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 Accuracy and Spatial Pattern Assessment of Forest Cover Change Datasets in Central Kalimantan

2018 ◽  
Vol 50 (2) ◽  
pp. 222 ◽  
Author(s):  
Sanjiwana Arjasakusuma ◽  
Uji Astrono Pribadi ◽  
Gilang Aria Seta
Keyword(s):  
Spatial Pattern ◽  
Forest Cover ◽  
Accuracy Assessment ◽  
Accurate Information ◽  
Forest Cover Change ◽  
Forest Change ◽  
Consistency Analysis ◽  
Error Matrix ◽  
Central Kalimantan ◽  
The Road

The accurate information of forest cover change is important to measure the amount of carbon release and sink. The newly-available remote sensing based products and method such as Daichi Forest/Non-Forest (FNF), Global Forest Change (GFC) datasets and Semi-automatic Claslite systems offers the benefit to derive these information in a quick and simple manner. We measured the accuracy by constructing area-proportion error matrix from 388 random sample points and assessed the consistency analysis by looking at the spatial pattern of deforestation and regrowth from built-up area, roads, and rivers from 2010 – 2015 in Katingan district, Central Kalimantan. Accuracy assessment showed that those 3 datasets indicate low to medium accuracy level in which the highest accuracy was achieved by Claslite who produced 71 % ± 5 % of overall accuracy. The consistency analysis provides a similar spatial pattern of deforestation and regrowth measured from the road, river, and built-up area though their distance sensitivity are different one to another. 

scholarly journals Assessment of Large Scale Land Cover Change Classifications and Drivers of Deforestation in Indonesia

2015 ◽  
Vol XL-7/W3 ◽  
pp. 557-562 ◽  
Author(s):  
A. Wijaya ◽  
R. A. Sugardiman Budiharto ◽  
A. Tosiani ◽  
D. Murdiyarso ◽  
L.V. Verchot
Keyword(s):  
Land Cover ◽  
Large Scale ◽  
Forest Cover ◽  
Spatial Information ◽  
Brazilian Amazon ◽  
Congo Basin ◽  
Reliable Estimate ◽  
Forest Conversion ◽  
Forest Cover Change ◽  
Forest Change

Indonesia possesses the third largest tropical forests coverage following Brazilian Amazon and Congo Basin regions. This country, however, suffered from the highest deforestation rate surpassing deforestation in the Brazilian Amazon in 2012. National capacity for forest change assessment and monitoring has been well-established in Indonesia and the availability of national forest inventory data could largely assist the country to report their forest carbon stocks and change over more than two decades. This work focuses for refining forest cover change mapping and deforestation estimate at national scale applying over 10,000 scenes of Landsat scenes, acquired in 1990, 1996, 2000, 2003, 2006, 2009, 2011 and 2012. Pre-processing of the data includes, geometric corrections and image mosaicking. The classification of mosaic Landsat data used multi-stage visual observation approaches, verified using ground observations and comparison with other published materials. There are 23 land cover classes identified from land cover data, presenting spatial information of forests, agriculture, plantations, non-vegetated lands and other land use categories. We estimated the magnitude of forest cover change and assessed drivers of forest cover change over time. Forest change trajectories analysis was also conducted to observe dynamics of forest cover across time. This study found that careful interpretations of satellite data can provide reliable information on forest cover and change. Deforestation trend in Indonesia was lower in 2000-2012 compared to 1990-2000 periods. We also found that over 50% of forests loss in 1990 remains unproductive in 2012. Major drivers of forest conversion in Indonesia range from shrubs/open land, subsistence agriculture, oil palm expansion, plantation forest and mining. The results were compared with other available datasets and we obtained that the MOF data yields reliable estimate of deforestation.

scholarly journals Using Geospatial Analysis to Map Forest Change in New Hampshire: 1996–Present

2020 ◽  
Vol 118 (6) ◽  
pp. 598-612
Author(s):  
Heather Grybas ◽  
Russell G Congalton ◽  
Andrew F Howard
Keyword(s):  
Land Cover ◽  
New Hampshire ◽  
Forest Cover ◽  
Landsat Imagery ◽  
The State ◽  
Forest Cover Change ◽  
Forest Change ◽  
Change Analysis ◽  
Land Cover Map ◽  
Forest Use

Abstract New Hampshire’s forests are vitally important to the state’s economy; however, there are indications that the state is experiencing a continuous loss in forest cover. We sought to investigate forest cover trends in New Hampshire. A baseline trend in forest cover between 1996 and 2010 was established using National Oceanic and Atmospheric Administration Coastal Change Analysis Program land cover data. A land cover map was then generated from Landsat imagery to extend the baseline trend to 2018. Results show that the state has experienced a continual decline in forest cover with the annual net loss steadily increasing from 0.14% between 1996 and 2001 to 0.27% between 2010 and 2018. Additionally, the more urbanized counties in southern New Hampshire are experiencing some of the greatest rates of net forest loss, most likely because of urbanization and agricultural expansion. This study demonstrated an effective methodology for tracking forest cover change and will hopefully inform future forest use policies.

scholarly journals Spatial-Temporal Land Use and Land Cover Changes in Urban Areas Using Remote Sensing Images and GIS Analysis: The Case Study of Opole, Poland

Geosciences ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 312
Author(s):  
Barbara Wiatkowska ◽  
Janusz Słodczyk ◽  
Aleksandra Stokowska
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Satellite Imagery ◽  
Urban Areas ◽  
Agricultural Land ◽  
Urban Expansion ◽  
Landsat 8 ◽  
Rate Of Increase ◽  
Management Procedures

Urban expansion is a dynamic and complex phenomenon, often involving adverse changes in land use and land cover (LULC). This paper uses satellite imagery from Landsat-5 TM, Landsat-8 OLI, Sentinel-2 MSI, and GIS technology to analyse LULC changes in 2000, 2005, 2010, 2015, and 2020. The research was carried out in Opole, the capital of the Opole Agglomeration (south-western Poland). Maps produced from supervised spectral classification of remote sensing data revealed that in 20 years, built-up areas have increased about 40%, mainly at the expense of agricultural land. Detection of changes in the spatial pattern of LULC showed that the highest average rate of increase in built-up areas occurred in the zone 3–6 km (11.7%) and above 6 km (10.4%) from the centre of Opole. The analysis of the increase of built-up land in relation to the decreasing population (SDG 11.3.1) has confirmed the ongoing process of demographic suburbanisation. The paper shows that satellite imagery and GIS can be a valuable tool for local authorities and planners to monitor the scale of urbanisation processes for the purpose of adapting space management procedures to the changing environment.

scholarly journals A Modified Bare Soil Index to Identify Bare Land Features during Agricultural Fallow-Period in Southeast Asia Using Landsat 8

Land ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 231
Author(s):  
Can Trong Nguyen ◽  
Amnat Chidthaisong ◽  
Phan Kieu Diem ◽  
Lian-Zhi Huo
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Urban Areas ◽  
Near Infrared ◽  
Urban Landscape ◽  
Bare Soil ◽  
Critical Element ◽  
Landsat 8 ◽  
Climate Conditions ◽  
Fallow Period

Bare soil is a critical element in the urban landscape and plays an essential role in urban environments. Yet, the separation of bare soil and other land cover types using remote sensing techniques remains a significant challenge. There are several remote sensing-based spectral indices for barren detection, but their effectiveness varies depending on land cover patterns and climate conditions. Within this research, we introduced a modified bare soil index (MBI) using shortwave infrared (SWIR) and near-infrared (NIR) wavelengths derived from Landsat 8 (OLI—Operational Land Imager). The proposed bare soil index was tested in two different bare soil patterns in Thailand and Vietnam, where there are large areas of bare soil during the agricultural fallow period, obstructing the separation between bare soil and urban areas. Bare soil extracted from the MBI achieved higher overall accuracy of about 98% and a kappa coefficient over 0.96, compared to bare soil index (BSI), normalized different bare soil index (NDBaI), and dry bare soil index (DBSI). The results also revealed that MBI considerably contributes to the accuracy of land cover classification. We suggest using the MBI for bare soil detection in tropical climatic regions.

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.

scholarly journals The importance of glacier and forest change in hydrological climate-impact studies

2013 ◽  
Vol 17 (2) ◽  
pp. 619-635 ◽  
Author(s):  
N. Köplin ◽  
B. Schädler ◽  
D. Viviroli ◽  
R. Weingartner
Keyword(s):  
Land Cover ◽  
Water Balance ◽  
Catchment Area ◽  
Forest Cover ◽  
Control Period ◽  
Climate Impact ◽  
Glacier Retreat ◽  
Climate Scenarios ◽  
Forest Change ◽  
Impact Studies

Abstract. Changes in land cover alter the water balance components of a catchment, due to strong interactions between soils, vegetation and the atmosphere. Therefore, hydrological climate impact studies should also integrate scenarios of associated land cover change. To reflect two severe climate-induced changes in land cover, we applied scenarios of glacier retreat and forest cover increase that were derived from the temperature signals of the climate scenarios used in this study. The climate scenarios were derived from ten regional climate models from the ENSEMBLES project. Their respective temperature and precipitation changes between the scenario period (2074–2095) and the control period (1984–2005) were used to run a hydrological model. The relative importance of each of the three types of scenarios (climate, glacier, forest) was assessed through an analysis of variance (ANOVA). Altogether, 15 mountainous catchments in Switzerland were analysed, exhibiting different degrees of glaciation during the control period (0–51%) and different degrees of forest cover increase under scenarios of change (12–55% of the catchment area). The results show that even an extreme change in forest cover is negligible with respect to changes in runoff, but it is crucial as soon as changes in evaporation or soil moisture are concerned. For the latter two variables, the relative impact of forest change is proportional to the magnitude of its change. For changes that concern 35% of the catchment area or more, the effect of forest change on summer evapotranspiration is equally or even more important than the climate signal. For catchments with a glaciation of 10% or more in the control period, the glacier retreat significantly determines summer and annual runoff. The most important source of uncertainty in this study, though, is the climate scenario and it is highly recommended to apply an ensemble of climate scenarios in the impact studies. The results presented here are valid for the climatic region they were tested for, i.e., a humid, mid-latitude mountainous environment. They might be different for regions where the evaporation is a major component of the water balance, for example. Nevertheless, a hydrological climate-impact study that assesses the additional impacts of forest and glacier change is new so far and provides insight into the question whether or not it is necessary to account for land cover changes as part of climate change impacts on hydrological systems.

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.

Opportunities for Reaping the Benefits of REDD+ in Sikkim Himalaya for Conservation and Enhancement of Carbon Stock

2017 ◽  
Vol 40 (3) ◽  
pp. 209-215
Author(s):  
Mohommad Shahid ◽  
◽  
L.K. Rai ◽  
Keyword(s):  
Climate Change ◽  
Forest Cover ◽  
Carbon Sink ◽  
Forest Degradation ◽  
Forest Cover Change ◽  
Change Analysis ◽  
Carbon Sequestration Potential ◽  
Sequestration Potential ◽  
Article 5

Paris Agreement recognized the role of forests as carbon sink for mitigation of climate change, under Article 5 as REDD+, i.e., reducing emissions from deforestation and forest degradation and role of conservation, sustainable management of forests and enhancement of forest carbon stocks. Forest cover change analysis was done between two time periods 2005 and 2015 to assess the forest degradation. Carbon sequestration potential of the forests of Sikkim for mitigating climate change is also estimated. Benefits of implementing of REDD+ in Sikkim involving local communities as stakeholder to conserve and sustainably manage the forest is assessed. Gaps and challenges faced by the stakeholder in implementing REDD+ at project level are also highlighted.

scholarly journals Deciphering forest change: Linking satellite-based forest cover change and community perceptions in a threatened landscape in India

AMBIO ◽  
2018 ◽  
Vol 48 (7) ◽  
pp. 790-800 ◽  
Author(s):  
Vikram Aditya ◽  
Thyagarajan Ganesh
Keyword(s):  
Forest Cover ◽  
Community Perceptions ◽  
Forest Cover Change ◽  
Forest Change
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