundation might be linked to the combination of long-term behavior of oceanographic variables such as wave and sea level, in coincidence with hydrological changes due to river works (i.e. dam constructions and channellings) and an increase of settlement areas, fish ponds, groundwater extraction, etc. A set of preliminary engineering measures, in conjunction with sediment managing schemes, is proposed for the sustainable development of the coastal zone.

scholarly journals Monitoring Urban Expansion Using Remote-Sensing Data Aided by Google Earth Engine

2021 ◽  
Vol 3 (1) ◽  
pp. 1-8
Author(s):  
Majid Aghlmand ◽  
Gordana Kaplan
Keyword(s):  
Remote Sensing ◽  
Accuracy Assessment ◽  
Urban Expansion ◽  
Remote Sensing Data ◽  
Google Earth ◽  
Support Vector ◽  
Sensing Data ◽  
Google Earth Engine ◽  
Landsat Satellite ◽  
The City

Urbanizationis accompanied by rapid social and economic development, while the process of urbanization causes the degradation of the natural ecology. Direct loss in vegetation biomass from areas with a high probability of urban expansion can contribute to the total emissions from tropical deforestation and land-use change. Monitoring of urban expansion is essential for more efficient urban planning, protecting the ecosystem and the environment. In this paper, we use remote sensing data aided by Google Earth Engine (GEE) to evaluate the urban expansion of the city of Isfahan in the last thirty years. Thus, in this paper we use Landsat satellite images from 1986 and 2019, integrated into GEE, implementing Support vector machine (SVM) classification method. The accuracy assessment for the classified images showed high accuracy (95-96%), while the results showed a significant increase in the urban area of the city of Isfahan, occupying more than 70% of the study area. For future studies, we recommend a more detailed investigation about the city expansion and the negative impacts that may occur due to urban expansion.

scholarly journals Turismo, espaço urbano e meio ambiente: análise do projeto de esgotamento sanitário do município de Maragogi (AL)

2017 ◽  
Vol 10 (2) ◽  
Author(s):  
Antônio de Padua Gomes D´Almeida Lins ◽  
Lindemberg Medeiros de Araujo ◽  
Walter Matias Lima
Keyword(s):  
Urban Space ◽  
Municipal Government ◽  
Google Earth ◽  
Space Environment ◽  
North Coast ◽  
Central Component ◽  
Structured Interviews ◽  
Environment Analysis ◽  
Planning Strategy ◽  
The North

Considerada como atividade socioeconômica importante e dinâmica, o turismo tem sido adotado como alternativa de desenvolvimento pelo governo de numerosos países, estados e municípios. Entretanto, além dos impactos positivos, essa atividade, pode causar graves problemas para os sistemas ecológicos, as paisagens e as comunidades que compõem os destinos. Portanto, é importante que se adote um planejamento a longo prazo que contemple, dentre outros aspectos, o saneamento ambiental, uma dimensão central do desenvolvimento sustentável. Para que isto ocorra, é importante que os projetos de saneamento sejam bem dimensionados e que haja ampla participação popular uma vez que os residentes conhecem muito bem o território local. O objetivo deste trabalho é analisar a implantação e operação do projeto de esgotamento sanitário de Maragogi, município do litoral norte de Alagoas. Maragogi é o segundo maior destino turístico de Alagoas, com quase 4.000 leitos, além de ser considerado pelo Ministério do Turismo um dos 65 Destinos Indutores do país. Para se atingir o objetivo deste trabalho, considerou-se importante analisar a visão de: a) técnicos que trabalham para o governo municipal; b) moradores, empreendedores e líderes locais que têm relação com o território; c) turistas. Para tanto, o estudo utilizou uma abordagem qualitativa e adotou como instrumentos de coleta de dados entrevistas abertas, entrevistas semiestruturadas, registro fotográfico, observação direta e exames de imagens remotas (Google Earth). O estudo identificou que o projeto de saneamento não contemplou todo o território do município de Maragogi, deixando várias fontes de esgoto fora do seu alcance. Graves problemas ambientais relacionados ao saneamento continuam ocorrendo, apesar da prefeitura utilizar como uma das suas estratégias de marketing dizer que o município é 100% saneado. Tourism, urban space and environment: analysis of the sewage project of the municipality of Maragogi (AL, Brazil) ABSTRACT Regarded as an important and dynamic socio-economic activity, tourism has been adopted as a development alternative by governments of many countries, states and municipalities. However, in addition to its positive impacts this activity can cause serious problems for ecological systems, landscapes and communities that make up the destinations. Therefore, it is important to adopt a long-term planning strategy that includes, among other things, environmental sanitation, as a central component of sustainable development. For this to happen, it is important that sanitation projects are well sized and that there is adequate popular participation as residents know the local territory. The objective of this study is to analyze the implementation and operation of the Maragogi´s sewage project, in the north coast of Alagoas (Brazil). Maragogi is the second largest tourist destination of Alagoas, with almost 4,000 beds, in addition to being considered by the Ministry of Tourism as one of the country´s 65 tourism attractor projects (Projeto Destinos Indutores). To achieve the objective of this work, it was considered important to analyze the views of: a) planners working for the municipal government; b) residents, entrepreneurs and local leaders; and c) tourists. Therefore, the study used a qualitative approach and adopted the followings data-collection instruments: open interviews, semi-structured interviews, photographic survey, direct observation, and examination of remote images (Google Earth). The study identified that the sanitation project did not include the entire territory of the municipality of Maragogi, leaving several sources of sewage out of the project´s reach. Serious sanitation-related environmental problems continue to occur, despite the local government continue to use as one of their marketing strategies the message that the municipality is 100% sanitized. KEYWORDS: Tourism; Urban Space; Environment; Sanitation.

scholarly journals DEFORESTATION MAPPING USING SENTINEL-1 AND OBJECT-BASED RANDOM FOREST CLASSIFICATION ON GOOGLE EARTH ENGINE

2021 ◽  
Vol XLIII-B3-2021 ◽  
pp. 865-872
Author(s):  
V. Yordanov ◽  
M. A. Brovelli
Keyword(s):  
Land Cover ◽  
Agricultural Land ◽  
Weather Conditions ◽  
Google Earth ◽  
Random Forest Classification ◽  
Machine Learning Classification ◽  
Forest Classification ◽  
Object Based ◽  
Short Period ◽  
Google Earth Engine

Abstract. Deforestation can be defined as the conversion of forest land cover to another type. It is a process that has massively accelerated its rate and extent in the last several decades. Mainly due to human activities related to socio-economic processes as population growth, expansion of agricultural land, wood extraction, etc. In the meantime, there are great efforts by governments and agencies to reduce these deforestation processes by implementing regulations, which cannot always be properly monitored whether are followed or not. In this work is proposed an approach that can provide forest loss estimations for a short period of time, by using Synthetic Aperture Radar imagery for an area in the Brazilian Amazon. SAR are providing data with almost no alteration due to weather conditions, however they may present other limitations. To mitigate the speckle effect, here was applied the dry coefficient, which is the mean of image values under the first quartile while preserving the spatial resolution. While for obtaining land cover maps containing only forest and non-forest areas an object-based machine learning classification on the Google Earth Engine platform was applied. The preliminary tests were carried out in a bitemporal manner between 2015 and 2019, followed by applying the approach monthly for the year of 2020. The outputs yielded very satisfactory and accurate results, allowing to estimate the forest dynamics for the area under consideration for each month.

Identifying multi-day to sub-daily supraglacial lake change in Greenland from Sentinel 2 and Landsat 8 imagery using Google Earth Engine

2021 ◽  
Author(s):  
Qiao Li ◽  
James Lea ◽  
Stephen Brough
Keyword(s):  
Google Earth ◽  
Landsat 8 ◽  
Lake Area ◽  
High Latitudes ◽  
Large Area ◽  
Large Lakes ◽  
North East ◽  
The North ◽  
Google Earth Engine ◽  
Sentinel 2

<p>Supraglacial lakes (SGLs) are a major component of Greenland’s surface hydrology and mass balance. Monitoring their evolution at multi-day to sub-daily timescales has traditionally been performed by relatively low-resolution sensors such as MODIS Terra, though opportunities exist for using higher spatial resolution sensors at high latitudes.</p><p>In this study, we take advantage of frequent orbital crossovers of Sentinel 2 and Landsat 8 imagery at high latitudes to monitor lakes at multi-day to sub-day temporal resolution, and spatial resolutions up to/over an order of magnitude higher than MODIS Terra (10 m to 30 m, compared to ~250 m for MODIS Terra). Through leveraging the cloud computing resources of Google Earth Engine (GEE), we have developed a workflow to track the evolution of lakes for all available Sentinel 2 and Landsat 8 images over a melt season.</p><p>Our workflow builds on the approach of Moussavi et al. (2020) that was developed for Antarctica, implementing it within GEE to explore its sensitivity and suitability for application to the catchment of the North East Greenland Ice Stream (NEGIS) for the 2019 melt season. To improve the efficiency of analysis, we analyse 282 large lakes (>0.125 km^2) that were previously identified through analysis of MODIS Terra imagery. All lake outlines are appended with image ID and lake area metadata to facilitate subsequent analysis, and allow each lake outline to be traced back to the original image that it was derived from. Our approach is able to monitor lake growth and drainage at unprecedented spatial and temporal resolutions over a large area, allowing the widespread characterization of seasonal lake evolution.</p>

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