scholarly journals The Use of Small Format Air Photos for Mapping Land Cover Changes in Gumuk Pasir Parangtritis Core-Zone, 2015-2019

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Maulidini Fatimah Azahra ◽  
J Jumadi ◽  
Agus Anggoro Sigit
Keyword(s):  
Land Cover ◽  
Sand Dune ◽  
Land Use Changes ◽  
Mapping Method ◽  
Aerial Photographs ◽  
Land Cover Changes ◽  
Core Zone ◽  
The Core ◽  
Object Based ◽  
Tourism Economy

Gumuk Pasir Parangtritis is one of the potentials of the coastal area of ​​Parangtritis village in Yogyakarta, with several important roles for the coastal ecosystem and its surroundings, such as ecology, disaster, tourism, economy, and aquifer reserves. However, behind this important role, the existence of sandbanks is increasingly threatened from year to year because the area of ​​sand cover continues to decline, especially in the core zone. Therefore, regular and effective mapping and monitoring efforts are needed. This study aims to a) conduct land cover mapping using the Geographic Object Based Image Analysis (GEOBIA) method in the 2015-2019 timeframe; b) analyze changes in land cover in the core zone of sandbanks during 2015-2019; and c) evaluate the results of restoration of sand dune core zone in terms of land cover changes that have occurred until 2019. Small format aerial photographs (FUFK) are the data used in this study while the mapping method used is rule-based classification. The land cover of the sand dune core zone in 2015 included buildings, vegetation, sand, roads and ponds, while in 2019 it was in the form of buildings, vegetation, sand, and roads. Based on the classification results in the two years, it can be seen that there are changes in land cover (including area) through the cross-section of the two classification results. Some of the factors include the number of land use changes, the amount of vegetation, and sand mining. Furthermore, this change can be used as a basis for evaluating the success of the restoration efforts of the Gumuk Pasir Parangtritis core zone to date. The results of the evaluation show that the restoration carried out so far has not had much impact so it can be said that it has not been successful, because the area of ​​sand cover has actually decreased a lot (from 528,680 m2 to 344,347 m2), while the land cover in the form of vegetation and buildings has increased in size (from 869,341 m2 to 1,037,879 m2 for vegetation cover and an area of ​​4,674 m2 to 22,953 m2 for buildings).

scholarly journals MAPPING OF LAND USE CHANGES IN THE CORE ZONE OF PARANGTRITIS SAND DUNES USING OBIA METHOD 2015-2020

2021 ◽  
Vol 13 (1) ◽  
pp. 109
Author(s):  
Latifa Melani Putri ◽  
Pramaditya Wicaksono
Keyword(s):  
Land Use ◽  
Image Analysis ◽  
Sand Dune ◽  
Sand Dunes ◽  
Land Use Changes ◽  
Dry Land ◽  
Core Zone ◽  
Object Based Image Analysis ◽  
The Core ◽  
Object Based

Indonesia has many types of unique and rare landforms, one of which is sand dunes, which is located in Parangtritis. Sand dune has the main function as a conservation area, natural wall for the tsunami disaster, water catchment area, and habitat for sand dune flora and fauna. However, the existence of sand dunes is currently threatened with extinction due to the decrease in their area, which is caused by changes in land use. Every year, the land use in the Parangtritis sand dune changes. Therefore, it is important to map land use changes to determine the changes that occur in the sand dune core zone. This study aims to map land use change in the core zone of sand dunes using small format aerial images and the OBIA (Object-Based Image Analysis) method. Land use in the study area is classified into nine classes, namely sand dunes, dry land forest, shrubs, coastal shoals, open field, built-up area and settlements, dry land agricultural fields, roads, and fishponds. The results showed that there were changes in all land use classes. Based on the accuracy assessment, the overall accuracy for 2020 was 68.95%, while the classification results for 2015 were 61.81%.Keywords: land use changes, OBIA, Small Format Aerial PhotographyIndonesia memiliki banyak jenis bentuklahan yang unik dan langka, salah satunya adalah gumuk pasir yang terletak di wilayah Parangtritis, Daerah Istimewa Yogyakarta. Gumuk pasir memiliki fungsi utama sebagai kawasan konservasi, tembok alami bencana tsunami, kawasan resapan air, serta habitat untuk flora fauna gumuk pasir. Namun, keberadaan gumuk pasir saat ini terancam punah oleh adanya penurunan luasannya, yang disebabkan oleh perubahan penggunaan lahan. Setiap tahun, penggunaan lahan di gumuk pasir Parangtritis mengalami perubahan, yang akhirnya menyebabkan luasan gumuk pasir selalu berkurang setiap tahunnya. Oleh karena itu, pemetaan perubahan penggunaan lahan penting untuk dilakukan untuk mengetahui perubahan yang terjadi di zona inti gumuk pasir. Penelitian ini bertujuan untuk memetakan perubahan penggunaan lahan di zona inti gumuk pasir menggunakan foto udara format kecil dan metode OBIA (Object-Based Image Analysis). Penggunaan lahan di wilayah kajian diklasifikasikan menjadi sembilan kelas yaitu gumuk pasir, hutan lahan kering, semak belukar, beting pantai, lahan terbuka, lahan terbangun dan permukiman, ladang, jalan dan tambak. Hasil penelitian menunjukkan adanya perubahan pada semua kelas penggunaan lahan. Berdasarkan uji akurasi, akurasi keseluruhan (overall accuracy) hasil klasifikasi penggunaan lahan tahun 2020 sebesar 68,95%, sedangkan hasil klasifikasi penggunaan lahan tahun 2015 sebesar 61,81%.Kata kunci: Perubahan Penggunaan Lahan, OBIA, Foto Udara Format Kecil 

scholarly journals Stimulating Implementation of Sustainable Development Goals and Conservation Action: Predicting Future Land Use/Cover Change in Virunga National Park, Congo

2020 ◽  
Vol 12 (4) ◽  
pp. 1570 ◽  
Author(s):  
Mads Christensen ◽  
Jamal Jokar Arsanjani
Keyword(s):  
Land Use ◽  
Sustainable Development ◽  
Land Cover ◽  
National Park ◽  
Sustainable Development Goals ◽  
Land Use Changes ◽  
Land Cover Changes ◽  
2030 Agenda ◽  
Development Goals ◽  
Land Cover Maps

The United Nations 2030 Agenda for Sustainable Development and the Sustainable Development Goals (SDG’s) presents a roadmap and a concerted platform of action towards achieving sustainable and inclusive development, leaving no one behind, while preventing environmental degradation and loss of natural resources. However, population growth, increased urbanisation, deforestation, and rapid economic development has decidedly modified the surface of the earth, resulting in dramatic land cover changes, which continue to cause significant degradation of environmental attributes. In order to reshape policies and management frameworks conforming to the objectives of the SDG’s, it is paramount to understand the driving mechanisms of land use changes and determine future patterns of change. This study aims to assess and quantify future land cover changes in Virunga National Park in the Democratic Republic of the Congo by simulating a future landscape for the SDG target year of 2030 in order to provide evidence to support data-driven decision-making processes conforming to the requirements of the SDG’s. The study follows six sequential steps: (a) creation of three land cover maps from 2010, 2015 and 2019 derived from satellite images; (b) land change analysis by cross-tabulation of land cover maps; (c) submodel creation and identification of explanatory variables and dataset creation for each variable; (d) calculation of transition potentials of major transitions within the case study area using machine learning algorithms; (e) change quantification and prediction using Markov chain analysis; and (f) prediction of a 2030 land cover. The model was successfully able to simulate future land cover and land use changes and the dynamics conclude that agricultural expansion and urban development is expected to significantly reduce Virunga’s forest and open land areas in the next 11 years. Accessibility in terms of landscape topography and proximity to existing human activities are concluded to be primary drivers of these changes. Drawing on these conclusions, the discussion provides recommendations and reflections on how the predicted future land cover changes can be used to support and underpin policy frameworks towards achieving the SDG’s and the 2030 Agenda for Sustainable Development.

scholarly journals Land Cover Changes in Open-Cast Mining Complexes Based on High-Resolution Remote Sensing Data

2019 ◽  
Author(s):  
Filipe Silveira Nascimento ◽  
Markus Gastauer ◽  
Pedro Walfir M. Souza-Filho ◽  
Wilson R. Nascimento Jr. ◽  
Diogo C. Santos ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Land Cover ◽  
Land Use Changes ◽  
Remote Sensing Data ◽  
Land Cover Changes ◽  
Special Focus ◽  
Open Cast Mining ◽  
High Resolution Satellite Images ◽  
Open Cast

Remote sensing technologies may play a fundamental role in the environmental assessment of open-cast mining and the accurate quantification of mine land rehabilitation efforts. Here, we developed a systematic geographic object-based image analysis (GEOBIA) approach to map the amount of revegetated area and to quantify the land-use changes in open-cast mines in the Carajás region situated in the eastern Amazon. Based on high-resolution satellite images from 2011 to 2015 from different sensors (GeoEye, WorldView-3 and Ikonos), we quantified forests, cangas (natural metalliferous savanna ecosystems), mine land, revegetated areas and water bodies. Based on the GEOBIA approach, threshold values were established to discriminate land cover classes using spectral bands, and the NDVI and NDWI indices and LiDAR digital ground and slope models. The overall accuracy was higher than 90%, and the Kappa indices varied between 0.82 and 0.88. During the observation period, the mining complex expanded; for that, canga and forest vegetation was converted to mine land. At the same time, the amount of revegetated area increased. Thus, we conclude that our approach is capable of providing consistent information regarding land cover changes in mines, with a special focus on the amount of revegetation necessary to fulfill environmental liabilities.

scholarly journals A high-resolution and harmonized model approach for reconstructing and analysing historic land changes in Europe

2016 ◽  
Vol 1 (1) ◽  
Author(s):  
Richard Fuchs
Keyword(s):  
High Resolution ◽  
The Netherlands ◽  
Land Cover ◽  
Atmospheric Carbon Dioxide ◽  
Land Use Changes ◽  
Aerial Photographs ◽  
Land Change ◽  
Reforestation Program ◽  
Land Changes ◽  
Model Approach

<p><span class="pb_authors"><strong>R. Fuchs<sup>1</sup>, M. Herold<sup>1</sup>, P. H. Verburg<sup>2</sup>, and J. G. P. W. Clevers<sup>1</sup></strong></span><br /><span class="pb_affiliations"><sup>1</sup>Laboratory of Geoinformation Science and Remote Sensing, Wageningen University, Droevendaalsesteeg 3, 6708 PB Wageningen, the Netherlands<br /><sup>2</sup>Institute for Environmental Studies, VU University Amsterdam, De Boelelaan 1085, 1081 HV Amsterdam, the Netherlands</span></p><p>Human-induced land use changes are nowadays the second largest contributor to atmospheric carbon dioxide after fossil fuel combustion. Existing historic land change reconstructions on the European scale do not sufficiently meet the requirements of greenhouse gas (GHG) and climate assessments, due to insufficient spatial and thematic detail and the consideration of various land change types. This paper investigates if the combination of different data sources, more detailed modelling techniques, and the integration of land conversion types allow us to create accurate, high-resolution historic land change data for Europe suited for the needs of GHG and climate assessments. We validated our reconstruction with historic aerial photographs from 1950 and 1990 for 73 sample sites across Europe and compared it with other land reconstructions like Klein Goldewijk et al. (2010, 2011), Ramankutty and Foley (1999), Pongratz et al. (2008) and Hurtt et al. (2006). The results indicate that almost 700 000 km2 (15.5%) of land cover in Europe has changed over the period 1950–2010, an area similar to France. In Southern Europe the relative amount was almost 3.5% higher than average (19%). Based on the results the specific types of conversion, hot-spots of change and their relation to political decisions and socio-economic transitions were studied. The analysis indicates that the main drivers of land change over the studied period were urbanization, the reforestation program resulting from the timber shortage after the Second World War, the fall of the Iron Curtain, the Common Agricultural Policy and accompanying afforestation actions of the EU. Compared to existing land cover reconstructions, the new method considers the harmonization of different datasets by achieving a high spatial resolution and regional detail with a full coverage of different land categories. These characteristics allow the data to be used to support and improve ongoing GHG inventories and climate research.</p><p><strong>Citation:</strong><span> Fuchs, R., Herold, M., Verburg, P. H., and Clevers, J. G. P. W.: A high-resolution and harmonized model approach for reconstructing and analysing historic land changes in Europe, Biogeosciences, 10, 1543-1559, doi:10.5194/bg-10-1543-2013, 2013.</span></p>

scholarly journals Intersection of Physical and Anthropogenic Effects on Land-Use/Land-Cover Changes in Coastal China of Jiangsu Province

2019 ◽  
Vol 11 (8) ◽  
pp. 2370 ◽  
Author(s):  
Xiaowei Chuai ◽  
Jiqun Wen ◽  
Dachang Zhuang ◽  
Xiaomin Guo ◽  
Ye Yuan ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Driving Forces ◽  
Land Use Changes ◽  
Temporal Analysis ◽  
Jiangsu Province ◽  
Land Cover Changes ◽  
Land Use Type

China is experiencing substantial land-use and land-cover change (LUCC), especially in coastal regions, and these changes have caused many ecological problems. This study selected a typical region of Jiangsu Province and completed a comprehensive and detailed spatial-temporal analysis regarding LUCC and the driving forces. The results show that the rate of land-use change has been accelerating, with land-use experiencing the most substantial changes from 2005 to 2010 for most land-use types and the period from 2010 to 2015 showing a reversed changing trend. Built-up land that occupies cropland was the main characteristic of land-use type change. Southern Jiangsu and the coastline region presented more obvious land-use changes. Social-economic development was the main factor driving increased built-up land expansion and cropland reduction. In addition, land-use policy can significantly affect land-use type changes. For land-cover changes, the normalized difference vegetation index (NDVI) for the land area without land-use type changes increased by 0.005 per year overall. Areas with increasing trends accounted for 82.43% of the total area. Both precipitation and temperature displayed more areas that were positively correlated with NDVI, especially for temperature. Temperature correlated more strongly with NDVI change than precipitation for most vegetation types. Our study can be used as a reference for land-use managers to ensure sustainable and ecological land-use and coastal management.

scholarly journals Multi-Type Forest Change Detection Using BFAST and Monthly Landsat Time Series for Monitoring Spatiotemporal Dynamics of Forests in Subtropical Wetland

2020 ◽  
Vol 12 (2) ◽  
pp. 341 ◽  
Author(s):  
Ling Wu ◽  
Zhaoliang Li ◽  
Xiangnan Liu ◽  
Lihong Zhu ◽  
Yibo Tang ◽  
...  
Keyword(s):  
Time Series ◽  
Land Cover ◽  
Dongting Lake ◽  
Spatiotemporal Dynamics ◽  
Data Availability ◽  
Rapid Expansion ◽  
Core Zone ◽  
The Core ◽  
Subtropical Wetland ◽  
Ndvi Time Series

Land cover changes, especially excessive economic forest plantations, have significantly threatened the ecological security of West Dongting Lake wetland in China. This work aimed to investigate the spatiotemporal dynamics of forests in the West Dongting Lake region from 2000 to 2018 using a reconstructed monthly Landsat NDVI time series. The multi-type forest changes, including conversion from forest to another land cover category, conversion from another land cover category to forest, and conversion from forest to forest (such as flooding and replantation post-deforestation), and land cover categories before and after change were effectively detected by integrating Breaks For Additive Seasonal and Trend (BFAST) and random forest algorithms with the monthly NDVI time series, with an overall accuracy of 87.8%. On the basis of focusing on all the forest regions extracted through creating a forest mask for each image in time series and merging these to produce an ‘anytime’ forest mask, the spatiotemporal dynamics of forest were analyzed on the basis of the acquired information of multi-type forest changes and classification. The forests are principally distributed in the core zone of West Donting Lake surrounding the water body and the southwestern mountains. The forest changes in the core zone and low elevation region are prevalent and frequent. The variation of forest areas in West Dongting Lake experienced three steps: rapid expansion of forest plantation from 2000 to 2005, relatively steady from 2006 to 2011, and continuous decline since 2011, mainly caused by anthropogenic factors, such as government policies and economic profits. This study demonstrated the applicability of the integrated BFAST method to detect multi-type forest changes by using dense Landsat time series in the subtropical wetland ecosystem with low data availability.

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