scholarly journals Profile, Level of Vulnerability and Spatial Pattern of Deforestation in Sulawesi Period of 1990 to 2018

Forests ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 191 ◽  
Author(s):  
Syamsu Rijal ◽  
Roland A. Barkey ◽  
Nasri ◽  
Munajat Nursaputra
Keyword(s):  
Land Cover ◽  
Forest Cover ◽  
Early Stage ◽  
Distribution Patterns ◽  
Small Scale ◽  
Landsat 8 ◽  
Agricultural Activities ◽  
Planning Agency ◽  
Low Rate ◽  
Observation Period

Deforestation is an event of loss of forest cover to another cover. Sulawesi forests have the potential to be deforested as with Sumatra and Kalimantan. This study aims to provide information on deforestation events in Sulawesi from 1990 to 2018. The data used in this study are (1) land cover in 1990, 2000, 2010; (2) Landsat 8 imagery in 2018; (3) administrative map of BIG in 2018. The methods used are (1) image classification with on-screen digitation techniques following the PPIK land cover classification guidelines, Forestry Planning Agency (2008) using ArcGIS Desktop 10.6 from ESRI; (2) overlapping maps; (3) analysis of deforestation; (4) analysis of deforestation profiles, (5) vulnerability analysis; and (6) analysis of distribution patterns of deforestation. The results showed that the profile of deforestation occurring on Sulawesi Island in the 1990–2018 observation period was dominated by profile 3-1-1 (the proportion of large forest area, the highest incidence of deforestation early stage at the beginning, at a low rate) in 13 districts. The level of vulnerability to deforestation is a non-vulnerable category (37 districts) which is directed to become a priority in handling deforestation in Sulawesi. Spatial patterns of the deforestation that occurred randomly and were scattered are dominated by shrubs, dryland agricultural activities, and small-scale plantations.

scholarly journals ALTERAÇÃO NA COBERTURA FLORESTAL DA REGIÃO NOROESTE DA AMAZÔNIA MATOGROSSENSE

Nativa ◽  
2019 ◽  
Vol 7 (5) ◽  
pp. 520
Author(s):  
Luani Rosa de Oliveira Piva ◽  
Rorai Pereira Martins Neto
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Forest Cover ◽  
Forest Conversion ◽  
Landsat 8 ◽  
Amazon Forest ◽  
Landsat 8 Oli ◽  
Mato Grosso ◽  
The Past ◽  
Landsat 5 Tm

Nos últimos anos, a intensificação das atividades antrópicas modificadoras da cobertura vegetal do solo em território brasileiro vem ocorrendo em larga escala. Para fins de monitoramento das alterações da cobertura florestal, as técnicas de Sensoriamento Remoto da vegetação são ferramentas imprescindíveis, principalmente em áreas extensas e de difícil acesso, como é o caso da Amazônia brasileira. Neste sentido, objetivou-se com este trabalho identificar as mudanças no uso e cobertura do solo no período de 20 anos nos municípios de Aripuanã e Rondolândia, Noroeste do Mato Grosso, visando quantificar as áreas efetivas que sofreram alterações. Para tal, foram utilizadas técnicas de classificação digital de imagens Landsat 5 TM e Landsat 8 OLI em três diferentes datas (1995, 2005 e 2015) e, posteriormente, realizada a detecção de mudanças para o uso e cobertura do solo. A classificação digital apresentou resultados excelentes, com índice Kappa acima de 0,80 para os mapas gerados, indicando ser uma ferramenta potencial para o uso e cobertura do solo. Os resultados denotaram uma conversão de áreas florestais principalmente para atividades antrópicas agrícolas, na ordem de 472 km², o que representa uma perda de 1,3% de superfície de floresta amazônica na região de estudo.Palavras-chave: conversão de áreas florestais; uso e cobertura do solo; classificação digital; análise multitemporal. CHANGE IN FOREST COVER OF THE NORTHWEST REGION OF AMAZON IN MATO GROSSO STATE ABSTRACT: In the past few years, the intensification of anthropic activities that modify the soil-vegetation cover in Brazil’s land has been occurring on a large scale. To monitor the forest cover changes, the techniques of Remote Sensing of vegetation are essential tools, especially in large areas and with difficult access, as is the case of the Brazilian Amazon. The aim of this work was to identify the changes in land use and land cover, over the past 20 years, in the municipalities of Aripuanã and Rondolândia, Northwest of Mato Grosso State, in order to quantify the effective altered areas. Landsat 5 TM and Landsat 8 OLI digital classification images techniques were used in three different dates (1995, 2005 and 2015) and, later, the detection to the land use and land cover changes. The digital classification showed excellent results, with kappa index above 0.80 for the generated maps, indicating the digital classification as a potential tool for land use and land cover. Results reflect the conversion of forest areas mainly for agricultural activities, in the order of 472 km², representing a loss of 1.3% of Amazon forest surface in the study region.Keywords: forest conversion; land use and land cover; digital classification; multitemporal analysis.

scholarly journals ANALISIS PERUBAHAN CADANGAN KARBON DI KAWASAN GUNUNG PADANG KOTA PADANG

JURNAL BUANA ◽  
2017 ◽  
Vol 1 (1) ◽  
pp. 94
Author(s):  
Rina Suksesi ◽  
Dedi Hermon ◽  
Endah Purwaningsih
Keyword(s):  
Land Cover ◽  
Supervised Classification ◽  
Sampling Method ◽  
Forest Cover ◽  
Sampling Technique ◽  
Residential Area ◽  
Carbon Stocks ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Quantitative Descriptive

This study aims to determine (1) changes in land cover in the Mount Padang Region in 1996, 2006 and 2016, (2) changes in carbon stocks as a result of changes in land cover in the Mount Padang Region of Padang City. The type of research is quantitative descriptive. Changes in land cover isanalyzed based on Landsat TM 5 of 1996 and 2006, as well as Landsat 8 OLI of 2016, using ENVI 4.5 and ArcGIS 10.1 and supervised classification method. Value of carbon stocks is obtained from the equation C = B ×% C (0.47), by predicting biomass on each type of carbon pool using allometric equations, which D2,62 ρ B = 0.11, B = exp {-2.134 + 2.530 × ln (D)}, B = 0.281 D2,06, and B = 0.030 D2,13, where D (diameter at breast height of trees, cm) and ρ (wood density). The sampling technique used is stratified random sampling method which refers to the technique of each plot on land cover classes which are then converted to thehectares area. The results of the analysis show that (1) the land cover in the Mount Padang Region of Padang City in 1996 has forest area of 744.23 Ha (92.6%), mixed garden area of 39.44 Ha (4.9%), shrubs of 17, 92 Ha (2.2%), and the settlement area of 2.35 Ha (0.3%). 2006 forest cover an area of 696.84 Ha (87%), mixed garden area of 18.84 Ha (2%), shrubs covering 37.55 Ha (5%), and residential area of 50.71 ha (6%). 2016 forest cover an area of 533.50 Ha (66%), mixed garden covering an area of 69.14 Ha (9%),shrubs covering 119.81 Ha (15%), and residential area of 81.49 Ha (10%). (2) the carbon stock in 1996 amounted to 495,800.03 tons, in 2006 a number of 458,165.73 tons, and in 2016 a number of 369,223.00 tons. Over the last 20 years, as a result of land cover changes in carbon stocks in Padang Mountain Region has been reduced as much as 126,577.03 tons.

scholarly journals Combining Multiband Remote Sensing and Hierarchical Distance Sampling to Establish Drivers of Bird Abundance

2019 ◽  
Vol 12 (1) ◽  
pp. 38 ◽  
Author(s):  
Ronny Richter ◽  
Arend Heim ◽  
Wieland Heim ◽  
Johannes Kamp ◽  
Michael Vohland
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Russian Far East ◽  
Habitat Preferences ◽  
Far East ◽  
Distance Sampling ◽  
Bird Species ◽  
Survey Method ◽  
Small Scale ◽  
Landsat 8

Information on habitat preferences is critical for the successful conservation of endangered species. For many species, especially those living in remote areas, we currently lack this information. Time and financial resources to analyze habitat use are limited. We aimed to develop a method to describe habitat preferences based on a combination of bird surveys with remotely sensed fine-scale land cover maps. We created a blended multiband remote sensing product from SPOT 6 and Landsat 8 data with a high spatial resolution. We surveyed populations of three bird species (Yellow-breasted Bunting Emberiza aureola, Ochre-rumped Bunting Emberiza yessoensis, and Black-faced Bunting Emberiza spodocephala) at a study site in the Russian Far East using hierarchical distance sampling, a survey method that allows to correct for varying detection probability. Combining the bird survey data and land cover variables from the remote sensing product allowed us to model population density as a function of environmental variables. We found that even small-scale land cover characteristics were predictable using remote sensing data with sufficient accuracy. The overall classification accuracy with pansharpened SPOT 6 data alone amounted to 71.3%. Higher accuracies were reached via the additional integration of SWIR bands (overall accuracy = 73.21%), especially for complex small-scale land cover types such as shrubby areas. This helped to reach a high accuracy in the habitat models. Abundances of the three studied bird species were closely linked to the proportion of wetland, willow shrubs, and habitat heterogeneity. Habitat requirements and population sizes of species of interest are valuable information for stakeholders and decision-makers to maximize the potential success of habitat management measures.

scholarly journals Trends of land cover change in a key biological corridor in Central Nepal

2017 ◽  
Vol 1 (2) ◽  
pp. 64-69
Author(s):  
KRIPA NEUPANE ◽  
AMBIKA P. GAUTAM ◽  
ARUN REGMI
Keyword(s):  
Land Cover ◽  
Land Cover Change ◽  
Forest Cover ◽  
Likelihood Method ◽  
Primary Data ◽  
Landsat 8 ◽  
Central Nepal ◽  
Biological Corridor ◽  
Conservation Awareness ◽  
Land Cover Maps

Neupane K, Gautam AP, Regmi A. 2017. Trends of land cover change in a key biological corridor in Central Nepal. Asian J For 1: 50-55. The study analyzed the changes in land cover in one of the key biological corridors in Central Nepal called the Barandabhar Corridor located in Chitwan District, during the last two decades (i.e. 1991 to 2013). The study is based on analysis of satellite imageries (Landsat 5 TM of 1991 and Landsat 8 OLI_TIRS of 2013) and primary data on drivers of land cover change, collected from the field. Supervised Maximum Likelihood method of image classification was used to produce the land cover maps for 1991 and 2013. The result showed that forest cover in the corridor increased by 7.03% while the coverage of shrubland, water and other land cover types decreased during the study period. Implementation of community based forest management programs, low dependency on forest resources, and increase in conservation awareness among the local people are found to be the main causes behind the increase in forest cover.

scholarly journals Land Use and Land Cover Change Analysis Using GIS and Remote Sensing in The Case of Kersa District, Jimma Zone, Oromia Region, Ethiopia

2021 ◽  
Author(s):  
Nigus Tekleselassie Tsegaye
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Forest Cover ◽  
Agricultural Land ◽  
Landsat Imagery ◽  
Natural Forest ◽  
Landsat 8 ◽  
Change Analysis ◽  
Object Based

Abstract Background: Land use and land cover change is driven by human actions and also drives changes that limit availability of products and services for human and livestock, and it can undermine environmental health as well. Therefore, this study was aimed at understanding land use and land cover change in Kersa district over the last 30 years. Time-series satellite images that included Landsat 5 TM, Landsat 7 ETM+, and Landsat 8 OLI/TIRS, which covered the time frame between 1990-2020, were used to determine the change in land use and land cover using object based classification.Results: The object based classification result revealed that in 1990 TM Landsat imagery, natural forest (16.07%), agroforestry (9.21%), village (12.03%), urban (1.93%), and agriculture (60.76%) were identified. The change result showed a rapid reduction in natural forest cover of 25.04%, 9.15%, and 23.11% occurred between (1990-2000), (2000-2010), and (2010-2020) study periods, respectively. Similarly agroforestry decreased by 0.88% and 63.9% (2000-2010) and (2010-2020), respectively. The finding indicates the increment of agricultural land, village, and urban, while the natural forest and agroforestry cover shows a declining trend.Conclusions: The finding implies that there was a rapid land use and land cover change in the study area. This resulted in loss of natural resource and biodiversity. Overall, proper and integrated approach in implementing policies and strategies related to land use and land cover management should be required in kersa district.

scholarly journals SPATIOTEMPORAL CHANGE DETECTION IN FOREST COVER DYNAMICS ALONG LANDSLIDE SUSCEPTIBLE REGION OF KARAKORAM HIGHWAY, PAKISTAN

2018 ◽  
Vol IV-3 ◽  
pp. 177-184
Author(s):  
Barira Rashid ◽  
Javed Iqbal
Keyword(s):  
Land Cover ◽  
Urban Areas ◽  
Forest Cover ◽  
Accuracy Assessment ◽  
Forest Degradation ◽  
Native Forest ◽  
Landsat 8 ◽  
Forest Cover Change ◽  
Forest Change ◽  
Karakoram Highway

Forest Cover dynamics and its understanding is essential for a country’s social, environmental, and political engagements. This research provides a methodical approach for the assessment of forest cover along Karakoram Highway. It has great ecological and economic significance because it’s a part of China-Pakistan Economic Corridor. Landsat 4, 5 TM, Landsat 7 ETM and Landsat 8 OLI imagery for the years 1990, 2000, 2010 and 2016 respectively were subjected to supervised classification in ArcMap 10.5 to identify forest change. The study area was categorized into five major land use land cover classes i.e., Forest, vegetation, urban, open land and snow cover. Results from post classification forest cover change maps illustrated notable decrease of almost 26 % forest cover over the time period of 26 years. The accuracy assessment revealed the kappa coefficients 083, 0.78, 0.77 and 0.85, respectively. Major reason for this change is an observed replacement of native forest cover with urban areas (12.5 %) and vegetation (18.6 %) However, there is no significant change in the reserved forests along the study area that contributes only 2.97 % of the total forest cover. The extensive forest degradation and risk prone topography of the region has increased the environmental risk of landslides. Hence, effective policies and forest management is needed to protect not only the environmental and aesthetic benefits of the forest cover but also to manage the disaster risks. Apart from the forest assessment, this research gives an insight of land cover dynamics, along with causes and consequences, thereby showing the forest degradation hotspots.

scholarly journals Monitoring Land Encroachment and Land Use & Land Cover (LULC) Change in The Pachhua Dun, Dehradun District Using Landsat Images 1989 and 2020

2021 ◽  
Vol 4 (1) ◽  
pp. 71
Author(s):  
Rahul Thapa ◽  
Vijay Bahuguna
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Change Detection ◽  
Forest Cover ◽  
Agricultural Land ◽  
Rate Of Change ◽  
Sustainable Land Use ◽  
Global Changes ◽  
Landsat 8 ◽  
Lulc Change

Remote sensing and G.I.S help acquire information on changing land use and land cover (LULC), and it plays a pivotal role in measuring and monitoring such local and global changes. The present analysis has been executed on Landsat 5 TM, 1989 and Landsat 8 OLI/TIRS, 2020 images of Pachhua Dun, including Dehradun & Mussoorie urban agglomeration. The present study aims to detect the land encroachment or area of change; rate of change and monitoring spatio-temporal variation in LULC change between 1989-2020 using change detection technique, supervised maximum likelihood classification, and Overall accuracy & Kappa Coefficient (K) was applied as an accuracy assessment tool. The results derived from the change detection analysis exhibits that the highest growth rate was recorded in built-up areas +247.75% (110 km2) and revealed the annual rate of change of 3.55 km2. or  7.99%, the highest among all LULC class during the overall study period of 31 years. The result also found that among all LULC class, the most significant LULC conversion took place from agricultural land to built-up areas followed by open/scrubland and vegetation/forest cover; approximately 69.9km2 of the area under agricultural land was found to be converted into built-up areas. At the same time, 38.9 km2 area of vegetation/forest cover and 36.3 km2 of the area of open/scrubland have converted into agricultural land. Rising anthropogenic influence and unsustainable land-use practices in the study area have led to a large-scale human encroachment and rapid transformation of the natural landscape into the cultural landscape. This analysis provides the essential long-term Geospatial information related to LULC change for making optimum decision-making process and sustainable land-use planning in the Pachhua Dun-Dehradun District, Uttarakhand, India. 

scholarly journals Land-Cover Classification of Coastal Wetlands Using the RF Algorithm for Worldview-2 and Landsat 8 Images

2019 ◽  
Vol 11 (16) ◽  
pp. 1927 ◽  
Author(s):  
Xiaoxue Wang ◽  
Xiangwei Gao ◽  
Yuanzhi Zhang ◽  
Xianyun Fei ◽  
Zhou Chen ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Image Classification ◽  
Classification Accuracy ◽  
Coastal Wetlands ◽  
Land Cover Classification ◽  
Support Vector ◽  
Small Scale ◽  
Landsat 8

Wetlands are one of the world’s most important ecosystems, playing an important role in regulating climate and protecting the environment. However, human activities have changed the land cover of wetlands, leading to direct destruction of the environment. If wetlands are to be protected, their land cover must be classified and changes to it monitored using remote sensing technology. The random forest (RF) machine learning algorithm, which offers clear advantages (e.g., processing feature data without feature selection and preferable classification result) for high spatial image classification, has been used in many study areas. In this research, to verify the effectiveness of this algorithm for remote sensing image classification of coastal wetlands, two types of spatial resolution images of the Linhong Estuary wetland in Lianyungang—Worldview-2 and Landsat-8 images—were used for land cover classification using the RF method. To demonstrate the preferable classification accuracy of the RF algorithm, the support vector machine (SVM) and k-nearest neighbor (k-NN) methods were also used to classify the same area of land cover for comparison with the results of RF classification. The study results showed that (1) the overall accuracy of the RF method reached 91.86%, higher than the SVM and k-NN methods by 4.68% and 4.72%, respectively, for Worldview-2 images; (2) at the same time, the classification accuracies of RF, SVM, and k-NN were 86.61%, 79.96%, and 77.23%, respectively, for Landsat-8 images; (3) for some land cover types having only a small number of samples, the RF algorithm also achieved better classification results using Worldview-2 and Landsat-8 images, and (4) the addition texture features could improve the classification accuracy of the RF method when using Worldview-2 images. Research indicated that high-resolution remote sensing images are more suitable for small-scale land cover classification image and that the RF algorithm can provide better classification accuracy and is more suitable for coastal wetland classification than the SVM and k-NN algorithms are.

scholarly journals Assessment Land Cover Change Using Normalized Difference Water Index (NDWI) In Bakun Reservoir, Sarawak

2021 ◽  
pp. 1-4
Author(s):  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Land Use Planning ◽  
Power Plants ◽  
Forest Cover ◽  
Equatorial Region ◽  
Water Bodies ◽  
Landsat 8 ◽  
Hydroelectric Power

The location of Sarawak State in the equatorial region makes it an area of high rainfall. For this reason, hydroelectric power plants have been built in several catchments in Sarawak, especially in the Kapit area. This needs to be harnessed to improve the economy and social living standards of the people of Sarawak in particular. This paper presents the land cover change by analyzing the stratification change for 30 years (1985-2018) at Bakun Dam, Sarawak. This study uses Landsat 5 and Landsat 8 satellite data. Both data have to go through pre-processing such as geometric, radiometric, and atmospheric corrections. In this study, Normalized Water Difference Index (NDWI) is used to classify water areas, built human areas, and vegetation areas. Overlay analysis was applied to identify areas that had changed over the 30 years in the study area. The results showed the greatest changes from vegetation areas to water bodies for 30 years. The results showed that the most affected land cover was forest cover with a reduction of 740 km², which shifted mainly to water bodies with 669.9 km² and human development with an area of 68.7 km². The study area is less populated and anthropogenic influences are rather low, but deforestation is observed in the upper river basin. These events would change the hydrological behavior of these catchments in the future. Land cover mapping is very important to provide information to those responsible for planning sustainable development. In addition, land cover maps are important for land use planning and land use regulation to avoid land-use conflicts.

scholarly journals Trajectories of land cover transformation in zonal types of landscapes of Indochina

2019 ◽  
Vol 151 (4) ◽  
pp. 1-14
Author(s):  
N. N. Alekseeva ◽  
О. А. Klimanova ◽  
D. А. Tretyachenko ◽  
A. I. Bancheva
Keyword(s):  
Land Cover ◽  
Land Cover Change ◽  
Land Surface ◽  
Forest Cover ◽  
Agricultural Sector ◽  
Surface Characteristics ◽  
Forest Degradation ◽  
Small Scale ◽  
Altitudinal Zonality ◽  
River Valleys

The article deals with the study of the land cover change of Indochina based on the MODIS Land Cover database for 2001—2012. Geospatial land cover data, which are objectively recorded land surface characteristics, are widely used for small-scale mapping of landscapes and ecological systems. The case region of Indochina was selected for the analysis of land cover transformation. In recent decades it has been undergoing active transformation of land use, associated with rapid economic development, substantial population growth, and reorientation of the agricultural sector to foreign markets. The processes of land cover change were studied within the boundaries of zonal types of landscapes, altitudinal zonality spectra, and groups of intrazonal landscapes. The density of changes is uneven in different zonal types of landscapes, the greatest range of transformations is characteristic to the deciduous monsoon forests, semi-evergreen forests (in the subequatorial belt), and within river valleys. The main trajectories of land cover change for 2001—2012 are as follows: 1) expansion of arable areas due to the reduction of forests, savannas and grasslands; 2) the likely increase in the area of perennial plantations (mainly rubber trees and oil palm); 3) forest degradation and spread of savannas; 4) fluctuations of land under shifting cultivation. Since the 2000s commercial production of perennial cash crops is the main cause of deforestation in the region. Land clearing for these needs could have a greater impact on forest cover than logging. The revealed features of land cover change for Indochina made it possible to specify the regional characteristics of the transformation processes as compared to global typology of land coverchanges.

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