scholarly journals Land change-based forest management scenario in the typology of island clusters in Maluku Province, Indonesia

2021 ◽  
Vol 22 (9) ◽  
Author(s):  
Patrich Papilaya ◽  
I NENGAH SURATI JAYA ◽  
TEDDY RUSOLONO ◽  
NINING PUSPANINGSIH
Keyword(s):  
Forest Management ◽  
Land Cover ◽  
Forest Cover ◽  
Forest Degradation ◽  
Land Change ◽  
Land Capability ◽  
Spatial Trend ◽  
Management Scenario ◽  
Spatial Trends ◽  
Land Cover Maps

Abstract. Papilaya PPE, Jaya INS, Rusolono T, Puspaningsih N. 2021. Land change-based forest management scenario in the typology of island clusters in Maluku Province, Indonesia. Biodiversitas 22: 3756-3763. This study aims to describe the development of forest area utilization scenarios with biophysical, social and spatial trend approaches. In this study, spatial trends were identified using forest and land cover maps from 2000 to 2018, and the methods used include change detection, spatial trend and overlay. The study was designed using forest cover scenarios along with spatial trends and social and biophysical approaches. The results of the 5 typologies of island clusters analysis showed that forest degradation has occurred in an area of ± 77102 ha between 2000 and 2018 with an average of 4283.4 ha/year. Furthermore, Total Land Cover Loss at the location of the five island cluster typology for 18 years was found to be ± 422805 Ha with an average of ± 23489.06 ha/year. The land capability was categorized into 3 classes. Therefore, the five spatial trends were known to form in the typology of five island clusters with different directions and magnitudes.

scholarly journals Multitemporal Analysis Using Landsat Thematic Mapper (TM) Bands for Forest Cover Classification in East Texas

2008 ◽  
Vol 32 (1) ◽  
pp. 21-27
Author(s):  
Jason C. Raines ◽  
Jason Grogan ◽  
I-Kuai Hung ◽  
James Kroll
Keyword(s):  
Land Cover ◽  
Classification Accuracy ◽  
Forest Cover ◽  
Thematic Mapper ◽  
Landsat Thematic Mapper ◽  
Forest Types ◽  
Significant Difference ◽  
Potential Benefits ◽  
Land Cover Maps ◽  
Band Combinations

Abstract Land cover maps have been produced using satellite imagery to monitor forest resources since the launch of Landsat 1. Research has shown that stacking leaf-on and leaf-off imagery (combining two separate images into one image for processing) may improve classification accuracy. It is assumed that the combination of data will aid in differentiation between forest types. In this study we explored potential benefits of using multidate imagery versus single-date imagery for operational forest cover classification as part of an annual remote sensing forest inventory system. Landsat Thematic Mapper (TM) imagery was used to classify land cover into four classes. Six band combinations were tested to determine differences in classification accuracy and if any were significant enough to justify the extra cost and increased difficulty of image acquisition. The effects of inclusion/exclusion of the moisture band (TM band 5) also were examined. Results show overall accuracy ranged from 72 to 79% with no significant difference between single and multidate classifications. We feel the minimal increase (3.06%) in overall accuracy, coupled with the operational difficulties of obtaining multiple (two), useable images per year, does not support the use of multidate stacked imagery. Additional research should focus on fully utilizing data from a single scene by improving classification methodologies.

scholarly journals A comparison of forest resource inventory, provincial land cover maps and field surveys for wildlife habitat analysis in the Great Lakes – St. Lawrence forest

2010 ◽  
Vol 86 (1) ◽  
pp. 77-86 ◽  
Author(s):  
Andrea J. Maxie ◽  
Karen F. Hussey ◽  
Stacey J. Lowe ◽  
Kevin R. Middel ◽  
Bruce A. Pond ◽  
...  
Keyword(s):  
Land Cover ◽  
Forest Cover ◽  
Satellite Image ◽  
Wildlife Habitat ◽  
Forest Resource ◽  
Habitat Analysis ◽  
Resource Inventory ◽  
Forest Resource Inventory ◽  
Land Cover Maps ◽  
Forest Cover Types

In a portion of central Ontario, Canada we assessed the classification agreement between field-based estimates of forest stand composition and each of two mapped data sources used in wildlife habitat studies, the Forest Resource Inventory (FRI) and satellite-image derived Provincial Land Cover (PLC). At two study areas, Algonquin Provincial Park (APP) and Wildlife Management Unit 49 (WMU49), we surveyed 119 forest stands and 40 water and wetland stands. Correspondence levels between FRI and field classifications were 48% in APP and 44% in WMU49 when assessing six forest cover types. With only four simplified forest cover types, levels improved to 77% in APP and 63% in WMU49. Correspondence between PLC and field classifications for three forested stand types was approximately 63% in APP and 55% in WMU49. Because of the poor to moderate level of correspondence we detected between map and field classifications, we recommend that care be exercised when FRI or PLC maps are used in forest and wildlife research and management planning. Key words: forest resource inventory, FRI, provincial land cover, PLC, Landsat Thematic Mapper, map accuracy, map correspondence, map agreement, Ontario, wildlife habitat

scholarly journals Drivers and dynamics of land use land cover in Ambung VDC of Tehrathum district, Nepal

2016 ◽  
Vol 26 (1) ◽  
pp. 90-96 ◽  
Author(s):  
D Pandey ◽  
B P Heyojoo ◽  
H Shahi
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Forest Cover ◽  
Group Discussion ◽  
Household Survey ◽  
Land Use Land Cover ◽  
Landsat Images ◽  
Severe Problem ◽  
Training Samples ◽  
Land Cover Maps

Land use and land cover change has immense impact on the global environment and ecosystem. Geospatial technologies are very important for monitoring these changes. This research aims to find out the land use land cover dynamics and drivers of Ambung VDC, Tehrathum district. The Landsat images of the year 1990 and 2013 were used for quantifying the changes. Household survey, key informant interview, focus group discussion, training samples collection and direct field observations were carried out to gather socio-economic and bio-physical data. Supervised classification was performed to prepare land cover maps. Change on land use was calculated by using post classification change detection. During 1990–2013, forest cover was found to have increased by 6.6%, agriculture decreased by 5.9% and others (barren, settlement, grass, rock and water bodies) decreased by 0.7%. The VDC was found to have severe problem of rapid drying of water resources in spite of the increase in forest cover, and so research should be carried out to find out the reason and solve the problem before it is too late.Banko JanakariA Journal of Forestry Information for NepalVol. 26, No. 1, Page:90-96, 2016

KAJIAN POLA PEMANFAATAN RUANG DI KABUPATEN GARUT BERBASIS DAYA DUKUNG LINGKUNGAN HIDUP

2010 ◽  
Vol 12 (2) ◽  
pp. 40
Author(s):  
Ardhy Firdian ◽  
Baba Barus ◽  
Didit Okta Pribadi
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Spatial Pattern ◽  
Carrying Capacity ◽  
Forest Cover ◽  
Land Capability ◽  
Environmental Carrying Capacity ◽  
Space Pattern ◽  
Land Carrying Capacity ◽  
Landsat Satellite

<p>Enviromental carrying capacity was measured in three methods,i.e land capability, land carrying capacity and water carrying capacity. Garut Regency which is located at the upstream Cimanuk Watershed has an important role in the sustainability of capacity for downstream area. The aims of this study are: (1) to identify land use in Garut Regency in 2009, (2) to identify land capability in Garut Regency, (3) to assess the suitability of land use with land capability and space pattern in Garut Regency, (4) to identify the status of environmental carrying capacity in Garut Regency, and (5) to set a space pattern based on environmental carrying capacity. Based on the interpretation of Landsat Satellite Imagery in 2009, dryland agriculture has dominated the coverage about 45.4% and forest cover about 23.8%. This study also shows that most area in Garut Regency is belong to Class IV land capability (36.4% of the regency area) without Class I of land capability. Suitabilty evaluation between land cover and land capabilty describe that 48,45% area is suitable, 50.4% area is not suitable and 1.18% area is conditionally suitable depending on limitation factors that affect land capability. Another evaluation between space patern and land capability shown that 59.0% area is suitable, 32.1% area is not suitable, and 8.84% area is conditionally suitable. Both status of land carrying capacity and water carrying capacity are deficit. According to spatial pattern based on land capability and existing forest, space that can be use as the preservation area is about 58.5% of the area, and space that can be use as the cultivation area is about 41.5% of the area of Garut Regency.<br />Keywords : Land capability, land cover/use, spatial pattern, water carrying capacity</p>

scholarly journals Understanding Current and Future Fragmentation Dynamics of Urban Forest Cover in the Nanjing Laoshan Region of Jiangsu, China

2020 ◽  
Vol 12 (1) ◽  
pp. 155 ◽  
Author(s):  
Wenjuan Shen ◽  
Xupeng Mao ◽  
Jiaying He ◽  
Jinwei Dong ◽  
Chengquan Huang ◽  
...  
Keyword(s):  
Land Cover ◽  
Markov Model ◽  
Forest Cover ◽  
Urban Forest ◽  
Detection Algorithm ◽  
Forest Area ◽  
Spatiotemporal Pattern ◽  
Forest Cover Change ◽  
Forest Interior ◽  
Land Cover Maps

Accurate acquisition of the spatiotemporal distribution of urban forests and fragmentation (e.g., interior and intact regions) is of great significance to contributing to the mitigation of climate change and the conservation of habitat biodiversity. However, the spatiotemporal pattern of urban forest cover changes related with the dynamics of interior and intact forests from the present to the future have rarely been characterized. We investigated fragmentation of urban forest cover using satellite observations and simulation models in the Nanjing Laoshan Region of Jiangbei New Area, Jiangsu, China, during 2002–2023. Object-oriented classification-based land cover maps were created to simulate land cover changes using the cellular automation-Markov chain (CA-Markov) model and the state transition simulation modeling. We then quantified the forest cover change by the morphological change detection algorithm and estimated the forest area density-based fragmentation patterns. Their relationships were built through the spatial analysis and statistical methods. Results showed that the overall accuracies of actual land cover maps were approximately 83.75–92.25% (2012–2017). The usefulness of a CA-Markov model for simulating land cover maps was demonstrated. The greatest proportion of forest with a low level of fragmentation was captured along with the decreasing percentage of fragmented area from 81.1% to 64.1% based on high spatial resolution data with the window size of 27 pixels × 27 pixels. The greatest increase in fragmentation (3% from 2016 to 2023) among the changes between intact and fragmented forest was reported. However, intact forest was modeled to have recovered in 2023 and restored to 2002 fragmentation levels. Moreover, we found 58.07 km2 and 0.35 km2 of interior and intact forests have been removed from forest area losses and added from forest area gains. The loss rate of forest interior and intact area exceeded the rate of total forest area loss. However, their approximate ratio (1) implying the loss of forest interior and intact area would have slight fragmentation effects on the remaining forests. This analysis illustrates the achievement of protecting and restoring forest interior; more importantly, excessive human activities in the surrounding area had been avoided. This study provides strategies for future forest conservation and management in large urban regions.

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 Future Simulation of Land Use Changes in Rapidly Urbanizing South China Based on Land Change Modeler and Remote Sensing Data

2020 ◽  
Vol 12 (11) ◽  
pp. 4350
Author(s):  
Sarah Hasan ◽  
Wenzhong Shi ◽  
Xiaolin Zhu ◽  
Sawaid Abbas ◽  
Hafiz Usman Ahmed Khan
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Urban Area ◽  
South China ◽  
Forest Cover ◽  
Nearest Neighbor ◽  
Land Use Land Cover ◽  
Land Change ◽  
Landsat Images ◽  
Land Change Modeler

Landscape transformations in rapidly urbanizing Guangdong, Hong Kong, and Macao (GHKM) regions of South China represent the most complex and dynamic processes altering the local ecology and environment. In this study, Land Change Modeler (LCM) is applied to land use land cover (LULC) maps for the years 2005, 2010, and 2017, derived from Landsat images, with the aim of understanding land use land cover change patterns during 2005–2017 and, further, to predict the future scenario of the years 2024 and 2031. Furthermore, the changes in spatial structural patterns are quantified and analyzed using selected landscape morphological metrics. The results show that the urban area has increased at an annual rate of 4.72% during 2005–2017 and will continue to rise from 10.31% (20,228.95 km2) in 2017 to 16.30% (31,994.55 km2) in 2031. This increase in urban area will encroach further into farmland and fishponds. However, forest cover will continue to increase from 45.02% (88,391.98 km2) in 2017 to 46.88% (92,049.62 km2) in 2031. This implies a decrease in the mean Euclidian nearest neighbor distance (ENN_MN) of forest patches (from 217.57 m to 206.46 m) and urban clusters (from 285.55 m to 245.06 m) during 2017–2031, indicating an accelerated landscape transformation if the current patterns of the change continues over the next decade. Thus, knowledge of the current and predicted LULC changes will help policy and decision makers to reconsider and develop new policies for the sustainable development and protection of natural resources.

scholarly journals Assessment of Land Cover Change and Its Impact on Changes in Soil Erosion Risk in Nepal

2018 ◽  
Vol 10 (12) ◽  
pp. 4715 ◽  
Author(s):  
Kabir Uddin ◽  
Mir Abdul Matin ◽  
Sajana Maharjan
Keyword(s):  
Soil Erosion ◽  
Land Cover ◽  
Land Cover Change ◽  
Soil Conservation ◽  
Forest Cover ◽  
Human Life ◽  
Landsat Images ◽  
Erosion Risk ◽  
Soil Erosion Risk ◽  
Land Cover Maps

Land cover change is a critical driver for enhancing the soil erosion risk in Nepal. Loss of the topsoil has a direct and indirect effect on human life and livelihoods. The present study provides an assessment of the decadal land use and land cover (LULC) change and consequent changes in the distribution of soil erosion risk for the years, 1990, 2000, and 2010, for the entire country of Nepal. The study attempted to understand how different land cover types change over the three decades and how it has changed the distribution of soil erosion risks in Nepal that would help in the development of soil conservation priority. The land cover maps were produced using geographic object-based image analysis (GEOBIA) using Landsat images. Soil erosion patterns were assessed using the revised universal soil loss equation (RUSLE) with the land cover as the input. The study shows that the forest cover is the most dominant land cover in Nepal that comprises about 6,200,000 ha forest cover. The estimated annual erosion was 129.30 million tons in 1990 and 110.53 million tons in 2010. The assessment of soil erosion dynamics was presented at the national, provincial, and district level. District wise analysis revealed that Gulmi, Parbat, Syangja, and the Tanahu district require priority for soil conservation.

scholarly journals Assessing land cover change in Namibia's Kavango East region: a multi-date object approach

2020 ◽  
Vol 344 ◽  
pp. 17-32
Author(s):  
Edward MUHOKO ◽  
Carlos De WASSEIGE ◽  
Vera DE CAUWER
Keyword(s):  
Land Cover ◽  
Land Cover Change ◽  
Forest Cover ◽  
The Novel ◽  
East Region ◽  
Novel Approach ◽  
Object Based ◽  
Global Issue ◽  
Dry Tropical Forests ◽  
Land Cover Maps

Land cover change is a global issue but its effects can be particularly severe in developing countries such as Namibia, by affecting the ecological functions of ecosystems and hence the sustainability of its development. Namibia’s arid conditions, due to low rainfall and high evapotranspiration rates, coupled with annual savannah fires, have resulted in a heterogenous landscape composed of a mixture of trees, shrubs and herbaceous plants. As a result, land cover maps are often inaccurate at the pixel level. Despite their relatively high accuracy, object-based image analyses are yet to be exhaustively applied to the dry tropical forests of Southern Africa.  The purpose of this study was to apply a multi-date object-based approach to land cover change, in order to determine its extent and dynamics in the heterogenous landscape of Kavango East, one of the regions with the highest forest cover in Namibia. Multi-date segmentation, mean band values and image differentiation were used to detect land cover changes in four periods (1990, 2000, 2009 and 2016). The most common land conversion for all the periods was from forest to cropland. In 1990, forests covered 58% of the land but by 2016, this had dropped to 55%. Meanwhile, cropland covered 3% of the study area in 1990 and had doubled to 6% by 2016. The novel approach used in this study has produced promising results compared to traditional methods, which are prone to errors in detecting post-classification changes. The method can therefore be recommended for long term monitoring of land cover and land use change in areas with similar environmental and biophysical conditions.

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