scholarly journals Intensified Management of Coffee Forest in Southwest Ethiopia Detected by Landsat Imagery

Forests ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 422 ◽  
Author(s):  
Byongjun Hwang ◽  
Kitessa Hundera ◽  
Bizuneh Mekuria ◽  
Adrian Wood ◽  
Andinet Asfaw

The high forests in southwest Ethiopia, some of the last remaining Afromontane forests in the country, are home to significant forest coffee production. While considered as beneficial in maintaining forests, there have been growing concerns about the degradation caused by intensive management for coffee production in these forests. However, no suitable methods have been developed to map the coffee forests. In this study, we developed a tie-point approach to consistently estimate the degree of degradation caused by intensive management by combining use of Landsat imagery with in-situ canopy cover and tree survey data. Our results demonstrate a clear distinction between undisturbed natural forest and heavily managed coffee forest due to changes in forest structure and canopy cover caused by intensive management in the coffee forest. Temporal analysis of 32 years of Landsat imagery reveals a progressive and significant transition in the level of degradation in the coffee forest over this period. This is the first time to our knowledge, that this progressive intensification of coffee forest has been measured. There is a major intensification in the mid-1990s, which follows the introduction of new liberal economic policies by the Federal government established in 1991, rising coffee prices, and changes in state control over access to the forest. The question remains as to how these 20 years of intensive management in coffee forest have affected forest biodiversity and, more importantly, how canopy trees in this forest can be regenerated in the future. This study provides potential satellite-based mapping and ground-based photography and tree survey methods to help investigate the impacts of intensive management within coffee forest on biodiversity and regeneration.

2020 ◽  
Author(s):  
Byongjun Hwang ◽  
Kitessa Hundera ◽  
Bizuneh Mekuria ◽  
Adrian Wood ◽  
Andinet Asfaw

<p>The high forests in southwest Ethiopia, some of the last remaining Afromontane forests in the country, are home to significant forest coffee production. While considered as beneficial in maintaining forests, there have been growing concerns about the degradation caused by intensive coffee production in the forests. However, yet no suitable methods have been developed to map the intensively managed coffee forests. In this study, we explore the feasibility of monitoring the extent of the degradation within the intensively managed coffee forests by using satellite imagery (Landsat-8 and Sentinel-2). For this, we conducted in-situ field canopy photo and tree surveys, and the results were analysed with satellite-derived vegetation indices such as NDVI and NBR. This feasibility study informed us that the detection of the intensively managed forest coffee areas (disturbances caused by this practice) using satellite imagery can be possible, as the dry-season forest structure (canopy, undergrowth) and vegetation indices in the intensively managed coffee forests are significantly distinctive from those in natural forests. This study will contribute to the long-term sustainable management of the coffee forest.</p>


2021 ◽  
Vol 2 (2) ◽  
pp. 56-64
Author(s):  
Iqbal Eko Noviandi ◽  
Ramadhan Alvien Hanif ◽  
Hasanah Rahma Nur ◽  
Nandi

Indonesia is a developing country whose construction and development are centered on the island of Java, especially in West Java Province. Sukabumi City is one of the areas in West Java. The development of urban areas is expanding due to various human needs to carry out the construction of buildings. Remote sensing that can be used to store developments with multi-temporal analysis with materials is Landsat imagery from 2001 to 2020. The method used is the Normalized Difference Built-up Index (NDBI). The purpose of this study is to map the development of the built-up land from year to year and predict the following years. The results of the research on the significant changes in built-up land occurred between 2013-2020, while from 2001 to 2013 there was not much change. Based on the research results, the total growth of built-up land was 1.539% per year with a population growth rate of 1.4% per year. The results of the analysis show that the area of ​​land built in Sukabumi City in 2028 is 186,7194 km2 or has increased by 21,2808 km2 since 2020.


Agromix ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 125-135
Author(s):  
Yohana Theresia Maria Astuti ◽  
Tri Nugraha Budi Santosa ◽  
Dian Pratama Putra ◽  
Enny Rahayu ◽  
Agus Solifudin ◽  
...  

This study aims to evaluate the dinamics of coffee production  in Mandang, Sucen Village, Gemawang District, Temanggung on 2018 and 2019. The research was carried out at  people coffee plantation in Mandang Hamlet, Sucen Village, Temanggung. Research using survey methods. Observation of performance with 30 samples taken by purposive sampling technique on 3 clones. Land suitability analysis was carried out at 3 observation points. The results obtained are: The vegetative characteristics  of robusta coffee BP 288 and BP 409 are better than  BP 358 clones, while the robusta coffee production is the same  on various clones and  plantation location.  The long dry season  in 2018 and 2019 has an effect on the decline of the number of leaves and coffee production in 2019 compared to 2018 in Mandang Hamlet, Sucen  Village, Gemawang district, Temanggung.


2017 ◽  
Vol 131 (1) ◽  
pp. 37-45
Author(s):  
Graham P. Dixon-MacCallum ◽  
Katie A.H. Bell ◽  
Patrick T. Gregory

Understanding habitat requirements of species is fundamental for their conservation and urban parks can provide key habitat for species in otherwise disturbed settings. Northwestern Gartersnakes (Thamnophis ordinoides) are common in parks in Saanich, British Columbia, but their specific habitat requirements are poorly understood. Based on previous studies and thermoregulatory needs of snakes, we predicted that edges, particularly field margins, would be heavily used by active snakes. We therefore used surveys that focused on edges to find snakes and measured edge-habitat use by comparing habitat variables at locations where snakes were found to the same variables at nearby random locations. Habitat variables included composition and structure of vegetation, substrate temperature, aspect, and slope. Overall, litter depth, canopy cover, a lack of bare ground and woody vegetation were the most important habitat variables for determining where snakes were found. our results provide a preliminary assessment to improve our understanding of habitat use for this species. The abundance of snakes found while surveying edges supports our initial assumption that edges are important habitat features but more work is required using multiple survey methods to further test this hypothesis.


Agronomy ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 940
Author(s):  
Rocío Ballesteros ◽  
Miguel A. Moreno ◽  
Fellype Barroso ◽  
Laura González-Gómez ◽  
José F. Ortega

The availability of a great amount of remote sensing data for precision agriculture purposes has set the question of which resolution and indices, derived from satellites or unmanned aerial vehicles (UAVs), offer the most accurate results to characterize vegetation. This study focused on assessing, comparing, and discussing the performances and limitations of satellite and UAV-based imagery in terms of canopy development, i.e., the leaf area index (LAI), and yield, i.e., the dry aboveground biomass (DAGB), for maize. Three commercial maize fields were studied over four seasons to obtain the LAI and DAGB. The normalized difference vegetation index (NDVI) and visible atmospherically resistant index (VARI) from satellite platforms (Landsat 5TM, 7 ETM+, 8OLI, and Sentinel 2A MSI) and the VARI and green canopy cover (GCC) from UAV imagery were compared. The remote sensing predictors in addition to the growing degree days (GDD) were assessed to estimate the LAI and DAGB using multilinear regression models (MRMs). For LAI estimation, better adjustments were obtained when predictors from the UAV platform were considered. The DAGB estimation revealed similar adjustments for both platforms, although the Landsat imagery offered slightly better adjustments. The results obtained in this study demonstrate the advantage of remote sensing platforms as a useful tool to estimate essential agronomic features.


2005 ◽  
Vol 8 (3) ◽  
pp. 289-296 ◽  
Author(s):  
Kevin Koy ◽  
William J. McShea ◽  
Peter Leimgruber ◽  
Barry N. Haack ◽  
Myint Aung
Keyword(s):  

Author(s):  
E. Sánchez-García ◽  
J. E. Pardo-Pascual ◽  
A. Balaguer-Beser ◽  
J. Almonacid-Caballer

A statistical analysis of the results obtained by the tool SELI (Shoreline Extraction from Landsat Imagery) is made in order to characterise the medium and long term period changes occurring on beaches. The analysis is based on the hypothesis that intraannual shifts of coastline positions hover around an average position, which would be significant when trying to set these medium and long term trends. Fluctuations around this average are understood as the effect of short-term changes -variations related to sea level, wave run-up, and the immediate morphological beach profile settings of the incident waves- whilst the alterations of the average position will obey changes relating to the global sedimentary harmony of the analysed beach segment. The goal of this study is to assess the validity of extracted Landsat shorelines knowing whether the intrinsic error could alter the position of the computed mean annual shoreline or if it is balanced out between the successive averaged images. Two periods are stablished for the temporal analysis in the area according to the availability of other data taken from high precision sources. Statistical tests performed to compare samples (Landsat versus high accuracy) indicate that the two sources of data provide similar information regarding annual means; coastal behaviour and dynamics, thereby verifying Landsat shorelines as useful data for evolutionary studies.


2021 ◽  
Vol 65 ◽  
pp. 101431
Author(s):  
Lien Rodríguez-López ◽  
Lisdelys González-Rodríguez ◽  
Iongel Duran-Llacer ◽  
Rolando Cardenas ◽  
Roberto Urrutia

2021 ◽  
Author(s):  
Merkebu Getachew ◽  
Kris Verheyen ◽  
Kassaye Tolessa ◽  
Biruk Ayalew ◽  
Kristoffer Hylander ◽  
...  

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