scholarly journals A Visual Assessment Scale for Rapid Evaluation of Mangrove Degradation, Using Examples from Myanmar and Madagascar

2021 ◽  
Author(s):  
Christoph Zöckler ◽  
Dominic Wodehouse ◽  
Matthias Markolf
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Assessment Tool ◽  
Land Use Changes ◽  
Visual Assessment ◽  
Assessment Scale ◽  
Agricultural Expansion ◽  
Rapid Evaluation ◽  
Practical Guide ◽  
Mangrove Degradation

Mangroves are globally threatened, disappearing and degraded. They are lost due to land use changes, mostly agricultural expansion and aquaculture, but also degraded by cutting by villagers and logging and timber extraction for domestic and economic purposes. Extent and conversion of mangroves can usually be estimated by applying remote sensing and modern drone technology, but the scale of degradation of mangrove habitats is not easily detected by such methods. In this paper we propose an assessment tool for a rapid evaluation on the degradation, using examples from different regions in Myanmar and Madagascar. We propose a visual and practical guide listing a range of 1–6 to identify and quantify the level of degradation. We demonstrate the application by displaying various examples from Myanmar and Madagascar and how this tool can be used for wider applications, discussing advantages scope, and limitations.

Hydrologic response of a watershed to land use changes: A remote sensing and GIS approach

2001 ◽  
Vol 22 (11) ◽  
pp. 2095-2108 ◽  
Author(s):  
T. Sharma ◽  
P. V. Satya Kiran ◽  
T. P. Singh ◽  
A. V. Trivedi ◽  
R. R. Navalgund
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Use Changes ◽  
Remote Sensing And Gis ◽  
Hydrologic Response

LUU CHECKER: A Web-based Tool to Incorporate Emerging LUs in the SWAT Model

2019 ◽  
Vol 35 (5) ◽  
pp. 723-731 ◽  
Author(s):  
Gurdeep Singh ◽  
Dharmendra Saraswat ◽  
Naresh Pai ◽  
Benjamin Hancock
Keyword(s):  
Land Use ◽  
Management Practices ◽  
Assessment Tool ◽  
Urban Forest ◽  
Swat Model ◽  
Land Use Changes ◽  
Web Based ◽  
Large Size ◽  
Hydrologic Response Unit ◽  
User Friendly

Abstract. Standard practice of setting up Soil and Water Assessment Tool (SWAT) involves use of a single land use (LU) layer under the assumption that no change takes place in LU condition irrespective of the length of simulation period. This assumption leads to erroneous conclusions about efficacy of management practices in those watersheds where land use changes (LUCs) (e.g. agriculture to urban, forest to agriculture etc.) occur during the simulation period. To overcome this limitation, we have developed a user-friendly, web-based tool named LUU Checker that helps create a composite LU layer by integrating multiple years of LU layers available in watersheds of interest. The results show that the use of composite LU layer for hydrologic response unit (HRU) delineation in 2474-km2 L’Anguile River Watershed in Arkansas was able to capture changed LU at subbasin level by using LU data available in the year 1999 and 2006, respectively. The web-based tool is applicable for large size watersheds and is accessible to multiple users from anywhere in the world. Keywords: Land use, Web-based tool, SWAT, LUU Checker.

scholarly journals Evaluating and Predicting the Effects of Land Use Changes on Hydrology in Wami River Basin, Tanzania

Hydrology ◽  
2020 ◽  
Vol 7 (1) ◽  
pp. 17 ◽  
Author(s):  
Sekela Twisa ◽  
Shija Kazumba ◽  
Mathew Kurian ◽  
Manfred F. Buchroithner
Keyword(s):  
Land Use ◽  
Water Resources ◽  
Assessment Tool ◽  
Swat Model ◽  
Land Use Changes ◽  
Management Strategies ◽  
River System ◽  
Least Squares Regression ◽  
Natural Forests ◽  
The Impact

Understanding the variation in the hydrological response of a basin associated with land use changes is essential for developing management strategies for water resources. The impact of hydrological changes caused by expected land use changes may be severe for the Wami river system, given its role as a crucial area for water, providing food and livelihoods. The objective of this study is to examine the influence of land use changes on various elements of the hydrological processes of the basin. Hybrid classification, which includes unsupervised and supervised classification techniques, is used to process the images (2000 and 2016), while CA–Markov chain analysis is used to forecast and simulate the 2032 land use state. In the current study, a combined approach—including a Soil and Water Assessment Tool (SWAT) model and Partial Least Squares Regression (PLSR)—is used to explore the influences of individual land use classes on fluctuations in the hydrological components. From the study, it is evident that land use has changed across the basin since 2000 (which is expected to continue in 2032), as well as that the hydrological effects caused by land use changes were observed. It has been found that the major land use changes that affected hydrology components in the basin were expansion of cultivation land, built-up area and grassland, and decline in natural forests and woodland during the study period. These findings provide baseline information for decision-makers and stakeholders concerning land and water resources for better planning and management decisions in the basin resources’ use.

scholarly journals Research on Land Use Changes in Panjin City Basing on Remote Sensing Data

2018 ◽  
Vol 153 ◽  
pp. 062050
Author(s):  
Hua Ding ◽  
Ru Ren Li ◽  
Li Shuang Sun ◽  
Xin Wang ◽  
Yu Mei Liu
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Use Changes ◽  
Remote Sensing Data ◽  
Sensing Data

scholarly journals Parallel Cellular Automata Markov Model for Land Use Change Prediction over MapReduce Framework

2019 ◽  
Vol 8 (10) ◽  
pp. 454 ◽  
Author(s):  
Junfeng Kang ◽  
Lei Fang ◽  
Shuang Li ◽  
Xiangrong Wang
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Cellular Automata ◽  
Markov Model ◽  
Agricultural Land ◽  
Land Use Changes ◽  
Remote Sensing Images ◽  
Mapreduce Framework ◽  
Construction Land ◽  
Model Based

The Cellular Automata Markov model combines the cellular automata (CA) model’s ability to simulate the spatial variation of complex systems and the long-term prediction of the Markov model. In this research, we designed a parallel CA-Markov model based on the MapReduce framework. The model was divided into two main parts: A parallel Markov model based on MapReduce (Cloud-Markov), and comprehensive evaluation method of land-use changes based on cellular automata and MapReduce (Cloud-CELUC). Choosing Hangzhou as the study area and using Landsat remote-sensing images from 2006 and 2013 as the experiment data, we conducted three experiments to evaluate the parallel CA-Markov model on the Hadoop environment. Efficiency evaluations were conducted to compare Cloud-Markov and Cloud-CELUC with different numbers of data. The results showed that the accelerated ratios of Cloud-Markov and Cloud-CELUC were 3.43 and 1.86, respectively, compared with their serial algorithms. The validity test of the prediction algorithm was performed using the parallel CA-Markov model to simulate land-use changes in Hangzhou in 2013 and to analyze the relationship between the simulation results and the interpretation results of the remote-sensing images. The Kappa coefficients of construction land, natural-reserve land, and agricultural land were 0.86, 0.68, and 0.66, respectively, which demonstrates the validity of the parallel model. Hangzhou land-use changes in 2020 were predicted and analyzed. The results show that the central area of construction land is rapidly increasing due to a developed transportation system and is mainly transferred from agricultural land.

scholarly journals Study on Coastline Changes of Xiamen City Based on Remote Sensing Images

2019 ◽  
Vol 136 ◽  
pp. 05003
Author(s):  
Yanfang Qin ◽  
Lin Ye ◽  
Siming Chen
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Use Changes ◽  
Remote Sensing Data ◽  
Length Change ◽  
Vector Data ◽  
Remote Sensing Images ◽  
Change Rate ◽  
Xiamen City ◽  
Spatio Temporal

Based on the Landsat remote sensing data, this paper had monitored the coastline changes of Xiamen city in recent 20 years. By extracting the coastline vector data of 1999, 2005, 2011 and 2017 respectively, the spatio-temporal characteristics of coastline changes on coastline length, change rate and land change area were analyzed, and the main driving factors were analyzed combined with the land use changes in the coastal swing area. The results show that: the total length of Xiamen's coastline increased from 235.16 km to 264.98 km during 1999-2017, and the land area increased from 1558.84 km2 to 1594.29 km2. The most significant changes occurred in Xiang'an district and Huli district with the coastline length increased by 16.38% during 2011-2017 and 22.14% during 1999-2005 respectively, while the changes were not very conspicuous in other areas. According to the land use changes in the coastal areas, the coastline changes in Xiamen City were mainly related to the expansion of construction land and port constructions in Haicang district, Xiang'an district and Huli district, as well as the expansion of aquaculture in the Xiang'an district.

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