A GIS-Based Approach for the Quantitative Assessment of Soil Quality and Sustainable Agriculture

Assessing soil quality is considered one the most important indicators to ensure planned and sustainable use of agricultural lands according to their potential. The current study was carried out to develop a spatial model for the assessment of soil quality, based on four main quality indices, Fertility Index (FI), Physical Index (PI), Chemical Index (CI), and Geomorphologic Index (GI), as well as the Geographic Information System (GIS) and remote sensing data (RS). In addition to the GI, the Normalized Difference Vegetation Index (NDVI) parameter were added to assess soil quality in the study area (western part of Matrouh Governorate, Egypt) as accurately as possible. The study area suffers from a lack of awareness of agriculture practices, and it depends on seasonal rain for cultivation. Thus, it is very important to assess soil quality to deliver valuable data to decision makers and regional governments to find the best ways to improve soil quality and overcome the food security problem. We integrated a Digital Elevation Model (DEM) with Sentinel-2 satellite images to extract landform units of the study area. Forty-eight soil profiles were created to represent identified geomorphic units of the investigated area. We used the model builder function and a geostatistical approach based on ordinary kriging interpolation to map the soil quality index of the study area and categorize it into different classes. The soil quality (SQ) of the study area, classified into four classes (i.e., high quality (SQ2), moderate quality (SQ3), low quality (SQ4), and very low quality (SQ5)), occupied 0.90%, 21.87%, 22.22%, and 49.23% of the total study area, respectively. In addition, 5.74% of the study area was classified as uncultivated area as a reference. The developed soil quality model (DSQM) shows substantial agreement (0.67) with the weighted additive model, according to kappa coefficient statics, and significantly correlated with land capability R2 (0.71). Hence, the model provides a full overview of SQ in the study area and can easily be implemented in similar environments to identify soil quality challenges and fight the negative factors that influence SQ, in addition to achieving environmental sustainability.

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Using Soil Survey Database to Assess Soil Quality in the Heterogeneous Taihang Mountains, North China

Sustainability ◽

10.3390/su10103443 ◽

2018 ◽

Vol 10 (10) ◽

pp. 3443 ◽

Cited By ~ 3

Author(s):

Shoubao Geng ◽

Peili Shi ◽

Ning Zong ◽

Wanrui Zhu

Keyword(s):

Land Cover ◽

Soil Quality ◽

Soil Type ◽

Quality Evaluation ◽

Vegetation Index ◽

Controlling Factors ◽

Soil Survey ◽

Boosted Regression Trees ◽

Soil Quality Index ◽

Data Set

Soil quality evaluation is an effective pathway to understanding the status of soil function and ecosystem productivity. Numerous studies have been made in managed ecosystems and land cover to quantify its effects on soil quality. However, little is coincident regarding soil quality assessment methods and its compatibility in highly heterogeneous soil. This paper used the soil survey database of Taihang Mountains as a case study to: (i) Examine the feasibility of soil quality evaluation with two different indicator methods: Total data set (TDS) and minimum data set (MDS); and (ii) analyze the controlling factors of regional soil quality. Principal component analysis (PCA) and the entropy method were used to calculate soil quality index (SQI). SQI values assessed from the TDS and MDS methods were both significantly correlated with normalized difference vegetation index (p < 0.001), suggesting that both indices were effective to describe soil quality and reflect vegetation growth status. However, the TDS method represented a slightly more accurate assessment than MDS in terms of variance explanation. Boosted regression trees (BRT) models and path analysis showed that soil type and land cover were the most important controlling factors of soil quality, within which soil type had the greatest direct effect and land cover had the most indirect effect. Compared to MDS, TDS is a more sensitive method for assessing regional soil quality, especially in heterogeneous mountains. Soil type is the fundamental factor to determining soil quality. Vegetation and land cover indirectly modulate soil properties and soil quality.

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Drought Risk Assessment in the Khushab Region of Pakistan Using Satellite Remote Sensing and Geospatial Methods

International Journal of Economic and Environmental Geology ◽

10.46660/ijeeg.vol10.iss1.2019.217 ◽

2019 ◽

Vol 10 (1) ◽

pp. 48-56 ◽

Cited By ~ 4

Author(s):

Muhammad Khubaib Abuzar ◽

Muhammad Shafiq ◽

Syed Amer Mahmood ◽

Muhammad Irfan ◽

Tayyaba Khalil ◽

...

Keyword(s):

Remote Sensing ◽

Social Life ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Standardized Precipitation Index ◽

Temporal Analysis ◽

Agricultural Drought ◽

Natural Phenomenon ◽

Drought Risk ◽

Gis And Remote Sensing

Drought is a harmful and slow natural phenomenon that has significant effects on the economy, social life,agriculture and environment of the country. Due to its slow process it is difficult to study this phenomenon. RemoteSensing and GIS tools play a key role in studying different hazards like droughts. The main objective of the study wasto investigate drought risk by using GIS and Remote Sensing techniques in district Khushab, Pakistan. Landsat ETMimages for the year 2003, 2009 and 2015 were utilized for spatial and temporal analysis of agricultural andmeteorological drought. Normalized difference vegetation index (NDVI) Standardized Precipitation Index (SPI) andrainfall anomaly indices were calculated to identify the drought prone areas in the study area. To monitormeteorological drought SPI values were used and NDVI was calculated for agricultural drought. These indices wereintegrated to compute the spatial and temporal drought maps. Three zones; no drought, slight drought and moderatedrought were identified. Final drought map shows that 30.21% of the area faces moderate drought, 28.36% faces slightdrought while nearly 41.3% faces no drought situation. Drought prevalence and severity is present more in the southernpart of Khushab district than the northern part. Most of the northern part is not under any type of drought. Thus, anoverall outcome of this study shows that risk areas can be assessed appropriately by integration of various data sourcesand thereby management plans can be prepared to deal with the hazard.

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Monitoring Land Cover Change Using Remote Sensing and GIS Techniques: a Case Study of Al-Dalmaj Marsh, Iraq

Journal of Engineering ◽

10.31026/j.eng.2018.09.07 ◽

2018 ◽

Vol 24 (9) ◽

pp. 96 ◽

Cited By ~ 1

Author(s):

Marwah Moojid Kadhim

Keyword(s):

Remote Sensing ◽

Land Cover ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Accurate Information ◽

Past Century ◽

Landsat Images ◽

Gis And Remote Sensing ◽

Vegetation Water ◽

Set Up

Al-Dalmaj marsh and the near surrounding area is a very promising area for energy resources, tourism, agricultural and industrial activities. Over the past century, the Al-Dalmaje marsh and near surroundings area endrous from a number of changes. The current study highlights the spatial and temporal changes detection in land cover for Al-Dalmaj marsh and near surroundings area using different analyses methods the supervised maximum likelihood classification method, the Normalized Difference Vegetation Index (NDVI), Geographic Information Systems(GIS), and Remote Sensing (RS). Techniques spectral indices were used in this study to determine the change of wetlands and drylands area and of other land classes, through analyses Landsat images for different three years (1990, 2003, 2016). The results indicated that there was an annual increase in vegetation was from 1990 with 980.68 km2, and 1420.35km2 in 2003 to 2072.98km2 in 2016. Whereas, the annual water coverage was about 185.95km2 in 1990 then dropped to 68.27km2 in 2003, and rose to 180.23 km2 in 2016. The water coverage increasing was on the account of barren lands areas, which were significantly decreased. These collected data can be used to deliver accurate information of the values of vegetation,water, wetlands and drylands sustainability of resources which can be used to make plans to increase tourism and protected areas by using barren lands which cannot be reclaimed for agriculture, and cultivate a new renewable energy can be set up as solar power stations.

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Multi-criteria modelling of drought: a study of Brandenburg Federal State, Germany

Modeling Earth Systems and Environment ◽

10.1007/s40808-021-01197-2 ◽

2021 ◽

Author(s):

Christopher Ihinegbu ◽

Taiwo Ogunwumi

Keyword(s):

Surface Temperature ◽

Land Surface Temperature ◽

Land Surface ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Agricultural Land ◽

Federal State ◽

Landsat 8 ◽

Gis And Remote Sensing ◽

Drought Assessment

AbstractDrought is the absence or below-required supply of precipitation, runoff and or moisture for an extended time period. Modelling drought is relevant in assessing drought incidence and pattern. This study aimed to model the spatial variation and incidence of the 2018 drought in Brandenburg using GIS and remote sensing. To achieve this, we employed a Multi-Criteria Approach (MCA) by using three parameters including Precipitation, Land Surface Temperature and Normalized Difference Vegetation Index (NDVI). We acquired the precipitation data from Deutsche Wetterdienst, Land Surface Temperature and NDVI from Landsat 8 imageries on the USGS Earth Explorer. The datasets were analyzed using ArcGIS 10.7. The information from these three datasets was used as parameters in assessing drought prevalence using the MCA. The MCA was used in developing the drought model, ‘PLAN’, which was used to classify the study area into three levels/zones of drought prevalence: moderate, high and extreme drought. We went further to quantify the agricultural areas affected by drought in the study area by integrating the land use map. Results revealed that 92% of the study area was severely and highly affected by drought especially in districts of Oberhavel, Uckermark, Potsdam-Staedte, and Teltow-Flaeming. Finding also revealed that 77.54% of the total agricultural land falls within the high drought zones. We advocated for the application of drought models (such as ‘PLAN’), that incorporates flexibility (tailoring to study needs) and multi-criteria (robustness) in drought assessment. We also suggested that adaptive drought management should be championed using drought prevalence mapping.

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Drought Risk Assessment in the Khushab Region of Pakistan Using Satellite Remote Sensing and Geospatial Methods

International Journal of Economic and Environmental Geology ◽

10.46660/ojs.v10i1.217 ◽

2019 ◽

Vol 10 (1) ◽

pp. 48-56

Author(s):

Muhammad Khubaib Abuzar ◽

Muhammad Shafiq ◽

Syed Amer Mahmood ◽

Muhammad Irfan ◽

Tayyaba Khalil ◽

...

Keyword(s):

Remote Sensing ◽

Social Life ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Standardized Precipitation Index ◽

Temporal Analysis ◽

Agricultural Drought ◽

Natural Phenomenon ◽

Drought Risk ◽

Gis And Remote Sensing

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ANALISIS TINGKAT KEHIJAUAN HUTAN DAERAH PERTAMBANGAN SAWAHLUNTO DENGAN METODE NDVI BERDASARKAN CITRA LANDSAT TAHUN 2006-2016

SPEKTRA Jurnal Fisika dan Aplikasinya ◽

10.21009/spektra.031.06 ◽

2018 ◽

Vol 3 (1) ◽

pp. 37-46

Author(s):

Bowo Eko Cahyono ◽

Yazella Feni Frahma ◽

Agung Tjahjo Nugroho

Keyword(s):

Land Cover ◽

Environmental Sustainability ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Satellite Image ◽

Mining Area ◽

Vegetation Density ◽

Dense Vegetation ◽

Value Range ◽

Landsat Satellite

Abstrak Pembukaan lahan hutan yang dijadikan lokasi pertambangan merupakan salah satu kegiatan yang dapat merubah jenis tutupan lahan atau sering disebut dengan konversi lahan. Salah satu daerah yang telah mengalami konversi lahan tersebut adalah Sawahlunto. Konversi lahan yang tidak menggunakan prinsip kelestarian lingkungan dapat mengakibatkan banyak hal negatif misalnya degradasi atau penurunan kualitas hutan. Tujuan dari penelitian ini adalah melakukan analisis tingkat degradasi hutan daerah pertambangan Sawahlunto tahun 2006 sampai 2016. Penelitian ini menggunakan teknologi penginderaan jauh berbasis citra satelit landsat. Citra satelit landsat ini diklasifikasikan dengan metode Normalized Difference Vegetation Index (NDVI) berdasarkan kerapatan vegetasi. Kemudian hasil klasifikasi ini dibuat dalam bentuk pemetaan. Klasifikasi pertama dikategorikan menjadi dua yakni hutan dan non hutan. Hasil yang didapatkan dari penelitian ini menunjukkan bahwa terjadi perubahan tutupan lahan yang semula hutan menjadi non hutan meningkat sebesar 7,5% selama kurun waktu sepuluh tahun. Klasifikasi selanjutnya yakni berdasarkan enam kategori yakni vegetasi sangat rapat, rapat, cukup rapat, non vegetasi 1, 2 dan 3. Dari klasifikasi ini, juga terlihat perubahan nilai NDVI maksimum maupun minimumnya. Tahun 2006 memiliki kisaran nilai NDVI maksimum 0,71 dan tahun 2016 memiliki kisaran nilai NDVI maksimum 0,56. Hal ini mengidentifikasi bahwa tingkat kehijauan yang ada di daerah pertambangan Sawahlunto menurun. Kata Kunci : degradasi, hutan, landsat, ndvi, klasifikasi, Sawahlunto. Abstract The clearing of forest land that is used as a mining site is one of the activities that can change the type of land cover or often called land conversion. One of the forest areas that convert the land is Sawahlunto. Conversion of land that does not use the principles of environmental sustainability can lead to many negative things one of which is the degradation. The purpose of this research is to analyze the level of forest degradation of Sawahlunto mining area in 2006 until 2016. This research uses a remote sen sing technology based on landsat satellite imagery. This landsat satellite image is classified by Normalized Difference Vegetation Index (NDVI) method based on vegetation density. Then the results of this classification is made in the form of mapping. The first classification is categorized into two namely forest and non forest. The results obtained from this study indicate that a change in land cover from forest to non-forest increased by 7.5% over a period of ten years. The next classification is based on six categories namely very dense vegetation, dense vegetation, fairly dense, non vegetation 1, 2 and 3. From this classification, also seen the change in NDVI maximum and minimum value. The year 2006 has a maximum NDVI value range of 0.71 and 2016 has a maximum NDVI value range of 0.56. This identifies that the existing greenness in the mining area of Sawahlunto is decreasing. Keyword : degradation, forest, landsat, ndvi, classification, Sawahlunto.

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EVALUATION OF THE POTENTIAL OF GREEN ROOFS APPLIED TO AN URBAN FABRIC USING GIS AND REMOTE SENSING DATA CASE OF THE NADOR CITY / MOROCCO

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlvi-4-w3-2021-177-2022 ◽

2022 ◽

Vol XLVI-4/W3-2021 ◽

pp. 177-184

Author(s):

R. Lambarki ◽

E. Achbab ◽

M. Maanan ◽

H. Rhinane

Keyword(s):

Surface Area ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Plant Cover ◽

Green Roofs ◽

Living Environment ◽

Green Spaces ◽

Surface Model ◽

Landsat 8 ◽

Gis And Remote Sensing

Abstract. Accelerated urban growth has affected many of the planet's natural processes. In cities, most of the surface is covered with asphalt and cement, which has changed the water and air cycles. To restore the balance of urban ecosystems, cities must find the means to create green spaces in an increasingly gray world. Green spaces provide the city and its inhabitants a better living environment. This article uses Nador city as a case study area, this project consists in studying the possibility for the roofs to receive vegetation. The first axis of this project is the quantification of the current vegetation cover at ground level by calculating the Normalized Difference Vegetation Index (NDVI) based on Satellite images Landsat 8, then the classification of the LiDAR point cloud, and the generation of a digital surface model (DSM) of the urban area. This type of derived data was used as the basis for the various stages of estimating the potential plant cover at the roof level. In order to study the different possible scenarios, a set of criteria was applied, such as the minimum roof area, the inclination and the duration of the sunshine on the roof, which is calculated using the linear model of angstrom Prescott based on solar radiation. The study shows that in the most conservative scenario, 21771 suitable buildings that had to be redeveloped into green roofs, with an appropriate surface area of 369.26Ha allowing a 63,40% increase in the city's green space by compared to the current state contributing to the improvement of the quality of life and urban comfort. The average budget for the installation of green roofs in a building with a surface area of 100 m2 varies between 60000dh and 170000dh depending on the type of green roofs used, extensive or intensive. These results would enable planners and researchers in green architecture sciences to carry out more detailed planning analyzes.

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IDENTIFIKASI PERUBAHAN KERAPATAN VEGETASI KOTA MANADO TAHUN 2001 SAMPAI 2015

MAJALAH ILMIAH GLOBE ◽

10.24895/mig.2017.19-1.448 ◽

2017 ◽

Vol 19 (1) ◽

pp. 65

Author(s):

Nurlita Indah Wahyuni ◽

Diah Irawati Dwi Arini ◽

Afandi Ahmad

Keyword(s):

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Landsat 8 ◽

Vegetation Density ◽

Forage Crops ◽

Area Change ◽

Gis And Remote Sensing ◽

Crown Density ◽

Landsat 7 ◽

The Impact

ABSTRAKKebutuhan manusia akan lahan di wilayah perkotaan menyebabkan perubahan fungsi lahan terutama pada area bervegetasi. Penelitian bertujuan untuk mengkaji perubahan kerapatan vegetasi tahun 2001 dan 2015 di Kota Manado serta pengaruhnya terhadap kualitas lingkungan. Penelitian dimulai dengan melakukan pengumpulan data citra satelit Landsat 7 tahun 2001 tanggal akuisisi 14 Februari 2001 dan Landsat 8 tanggal akusisi 25 Maret 2015, data-data pendukung lainnya yaitu peta administrasi kota Manado tahun 2010, peta rupa bumi kota Manado skala 1:50.000. Metode yang digunakan dalam penelitian ini adalah perbandingan nilai normalized difference vegetation index (NDVI) dengan kanal merah (red) dan infra merah dekat (NIR) yang sudah dikonversi ke nilai reflektan. Teknik analisis menggunakan Sistem Informasi Geografis (SIG) dan penginderaan jauh dengan menentukan kerapatan vegetasi dan diklasifikasikan menjadi kelas kerapatan. Hasil penelitian menunjukkan bahwa perbandingan kelas kerapatan antara 2001 dan 2015 sebagai berikut kelas tidak bervegetasi (air dan awan) mengalami peningkatan sebesar 14,29%, kelas tidak rapat (lahan kosong, pemukiman, bangunan, dan industri) mengalami peningkatan sebesar 42,56%, kelas cukup rapat (tegalan dan tumbuhan ternak) mengalami peningkatan sebesar 48,94%, kelas rapat (perkebunan, sawah kering, dan semak belukar) mengalami penurunan sebesar 68,46% dan kelas sangat rapat (hutan lebat) mengalami penurunan sebesar 314,07%. Selama kurun waktu 15 tahun penurunan areal bervegetasi di Kota Manado diperkirakan 10,57%. Perubahan areal bervegetasi di Kota Manado signifikan terjadi karena kegiatan reklamasi pantai menjadi lahan terbangun serta lahan kosong dan perkebunan menjadi perumahan. Dampak yang saat ini mulai dirasakan dengan adanya perubahan areal bervegetasi adalah peningkatan suhu dan polusi udara di wilayah perkotaan.Kata kunci:Landsat, Normalized Difference Vegetation Index (NDVI), kerapatan, Kota Manado ABSTRACTHuman demand on urban land has brought various impacts toward land use, one of them is vegetation area change. This study aims to identify vegetation density change between period 2001 and 2015 in Manado area along with its influence toward environment quality. The data was collected from Landsat 7 imagery with acquisition date on February 14th 2001 and Landsat 8 imagery with acquisition date on March 25th 2015. Supporting data i.e. administrative map of Manado City in 2010 and basic map of Manado in scale 1:50.000. We compared normalized difference vegetation index (NDVI) between red band and near infra red (NIR) band. Geographic Information System (GIS) and remote sensing techniques were used to determine and classify crown density of vegetation. The result showed that the density class comparison between 2001 and 2015 were: no vegetation (water body and cloud) increased 14,29%, low dense (bareland, residence, buildings and industry) increased 42,56%, moderately dense (garden and forage crops) increased 48,94%, dense (plantation, dry field and shrubs) decreased 68,46% and highly dense (forest) decreased 314,07%. In the period 15 years there was decreasing of vegetation area in Manado city 10,57% approximately. The significance change of Manado City was occurred due to coast reclamation into building area as well as bare land and plantation become residence. The impact of vegetation area change is the increasing of temperature and air pollution in urban area.Keywords: Landsat, Normalized Difference Vegetation Index (NDVI), density, Manado City

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Spatial analysis of Prosopis Juliflora trees, its environmental and developmental effects on Wadi Yiba in the southwest of Saudi Arabia: التحليل المكاني لأشجار البرسوبس وآثاره البيئية والتنموية على وادي يــبة جنوب غرب المملكة العربية السعودية

Journal of natural sciences, life and applied sciences - مجلة العلوم الطبيعية و الحياتية والتطبيقية ◽

10.26389/ajsrp.w290621 ◽

2021 ◽

Vol 5 (4) ◽

pp. 97-63

Author(s):

Norah Ali Alshehri Norah Ali Alshehri

Keyword(s):

Saudi Arabia ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Spatial Information ◽

Prosopis Juliflora ◽

South American ◽

Landsat Images ◽

Gis And Remote Sensing ◽

Invasive Shrub ◽

Future Situation

Prosopis Juliflora is an invasive shrub or tree native to South American countries. It is one of the most important exotic and invasive organisms that are spread in the Kingdom of Saudi Arabia. This study concentrates on investigating the widespread of Prosopis Juliflora in Wadi Yiba، located in the southwest of the Kingdom، and given the possibilities offered by geographic information system (GIS) and remote sensing to help determine the areas of spread of the plant and its size، and to take the best capabilities، especially with regard to processing and analyzing large and diverse spatial information، the present research aims to use this in evaluating the current and future situation of the spread of plants in Wadi Yiba، and the extent of its impact on the environment، while suggesting appropriate ways to manage it. The research relied on the use of Landsat images، working with the subtraction method، and subjecting the images to the object-oriented classification، by taking 30 specimens for each cover and merging these specimens، and the layers of vegetation cover were derived using the normalized difference vegetation index (NDVI) for each year. The research concluded that there is a concentration in the spread of Prosopis Juliflora in the center and north of Wadi Yiba، especially in the city of Therban and villages of Al-Balqa’a، Al-Tala’i، Sabt Al-Jara، and Khamis Harb، with a spread along the valley to the estuary. At the end، the research recommended the establishment of a research center for the study of Prosopis Juliflora in Assir region، and an attempt to develop economic plans to benefit from Prosopis Juliflora in Wadi Yiba.

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MONITORING MODEL OF LAND COVER CHANGE FOR THE INDICATION OF DEVEGETATION AND REVEGETATION USING SENTINEL-2

International Journal of Remote Sensing and Earth Sciences (IJReSES) ◽

10.30536/j.ijreses.2020.v17.a3385 ◽

2021 ◽

Vol 17 (2) ◽

pp. 163

Author(s):

Samsul Arifin ◽

Tatik Kartika

Keyword(s):

Land Cover ◽

Land Cover Change ◽

Environmental Sustainability ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Remote Sensing Data ◽

Threshold Value ◽

Monitoring Model ◽

Land Changes ◽

Sentinel 2

IInformation on land cover change is very important for various purposes, including the monitoring of changes for environmental sustainability. The objective of this study is to create a monitoring model of land cover change for the indication of devegetation and revegetation usingdata fromSentinel-2 from 2017 to 2018 of the Brantas watershed.This is one of the priority watersheds in Indonesia, so it is necessary to observe changes in its environment, including land cover change. Such change can be detected using remote sensing data. The method used is a hybrid between Normalized Difference Vegetation Index(NDVI) and Normalized Burn Ratio (NBR) which aims to detect land changes with a focus on devegetationand revegetation by determining the threshold value for vegetation index (ΔNDVI) and open land index (ΔNBR).The study found that the best thresholds to detect revegetation were ΔNDVI > 0.0309 and ΔNBR < 0.0176 and to detect devegetation ΔNDVI < -0.0206 and ΔNBR > 0.0314.It is concluded that Sentinel-2 data can be used to monitor land changes indicating devegetation and revegetation with established NDVI and NBR threshold conditions.

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