A 1 km global cropland dataset from 10 000 BCE to 2100 CE

Cropland greatly impacts food security, energy supply, biodiversity, biogeochemical cycling, and climate change. Accurately and systematically understanding the effects of agricultural activities requires cropland spatial information with high resolution and a long time span. In this study, the first 1 km resolution global cropland proportion dataset for 10 000 BCE–2100 CE was produced. With the cropland map initialized in 2010 CE, we first harmonized the cropland demands extracted from the History Database of the Global Environment 3.2 (HYDE 3.2) and the Land-Use Harmonization 2 (LUH2) datasets and then spatially allocated the demands based on the combination of cropland suitability, kernel density, and other constraints. According to our maps, cropland originated from several independent centers and gradually spread to other regions, influenced by some important historical events. The spatial patterns of future cropland change differ in various scenarios due to the different socioeconomic pathways and mitigation levels. The global cropland area generally shows an increasing trend over the past years, from 0×106 km2 in 10 000 BCE to 2.8×106 km2 in 1500 CE, 6.2×106 km2 in 1850 CE, and 16.4×106 km2 in 2010 CE. It then follows diverse trajectories under future scenarios, with the growth rate ranging from 16.4 % to 82.4 % between 2010 CE and 2100 CE. There are large area disparities among different geographical regions. The mapping result coincides well with widely used datasets at present in both distribution pattern and total amount. With improved spatial resolution, our maps can better capture the cropland distribution details and spatial heterogeneity. The spatiotemporally continuous and conceptually consistent global cropland dataset serves as a more comprehensive alternative for long-term earth system simulations and other precise analyses. The flexible and efficient harmonization and downscaling framework can be applied to specific regions or extended to other land use and cover types through the adjustable parameters and open model structure. The 1 km global cropland maps are available at https://doi.org/10.5281/zenodo.5105689 (Cao et al., 2021a).

A 1 km global cropland dataset from 10000 BCE to 2100 CE

Cropland greatly impacts food security, energy supply, biodiversity, biogeochemical cycling, and climate change. Accurately and systematically understanding the effects of agricultural activities requires cropland spatial information with high resolution and a long time span. In this study, the first 1 km resolution global cropland proportion dataset for 10000 BCE–2100 CE was produced. With the cropland map initialized in 2010 CE, we first harmonized the cropland demands extracted from the History Database of the Global Environment 3.2 (HYDE 3.2) and the Land-Use Harmonization 2 (LUH2) datasets, and then spatially allocated the demands based on the combination of cropland suitability, kernel density, and other constraints. According to our maps, cropland originated from several independent centers and gradually spread to other regions, influenced by some important historical events. The spatial patterns of future cropland change differ in various scenarios due to the different socioeconomic pathways and mitigation levels. The global cropland area generally shows an increasing trend over the past years, from 0 million km2 in 10000 BCE grows to 2.8 million km2 in 1500 CE, 6.2 million km2 in 1850 CE, and 16.4 million km2 in 2010 CE. It then follows diverse trajectories under future scenarios, with the growth rate ranging from 18.6 % to 82.4 % between 2010 CE and 2100 CE. There are large area disparities among different geographical regions. The mapping result coincides well with widely-used datasets at present in both distribution pattern and total amount. With improved spatial resolution, our maps can better capture the cropland distribution details and spatial heterogeneity. The spatiotemporally continuous and conceptually consistent global cropland dataset serves as a more comprehensive alternative for long-term earth system simulations and other precise analyses. The flexible and efficient harmonization and downscaling framework can be applied to specific regions or extended to other land use/cover types through the adjustable parameters and open model structure. The 1 km global cropland maps are available at https://doi.org/10.5281/zenodo.5105689 (Cao et al., 2021a).

Mapping Essential Urban Land Use Categories in Beijing with a Fast Area of Interest (AOI)-Based Method

Urban land use mapping is critical to understanding human activities in space. The first national mapping result of essential urban land use categories of China (EULUC-China) was released in 2019. However, the overall accuracies in some of the plain cities such as Beijing, Chengdu, and Zhengzhou were lower than 50% because many parcel-based mapping units are large with mixed land uses. To address this shortcoming, we proposed an area of interest (AOI)-based mapping approach, choosing Beijing as our study area. The mapping process includes two major steps. First, grids with different sizes (i.e., 300 m, 200 m, and 100 m) were derived from original land parcels to obtain classification units with a suitable size. Then, features within these grids were extracted from Sentinel-2 spectral data, point of interest (POI), and Tencent Easygo crowdedness data. These features were classified using a random forest (RF) classifier with AOI data, resulting in a 10-category map of EULUC. Second, we superimposed the AOIs layer on classified units to do some rectification and offer more details at the building scale. The overall accuracy of the AOI layer reached 98%, and the overall accuracy of the mapping results reached 77%. This study provides a fast method for accurate geographic sample collection, which substantially reduces the amount of fieldwork for sample collection and improves the classification accuracy compared to previous EULUC mapping. The detailed urban land use map could offer more support for urban planning and environmental policymaking.

Pemetaan dan Rancangan Intervensi Untuk Beban Kerja Mental Overload pada Dosen IAIN Palangka Raya

Penelitian ini bertujuan untuk mengetahui pemetaan dan rancangan intervensi untuk beban kerja mental overload pada Dosen IAIN Palangka Raya. Jumlah subjek pada penelitian ini adalah 31 orang yang terdiri dari Dosen PNS dan Non PNS yang memiliki beban kerja dalam melaksanakan Tri Dharma Perguruan Tinggi minimal dalam satu Tahun Ajaran terakhir (Ganjil 2018/2019 atau Genap 2018/2019) lebih dari 16 Satuan Kredit Semester. Pengukuran beban kerja secara mental atau psikologis dapat diukur salah satunya dengan metode NASA-TLX. Metode NASA-TLX ialah suatu alat ukur yang digunakan dalam mengukur beban kerja mental secara subjektif. Hasil pemetaan beban kerja mental yaitu didapatkan skor rata-rata beban kerja mental sebesar 82 (delapan puluh dua) yang berada pada kategori berat. This study aims to determine the mapping and intervention design for mental overload workloads at IAIN Palangka Raya lecturers. The number of subjects in this study was 31 people consisting of PNS and Non-PNS lecturers who had a workload in implementing the Tri Dharma of Higher Education in the last one academic year (Odd 2018/2019 or Even 2018/2019) more than 16 Semester Credit Units. One of the mental or psychological measurements of workload is the NASA-TLX method. A NASA-TLX method is a measuring tool used in measuring mental workload subjectively. The mental workload mapping result is that the mental workload average score is 82 (eighty-two), which is in the heavy category.

EXPERIMENTAL ASSESSMENT OF 3D NARROW SPACE MAPPING TECHNOLOGIES

Narrow space surveying and mapping is of high importance for many applications, with the demand for digital 3D models in a low-cost and relatively fast way growing rapidly. This paper examines SLAM-based and image-based mapping systems for indoor mapping and focuses on the comparison of the 3D point clouds acquired from two commercial mapping systems, Leica BLK2GO and Matterport Pro2 3D (MC250). Issues that are addressed include the effect of the mapping trajectory on the produced mapping result, and the amount of mapping propagation error in narrow space surveying. The two systems are experimentally compared against both an ideal geometric target facility and in an example environment of a narrow corridor. Finally, results are given with derived metrics that can be possibly extended to several real applications.

Model Reduksi Risiko Kountur berdasarkan Perilaku Petani Jagung di Pulau Madura

<p>Corn as a food crop was grown by a lot of farmers in Madura Island. Madura farmers planted two kinds of corn varieties, namely local and hybrid. The main problem in corn farming on this island was its lower average yield than in other East Java regions. One of the main reasons for this low productivity was farming risk faced by farmers. This study aimed to identify risky behavior and design risk reduction by using Kountur model. Data were collected from 120 corn farmers that were chosen to represent corn farming conditions in Madura. The method of analysis used descriptive quantitative by using the Likert scale and contour risk model. The model categorized risk sources based on the opportunities and its impacts. This mapping result was used as a base for designing a strategy to reduce risk. The results showed that the behavior of both local and hybrid corn farmers was categorized mostly (around 80%) as risk-neutral and the rest as risk lovers. The Kountur analysis showed that the sources of risk with high opportunities and its impacts were corn price fluctuation, input price increase, pest and plant disease attacks, and labor force availability. This research suggests that risk reduction can be made by strengthening farmers’ bargaining position, improving the management of tradable input stock, applying integrated pest and disease management (IPM), and revitalizing <em>“gotong royong”</em> working system.</p><p> </p><p>Abstrak</p><p>Jagung merupakan tanaman pangan yang banyak diusahakan oleh petani di Pulau Madura. Petani di Pulau Madura menanam jagung varietas lokal dan hibrida. Masalah utama dalam usaha tani jagung di wilayah ini adalah capaian rata-rata produktivitas jauh lebih rendah dibandingkan daerah lain di Jawa Timur. Salah satu faktor penyebab rendahnya produktivitas adalah tingginya risiko berusaha tani yang dihadapi petani. Penelitian ini bertujuan untuk mengidentifikasi perilaku risiko dan mendesain pengurangan risiko dengan menggunakan Model Kountur. Data dikumpulkan dari 120 petani jagung yang dipilih untuk mewakili gambaran usaha tani jagung di Madura. Metode analisis yang digunakan adalah diskriptif kuantitatif dengan menggunakan skala Likert dan model risiko Kountur. Model ini mengelompokkan sumber-sumber risiko berdasarkan peluang dan dampaknya. Hasil pemetaan digunakan sebagai dasar untuk mendesain strategi reduksi risiko. Hasil penelitian menunjukkan bahwa perilaku kedua kelompok petani jagung lokal dan jagung hibrida sama, yaitu sebagian besar petani (sekitar 80%) <em>risk neutral</em> dan sisanya <em>risk lover</em>. Berdasarkan analisis Kountur, diketahui sumber risiko yang peluang dan dampaknya besar adalah fluktuasi harga jagung, kenaikan harga input, serangan hama dan penyakit, serta ketersediaan tenaga kerja. Reduksi risiko yang dapat dilakukan adalah merevitalisasi keberadaan kelompok tani dengan berbagai macam program, antara lain yaitu penguatan posisi tawar dalam penentuan harga, manajemen stok input yang diperdagangkan, penggunaan Pengelolaan Hama dan Penyakit Terpadu (PHT), dan mengintensifkan kembali sistem kerja gotong royong.</p>

Pemetaan Arah Desain Rice box untuk Pengguna Di Indonesia

In 2011 and 2016, the author had been designed a rice box based on user aspect. The result indicated the change of rice box product design in form of dimension/ load capacity. This indication then followed by continued study in order to find the comprehensive design of rice box development. This research is focused on design mapping based on design direction of rice box that had been done in 2011, 2016 and 2019, also perceptual mapping method on existing rice box products. The aim is to find the tendency user preference to rice box design. The result showed that the significant value for user preference is rice box with capacity of 12 kg and slowly leave the rice box with capacity of 30 kg. This study also argued that there is an implication of rice consumption changing. The result is hopefully could become the reference in rice box design based on mapping result that can be applied by industrial stakeholder.

Optimasi Proses Klasterisasi di MySQL DBMS dengan Mengintegrasikan Algoritme MIC-Kmeans Menggunakan Bahasa SQL dalam Stored Procedure

<p>Proses klasterisasi data di <em>DBMS</em> akan lebih efisien jika dilakukan langsung di dalam <em>DBMS</em> itu sendiri karena <em>DBMS</em> mendukung untuk pengelolaan data yang baik. <em>SQL-Kmeans</em> merupakan salah satu metode yang sebelumnya telah digunakan untuk mengintegrasikan algoritme klasterisasi <em>K-means</em> ke dalam <em>DBMS</em> menggunakan <em>SQL</em>. Akan tetapi, metode ini juga membawa kelemahan dari algoritme <em>K-means</em> itu sendiri yaitu lamanya iterasi untuk mencapai konvergen dan keakuratan hasil klasterisasi yang belum optimal akibat dari proses inisialisasi <em>centroid</em> awal secara acak. Algoritme <em>Median Initial Centroid (MIC)-Kmeans</em> merupakan pengembangan dari algoritme <em>K-means</em> yang bisa memberikan solusi optimal dalam menentukan awal <em>centroid</em> yang berdampak pada keakuratan dan lamanya iterasi. Dengan keunggulan yang dimiliki algoritme <em>MIC-Kmeans</em>, maka dalam penelitian ini dipilih sebagai alternatif algoritme yang diintegrasikan dalam proses klasterisasi data secara langsung di <em>DBMS</em> menggunakan <em>SQL</em>. Proses integrasinya meliputi 4 tahap yaitu tahap inisialisasi tabel <em>dataset</em>, tahap pemetaan algoritme <em>MIC-Kmeans</em> pada <em>SQL</em> dan tabel <em>dataset</em>, tahap perancangan <em>SQL </em>untuk tiap hasil pemetaan dan tahap implementasi rancangan <em>SQL</em> dalam <em>MySQL</em> <em>stored procedure</em>. Hasil pengujian menunjukkan bahwa metode <em>SQL MIC-Kmeans</em> bisa mengurangi 43% jumlah iterasi dan mengurangi 39% waktu yang dibutuhkan dari metode <em>SQL-Kmeans</em> untuk mencapai konvergen. Selain itu, nilai rata-rata <em>silhouette coefficient </em>metode <em>SQL MIC-Kmeans</em> adalah 0,79 dan masuk dalam kategori <em>strong structure</em> (nilai rentang 0,7 sampai 1). Sedangkan nilai rata-rata <em>silhouette coefficient </em>metode <em>SQL-Kmeans </em>adalah<em> </em>0,68<em> </em>dan masuk dalam kategori <em>medium structure </em>(nilai rentang 0,5 sampai 0,7).</p><p class="Judul2"><strong><em>Abstract</em></strong></p><p class="Judul2"><em>The process of data clustering in the DBMS will be more efficient because the DBMS supports good data management. SQL-Kmeans is a method that has been used to integrate K-means clustering algorithms into DBMS using SQL. However, it carries the weakness of the K-means algorithm itself in the duration of iterations to reach convergence and the accuracy of clustering due to the centroid initialization process randomly. Median Initial Centroid (MIC)-Kmeans algorithm is a development of the K-means algorithm that can provide the optimal solution in determining the initial centroid which has an impact on the accuracy and duration of iterations. With the advantages of the MIC-Kmeans algorithm, the method was chosen as an alternative algorithm to be integrated in the DBMS using SQL for a clustering. The integration process includes 4 stages, there are dataset initialization, SQL algorithm mapping and dataset table, SQL design for each mapping result, and implementation SQL in the MySQL stored procedure. The test results show that the SQL MIC-Kmeans method can reduce 43% the number of iterations and reduce 39% of the time required from the SQL-Kmeans method to reach convergence. In addition, the average value of the coefficient SQL MIC-Kmeans method is 0.79 and categorized as strong structure (value ranges from 0.7 to 1). While, the average value of the coefficient SQL-Kmeans method is 0.68 and categorized as medium structure (value ranges from 0.5 to 0.7).</em></p>

Kajian Morfometri Ranu Grati Menggunakan GPSMAP 585 dan SIG

<strong>Ranu Grati’s Morphometry Study Using GPSMAP 585 and GIS</strong>. In the study of pollution load capacity of a reservoir or lake, its required information such as innudation area, average of depths and innudation volume, but those data at sometimes unavailable and out of date. The aims of this research are to find out depth distribution in Ranu Grati and represent it on a map. Depth map or bathymetry map that resulted is show morphological condition that can be used for further study e.g calculation of Ranu Grati capacity for aquaculture. Area of inundation, inundation volume and average depth of Ranu Grati can be figured out by using Garmin GPSMAP 585, Sentinel 2a imagery, BingMap and GIS analysis with ArcGIS according to those mapping data. Visualization of the mapping result through 3D view is used to increase understanding Ranu Grati morphometric conditions such as for Ranu Grati carriying capacity for aquaculture etc.. The result shows maximum depth that recorded during mapping is 121, 9 m. Meanwhile, area of inundation and volume are 1.734.223,07 m² and 124.491.952,55 m³respectively.

Analisis Model SIPABIO dalam Pemetaan Potensi Konflik Menjelang Pemilu Legslatif Tahun 2019 di Kabupaten Aceh

Kabupaten Aceh Tenggara merupakan daerah yang sering luput dari pemantauan konflik pemilu. Hal ini terlihat dari hasil pemantauan pemilu oleh beberapa lembaga yang menyatakan bahwa Aceh Tenggara tidak termasuk kedalam daerah rawan konflik. Sebaliknya, pemberitaan disejumlah media masa menuliskan konflik pemilu di Aceh Tenggara terjadi mulai dari tahun 20062017.Penelitian ini bertujuan untuk memetakan konflik pemilu yang terjadi di Aceh tenggara sepanjang tahun 2006-2017. Hasil pemetaan konflik ini dipergunakan untuk memproyeksikan potensi konflik yang mungkin muncul pada pemilu legislatif 2019. Penelitian ini pula menggunakan metode kualitatif dengan memantau media masa baik cetak dan elektronik serta mengunjungi langsung Kabupaten Aceh Tenggara untuk melakukan wawancara dengan pihak terkait. Data yang didapatkan dianalisis dengan menggunakan model SIPABIO (Source, Issue Parties, Attitude, Behavior, Intervention, and Outcome). Hasil dari penelitian ini menunjukkan bahwa Aceh Tenggara merupakan daerah berpotensi konflik. Berdasarkan hasil pemetaan konflik model SIPABIO, dapat disimpulkan bahwa terdapat tiga pihak utama yang menjadi sumber konflik yaitu KIP Aceh Tenggara, Kepolisian, dan simpatisan masing-masing calon. Ketiganya dominan menunjukkan sikap non coercive action dengan melakukan intimidasi, money politic, dan demonstrasi. Meskipun potensi konflik relatif kecil, kewaspadaan dan tindakan preventif harus terus diupayakan untuk meminimalisir terjadinya konflik pada pemilu legislatif yang akan datang. Southeast Aceh is a region which is often missed from general election conflict surveillance. This can be seen from the general election surveillance result of some institutions which stated that Southeast Aceh was not included into an area with high conflict possibility. On the other hand, the news from some of mass media stated that general election conflict in Southeast Aceh occurred since 2006-2017. This research aimed to map the general election conflict which happened in Southeast Aceh in 2006-2017. The result of the conflict mapping was used to project conflict potential which might happen in legislative general election 2019. This research used qualitative method by observing printed and electronic mass media and also including a visit to Southeast Aceh to interview the involving party. The data were analyzed using Source, Issue, Parties, Attitude, Behavior, Intervention, and Outcome (SIPABIO) model. The research result showed that Southeast Aceh was an area with conflict potential. Based on the SIPABIO conflict mapping result, it could be concluded that there were three main parties acting as the conflict sources; they were Southeast Aceh Central Information Commission (KIP), Police, and the supporters of the candidates. These three parties were dominant in showing non-coercive action behavior by doing intimidation, money-politic, and demonstration. Although the conflict potential was relatively low, alertness and preventive action must always be maintained in order to minimize the conflict possibility in the future legislative general election.