Evaluation of vegetation greenness metrics for characterizing tropical forest cover types–a case study using NOAA AVHRR datasets

2007 ◽  
Vol 22 (1) ◽  
pp. 29-48 ◽  
Author(s):  
K. Vadrevu ◽  
K. V. S. Badarinath ◽  
E. Anuradha
2017 ◽  
Vol 31 (2) ◽  
pp. 209-219 ◽  
Author(s):  
Ronggo Sadono ◽  
Hartono Hartono ◽  
Mochammad Maksum Machfoedz ◽  
Setiaji Setiaji

Volcanic eruption is one of the natural factors that affect land cover changes. This study aimed to monitor land cover changes using a remote sensing approach in Cangkringan Sub-district, Yogyakarta, Indonesia, one of the areas most vulnerable to Mount Merapi eruption. Three satellite images, dating from 2001, 2006 and 2011, were used as main data for land cover classification based on a supervised classification approach. The land cover detection analysis was undertaken by overlaying the classification results from those images. The results show that the dominant land cover class is annual crops, covering 40% of the study area, while the remaining 60% consists of forest cover types, dryland farming, paddy fields, settlements, and bare land. The forests were distributed in the north, and the annual crops in the middle of the study area, while the villages and the rice fields were generally located in the south. In the 2001–2011 period, forests were the most increased land cover type, while annual crops decreased the most, as a result of the eruption of Mount Merapi in 2010. Such data and information are important for the local government or related institutions to formulate Detailed Spatial Plans (RDTR) in the Disaster-Prone Areas (KRB).


2022 ◽  
Vol 302 ◽  
pp. 114067
Author(s):  
Manoranjan Mishra ◽  
Celso Augusto Guimarães Santos ◽  
Thiago Victor Medeiros do Nascimento ◽  
Manoj Kumar Dash ◽  
Richarde Marques da Silva ◽  
...  

2020 ◽  
Vol 9 (5) ◽  
pp. 311 ◽  
Author(s):  
Sujit Bebortta ◽  
Saneev Kumar Das ◽  
Meenakshi Kandpal ◽  
Rabindra Kumar Barik ◽  
Harishchandra Dubey

Several real-world applications involve the aggregation of physical features corresponding to different geographic and topographic phenomena. This information plays a crucial role in analyzing and predicting several events. The application areas, which often require a real-time analysis, include traffic flow, forest cover, disease monitoring and so on. Thus, most of the existing systems portray some limitations at various levels of processing and implementation. Some of the most commonly observed factors involve lack of reliability, scalability and exceeding computational costs. In this paper, we address different well-known scalable serverless frameworks i.e., Amazon Web Services (AWS) Lambda, Google Cloud Functions and Microsoft Azure Functions for the management of geospatial big data. We discuss some of the existing approaches that are popularly used in analyzing geospatial big data and indicate their limitations. We report the applicability of our proposed framework in context of Cloud Geographic Information System (GIS) platform. An account of some state-of-the-art technologies and tools relevant to our problem domain are discussed. We also visualize performance of the proposed framework in terms of reliability, scalability, speed and security parameters. Furthermore, we present the map overlay analysis, point-cluster analysis, the generated heatmap and clustering analysis. Some relevant statistical plots are also visualized. In this paper, we consider two application case-studies. The first case study was explored using the Mineral Resources Data System (MRDS) dataset, which refers to worldwide density of mineral resources in a country-wise fashion. The second case study was performed using the Fairfax Forecast Households dataset, which signifies the parcel-level household prediction for 30 consecutive years. The proposed model integrates a serverless framework to reduce timing constraints and it also improves the performance associated to geospatial data processing for high-dimensional hyperspectral data.


1994 ◽  
Vol 22 (1) ◽  
pp. 21-29 ◽  
Author(s):  
S. Sudhakar ◽  
R. K. Das ◽  
D. Chakraborty ◽  
B. K. Bardhan Roy ◽  
A. K. Raha ◽  
...  

1993 ◽  
Vol 69 (6) ◽  
pp. 667-671 ◽  
Author(s):  
John A. Drieman

The need for a current, regional perspective of the forest of Labrador was identified. Mapping of forest cover types, peat-lands, recent burns and clearcut disturbances was accomplished through visual interpretation of 1:1,000,000 scale Landsat Thematic mapper colour composite transparencies and the transfer of interpreted polygons to a geographic information system. The mapping and verification process is described in this paper. The end product, a forest resource map, provides the most up-to-date and detailed information on Labrador's forest cover types and disturbances available on a single map. The digital format of the map facilities area summaries, viewing and printing.


Author(s):  
Julie Betbeder ◽  
Damien Arvor ◽  
Lilian Blanc ◽  
Guillaume Cornu ◽  
Clement Bourgoin ◽  
...  

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