scholarly journals Land Use and Land Cover Dynamics and Assessing the Ecosystem Service Values in the Trans-Boundary Gandaki River Basin, Central Himalayas

2018 ◽  
Vol 10 (9) ◽  
pp. 3052 ◽  
Author(s):  
Raju Rai ◽  
Yili Zhang ◽  
Basanta Paudel ◽  
Bipin Acharya ◽  
Laxmi Basnet
Keyword(s):  
Land Use ◽  
Ecosystem Services ◽  
Land Cover ◽  
River Basin ◽  
Ecosystem Service ◽  
Satellite Image ◽  
Landsat 8 ◽  
Barren Land ◽  
Central Himalayas ◽  
Land Cover Types

Land use and land cover is a fundamental variable that affects many parts of social and physical environmental aspects. Land use and land cover changes (LUCC) has been known as one of the key drivers of affecting in ecosystem services. The trans-boundary Gandaki River Basin (GRB) is the part of Central Himalayas, a tributary of Ganges mega-river basin plays a crucial role on LUCC and ecosystem services. Due to the large topographic variances, the basin has existed various land cover types including cropland, forest cover, built-up area, river/lake, wetland, snow/glacier, grassland, barren land and bush/shrub. This study used Landsat 5-TM (1990), Landsat 8-OLI (2015) satellite image and existing national land cover database of Nepal of the year 1990 to analyze LUCC and impact on ecosystem service values between 1990 and 2015. Supervised classification with maximum likelihood algorithm was applied to obtain the various land cover types. To estimate the ecosystem services values, this study used coefficients values of ecosystem services delivered by each land cover class. The combined use of GIS and remote sensing analysis has revealed that grassland and snow cover decreased from 10.62% to 7.62% and 9.55% to 7.27%, respectively compared to other land cover types during the 25 years study period. Conversely, cropland, forest and built-up area have increased from 31.78% to 32.67%, 32.47–33.22% and 0.19–0.59%, respectively in the same period. The total ecosystem service values (ESV) was increased from 50.16 × 108 USD y−1 to 51.84 × 108 USD y−1 during the 25 years in the GRB. In terms of ESV of each of land cover types, the ESV of cropland, forest, water bodies, barren land were increased, whereas, the ESV of snow/glacier and grassland were decreased. The total ESV of grassland and snow/glacier cover were decreased from 3.12 × 108 USD y−1 to 1.93 × 108 USD y−1 and 0.26 × 108 USD y−1 to 0.19 × 108 USD y−1, respectively between 1990 and 2015. The findings of the study could be a scientific reference for the watershed management and policy formulation to the trans-boundary watershed.

scholarly journals Assessment of Ecosystem Services Value Based on Land Use and Land Cover Changes in the Transboundary Karnali River Basin, Central Himalayas

2019 ◽  
Vol 11 (11) ◽  
pp. 3183 ◽  
Author(s):  
Bhaskar Shrestha ◽  
Qinghua Ye ◽  
Nitesh Khadka
Keyword(s):  
Land Use ◽  
Ecosystem Services ◽  
Land Cover ◽  
River Basin ◽  
Geographical Information ◽  
Barren Land ◽  
Central Himalayas ◽  
Ecosystem Services Value ◽  
Management Interventions ◽  
Spatio Temporal

Land use and land cover change (LUCC) and its spatio-temporal characteristics are essential for natural resource management and sustainable development. LUCC is one of the major factors that affect the ecosystem and the services it provides. In this study, we used remote sensing techniques and a geographical information system to extract the land cover categories based on the Object-Based Image Analysis (OBIA) technique from Landsat TM/ETM/OLI satellite images in the transboundary Karnali River Basin (KRB, China and Nepal) of central Himalayas from 2000 to 2017. Spatio-temporal integrated methodology—Tupu was used to spatially show the LUCC as well as spatial characteristics of the arisen Tupu and shrunken Tupu. In addition, the ecosystem services value (ESV) were obtained and analyzed for each land cover category. In 2017, forest covered the highest area (33.45%) followed by bare area (30.3%), shrub/grassland (18.49%), agriculture (13.12%), snow/ice (4.32%), waterbody (0.3%) and built-up area (0.04%) in the KRB. From 2000 to 2017, the areas of forest, waterbody and snow/ice have decreased by 0.59, 6.14, and 1072.1 km2, respectively. Meanwhile, the areas of shrub/grassland, agriculture, barren land, and built-up categories have increased by 82.21, 1.44, 991.97, and 3.11 km2, respectively. These changes in the land cover have led to an increase in the ESV of the basin, especially the increase in shrub/grassland, agriculture, and water bodies (in the higher elevation). The total ESV of the basin was increased by $1.59 × 106 from 2000 to 2017. Anthropogenic factors together with natural phenomena drive LUCC in the basin and thus the ESV. The findings of this study could facilitate the basin-level policy formulation to guide future conservation and development management interventions.

scholarly journals Qualifying Land Use and Land Cover Dynamics and Their Impacts on Ecosystem Service in Central Himalaya Transboundary Landscape Based on Google Earth Engine

Land ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 173
Author(s):  
Changjun Gu ◽  
Yili Zhang ◽  
Linshan Liu ◽  
Lanhui Li ◽  
Shicheng Li ◽  
...  
Keyword(s):  
Land Use ◽  
Ecosystem Services ◽  
Land Cover ◽  
Ecosystem Service ◽  
Forest Cover ◽  
Google Earth ◽  
Forest Cover Change ◽  
Sacred Landscape ◽  
Lulc Changes ◽  
Google Earth Engine

Land use and land cover (LULC) changes are regarded as one of the key drivers of ecosystem services degradation, especially in mountain regions where they may provide various ecosystem services to local livelihoods and surrounding areas. Additionally, ecosystems and habitats extend across political boundaries, causing more difficulties for ecosystem conservation. LULC in the Kailash Sacred Landscape (KSL) has undergone obvious changes over the past four decades; however, the spatiotemporal changes of the LULC across the whole of the KSL are still unclear, as well as the effects of LULC changes on ecosystem service values (ESVs). Thus, in this study we analyzed LULC changes across the whole of the KSL between 2000 and 2015 using Google Earth Engine (GEE) and quantified their impacts on ESVs. The greatest loss in LULC was found in forest cover, which decreased from 5443.20 km2 in 2000 to 5003.37 km2 in 2015 and which mainly occurred in KSL-Nepal. Meanwhile, the largest growth was observed in grassland (increased by 548.46 km2), followed by cropland (increased by 346.90 km2), both of which mainly occurred in KSL-Nepal. Further analysis showed that the expansions of cropland were the major drivers of the forest cover change in the KSL. Furthermore, the conversion of cropland to shrub land indicated that farmland abandonment existed in the KSL during the study period. The observed forest degradation directly influenced the ESV changes in the KSL. The total ESVs in the KSL decreased from 36.53 × 108 USD y−1 in 2000 to 35.35 × 108 USD y−1 in 2015. Meanwhile, the ESVs of the forestry areas decreased by 1.34 × 108 USD y−1. This shows that the decrease of ESVs in forestry was the primary cause to the loss of total ESVs and also of the high elasticity. Our findings show that even small changes to the LULC, especially in forestry areas, are noteworthy as they could induce a strong ESV response.

Making Of Classification Land Cover Through Result Of Visual Data Satellite Image Analysis Landsat 8 OLI : Case Study in Tapaktuan District, South Aceh District

2021 ◽  
Vol 6 (1) ◽  
pp. 59-65
Author(s):  
Safridatul Audah ◽  
Muharratul Mina Rizky ◽  
Lindawati
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Image Classification ◽  
Satellite Image ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Sensing Technology ◽  
Open Land ◽  
Cover Class ◽  
Satellite Image Analysis

Tapaktuan is the capital and administrative center of South Aceh Regency, which is a sub-district level city area known as Naga City. Tapaktuan is designated as a sub-district to be used for the expansion of the capital's land. Consideration of land suitability is needed so that the development of settlements in Tapaktuan District is directed. The purpose of this study is to determine the level of land use change from 2014 to 2018 by using remote sensing technology in the form of Landsat-8 OLI satellite data through image classification methods by determining the training area of the image which then automatically categorizes all pixels in the image into land cover class. The results obtained are the results of the two image classification tests stating the accuracy of the interpretation of more than 80% and the results of the classification of land cover divided into seven forms of land use, namely plantations, forests, settlements, open land, and clouds. From these classes, the area of land cover change in Tapaktuan is increasing in size from year to year.

scholarly journals Transboundary analysis of the land cover in Razdolnaya river basin

2021 ◽  
pp. 70-77
Author(s):  
Т.К. МУЗЫЧЕНКО ◽  
М.Н. МАСЛОВА
Keyword(s):  
Land Use ◽  
Land Cover ◽  
River Basin ◽  
Rice Fields ◽  
Landsat 8 ◽  
Agricultural Lands ◽  
Transboundary River ◽  
Russian Part ◽  
Land Use Structure ◽  
Sentinel 2

В статье рассмотрено пространственное распределение типов земель в пределах трансграничного бассейна р. Раздольная. На основе дешифрирования космических снимков Sentinel-2 и Landsat 8 составлена карта пространственного распределения типов земель по состоянию на 2019 г. Исходя из геоэкологической классификации ландшафтов В.А. Николаева в данной работе было выделено 12 типов земель: используемые и неиспользуемые сельскохозяйственные земли, используемые и неиспользуемые рисовые поля, карьеры, леса, лесопосадки, рубки, луга, застроенные земли, водные объекты, а также кустарники и редколесья. Представлены абсолютные и относительные площади для каждого типа земель по трансграничному бассейну в целом, а также отдельно для его российской и китайской частей. По результатам дешифрирования данных дистанционного зондирования установлено, что российская и китайская части бассейна р. Раздольная имеют существенные трансграничные различия в структуре земель. На российской части бассейна лесами покрыто чуть более половины площади, но при этом значительные площади занимают сельскохозяйственные земли и луга. В некоторых местах луга и сельскохозяйственные земли преобладают в большей степени, чем леса. На китайской части лесные территории доминируют над другими типами земель. Сельскохозяйственные земли и луга образуют узкие и длинные полосы и имеют более мозаичное распространение, чем на российской части. Здесь заметно меньше площади застроенных земель, а площади рубок и лесопосадок больше, чем на российской части. Площади карьеров примерно равны в обеих частях бассейна. The transboundary Razdolnaya river basin is nearly evenly split up between Primorsky Krai of Russian Federation and Heilongjiang and Jilin provinces of People’s Republic of China. The Chinese and the Russian parts of the transboundary river have developed independently of each other. Therefore, the two have a different land cover and land use structure. The analysis of land cover and land use structure is of utmost importance for the understanding the modern state of land development and the possibilities of its future development. Using the remote sensing data, such as Sentinel-2 and Landsat 8 satellite imagery, the land cover and land use map of the Razdolnaya transboundary river basin for 2019 has been composed by means of the ArcMap 10.5 software package. According to V.A. Nikolaev’s geoecological classification of landscapes, we have identified 12 land types: forests, meadows, shrubs and woodlands, agricultural lands, unused agricultural lands, rice fields, unused rice fields, built-up areas, reforestation lands, logging, quarries, and bodies of water. We have provided area coverage for each type of land of the whole transboundary basin, and for the Russian and Chinese parts. According to the results of computer-aided visual deciphering and automatic deciphering, forests are the most common land use type in the basin. In the Chinese part of the basin, forests dominate over the other types of land. Agricultural lands and meadows have assumed narrow and linear shapes. Built-up areas have less coverage here than in the Russian part of the basin. However, the coverage of logging and reforestation lands is considerably larger than in the Russian part of the basin. In the Russian part of the basin, forests co-dominate with the agricultural lands and meadows. In some areas of this part of the basin forests disappear almost completely. The Russian part of the basin also has the larger coverage of shrubs and woodlands, unused agricultural lands, rice fields and unused rice fields. The coverage of quarries is roughly equal in both parts of the basin.

scholarly journals Urban Bare Land Classification Using NDBaI Index Based on Combination of Sentinel 2 MSI and Landsat 8 Multiresolution Images

2020 ◽  
Vol 36 (2) ◽  
Author(s):  
Trinh Le Hung
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Satellite Image ◽  
Urban Land ◽  
Landsat 8 ◽  
Land Classification ◽  
Infrared Band ◽  
Urban Land Cover ◽  
Bare Land ◽  
Sentinel 2

The classification of urban land cover/land use is a difficult task due to the complexity in the structure of the urban surface. This paper presents the method of combining of Sentinel 2 MSI and Landsat 8 multi-resolution satellite image data for urban bare land classification based on NDBaI index. Two images of Sentinel 2 and Landsat 8 acquired closely together, were used to calculate the NDBaI index, in which sortware infrared band (band 11) of Sentinel 2 MSI image and thermal infrared band (band 10) of Landsat 8 image were used to improve the spatial resolution of NDBaI index. The results obtained from two experimental areas showed that, the total accuracy of classifying bare land from the NDBaI index which calculated by the proposed method increased by about 6% compared to the method using the NDBaI index, which is calculated using only Landsat 8 data. The results obtained in this study contribute to improving the efficiency of using free remote sensing data in urban land cover/land use classification.

scholarly journals Ecosystem Service Values Changes in Response to Land-Use/Land-Cover Dynamics in Dry Afromontane Forest in Northern Ethiopia

2019 ◽  
Vol 16 (23) ◽  
pp. 4653 ◽  
Author(s):  
Negasi Solomon ◽  
Alcade C. Segnon ◽  
Emiru Birhane
Keyword(s):  
Land Use ◽  
Ecosystem Services ◽  
Land Cover ◽  
Ecosystem Service ◽  
Forest Cover ◽  
Northern Ethiopia ◽  
Land Use Land Cover ◽  
Afromontane Forest ◽  
Land Cover Dynamics ◽  
Dry Afromontane Forest

Despite their importance as sources of ecosystem services supporting the livelihoods of millions of people, forest ecosystems have been changing into other land use systems over the past decades across the world. While forest cover change dynamics have been widely documented in various ecological systems, how these changes affect ecosystem service values has received limited attention. In this study we assessed the impact of land-use/land-cover dynamics on ecosystem service values in dry Afromontane forest in Northern Ethiopia. We estimated ecosystem service values and their changes based on the benefit transfer method using land cover data of the years 1985, 2000, and 2016 with their corresponding locally valid value coefficients and from the Ecosystem service valuation database. The total ecosystem service values of the whole study area were about USD 16.6, 19.0, and 18.1 million in 1985, 2000, and 2016, respectively. The analyses indicated an increase in ecosystem service values from 1985 to 2000 and a decrease in ecosystem service values from 2000 to 2016. Similarly, the contribution of specific ecosystem services increased in the first study period and decreased in the second study period. The findings highlight how forest cover dynamics can be translated into changes in ecosystem service values in dry Afromontane forest ecosystems in Northern Ethiopia and showed how specific ecosystem services contributed to the observed trends. The findings also illustrated the temporal heterogeneity in the impacts of land-use/land-cover dynamics on values of ecosystem services. The findings can serve as crucial inputs for policy and strategy formulations for the sustainable use and management of forest resources and can also guide the allocation of limited resources among competing demands to safeguard the ecosystems that offer the best-valued services.

scholarly journals Land cover classification using landsat-8 optical data and supervised classifiers

2018 ◽  
Vol 7 (2.17) ◽  
pp. 101
Author(s):  
K V. Ramana Rao ◽  
Prof P. Rajesh Kumar
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Classification ◽  
Optical Data ◽  
Landsat 8 ◽  
Barren Land ◽  
Detection Techniques ◽  
Time Periods ◽  
Classification Information ◽  
Landsat Satellite

Land use and land cover information of an area has got importance in various aspects mainly because of various development activities that are taking place in every part of the world. Various satellite sensors are providing the required data collected by remote sensing techniques in the form of images using which the land use land cover information can be analyzed.  Constistency of Landsat satellite is illustrated with two time periods such as Operational Land Imager (OLI) of 2013 and consecutive 2014 procured by earth explorer with quantified changes for the same period in visakhapatnam of hudhud cyclone. Since this city is consisting of mainly urban, vegetation, few water bodies, some area of agriculture and barren,five classes have been chosen from the study area. The results indicate that due to the hudhud event some changes took place.  vegetation and built-up land have been increased by An increase of 19.1% (6.3 km2) and 11% (5.36 km2) has been observed in the case of vegetation and built up area  where as a decrease of 1.2% (4.06 km2), 6.1% (1.70 km2) and 1.2% (0.72 km2) has been observed in the case of  agriculture, barren land, and water body respectively. With the help of available satellite imagery belonging to the same area and of different time periods along with the  change detection techniques landscape dynamics have been analyzed. Using various classification algorithms along with the data available from the satellite sensor the land use and land cover classification information of the study area has been obtained. The maximum likelihood algorithm provided better results compared to other classification techniques and the accuracy achieved with this algorithm is 99.930% (overall accuracy) and 0.999 (Kappa coefficient).  

Response of Ecological Services Value to Land Use Change in the Shiyang River Basin: A Case Study in Wuwei Region

2012 ◽  
Vol 518-523 ◽  
pp. 5116-5120
Author(s):  
Pei Ji Shi ◽  
Xue Bin Zhang ◽  
Jun Luo ◽  
Xue Min Zhang
Keyword(s):  
Land Use ◽  
Ecosystem Services ◽  
Land Use Change ◽  
River Basin ◽  
Ecosystem Service ◽  
Main Part ◽  
Land Use Pattern ◽  
Shiyang River Basin ◽  
Unused Land

Based on the detailed survey of land use change in Shiyang river basin, referencing Costanza, and Xie et al’ research results of the value of ecosystem services, this article probed the variation of land use and value of ecosystem service in Wuwei region. The results are: from 1997 to 2006, the area of woodland, construction land and garden land are increasing, while farmland, grassland, water and unused land are continuing to decrease. Land-use intensity is gradually increasing, the land use pattern towards to a centralized style. The values of ecosystem services are overall upward, and change faster than ever. The main part of the value of ecosystem service is constituted by the value of grassland, woodland and farmland. So it’s important to control the expansion of urban construction, strength the protection of the water, restore and enhance regional ecosystem services in the future.

scholarly journals NDVI Based Assessment of Land Cover Changes Using Remote Sensing and GIS (A case study of Srinagar district, Kashmir)

2020 ◽  
Author(s):  
Perminder Singh ◽  
Ovais Javeed
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Urban Areas ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Satellite Image ◽  
Spectral Signature ◽  
Landsat 8 ◽  
Thematic Mapping

Normalized Difference Vegetation Index (NDVI) is an index of greenness or photosynthetic activity in a plant. It is a technique of obtaining  various features based upon their spectral signature  such as vegetation index, land cover classification, urban areas and remaining areas presented in the image. The NDVI differencing method using Landsat thematic mapping images and Landsat oli  was implemented to assess the chane in vegetation cover from 2001to 2017. In the present study, Landsat TM images of 2001 and landsat 8 of 2017 were used to extract NDVI values. The NDVI values calculated from the satellite image of the year 2001 ranges from 0.62 to -0.41 and that of the year 2017 shows a significant change across the whole region and its value ranges from 0.53 to -0.10 based upon their spectral signature .This technique is also  used for the mapping of changes in land use  and land cover.  NDVI method is applied according to its characteristic like vegetation at different NDVI threshold values such as -0.1, -0.09, 0.14, 0.06, 0.28, 0.35, and 0.5. The NDVI values were initially computed using the Natural Breaks (Jenks) method to classify NDVI map. Results confirmed that the area without vegetation, such as water bodies, as well as built up areas and barren lands, increased from 35 % in 2001 to 39.67 % in 2017.Key words: Normalized Difference Vegetation Index,land use/landcover, spectral signature 

scholarly journals THE CARRYING CAPACITY ON ECOSYSTEM SERVICES OF LAND USE CHANGE AT BORDER ENTIKONG

2018 ◽  
Vol 3 (2) ◽  
pp. 11
Author(s):  
Robby Irsan ◽  
Luthfi Muta'ali ◽  
S Sudrajat
Keyword(s):  
Land Use ◽  
Ecosystem Services ◽  
Land Cover ◽  
Natural Resources ◽  
Carrying Capacity ◽  
Ecosystem Service ◽  
Spatial Planning ◽  
Clean Water ◽  
Border Area ◽  
Mixed Plantation

Entikong Region is located in Sanggau Regency, West Kalimantan Province, Indonesia, which is directly adjacent to Malaysia. Land use in the Border Area, which is massive and irregular, results in environmental degradation, deculturization, and lack of living standards of the community. High population growth in the border areas leads to excessive use of natural resources, and used land is not appropriately allocated. The land has limited function, and if the demand for the land is greater than the carrying capacity, there will be an imbalance that results in land degradation and its environment. The purpose of this study is to identify the type and extent of land function switch, analyze provider services as part of the Land Support Capacity Ecosystem services, and identify the Accuracy of Image Interpretation. The results showed that the increasing area of massive land use comes from a mixed plantation in 2017 increased by 60.6% of the total area of Entikong District. Degradation occurs in primary forest land use component which is only 18.6% of Entikong's total area in 2017. This indicates that the use of mixed plantation land acquires the protected forest, with many palm, rubber, and pepper. Similarly, the percentage of accuracy test from the interpretation result reaches 83.33% from 42 sample points in accordance with the real conditions. The Value of Clean Water Ecosystem Service Providers in 2011 was 0.36 and was 0.33 in 2017. Then within the period of almost 7 years, it is decreased by 0.03. Thus, the Ecosystem Service Index of clean water providers has a value less than 1, it means the function of the area as a provider of clean water is very small. Similarly, the Provider Ecosystem Services Index for Foodstuffs, the Value of Food Ecosystem Services Index in 2011 was 0.32 and was 0.31 in 2017, then within the nearly 7-year period, it is decreased by 0.01. The ecosystem services index as a food supply provider for the Entikong border area is very low (less than 1) which means the carrying capacity of the environment is not good enough for supplying food needs in Entikong. This indicates that there is a reduction in the availability of environmental services, and if it continues, then Environmental Assets declines sharply and services derived from nature will be lost or will be expensive in the near future. Thus, optimization and revitalization of land use are necessary by applying various policies related to development in the border area in Entikong District. Keywords: Borders, Land Use, Ecosystem Provider Services.   References Admadhani, D. N., Hajil, A. H. S., & Susanawati, L. D. (2013). Analysis of Water Supply and Water Demand for Carrying Capacity Assessment ( Case Study of Malang ). Journal of Natural Resources and Environment. Asdak, C., & Salim, H. (2006). Water Resource Capacity As a Spatial Planning Consideration. Journal of Environmental Engineering P3TL-BPPT. Ernan Rustiadi, Sunsus Saefulhakim, D. R. P. (2011). Planning and Regional Development. Restpent Press. Ghozali. (2013). Referral of Land Use Utilization Through Ecological Footprint in Gresik Regency. Territory and Environment, 1 No.1, 67–78. Hamidy, Z. (2003). Land Cover Change, Composition, and Life Type in Suakaidupan Cikepuh. Faculty of Forestry, IPB. Muta’ali, L. (2015). Regional Analysis Techniques For Regional Planning, Spatial Planning, and Environment (Februari). Yogyakarta: Faculty of Geography UGM. National Standardization Department. (2010). Classification of Land Cover. Purwadhi. (2008). Introduction Remote Sensing Imagery Interpretation. Semarang: LAPAN. Riqqi, A. (2014). Design Concept Techniques Determination of Supporting Capacity and Capacity of the National Environment and Islands / Islands And Provinces. Bali: KLH. Saripin, I. (2003). Identify Land Use Using Landsat TM Imagery. Agricultural Engineering Bulletin. Varika. (2015). Monitoring of Ecosystem Service-Based Ecotourism (Recreation and Ecotourism) Capacity in 2000 and 2015 Using Landsat Image in Badung Regency, Bali. Viska. (2012). Land Use Direction in Batu City Based on Ecological Ecosystem Approach. Pomits Technique, 1 No.1, 1–6.    

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