scholarly journals Analisa Penyebaran Potensi Kekeringan Lahan di Kabupaten Rembang

2020 ◽  
Vol 33 (2) ◽  
Author(s):  
Martza Swastikasari ◽  
Natania Frislya Nanulaitta
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Agricultural Land ◽  
Satellite Image ◽  
Infiltration Rate ◽  
High Water ◽  
Rainfall Data ◽  
Water Infiltration ◽  
Central Java ◽  
Water Holding

Kekeringan lahan yang melanda suatu daerah menimbulkan dampak yang besar terhadap produktivitas lahan pertanian. Terjadinya kekeringan ini disebabkan oleh defisit air akibat kurangnya hujan yang jatuh, laju infiltrasi air yang tinggi serta jenis tanaman yang tidak sesuai dengan ketersediaan air.  Untuk meminimalkan dampak yang terjadi akibat kekeringan lahan maka perlu dilakukan antisipasi dengan mengetahui defisit dan surflus air lahan melalui data curah hujan serta kemampuan tanah menahan air (Water Holding Capasity). Oleh sebab itu, dalam penelitian ini penulis mencoba untuk menganalisa penyebaran potensi penyebaran kekeringan di wilayah Kabupaten Rembang Propinsi Jawa Tengah. Parameter yang didapat yaitu interpretasi dari citra satelit lansat 8 (OLI), data statistik Kabupaten Rembang, dan data curah hujan. Didalam penelitian ini juga penulis menggunakan indeks vegetasi NDVI (Normalized Difference Vegetation Index) dan SAVI (Soil-Adjusted Vegetation Index)yang dapat menghasilkan rata-rata luas wilayah potensi kekeringan di masing-masing kecamatan pada Kabupaten Rembang. Land drought that hit a region has a great impact on the productivity of agricultural land. The occurrence of this drought is caused by water deficit due to lack of falling rain, high water infiltration rate and types of plants that are not in accordance with the availability of water. To minimize the impacts caused by land drought, it is necessary to be anticipated by knowing the deficit and land water surfs through rainfall data and the ability of water holding capasity. Therefore in this study the authors try to analyze the spread of potential spread of drought in rembang district of central java province. The parameters obtained are the interpretation of satellite image 8 (OLI), statistical data of Rembang Regency, and rainfall data. In this study, the authors used the NDVI (Normalized Difference Vegetation Index) and SAVI (Soil-Adjusted Vegetation Index) vegetation index which can produce the average of drought potential areas in each sub-district in Rembang district.

scholarly journals WAKTU TANAM KAPAS DI JAWA TENGAH

2020 ◽  
Vol 11 (2) ◽  
pp. 52
Author(s):  
PRIMA DIARINI RIAJAYA ◽  
MOCH. SHOLEH ◽  
F.T. KADARWATI
Keyword(s):  
Gossypium Hirsutum ◽  
Rainfall Variability ◽  
Seasonal Pattern ◽  
Clay Content ◽  
High Water ◽  
Rainfall Data ◽  
Rainfall Analysis ◽  
Central Java ◽  
Probability Methods ◽  
Water Holding

<p>ABSTRAK<br />Curah hujan merupakan salah satu unsur iklim yang sangat<br />berpengaruh terhadap produksi kapas. Variasi hujan di lahan tadah hujan<br />Jawa Tengah sangat tinggi sehingga diperlukan penetapan waktu tanam.<br />Waktu tanam ditetapkan berdasarkan analisis hujan lebih dari 20 tahun<br />dari 31 stasiun hujan yang tersebar di Kabupaten Grobogan, Wonogiri,<br />Blora, Pemalang, Tegal, dan Brebes. Data dianalisis menggunakan metode<br />peluang Markov Order Pertama dan perhitungan peluang selang kering<br />berturut-turut. Peluang hujan yang dianalisis berupa peluang hujan<br />mingguan lebih dari 10, 20, 30, 40, dan 50 mm. Besar peluang hujan<br />mingguan lebih dari 60% untuk mendapatkan hujan lebih dari 20 mm dan<br />30 mm dipakai dalam penentuan minggu tanam, selanjutnya disesuaikan<br />dengan peluang kering berturut-turut. Minggu tanam paling lambat (MPL)<br />di Kabupaten Grobogan dan Wonogiri berkisar minggu I Desember sampai<br />minggu I Januari. MPL di Kabupaten Blora, Pemalang, Tegal, dan Brebes<br />adalah minggu I-IV Januari. Sebagian besar lahan yang digunakan untuk<br />kapas bertekstur liat dengan kandungan liat di atas 60%. Ketersediaan air<br />dari hujan cukup untuk memenuhi kebutuhan air kapas dan didukung oleh<br />kemampuan tanah menyimpan air yang tinggi.<br />Kata kunci : Kapas, Gossypium hirsutum, waktu tanam, periode kering,<br />masa tanam, Jawa Tengah</p><p><br />ABSTRACT<br />Cotton planting times in Central Java<br />Climatic elements particularly rainfall strongly influences successful<br />prediction of rainfed cotton yield. Rainfall variability varies amongst the<br />seasons. Longterm rainfall data were required for rainfall analysis to get<br />reliable probabilities. The rainfall analysis was done using Markov Chain<br />First Order Probability and dryspell probability methods. Initial and<br />conditional probabilities of rainfall for selected amounts (10, 20, 30, 40<br />and 50 mm/week) were analysed. Rainfall probabilities over 60% to have<br />20-30 mm rainfall per week were used to identify cotton planting times.<br />The rainfall data were collected from 31 rainfall stations in Central Java<br />(Grobogan, Wonogiri, Blora, Pemalang, Tegal, and Brebes). The planting<br />times varied from the first week of December to the first week of January<br />for Grobogan and Wonogiri. The planting times in Blora, Pemalang,<br />Tegal, and Brebes ranged from early to late January. The majority of land<br />used for cotton has high clay content with high water holding capacity<br />which is sufficient to meet the cotton water requirement.<br />Key words : Cotton, Gossypium hirsutum, planting time, dryspell,<br />seasonal pattern, Central Java</p>

HEALTHINESS OF OIL PALM PLANTATION TOWARDS SUSTAINABILITY OF ENVIRONMENT

2020 ◽  
Vol 7 (1) ◽  
pp. 21
Author(s):  
Faradina Marzukhi ◽  
Nur Nadhirah Rusyda Rosnan ◽  
Md Azlin Md Said
Keyword(s):  
Oil Palm ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Satellite Image ◽  
Vegetation Indices ◽  
Soil Nutrient ◽  
Oil Palm Plantation ◽  
Sustainable Environment ◽  
Moisture Analysis ◽  
The Relationship

The aim of this study is to analyse the relationship between vegetation indices of Normalized Difference Vegetation Index (NDVI) and soil nutrient of oil palm plantation at Felcra Nasaruddin Bota in Perak for future sustainable environment. The satellite image was used and processed in the research. By Using NDVI, the vegetation index was obtained which varies from -1 to +1. Then, the soil sample and soil moisture analysis were carried in order to identify the nutrient values of Nitrogen (N), Phosphorus (P) and Potassium (K). A total of seven soil samples were acquired within the oil palm plantation area. A regression model was then made between physical condition of the oil palms and soil nutrients for determining the strength of the relationship. It is hoped that the risk map of oil palm healthiness can be produced for various applications which are related to agricultural plantation.

scholarly journals Urban Fire Severity and Vegetation Dynamics in Southern California

2020 ◽  
Vol 13 (1) ◽  
pp. 19
Author(s):  
Lauren E. H. Mathews ◽  
Alicia M. Kinoshita
Keyword(s):  
Vegetation Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Current Knowledge ◽  
Fire Severity ◽  
Satellite Image ◽  
Burn Severity ◽  
Native Vegetation ◽  
Riparian Areas ◽  
The Impact

A combination of satellite image indices and in-field observations was used to investigate the impact of fuel conditions, fire behavior, and vegetation regrowth patterns, altered by invasive riparian vegetation. Satellite image metrics, differenced normalized burn severity (dNBR) and differenced normalized difference vegetation index (dNDVI), were approximated for non-native, riparian, or upland vegetation for traditional timeframes (0-, 1-, and 3-years) after eleven urban fires across a spectrum of invasive vegetation cover. Larger burn severity and loss of green canopy (NDVI) was detected for riparian areas compared to the uplands. The presence of invasive vegetation affected the distribution of burn severity and canopy loss detected within each fire. Fires with native vegetation cover had a higher severity and resulted in larger immediate loss of canopy than fires with substantial amounts of non-native vegetation. The lower burn severity observed 1–3 years after the fires with non-native vegetation suggests a rapid regrowth of non-native grasses, resulting in a smaller measured canopy loss relative to native vegetation immediately after fire. This observed fire pattern favors the life cycle and perpetuation of many opportunistic grasses within urban riparian areas. This research builds upon our current knowledge of wildfire recovery processes and highlights the unique challenges of remotely assessing vegetation biophysical status within urban Mediterranean riverine systems.

scholarly journals Sentinel-2 Based Temporal Detection of Agricultural Land Use Anomalies in Support of Common Agricultural Policy Monitoring

2018 ◽  
Vol 7 (10) ◽  
pp. 405 ◽  
Author(s):  
Urška Kanjir ◽  
Nataša Đurić ◽  
Tatjana Veljanovski
Keyword(s):  
Land Use ◽  
Time Series ◽  
Agricultural Policy ◽  
Common Agricultural Policy ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Agricultural Land ◽  
Agricultural Land Use ◽  
Land Use Control ◽  
Sentinel 2

The European Common Agricultural Policy (CAP) post-2020 timeframe reform will reshape the agriculture land use control procedures from a selected risk fields-based approach into an all-inclusive one. The reform fosters the use of Sentinel data with the objective of enabling greater transparency and comparability of CAP results in different Member States. In this paper, we investigate the analysis of a time series approach using Sentinel-2 images and the suitability of the BFAST (Breaks for Additive Season and Trend) Monitor method to detect changes that correspond to land use anomaly observations in the assessment of agricultural parcel management activities. We focus on identifying certain signs of ineligible (inconsistent) use in permanent meadows and crop fields in one growing season, and in particular those that can be associated with time-defined greenness (vegetation vigor). Depending on the requirements of the BFAST Monitor method and currently time-limited Sentinel-2 dataset for the reliable anomaly study, we introduce customized procedures to support and verify the BFAST Monitor anomaly detection results using the analysis of NDVI (Normalized Difference Vegetation Index) object-based temporal profiles and time-series standard deviation output, where geographical objects of interest are parcels of particular land use. The validation of land use candidate anomalies in view of land use ineligibilities was performed with the information on declared land annual use and field controls, as obtained in the framework of subsidy granting in Slovenia. The results confirm that the proposed combined approach proves efficient to deal with short time series and yields high accuracy rates in monitoring agricultural parcel greenness. As such it can already be introduced to help the process of agricultural land use control within certain CAP activities in the preparation and adaptation phase.

scholarly journals ESTIMASI PRODUKSI PADI DENGAN ANALISIS CITRA SATELIT LANDSAT 8 DI KABUPATEN KLUNGKUNG PROVINSI BALI

2018 ◽  
Vol 12 (1) ◽  
pp. 93
Author(s):  
Made Arya Bhaskara Putra ◽  
I Wayan Nuarsa ◽  
I Wayan Sandi Adnyana
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Satellite Image ◽  
Image Data ◽  
Research Area ◽  
Rice Production ◽  
Landsat 8 ◽  
Estimation Model ◽  
Accuracy Test ◽  
Accuracy Level

Rice crop is one of the important commodities that must always be available, so estimation of rice production becomes very important to do before harvesting time to know the food availability. The technology that can be used is remote sensing technology using Landsat 8 Satellite. The aims of this study were (1) to obtain the model of estimation of rice production with Landsat 8 image analysis, and (2) to know the accuracy of the model that obtained by Landsat 8. The research area is located in three sub-districts in Klungkung regency. Analysis in this research was conducted by single band analysis and analysis of vegetation index of satellite image of Landsat 8. Estimation model of rice production was developed by finding the relationship between satellite image data and rice production data. The final stage is the accuracy test of the rice production estimation model, with t test and regression analysis. The results showed: (1) estimation of rice production can be calculated between 67 to 77 days after planting; (2) there was a positive correlation between NDVI (Normalized Difference Vegetation Index) vegetation index value with rice yield; (3) the model of rice production estimation is y = 2.0442e1.8787x (x is NDVI value of Landsat 8 and y is rice production); (4) The results of the model accuracy test showed that the obtained model is suitable to predict rice production with accuracy level is 89.29% and standard error of production estimation is + 0.443 ton/ha. Based on research results, it can be concluded that Landsat 8 Satellite image can be used to estimate rice production and the accuracy level is 89.29%. The results are expected to be a reference in estimating rice production in Klungkung Regency.

scholarly journals Patterns of water infiltration and soil degradation over a 120-yr chronosequence from forest to agriculture in western Kenya

2011 ◽  
Vol 8 (4) ◽  
pp. 6993-7015 ◽  
Author(s):  
G. Nyberg ◽  
A. Bargués Tobella ◽  
J. Kinyangi ◽  
U. Ilstedt
Keyword(s):  
Bulk Density ◽  
Soil Degradation ◽  
Agricultural Land ◽  
Infiltration Rate ◽  
Water Infiltration ◽  
Native Forest ◽  
Western Kenya ◽  
Soil C ◽  
Soil C And N ◽  
C And N

Abstract. Soil degradation is commonly reported in the tropics where forest is converted to agriculture. Much of the native forest in the highlands of western Kenya has been converted to agricultural land in order to feed the growing population, and more land is being cleared. In tropical Africa, this land use change results in progressive soil degradation, as the period of cultivation increases. Sites that were converted to agriculture at different times can be evaluated as a chronosequence; this can aid in our understanding of the processes at work, particularly those in the soil. Both levels and variation of infiltration, soil carbon and other parameters are influenced by management within agricultural systems, but they have rarely been well documented in East Africa. We constructed a chronosequence for an area of western Kenya, using two native forest sites and six fields that had been converted to agriculture for varying lengths of time. We assessed changes in infiltrability (the steady-state infiltration rate), soil C and N, bulk density, δ13C, and the proportion of macro- and microaggregates in soil along a 119 yr chronosequence of conversion from natural forest to agriculture. Infiltration, soil C and N, decreased rapidly after conversion, while bulk density increased. Median infiltration rates fell to about 15 % of the initial values in the forest and C and N values dropped to around 60 %, whilst the bulk density increased by 50 %. Despite high spatial variability in infiltrability, these parameters correlated well with time since conversion and with each other. Our results indicate that landscape planners should include wooded elements in the landscape in sufficient quantity to ensure water infiltration at rates that prevent runoff and erosion. This should be the case for restoring degraded landscapes, as well as for the development of new agricultural areas.

scholarly journals Impact of Differences in Land Management on Natural Vegetation in Semi-Dry Areas: The Case Study of the Adi Zaboy Watershed in the Kilite Awlaelo District, Eastern Tigray Region, Ethiopia

Environments ◽  
2018 ◽  
Vol 6 (1) ◽  
pp. 2 ◽  
Author(s):  
Ryunosuke Ogawa ◽  
Masahiro Hirata ◽  
Birhane Gebremedhin ◽  
Satoshi Uchida ◽  
Toru Sakai ◽  
...  
Keyword(s):  
Land Management ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Satellite Image ◽  
Field Investigation ◽  
Sustainable Land Management ◽  
Forest Land ◽  
Grazing Land ◽  
Feed Resources ◽  
Use Of Resources

The search for a sustainable land management has become a universal issue. It is especially necessary to discuss sustainable land management and to secure a site with enough feed supply to improve the lives of the farmers in the Ethiopian Highlands. This research studied the Adi Zaboy watershed in Tigray in order to reveal the changes in land management, assess how the different forms of land management affected the vegetation through unsupervised classification and normalized difference vegetation index (NDVI) analysis with geographic information system (GIS) 10.5 using a WorldView-2 satellite image taken in September 2016 and field investigation, and consider how to allow both environmental preservation and sustainable use of feed resources. The land management types at the research site were classified as “seasonally-closed grazing land”, “prohibited grazing and protected forest land”, and “free grazing land”. On comparing the NDVI of each type of land management, it was found that the seasonally-closed grazing land makes it highly possible to secure and supply feed resources by limiting the grazing period. The expansion of the prohibited grazing and protected forest land is likely to tighten the restriction on the use of resources. Therefore, sustainable land management to secure feed resources may be possible by securing and actively using seasonally-closed grazing land, securing feed by a cut-and-carry, and using satellite images and GIS.

scholarly journals Using Hyperspectral and Multispectral Indices to Detect Water Stress for an Urban Turfgrass System

Agronomy ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. 439 ◽  
Author(s):  
Badzmierowski ◽  
McCall ◽  
Evanylo
Keyword(s):  
Water Stress ◽  
Spectral Reflectance ◽  
Festuca Arundinacea ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
High Water ◽  
Management Tool ◽  
N Accumulation ◽  
Spatial Coverage ◽  
Reflectance Data

Spectral reflectance measurements collected from hyperspectral and multispectral radiometers have the potential to be a management tool for detecting water and nutrient stress in turfgrass. Hyperspectral radiometers collect hundreds of narrowband reflectance data compared to multispectral radiometers that collect three to ten broadband reflectance data for a cheaper cost. Spectral reflectance data have been used to create vegetation indices such as the normalized difference vegetation index (NDVI) and the simple ratio vegetation index (RVI) to assess crop growth, density, and fertility. Other indices such as the water band index (WBI) (narrowband index) and green-to-red ratio index (GRI) (both broadband and narrowband index) have been proposed to predict soil moisture status in turfgrass systems. The objective of this study was to compare the value of multispectral and hyperspectral radiometers to assess soil volumetric water content (VWC) and tall fescue (Festuca arundinacea Schreb.) responses. The multispectral radiometer VI had the strongest relationships to turfgrass quality, biomass, and tissue N accumulation during the trial period (April 2017–August 2018). Soil VWC had the strongest relationship to WBI (r = 0.60), followed by GRI and NDVI (both r = 0.54) for the 0% evapotranspiration (ET). Nonlinear regression showed strong relationships at high water stress periods in each year for WBI (r = 0.69–0.79), GRI (r = 0.64–0.75), and NDVI (r = 0.58–0.79). Broadband index data collected using a mobile multispectral sensor is a cheaper alternative to hyperspectral radiometry and can provide better spatial coverage.

scholarly journals Rainfall Trend and Its Relationship with Normalized Difference Vegetation Index in a Restored Semi-Arid Wetland of South Africa

2020 ◽  
Vol 12 (21) ◽  
pp. 8919
Author(s):  
Florence M. Murungweni ◽  
Onisimo Mutanga ◽  
John O. Odiyo
Keyword(s):  
South Africa ◽  
Quantile Regression ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Rainfall Data ◽  
Ecosystem Change ◽  
Annual Rainfall ◽  
Rainfall Trend ◽  
Vegetation Productivity ◽  
Rainfall Trends

Clearance of terrestrial wetland vegetation and rainfall variations affect biodiversity. The rainfall trend–NDVI (Normalized Difference Vegetation Index) relationship was examined to assess the extent to which rainfall affects vegetation productivity within Nylsvley, Ramsar site in Limpopo Province, South Africa. Daily rainfall data measured from eight rainfall stations between 1950 and 2016 were used to generate seasonal and annual rainfall data. Mann-Kendall and quantile regression were applied to assess trends in rainfall data. NDVI was derived from satellite images from between 1984 and 2003 using Zonal statistics and correlated with rainfall of the same period to assess vegetation dynamics. Mann-Kendall and Sen’s slope estimator showed only one station had a significant increasing rainfall trend annually and seasonally at p < 0.05, whereas all the other stations showed insignificant trends in both rainfall seasons. Quantile regression showed 50% and 62.5% of the stations had increasing annual and seasonal rainfall, respectively. Of the stations, 37.5% were statistically significant at p < 0.05, indicating increasing and decreasing rainfall trends. These rainfall trends show that the rainfall of Nylsvley decreased between 1995 and 2003. The R2 between rainfall and NDVI of Nylsvley is 55% indicating the influence of rainfall variability on vegetation productivity. The results underscore the impact of decadal rainfall patterns on wetland ecosystem change.

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