2024-08-28 05:10:02 +00:00
{
"cells": [
{
"cell_type": "code",
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"id": "1a452ff0-7c2f-4fa7-abf4-f7c8b09a9932",
2024-09-23 04:14:06 +00:00
"metadata": {
"tags": []
},
2024-08-28 05:10:02 +00:00
"outputs": [
{
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" */\n",
"function render(props, node) {\n",
" var div = document.createElement(\"div\");\n",
" var script = document.createElement(\"script\");\n",
" node.appendChild(div);\n",
" node.appendChild(script);\n",
"}\n",
"\n",
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" */\n",
"function handle_add_output(event, handle) {\n",
" var output_area = handle.output_area;\n",
" var output = handle.output;\n",
" if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
" return\n",
" }\n",
" var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
" var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
" if (id !== undefined) {\n",
" var nchildren = toinsert.length;\n",
" var html_node = toinsert[nchildren-1].children[0];\n",
" html_node.innerHTML = output.data[HTML_MIME_TYPE];\n",
" var scripts = [];\n",
" var nodelist = html_node.querySelectorAll(\"script\");\n",
" for (var i in nodelist) {\n",
" if (nodelist.hasOwnProperty(i)) {\n",
" scripts.push(nodelist[i])\n",
" }\n",
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"\n",
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" var newScript = document.createElement(\"script\");\n",
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" oldScript.parentNode.replaceChild(newScript, oldScript);\n",
" });\n",
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" toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n",
" }\n",
" output_area._hv_plot_id = id;\n",
" if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n",
" window.PyViz.plot_index[id] = Bokeh.index[id];\n",
" } else {\n",
" window.PyViz.plot_index[id] = null;\n",
" }\n",
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" var bk_div = document.createElement(\"div\");\n",
" bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
" var script_attrs = bk_div.children[0].attributes;\n",
" for (var i = 0; i < script_attrs.length; i++) {\n",
" toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
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" output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
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" var id = handle.cell.output_area._hv_plot_id;\n",
" var server_id = handle.cell.output_area._bokeh_server_id;\n",
" if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n",
" var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n",
" if (server_id !== null) {\n",
" comm.send({event_type: 'server_delete', 'id': server_id});\n",
" return;\n",
" } else if (comm !== null) {\n",
" comm.send({event_type: 'delete', 'id': id});\n",
" }\n",
" delete PyViz.plot_index[id];\n",
" if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n",
" var doc = window.Bokeh.index[id].model.document\n",
" doc.clear();\n",
" const i = window.Bokeh.documents.indexOf(doc);\n",
" if (i > -1) {\n",
" window.Bokeh.documents.splice(i, 1);\n",
" }\n",
" }\n",
"}\n",
"\n",
"/**\n",
" * Handle kernel restart event\n",
" */\n",
"function handle_kernel_cleanup(event, handle) {\n",
" delete PyViz.comms[\"hv-extension-comm\"];\n",
" window.PyViz.plot_index = {}\n",
"}\n",
"\n",
"/**\n",
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" */\n",
"function handle_update_output(event, handle) {\n",
" handle_clear_output(event, {cell: {output_area: handle.output_area}})\n",
" handle_add_output(event, handle)\n",
"}\n",
"\n",
"function register_renderer(events, OutputArea) {\n",
" function append_mime(data, metadata, element) {\n",
" // create a DOM node to render to\n",
" var toinsert = this.create_output_subarea(\n",
" metadata,\n",
" CLASS_NAME,\n",
" EXEC_MIME_TYPE\n",
" );\n",
" this.keyboard_manager.register_events(toinsert);\n",
" // Render to node\n",
" var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
" render(props, toinsert[0]);\n",
" element.append(toinsert);\n",
" return toinsert\n",
" }\n",
"\n",
" events.on('output_added.OutputArea', handle_add_output);\n",
" events.on('output_updated.OutputArea', handle_update_output);\n",
" events.on('clear_output.CodeCell', handle_clear_output);\n",
" events.on('delete.Cell', handle_clear_output);\n",
" events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n",
"\n",
" OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
" safe: true,\n",
" index: 0\n",
" });\n",
"}\n",
"\n",
"if (window.Jupyter !== undefined) {\n",
" try {\n",
" var events = require('base/js/events');\n",
" var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
" if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
" register_renderer(events, OutputArea);\n",
" }\n",
" } catch(err) {\n",
" }\n",
"}\n"
],
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},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/html": [
"<style>*[data-root-id],\n",
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" box-sizing: border-box;\n",
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"\n",
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".cell-output-ipywidget-background:has(\n",
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".cell-output-ipywidget-background:has(> .lm-Widget > *[data-root-id]) {\n",
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"</style>"
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},
"metadata": {},
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"data": {
"application/javascript": [
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" console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
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" console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
" }\n",
"\n",
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" console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
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" require([\"jspanel\"], function(jsPanel) {\n",
"\twindow.jsPanel = jsPanel\n",
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" })\n",
" require([\"jspanel-modal\"], function() {\n",
"\ton_load()\n",
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"\ton_load()\n",
" })\n",
" require([\"jspanel-hint\"], function() {\n",
"\ton_load()\n",
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"\ton_load()\n",
" })\n",
" require([\"jspanel-dock\"], function() {\n",
"\ton_load()\n",
" })\n",
" require([\"gridstack\"], function(GridStack) {\n",
"\twindow.GridStack = GridStack\n",
"\ton_load()\n",
" })\n",
" require([\"notyf\"], function() {\n",
"\ton_load()\n",
" })\n",
" root._bokeh_is_loading = css_urls.length + 9;\n",
" } else {\n",
" root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n",
" }\n",
"\n",
" var existing_stylesheets = []\n",
" var links = document.getElementsByTagName('link')\n",
" for (var i = 0; i < links.length; i++) {\n",
" var link = links[i]\n",
" if (link.href != null) {\n",
"\texisting_stylesheets.push(link.href)\n",
" }\n",
" }\n",
" for (var i = 0; i < css_urls.length; i++) {\n",
" var url = css_urls[i];\n",
" if (existing_stylesheets.indexOf(url) !== -1) {\n",
"\ton_load()\n",
"\tcontinue;\n",
" }\n",
" const element = document.createElement(\"link\");\n",
" element.onload = on_load;\n",
" element.onerror = on_error;\n",
" element.rel = \"stylesheet\";\n",
" element.type = \"text/css\";\n",
" element.href = url;\n",
" console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
" document.body.appendChild(element);\n",
" } if (((window['jsPanel'] !== undefined) && (!(window['jsPanel'] instanceof HTMLElement))) || window.requirejs) {\n",
" var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/jspanel.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu.js', 'https://cdn.holoviz.org/panel/1.2.3/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock.js'];\n",
" for (var i = 0; i < urls.length; i++) {\n",
" skip.push(urls[i])\n",
" }\n",
" } if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n",
" var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/gridstack/gridstack@7.2.3/dist/gridstack-all.js'];\n",
" for (var i = 0; i < urls.length; i++) {\n",
" skip.push(urls[i])\n",
" }\n",
" } if (((window['Notyf'] !== undefined) && (!(window['Notyf'] instanceof HTMLElement))) || window.requirejs) {\n",
" var urls = ['https://cdn.holoviz.org/panel/1.2.3/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n",
" for (var i = 0; i < urls.length; i++) {\n",
" skip.push(urls[i])\n",
" }\n",
" } var existing_scripts = []\n",
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" for (var i = 0; i < scripts.length; i++) {\n",
" var script = scripts[i]\n",
" if (script.src != null) {\n",
"\texisting_scripts.push(script.src)\n",
" }\n",
" }\n",
" for (var i = 0; i < js_urls.length; i++) {\n",
" var url = js_urls[i];\n",
" if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n",
"\tif (!window.requirejs) {\n",
"\t on_load();\n",
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" var element = document.createElement('script');\n",
" element.onload = on_load;\n",
" element.onerror = on_error;\n",
" element.async = false;\n",
" element.src = url;\n",
" console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
" document.head.appendChild(element);\n",
" }\n",
" for (var i = 0; i < js_modules.length; i++) {\n",
" var url = js_modules[i];\n",
" if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n",
"\tif (!window.requirejs) {\n",
"\t on_load();\n",
"\t}\n",
"\tcontinue;\n",
" }\n",
" var element = document.createElement('script');\n",
" element.onload = on_load;\n",
" element.onerror = on_error;\n",
" element.async = false;\n",
" element.src = url;\n",
" element.type = \"module\";\n",
" console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
" document.head.appendChild(element);\n",
" }\n",
" for (const name in js_exports) {\n",
" var url = js_exports[name];\n",
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"\tif (!window.requirejs) {\n",
"\t on_load();\n",
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" }\n",
" var element = document.createElement('script');\n",
" element.onerror = on_error;\n",
" element.async = false;\n",
" element.type = \"module\";\n",
" console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
" element.textContent = `\n",
" import ${name} from \"${url}\"\n",
" window.${name} = ${name}\n",
" window._bokeh_on_load()\n",
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" }\n",
" if (!js_urls.length && !js_modules.length) {\n",
" on_load()\n",
" }\n",
" };\n",
"\n",
" function inject_raw_css(css) {\n",
" const element = document.createElement(\"style\");\n",
" element.appendChild(document.createTextNode(css));\n",
" document.body.appendChild(element);\n",
" }\n",
"\n",
" var js_urls = [];\n",
" var js_modules = [];\n",
" var js_exports = {};\n",
" var css_urls = [];\n",
" var inline_js = [ function(Bokeh) {\n",
" Bokeh.set_log_level(\"info\");\n",
" },\n",
"function(Bokeh) {} // ensure no trailing comma for IE\n",
" ];\n",
"\n",
" function run_inline_js() {\n",
" if ((root.Bokeh !== undefined) || (force === true)) {\n",
" for (var i = 0; i < inline_js.length; i++) {\n",
" inline_js[i].call(root, root.Bokeh);\n",
" }\n",
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"\tvar NewBokeh = root.Bokeh;\n",
"\tif (Bokeh.versions === undefined) {\n",
"\t Bokeh.versions = new Map();\n",
"\t}\n",
"\tif (NewBokeh.version !== Bokeh.version) {\n",
"\t Bokeh.versions.set(NewBokeh.version, NewBokeh)\n",
"\t}\n",
"\troot.Bokeh = Bokeh;\n",
" }} else if (Date.now() < root._bokeh_timeout) {\n",
" setTimeout(run_inline_js, 100);\n",
" } else if (!root._bokeh_failed_load) {\n",
" console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
" root._bokeh_failed_load = true;\n",
" }\n",
" root._bokeh_is_initializing = false\n",
" }\n",
"\n",
" function load_or_wait() {\n",
" // Implement a backoff loop that tries to ensure we do not load multiple\n",
" // versions of Bokeh and its dependencies at the same time.\n",
" // In recent versions we use the root._bokeh_is_initializing flag\n",
" // to determine whether there is an ongoing attempt to initialize\n",
" // bokeh, however for backward compatibility we also try to ensure\n",
" // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n",
" // before older versions are fully initialized.\n",
" if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n",
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},
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"text": [
2024-09-23 08:24:46 +00:00
"CPU times: user 13.3 s, sys: 4.22 s, total: 17.5 s\n",
"Wall time: 11 s\n"
2024-08-28 05:10:02 +00:00
]
}
],
"source": [
"%%time\n",
"%matplotlib inline\n",
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]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "219d4303-b606-45e1-a3a7-0b52e3cfe279",
2024-09-23 04:14:06 +00:00
"metadata": {
"tags": []
},
2024-08-28 05:10:02 +00:00
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
2024-09-23 08:24:46 +00:00
"Starting new cluster.\n",
"CPU times: user 787 ms, sys: 55.6 ms, total: 843 ms\n",
"Wall time: 10.2 s\n"
2024-08-28 05:10:02 +00:00
]
},
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"data": {
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" <div style=\"margin-left: 48px;\">\n",
" <h3 style=\"margin-bottom: 0px;\">Client</h3>\n",
2024-09-23 08:24:46 +00:00
" <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Client-7794ccc2-7984-11ef-8a19-c203d8520d0b</p>\n",
2024-08-28 05:10:02 +00:00
" <table style=\"width: 100%; text-align: left;\">\n",
"\n",
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" \n",
" <td style=\"text-align: left;\"><strong>Connection method:</strong> Cluster object</td>\n",
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" \n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
2024-09-23 08:24:46 +00:00
" <strong>Dashboard: </strong> <a href=\"https://hub.asia.easi-eo.solutions/services/dask-gateway/clusters/easihub.2f308b6e03354a3ea9982ee8bf367ac0/status\" target=\"_blank\">https://hub.asia.easi-eo.solutions/services/dask-gateway/clusters/easihub.2f308b6e03354a3ea9982ee8bf367ac0/status</a>\n",
2024-08-28 05:10:02 +00:00
" </td>\n",
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" \n",
2024-09-23 08:24:46 +00:00
" <button style=\"margin-bottom: 12px;\" data-commandlinker-command=\"dask:populate-and-launch-layout\" data-commandlinker-args='{\"url\": \"https://hub.asia.easi-eo.solutions/services/dask-gateway/clusters/easihub.2f308b6e03354a3ea9982ee8bf367ac0/status\" }'>\n",
2024-08-28 05:10:02 +00:00
" Launch dashboard in JupyterLab\n",
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" \n",
"\n",
" \n",
" <details>\n",
" <summary style=\"margin-bottom: 20px;\"><h3 style=\"display: inline;\">Cluster Info</h3></summary>\n",
" <div style='background-color: #f2f2f2; display: inline-block; padding: 10px; border: 1px solid #999999;'>\n",
" <h3>GatewayCluster</h3>\n",
" <ul>\n",
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" <li><b>Name: </b>easihub.2f308b6e03354a3ea9982ee8bf367ac0\n",
" <li><b>Dashboard: </b><a href='https://hub.asia.easi-eo.solutions/services/dask-gateway/clusters/easihub.2f308b6e03354a3ea9982ee8bf367ac0/status' target='_blank'>https://hub.asia.easi-eo.solutions/services/dask-gateway/clusters/easihub.2f308b6e03354a3ea9982ee8bf367ac0/status</a>\n",
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" </ul>\n",
"</div>\n",
"\n",
" </details>\n",
" \n",
"\n",
" </div>\n",
"</div>"
],
"text/plain": [
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"<Client: 'tls://10.0.55.227:8786' processes=0 threads=0, memory=0 B>"
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]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"%%time\n",
"# Dask gateway\n",
"cluster, client = notebook_utils.initialize_dask(use_gateway=True, workers=(1,4))\n",
"dc = datacube.Datacube()\n",
"\n",
"# Configure s3 access\n",
"configure_s3_access(aws_unsigned=False, requester_pays=True, client=client)\n",
"\n",
"client"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "56a9e23b-435e-4235-b09d-196662813f5a",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"## cấu hình thời gian lấy ảnh và tọa độ\n",
"date_range = ('2022-09-01', '2023-10-01')\n",
"longtitude_range = (105.86575, 105.94120)\n",
"latitude_range = (9.65070, 9.69850)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "606d23a3-7db6-4eb2-9d31-1e31ee3aaef7",
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Most common native CRS: EPSG:32648\n",
"No datasets require offset correction\n",
"The valid_data_mask and scale (no offset) have been applied to the reflectance bands\n"
]
},
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"</style><pre class='xr-text-repr-fallback'><xarray.Dataset>\n",
"Dimensions: (time: 78, y: 532, x: 830)\n",
"Coordinates:\n",
" * time (time) datetime64[ns] 2022-09-02T03:35:38.706000 ... 2023-09...\n",
" * y (y) float64 1.072e+06 1.072e+06 ... 1.067e+06 1.067e+06\n",
" * x (x) float64 5.95e+05 5.95e+05 5.95e+05 ... 6.033e+05 6.033e+05\n",
" spatial_ref int32 32648\n",
"Data variables:\n",
" red (time, y, x) float32 dask.array<chunksize=(1, 532, 830), meta=np.ndarray>\n",
" nir (time, y, x) float32 dask.array<chunksize=(1, 532, 830), meta=np.ndarray>\n",
" scl (time, y, x) uint8 dask.array<chunksize=(1, 532, 830), meta=np.ndarray>\n",
"Attributes:\n",
" crs: EPSG:32648\n",
2024-09-23 08:24:46 +00:00
" grid_mapping: spatial_ref</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-015b6a41-a159-41e3-9333-d6b6aa54fa2d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-015b6a41-a159-41e3-9333-d6b6aa54fa2d' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 78</li><li><span class='xr-has-index'>y</span>: 532</li><li><span class='xr-has-index'>x</span>: 830</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-854fd545-c093-42df-9cfd-15ac44872d8d' class='xr-section-summary-in' type='checkbox' checked><label for='section-854fd545-c093-42df-9cfd-15ac44872d8d' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-09-02T03:35:38.706000 ... 2...</div><input id='attrs-068c0a5b-4110-43cc-a5ec-30b6333b8727' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-068c0a5b-4110-43cc-a5ec-30b6333b8727' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-670b2524-edc3-4ba1-b586-e2ecb6c35d56' class='xr-var-data-in' type='checkbox'><label for='data-670b2524-edc3-4ba1-b586-e2ecb6c35d56' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd></dl></div><div class='xr-var-data'><pre>array(['2022-09-02T03:35:38.706000000', '2022-09-07T03:35:28.392000000',\n",
2024-08-28 05:10:02 +00:00
" '2022-09-12T03:35:36.984000000', '2022-09-17T03:35:28.396000000',\n",
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" '2022-10-02T03:35:33.797000000', '2022-10-07T03:35:23.874000000',\n",
" '2022-10-12T03:35:31.889000000', '2022-10-17T03:35:25.895000000',\n",
" '2022-10-22T03:35:28.478000000', '2022-10-27T03:35:25.671000000',\n",
" '2022-11-01T03:35:30.553000000', '2022-11-06T03:35:24.840000000',\n",
" '2022-11-11T03:35:30.080000000', '2022-11-16T03:35:26.282000000',\n",
" '2022-11-21T03:35:27.133000000', '2022-11-26T03:35:25.806000000',\n",
" '2022-12-01T03:35:26.747000000', '2022-12-06T03:35:23.575000000',\n",
" '2022-12-11T03:35:26.920000000', '2022-12-16T03:35:24.874000000',\n",
" '2022-12-21T03:35:24.727000000', '2022-12-26T03:35:25.874000000',\n",
" '2022-12-31T03:35:25.489000000', '2023-01-05T03:35:26.328000000',\n",
" '2023-01-10T03:35:24.897000000', '2023-01-15T03:35:22.879000000',\n",
" '2023-01-20T03:35:21.331000000', '2023-01-25T03:35:24.561000000',\n",
" '2023-01-30T03:35:24.703000000', '2023-02-04T03:35:25.086000000',\n",
" '2023-02-09T03:35:25.381000000', '2023-02-14T03:35:24.987000000',\n",
" '2023-02-24T03:35:26.862000000', '2023-03-01T03:35:23.929000000',\n",
" '2023-03-06T03:35:29.457000000', '2023-03-11T03:35:21.972000000',\n",
" '2023-03-16T03:35:30.684000000', '2023-03-21T03:35:25.016000000',\n",
" '2023-03-26T03:35:29.316000000', '2023-03-31T03:35:24.882000000',\n",
" '2023-04-05T03:35:29.667000000', '2023-04-10T03:35:26.745000000',\n",
" '2023-04-15T03:35:27.482000000', '2023-04-20T03:35:25.073000000',\n",
" '2023-04-25T03:35:28.492000000', '2023-04-30T03:35:26.887000000',\n",
" '2023-05-05T03:35:29.183000000', '2023-05-10T03:35:26.031000000',\n",
" '2023-05-15T03:35:30.428000000', '2023-05-20T03:35:28.932000000',\n",
" '2023-05-25T03:35:31.398000000', '2023-05-30T03:35:30.380000000',\n",
" '2023-06-04T03:35:30.790000000', '2023-06-09T03:35:30.281000000',\n",
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" '2023-08-03T03:35:31.242000000', '2023-08-08T03:35:31.056000000',\n",
" '2023-08-13T03:35:32.189000000', '2023-08-18T03:35:32.563000000',\n",
" '2023-08-23T03:35:30.964000000', '2023-08-28T03:35:32.323000000',\n",
" '2023-09-02T03:35:31.370000000', '2023-09-07T03:35:31.878000000',\n",
" '2023-09-12T03:35:30.073000000', '2023-09-17T03:35:30.006000000',\n",
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2024-09-23 08:24:46 +00:00
" dtype='datetime64[ns]')</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.072e+06 1.072e+06 ... 1.067e+06</div><input id='attrs-ea6fdb26-8387-45c6-baf1-fd97917627da' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ea6fdb26-8387-45c6-baf1-fd97917627da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8f0a9737-cf27-4030-8dae-069806115f0a' class='xr-var-data-in' type='checkbox'><label for='data-8f0a9737-cf27-4030-8dae-069806115f0a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>metre</dd><dt><span>resolution :</span></dt><dd>-10.0</dd><dt><span>crs :</span></dt><dd>EPSG:32648</dd></dl></div><div class='xr-var-data'><pre>array([1072225., 1072215., 1072205., ..., 1066935., 1066925., 1066915.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.95e+05 5.95e+05 ... 6.033e+05</div><input id='attrs-403e03f1-0ce6-4759-98cf-211d597e4336' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-403e03f1-0ce6-4759-98cf-211d597e4336' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b47eafc2-3c4c-453f-a539-6b063a21d396' class='xr-var-data-in' type='checkbox'><label for='data-b47eafc2-3c4c-453f-a539-6b063a21d396' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>metre</dd><dt><span>resolution :</span></dt><dd>10.0</dd><dt><span>crs :</span></dt><dd>EPSG:32648</dd></dl></div><div class='xr-var-data'><pre>array([594975., 594985., 594995., ..., 603245., 603255., 603265.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>32648</div><input id='attrs-dfe3b72b-df90-45f6-837e-5073d36bf3b1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dfe3b72b-df90-45f6-837e-5073d36bf3b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-33af120e-dc73-4b93-9064-a1a9e1e5f212' class='xr-var-data-in' type='checkbox'><label for='data-33af120e-dc73-4b93-9064-a1a9e1e5f212' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>spatial_ref :</span></dt><dd>PROJCS["WGS 84 / UTM zone 48N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",105],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],AUTHORITY["EPSG","32648"]]</dd><dt><span>grid_mapping_name :</span></dt><dd>transverse_mercator</dd></dl></div><div class='xr-var-data'><pre>array(32648, dtype=int32)</pre>
2024-08-28 05:10:02 +00:00
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2024-09-23 08:24:46 +00:00
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2024-08-28 05:10:02 +00:00
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2024-09-23 08:24:46 +00:00
"</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>scl</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>dask.array<chunksize=(1, 532, 830), meta=np.ndarray></div><input id='attrs-2fd4a5d5-0da4-404a-a32d-a0450e40ce18' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2fd4a5d5-0da4-404a-a32d-a0450e40ce18' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2e43ba1a-78ad-478a-9c34-8d7ef6dae55b' class='xr-var-data-in' type='checkbox'><label for='data-2e43ba1a-78ad-478a-9c34-8d7ef6dae55b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>1</dd><dt><span>nodata :</span></dt><dd>0</dd><dt><span>flags_definition :</span></dt><dd>{'qa': {'bits': [0, 1, 2, 3, 4, 5, 6, 7], 'values': {'0': 'no data', '1': 'saturated or defective', '2': 'dark area pixels', '3': 'cloud shadows', '4': 'vegetation', '5': 'bare soils', '6': 'water', '7': 'unclassified', '8': 'cloud medium probability', '9': 'cloud high probability', '10': 'thin cirrus', '11': 'snow or ice'}, 'description': 'Sen2Cor Scene Classification'}}</dd><dt><span>crs :</span></dt><dd>EPSG:32648</dd><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div><div class='xr-var-data'><table>\n",
2024-08-28 05:10:02 +00:00
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"</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-eee174a9-c338-4a34-b832-d34ba94454c6' class='xr-section-summary-in' type='checkbox' ><label for='section-eee174a9-c338-4a34-b832-d34ba94454c6' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-38e92405-89f5-47d5-bcd8-a0db3fccf83c' class='xr-index-data-in' type='checkbox'/><label for='index-38e92405-89f5-47d5-bcd8-a0db3fccf83c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex(['2022-09-02 03:35:38.706000', '2022-09-07 03:35:28.392000',\n",
2024-08-28 05:10:02 +00:00
" '2022-09-12 03:35:36.984000', '2022-09-17 03:35:28.396000',\n",
" '2022-09-22 03:35:33.676000', '2022-09-27 03:35:26.885000',\n",
" '2022-10-02 03:35:33.797000', '2022-10-07 03:35:23.874000',\n",
" '2022-10-12 03:35:31.889000', '2022-10-17 03:35:25.895000',\n",
" '2022-10-22 03:35:28.478000', '2022-10-27 03:35:25.671000',\n",
" '2022-11-01 03:35:30.553000', '2022-11-06 03:35:24.840000',\n",
" '2022-11-11 03:35:30.080000', '2022-11-16 03:35:26.282000',\n",
" '2022-11-21 03:35:27.133000', '2022-11-26 03:35:25.806000',\n",
" '2022-12-01 03:35:26.747000', '2022-12-06 03:35:23.575000',\n",
" '2022-12-11 03:35:26.920000', '2022-12-16 03:35:24.874000',\n",
" '2022-12-21 03:35:24.727000', '2022-12-26 03:35:25.874000',\n",
" '2022-12-31 03:35:25.489000', '2023-01-05 03:35:26.328000',\n",
" '2023-01-10 03:35:24.897000', '2023-01-15 03:35:22.879000',\n",
" '2023-01-20 03:35:21.331000', '2023-01-25 03:35:24.561000',\n",
" '2023-01-30 03:35:24.703000', '2023-02-04 03:35:25.086000',\n",
" '2023-02-09 03:35:25.381000', '2023-02-14 03:35:24.987000',\n",
" '2023-02-24 03:35:26.862000', '2023-03-01 03:35:23.929000',\n",
" '2023-03-06 03:35:29.457000', '2023-03-11 03:35:21.972000',\n",
" '2023-03-16 03:35:30.684000', '2023-03-21 03:35:25.016000',\n",
" '2023-03-26 03:35:29.316000', '2023-03-31 03:35:24.882000',\n",
" '2023-04-05 03:35:29.667000', '2023-04-10 03:35:26.745000',\n",
" '2023-04-15 03:35:27.482000', '2023-04-20 03:35:25.073000',\n",
" '2023-04-25 03:35:28.492000', '2023-04-30 03:35:26.887000',\n",
" '2023-05-05 03:35:29.183000', '2023-05-10 03:35:26.031000',\n",
" '2023-05-15 03:35:30.428000', '2023-05-20 03:35:28.932000',\n",
" '2023-05-25 03:35:31.398000', '2023-05-30 03:35:30.380000',\n",
" '2023-06-04 03:35:30.790000', '2023-06-09 03:35:30.281000',\n",
" '2023-06-14 03:35:31.608000', '2023-06-19 03:35:30.646000',\n",
" '2023-06-24 03:35:30.720000', '2023-06-29 03:35:30.713000',\n",
" '2023-07-04 03:35:31.975000', '2023-07-09 03:35:31.850000',\n",
" '2023-07-14 03:35:31.327000', '2023-07-19 03:35:30.791000',\n",
" '2023-07-24 03:35:32.589000', '2023-07-29 03:35:31.826000',\n",
" '2023-08-03 03:35:31.242000', '2023-08-08 03:35:31.056000',\n",
" '2023-08-13 03:35:32.189000', '2023-08-18 03:35:32.563000',\n",
" '2023-08-23 03:35:30.964000', '2023-08-28 03:35:32.323000',\n",
" '2023-09-02 03:35:31.370000', '2023-09-07 03:35:31.878000',\n",
" '2023-09-12 03:35:30.073000', '2023-09-17 03:35:30.006000',\n",
" '2023-09-22 03:35:30.187000', '2023-09-27 03:35:28.858000'],\n",
2024-09-23 08:24:46 +00:00
" dtype='datetime64[ns]', name='time', freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e76bc9a4-975e-4229-ba9f-f510d4eb9547' class='xr-index-data-in' type='checkbox'/><label for='index-e76bc9a4-975e-4229-ba9f-f510d4eb9547' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1072225.0, 1072215.0, 1072205.0, 1072195.0, 1072185.0, 1072175.0,\n",
2024-08-28 05:10:02 +00:00
" 1072165.0, 1072155.0, 1072145.0, 1072135.0,\n",
" ...\n",
" 1067005.0, 1066995.0, 1066985.0, 1066975.0, 1066965.0, 1066955.0,\n",
" 1066945.0, 1066935.0, 1066925.0, 1066915.0],\n",
2024-09-23 08:24:46 +00:00
" dtype='float64', name='y', length=532))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d319f184-8964-42bf-8b3e-6bf131a15c51' class='xr-index-data-in' type='checkbox'/><label for='index-d319f184-8964-42bf-8b3e-6bf131a15c51' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([594975.0, 594985.0, 594995.0, 595005.0, 595015.0, 595025.0, 595035.0,\n",
2024-08-28 05:10:02 +00:00
" 595045.0, 595055.0, 595065.0,\n",
" ...\n",
" 603175.0, 603185.0, 603195.0, 603205.0, 603215.0, 603225.0, 603235.0,\n",
" 603245.0, 603255.0, 603265.0],\n",
2024-09-23 08:24:46 +00:00
" dtype='float64', name='x', length=830))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f6f57c22-7e38-4dac-9161-9bf77e9db006' class='xr-section-summary-in' type='checkbox' checked><label for='section-f6f57c22-7e38-4dac-9161-9bf77e9db006' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>crs :</span></dt><dd>EPSG:32648</dd><dt><span>grid_mapping :</span></dt><dd>spatial_ref</dd></dl></div></li></ul></div></div>"
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],
"text/plain": [
"<xarray.Dataset>\n",
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"Coordinates:\n",
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" * y (y) float64 1.072e+06 1.072e+06 ... 1.067e+06 1.067e+06\n",
" * x (x) float64 5.95e+05 5.95e+05 5.95e+05 ... 6.033e+05 6.033e+05\n",
" spatial_ref int32 32648\n",
"Data variables:\n",
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" nir (time, y, x) float32 dask.array<chunksize=(1, 532, 830), meta=np.ndarray>\n",
" scl (time, y, x) uint8 dask.array<chunksize=(1, 532, 830), meta=np.ndarray>\n",
"Attributes:\n",
" crs: EPSG:32648\n",
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]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"## truy vấn ảnh vệ tinh sen2\n",
"data = load_data(dc, date_range, longtitude_range, latitude_range)\n",
"notebook_utils.heading(notebook_utils.xarray_object_size(data))\n",
"display(data)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "54e04079-2c12-4de1-8541-0579fbfad4a1",
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
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"text/plain": [
" bits \\\n",
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{
"data": {
"text/plain": [
"{'0': 'no data',\n",
" '1': 'saturated or defective',\n",
" '2': 'dark area pixels',\n",
" '3': 'cloud shadows',\n",
" '4': 'vegetation',\n",
" '5': 'bare soils',\n",
" '6': 'water',\n",
" '7': 'unclassified',\n",
" '8': 'cloud medium probability',\n",
" '9': 'cloud high probability',\n",
" '10': 'thin cirrus',\n",
" '11': 'snow or ice'}"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
2024-09-23 08:24:46 +00:00
"CPU times: user 83.7 ms, sys: 11.6 ms, total: 95.3 ms\n",
"Wall time: 93.1 ms\n"
2024-08-28 05:10:02 +00:00
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
2024-09-23 08:24:46 +00:00
"model_id": "209e9d51b2f04cafbe42698101310087",
2024-08-28 05:10:02 +00:00
"version_major": 2,
"version_minor": 0
},
"text/plain": [
"VBox()"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%%time\n",
"# Tiến hành loại bỏ các vị trí bị mây ảnh hưởng\n",
"result = mask_clean(data)\n",
"progress(result)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "565f467b-3002-4d24-a300-d34ce548f7e3",
"metadata": {
"tags": []
},
"outputs": [
{
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"</style><pre class='xr-text-repr-fallback'><xarray.DataArray 'NDVI' (time: 78, y: 532, x: 830)>\n",
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2024-09-23 08:24:46 +00:00
" spatial_ref int32 32648</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'NDVI'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 78</li><li><span class='xr-has-index'>y</span>: 532</li><li><span class='xr-has-index'>x</span>: 830</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-ff19fa9a-6dc7-49a7-b880-a65e486c15d3' class='xr-array-in' type='checkbox' checked><label for='section-ff19fa9a-6dc7-49a7-b880-a65e486c15d3' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>dask.array<chunksize=(1, 532, 830), meta=np.ndarray></span></div><div class='xr-array-data'><table>\n",
2024-08-28 05:10:02 +00:00
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2024-09-23 08:24:46 +00:00
"</table></div></div></li><li class='xr-section-item'><input id='section-f58a8ce8-09b4-4b48-910f-9c1f407db1ed' class='xr-section-summary-in' type='checkbox' checked><label for='section-f58a8ce8-09b4-4b48-910f-9c1f407db1ed' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2022-09-02T03:35:38.706000 ... 2...</div><input id='attrs-c4bec759-ef32-4cec-b8e1-7185094e9c78' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c4bec759-ef32-4cec-b8e1-7185094e9c78' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0328c7e2-4733-4e9b-8171-2f3525b1d6ad' class='xr-var-data-in' type='checkbox'><label for='data-0328c7e2-4733-4e9b-8171-2f3525b1d6ad' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd></dl></div><div class='xr-var-data'><pre>array(['2022-09-02T03:35:38.706000000', '2022-09-07T03:35:28.392000000',\n",
2024-08-28 05:10:02 +00:00
" '2022-09-12T03:35:36.984000000', '2022-09-17T03:35:28.396000000',\n",
" '2022-09-22T03:35:33.676000000', '2022-09-27T03:35:26.885000000',\n",
" '2022-10-02T03:35:33.797000000', '2022-10-07T03:35:23.874000000',\n",
" '2022-10-12T03:35:31.889000000', '2022-10-17T03:35:25.895000000',\n",
" '2022-10-22T03:35:28.478000000', '2022-10-27T03:35:25.671000000',\n",
" '2022-11-01T03:35:30.553000000', '2022-11-06T03:35:24.840000000',\n",
" '2022-11-11T03:35:30.080000000', '2022-11-16T03:35:26.282000000',\n",
" '2022-11-21T03:35:27.133000000', '2022-11-26T03:35:25.806000000',\n",
" '2022-12-01T03:35:26.747000000', '2022-12-06T03:35:23.575000000',\n",
" '2022-12-11T03:35:26.920000000', '2022-12-16T03:35:24.874000000',\n",
" '2022-12-21T03:35:24.727000000', '2022-12-26T03:35:25.874000000',\n",
" '2022-12-31T03:35:25.489000000', '2023-01-05T03:35:26.328000000',\n",
" '2023-01-10T03:35:24.897000000', '2023-01-15T03:35:22.879000000',\n",
" '2023-01-20T03:35:21.331000000', '2023-01-25T03:35:24.561000000',\n",
" '2023-01-30T03:35:24.703000000', '2023-02-04T03:35:25.086000000',\n",
" '2023-02-09T03:35:25.381000000', '2023-02-14T03:35:24.987000000',\n",
" '2023-02-24T03:35:26.862000000', '2023-03-01T03:35:23.929000000',\n",
" '2023-03-06T03:35:29.457000000', '2023-03-11T03:35:21.972000000',\n",
" '2023-03-16T03:35:30.684000000', '2023-03-21T03:35:25.016000000',\n",
" '2023-03-26T03:35:29.316000000', '2023-03-31T03:35:24.882000000',\n",
" '2023-04-05T03:35:29.667000000', '2023-04-10T03:35:26.745000000',\n",
" '2023-04-15T03:35:27.482000000', '2023-04-20T03:35:25.073000000',\n",
" '2023-04-25T03:35:28.492000000', '2023-04-30T03:35:26.887000000',\n",
" '2023-05-05T03:35:29.183000000', '2023-05-10T03:35:26.031000000',\n",
" '2023-05-15T03:35:30.428000000', '2023-05-20T03:35:28.932000000',\n",
" '2023-05-25T03:35:31.398000000', '2023-05-30T03:35:30.380000000',\n",
" '2023-06-04T03:35:30.790000000', '2023-06-09T03:35:30.281000000',\n",
" '2023-06-14T03:35:31.608000000', '2023-06-19T03:35:30.646000000',\n",
" '2023-06-24T03:35:30.720000000', '2023-06-29T03:35:30.713000000',\n",
" '2023-07-04T03:35:31.975000000', '2023-07-09T03:35:31.850000000',\n",
" '2023-07-14T03:35:31.327000000', '2023-07-19T03:35:30.791000000',\n",
" '2023-07-24T03:35:32.589000000', '2023-07-29T03:35:31.826000000',\n",
" '2023-08-03T03:35:31.242000000', '2023-08-08T03:35:31.056000000',\n",
" '2023-08-13T03:35:32.189000000', '2023-08-18T03:35:32.563000000',\n",
" '2023-08-23T03:35:30.964000000', '2023-08-28T03:35:32.323000000',\n",
" '2023-09-02T03:35:31.370000000', '2023-09-07T03:35:31.878000000',\n",
" '2023-09-12T03:35:30.073000000', '2023-09-17T03:35:30.006000000',\n",
" '2023-09-22T03:35:30.187000000', '2023-09-27T03:35:28.858000000'],\n",
2024-09-23 08:24:46 +00:00
" dtype='datetime64[ns]')</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.072e+06 1.072e+06 ... 1.067e+06</div><input id='attrs-63c623b4-3629-415f-946c-b02ba3e19764' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-63c623b4-3629-415f-946c-b02ba3e19764' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6fd652fb-0bef-4785-b7a0-e49d8c83bc4b' class='xr-var-data-in' type='checkbox'><label for='data-6fd652fb-0bef-4785-b7a0-e49d8c83bc4b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>metre</dd><dt><span>resolution :</span></dt><dd>-10.0</dd><dt><span>crs :</span></dt><dd>EPSG:32648</dd></dl></div><div class='xr-var-data'><pre>array([1072225., 1072215., 1072205., ..., 1066935., 1066925., 1066915.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.95e+05 5.95e+05 ... 6.033e+05</div><input id='attrs-ad197b55-a390-4a13-b336-11ea9980a44f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ad197b55-a390-4a13-b336-11ea9980a44f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ca1e370f-8b9b-4d2d-993f-4badcc71d857' class='xr-var-data-in' type='checkbox'><label for='data-ca1e370f-8b9b-4d2d-993f-4badcc71d857' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>metre</dd><dt><span>resolution :</span></dt><dd>10.0</dd><dt><span>crs :</span></dt><dd>EPSG:32648</dd></dl></div><div class='xr-var-data'><pre>array([594975., 594985., 594995., ..., 603245., 603255., 603265.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>32648</div><input id='attrs-c60a48cd-9838-47eb-91f8-26cf37c82f16' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c60a48cd-9838-47eb-91f8-26cf37c82f16' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4561b323-1d00-4921-9282-fd73c290642d' class='xr-var-data-in' type='checkbox'><label for='data-4561b323-1d00-4921-9282-fd73c290642d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>spatial_ref :</span></dt><dd>PROJCS["WGS 84 / UTM zone 48N",GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.0174532925199433,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]],PROJECTION["Transverse_Mercator"],PARAMETER["latitude_of_origin",0],PARAMETER["central_meridian",105],PARAMETER["scale_factor",0.9996],PARAMETER["false_easting",500000],PARAMETER["false_northing",0],UNIT["metre",1,AUTHORITY["EPSG","9001"]],AXIS["Easting",EAST],AXIS["Northing",NORTH],AUTHORITY["EPSG","32648"]]</dd><dt><span>grid_mapping_name :</span></dt><dd>transverse_mercator</dd></dl></div><div class='xr-var-data'><pre>array(32648, dtype=int32)</pre>
2024-08-28 05:10:02 +00:00
" '2022-09-12 03:35:36.984000', '2022-09-17 03:35:28.396000',\n",
" '2022-09-22 03:35:33.676000', '2022-09-27 03:35:26.885000',\n",
" '2022-10-02 03:35:33.797000', '2022-10-07 03:35:23.874000',\n",
" '2022-10-12 03:35:31.889000', '2022-10-17 03:35:25.895000',\n",
" '2022-10-22 03:35:28.478000', '2022-10-27 03:35:25.671000',\n",
" '2022-11-01 03:35:30.553000', '2022-11-06 03:35:24.840000',\n",
" '2022-11-11 03:35:30.080000', '2022-11-16 03:35:26.282000',\n",
" '2022-11-21 03:35:27.133000', '2022-11-26 03:35:25.806000',\n",
" '2022-12-01 03:35:26.747000', '2022-12-06 03:35:23.575000',\n",
" '2022-12-11 03:35:26.920000', '2022-12-16 03:35:24.874000',\n",
" '2022-12-21 03:35:24.727000', '2022-12-26 03:35:25.874000',\n",
" '2022-12-31 03:35:25.489000', '2023-01-05 03:35:26.328000',\n",
" '2023-01-10 03:35:24.897000', '2023-01-15 03:35:22.879000',\n",
" '2023-01-20 03:35:21.331000', '2023-01-25 03:35:24.561000',\n",
" '2023-01-30 03:35:24.703000', '2023-02-04 03:35:25.086000',\n",
" '2023-02-09 03:35:25.381000', '2023-02-14 03:35:24.987000',\n",
" '2023-02-24 03:35:26.862000', '2023-03-01 03:35:23.929000',\n",
" '2023-03-06 03:35:29.457000', '2023-03-11 03:35:21.972000',\n",
" '2023-03-16 03:35:30.684000', '2023-03-21 03:35:25.016000',\n",
" '2023-03-26 03:35:29.316000', '2023-03-31 03:35:24.882000',\n",
" '2023-04-05 03:35:29.667000', '2023-04-10 03:35:26.745000',\n",
" '2023-04-15 03:35:27.482000', '2023-04-20 03:35:25.073000',\n",
" '2023-04-25 03:35:28.492000', '2023-04-30 03:35:26.887000',\n",
" '2023-05-05 03:35:29.183000', '2023-05-10 03:35:26.031000',\n",
" '2023-05-15 03:35:30.428000', '2023-05-20 03:35:28.932000',\n",
" '2023-05-25 03:35:31.398000', '2023-05-30 03:35:30.380000',\n",
" '2023-06-04 03:35:30.790000', '2023-06-09 03:35:30.281000',\n",
" '2023-06-14 03:35:31.608000', '2023-06-19 03:35:30.646000',\n",
" '2023-06-24 03:35:30.720000', '2023-06-29 03:35:30.713000',\n",
" '2023-07-04 03:35:31.975000', '2023-07-09 03:35:31.850000',\n",
" '2023-07-14 03:35:31.327000', '2023-07-19 03:35:30.791000',\n",
" '2023-07-24 03:35:32.589000', '2023-07-29 03:35:31.826000',\n",
" '2023-08-03 03:35:31.242000', '2023-08-08 03:35:31.056000',\n",
" '2023-08-13 03:35:32.189000', '2023-08-18 03:35:32.563000',\n",
" '2023-08-23 03:35:30.964000', '2023-08-28 03:35:32.323000',\n",
" '2023-09-02 03:35:31.370000', '2023-09-07 03:35:31.878000',\n",
" '2023-09-12 03:35:30.073000', '2023-09-17 03:35:30.006000',\n",
" '2023-09-22 03:35:30.187000', '2023-09-27 03:35:28.858000'],\n",
2024-09-23 08:24:46 +00:00
" dtype='datetime64[ns]', name='time', freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c0523781-6f7e-4249-9a6b-2d520b2ffc91' class='xr-index-data-in' type='checkbox'/><label for='index-c0523781-6f7e-4249-9a6b-2d520b2ffc91' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1072225.0, 1072215.0, 1072205.0, 1072195.0, 1072185.0, 1072175.0,\n",
2024-08-28 05:10:02 +00:00
" 1072165.0, 1072155.0, 1072145.0, 1072135.0,\n",
" ...\n",
" 1067005.0, 1066995.0, 1066985.0, 1066975.0, 1066965.0, 1066955.0,\n",
" 1066945.0, 1066935.0, 1066925.0, 1066915.0],\n",
2024-09-23 08:24:46 +00:00
" dtype='float64', name='y', length=532))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-952b7d2f-e8c7-4bd5-b7f4-3d13ee1ae66c' class='xr-index-data-in' type='checkbox'/><label for='index-952b7d2f-e8c7-4bd5-b7f4-3d13ee1ae66c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([594975.0, 594985.0, 594995.0, 595005.0, 595015.0, 595025.0, 595035.0,\n",
2024-08-28 05:10:02 +00:00
" 595045.0, 595055.0, 595065.0,\n",
" ...\n",
" 603175.0, 603185.0, 603195.0, 603205.0, 603215.0, 603225.0, 603235.0,\n",
" 603245.0, 603255.0, 603265.0],\n",
2024-09-23 08:24:46 +00:00
" dtype='float64', name='x', length=830))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cc7e3cc9-45f4-48a7-9136-92c878bbf242' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-cc7e3cc9-45f4-48a7-9136-92c878bbf242' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
2024-08-28 05:10:02 +00:00
],
"text/plain": [
"<xarray.DataArray 'NDVI' (time: 78, y: 532, x: 830)>\n",
"dask.array<truediv, shape=(78, 532, 830), dtype=float32, chunksize=(1, 532, 830), chunktype=numpy.ndarray>\n",
"Coordinates:\n",
" * time (time) datetime64[ns] 2022-09-02T03:35:38.706000 ... 2023-09...\n",
" * y (y) float64 1.072e+06 1.072e+06 ... 1.067e+06 1.067e+06\n",
" * x (x) float64 5.95e+05 5.95e+05 5.95e+05 ... 6.033e+05 6.033e+05\n",
" spatial_ref int32 32648"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Tiến hành tính toán NDVI\n",
"ds1 = calculate_indices(result, index='NDVI', satellite_mission='s2')\n",
"ndvi = ds1[\"NDVI\"]\n",
"display(ndvi)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "f3930d43-c159-49bf-8260-68b14681729d",
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
2024-09-23 08:24:46 +00:00
"<matplotlib.image.AxesImage at 0x7fab18e85240>"
2024-08-28 05:10:02 +00:00
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"## ảnh ndvi chưa fill nan\n",
"plt.imshow(ndvi.isel(time=50))"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "5372d50c-7b05-475e-bdce-ed36a8ea794d",
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
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"<matplotlib.image.AxesImage at 0x7fab1939bac0>"
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]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# đặt thời gian các mùa\n",
"time_split = [slice('2022-09-01', '2023-01-01'), \n",
" slice('2023-01-01', '2023-05-01'),\n",
" slice('2023-05-01', '2023-07-01'),\n",
" slice('2023-07-01', '2023-10-01')]\n",
"\n",
"# fill nan\n",
"fill_nan_ndvi = fill_nan(ndvi, time_split)\n",
"\n",
"## ảnh ndivi đã fill nan\n",
"plt.imshow(fill_nan_ndvi.isel(time=50))"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "4e11434c-24ff-48f4-8611-b3baeb300de3",
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
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"CPU times: user 73.6 ms, sys: 2.22 ms, total: 75.8 ms\n",
"Wall time: 74.4 ms\n"
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]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
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"model_id": "1a7be681f2be4f109990b2ec364a3ef2",
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"version_major": 2,
"version_minor": 0
},
"text/plain": [
"VBox()"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"%%time\n",
"## tính ndvi theo tháng\n",
"average_ndvi = fill_nan_ndvi.resample(time='1M').mean().persist()\n",
"progress(average_ndvi)"
]
},
{
"cell_type": "code",
"execution_count": 10,
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"id": "a11993d1-567f-4d06-a772-5786bdeeb317",
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"metadata": {
"tags": []
},
"outputs": [],
"source": [
"# compute average_ndvi\n",
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"average_ndvi = average_ndvi.compute()"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "34e7fd9c-3a16-4c82-b210-2afc4a84772e",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"## cấu hình và vh vv file\n",
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"name_vh = \"ThuanHoa/ThuanHoa_VH.tif\"\n",
"name_vv = \"ThuanHoa/ThuanHoa_VV.tif\"\n",
"\n",
"# load dữ liệu sen1\n",
"dsvh, dsvv = load_sen1(name_vh, name_vv)"
]
},
{
"cell_type": "code",
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"execution_count": 12,
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"id": "5d29d5cf-31fd-4263-8ae4-2eb9690f739e",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"# load model RF\n",
"loaded_model = joblib.load(os.path.join(\"model_train\", \"model.joblib\"))\n",
"\n",
"# dự đoán\n",
"data_array = predict(loaded_model, data.rio.crs, average_ndvi, dsvh, dsvv)"
]
},
{
"cell_type": "code",
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"execution_count": 13,
"id": "b6e705b1-f1e4-4c94-90aa-4e2ecd56290f",
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"metadata": {
"tags": []
},
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"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
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"/tmp/ipykernel_18969/1105393975.py:27: UserWarning: set_ticklabels() should only be used with a fixed number of ticks, i.e. after set_ticks() or using a FixedLocator.\n",
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" cbar.ax.set_yticklabels(labels)\n"
]
},
{
"data": {
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"text/plain": [
"<Figure size 640x480 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
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"source": [
"# cấu hình màu cho các loại đất\n",
"colors = [\n",
" \"#abcee9\",\n",
" \"#ffef44\",\n",
" \"#c4ff9e\",\n",
" \"#ffd6a8\",\n",
" \"#93ddda\",\n",
" \"#1aeef7\",\n",
" \"#ffa7f2\",\n",
" \"#33ee33\"\n",
"]\n",
"labels = [\n",
" \"Lúa tôm\",\n",
" \"Lúa\",\n",
" \"CHN\",\n",
" \"CLN\",\n",
" \"TS\",\n",
" \"Sông\",\n",
" \"Đất xây dựng\",\n",
" \"Rừng\"\n",
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"]\n",
"\n",
"# hiển thị phân loại sử dụng đất\n",
"cmap = ListedColormap(colors)\n",
"img = data_array.plot(cmap=cmap, add_colorbar=False)\n",
"cbar = plt.colorbar(img)\n",
"cbar.ax.set_yticklabels(labels)\n",
"plt.title(\"Phân loại sử dụng đất\")\n",
"plt.axis('off')\n",
"plt.show()"
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]
},
{
"cell_type": "code",
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"execution_count": 14,
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"id": "caa6893e-4167-4d85-8c5e-d03cdb55f71f",
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/env/lib/python3.10/site-packages/xarray/core/duck_array_ops.py:191: RuntimeWarning: invalid value encountered in cast\n",
" return data.astype(dtype, **kwargs)\n"
]
}
],
"source": [
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"# cấu hình shapefile ranh giới thuận hòa\n",
"thuanhoa_path = \"ThuanHoa/region/ST_ThuanHoa_Boundaryofficially.shp\"\n",
"\n",
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"# cắt theo ranh giới xã thuận hòa\n",
"region_result = cut_according_shp(thuanhoa_path, average_ndvi, data_array)"
]
},
{
"cell_type": "code",
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"execution_count": 15,
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"id": "177a672f-dc68-4987-a3c6-2123dff257c0",
"metadata": {
"tags": []
},
"outputs": [
{
"data": {},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/vnd.holoviews_exec.v0+json": "",
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" <div id=\"daab6490-3736-480c-be45-e5269a1d3280\" data-root-id=\"p1003\" style=\"display: contents;\"></div>\n",
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"</div>\n",
"<script type=\"application/javascript\">(function(root) {\n",
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" var docs_json = {\"46cedef9-0b0a-487f-b526-3a45cea872a9\":{\"version\":\"3.2.2\",\"title\":\"Bokeh Application\",\"roots\":[{\"type\":\"object\",\"name\":\"Row\",\"id\":\"p1003\",\"attributes\":{\"name\":\"Row00918\",\"stylesheets\":[\"\\n:host(.pn-loading.pn-arc):before, .pn-loading.pn-arc:before {\\n background-image: url(\\\"data:image/svg+xml;base64,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\\\");\\n background-size: auto calc(min(50%, 400px));\\n}\",{\"type\":\"object\",\"name\":\"ImportedStyleSheet\",\"id\":\"p1006\",\"attributes\":{\"url\":\"https://cdn.holoviz.org/panel/1.2.3/dist/css/loading.css\"}},{\"type\":\"object\",\"name\":\"ImportedStyleSheet\",\"id\":\"p1066\",\"attributes\":{\"url\":\"https://cdn.holoviz.org/panel/1.2.3/dist/css/listpanel.css\"}},{\"type\":\"object\",\"name\":\"ImportedStyleSheet\",\"id\":\"p1004\",\"attributes\":{\"url\":\"https://cdn.holoviz.org/panel/1.2.3/dist/bundled/theme/default.css\"}},{\"type\":\"object\",\"name\":\"ImportedStyleSheet\",\"id\":\"p1005\",\"attributes\":{\"url\":\"https://cdn.holoviz.org/panel/1.2.3/dist/bundled/theme/native.css\"}}],\"min_width\":700,\"margin\":0,\"sizing_mode\":\"stretch_width\",\"align\":\"start\",\"children\":[{\"type\":\"object\",\"name\":\"Spacer\",\"id\":\"p1007\",\"attributes\":{\"name\":\"HSpacer00926\",\"stylesheets\":[\"\\n:host(.pn-loading.pn-arc):before, .pn-loading.pn-arc:before {\\n background-image: url(\\\"data:image/svg+xml;base64,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\\\");\\n background-size: auto calc(min(50%, 400px));\\n}\",{\"id\":\"p1006\"},{\"id\":\"p1004\"},{\"id\":\"p1005\"}],\"margin\":0,\"sizing_mode\":\"stretch_width\",\"align\":\"start\"}},{\"type\":\"object\",\"name\":\"Figure\",\"id\":\"p1015\",\"attributes\":{\"subscribed_events\":{\"type\":\"set\",\"entries\":[\"rangesupdate\"]},\"width\":700,\"height\":300,\"margin\":[5,10],\"sizing_mode\":\"fixed\",\"align\":\"start\",\"x_range\":{\"type\":\"object\",\"name\":\"Range1d\",\"id\":\"p1008\",\"attributes\":{\"tags\":[[[\"x\",\"x coordinate of projection\",\"metre\"]],[]],\"start\":592913.3333333334,\"end\":605326.6666666666,\"reset_start\":592913.3333333334,\"reset_end\":605326.6666666666}},\"y_range\":{\"type\":\"object\",\"name\":\"Range1d\",\"id\":\"p1009\",\"attributes\":{\"tags\":[[[\"y\",\"y coordinate of projection\",\"metre\"]],{\"type\":\"map\",\"entries\":[[\"invert_yaxis\",false],[\"autorange\",false]]}],\"start\":1066910.0,\"end\":1072230.0,\"reset_start\":1066910.0,\"reset_end\":1072230.0}},\"x_scale\":{\"type\":\"object\",\"name\":\"LinearScale\",\"id\":\"p1025\"},\"y_scale\":{\"type\":\"object\",\"name\":\"LinearScale\",\"id\":\"p1026\"},\"title\":{\"type\":\"object\",\"name\":\"Title\",\"id\":\"p1018\",\"attributes\":{\"text\":\"Ph\\u00e2n lo\\u1ea1i s\\u1eed d\\u1ee5ng \\u0111\\u1ea5t\",\"text_color\":\"black\",\"text_font_size\":\"12pt\"}},\"rende
" var render_items = [{\"docid\":\"46cedef9-0b0a-487f-b526-3a45cea872a9\",\"roots\":{\"p1003\":\"daab6490-3736-480c-be45-e5269a1d3280\"},\"root_ids\":[\"p1003\"]}];\n",
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" var docs = Object.values(docs_json)\n",
" if (!docs) {\n",
" return\n",
" }\n",
" const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
" const is_dev = py_version.indexOf(\"+\") !== -1 || py_version.indexOf(\"-\") !== -1\n",
" function embed_document(root) {\n",
" var Bokeh = get_bokeh(root)\n",
" Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
" for (const render_item of render_items) {\n",
" for (const root_id of render_item.root_ids) {\n",
"\tconst id_el = document.getElementById(root_id)\n",
"\tif (id_el.children.length && (id_el.children[0].className === 'bk-root')) {\n",
"\t const root_el = id_el.children[0]\n",
"\t root_el.id = root_el.id + '-rendered'\n",
"\t}\n",
" }\n",
" }\n",
" }\n",
" function get_bokeh(root) {\n",
" if (root.Bokeh === undefined) {\n",
" return null\n",
" } else if (root.Bokeh.version !== py_version && !is_dev) {\n",
" if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
"\treturn null\n",
" }\n",
" return root.Bokeh.versions.get(py_version);\n",
" } else if (root.Bokeh.version === py_version) {\n",
" return root.Bokeh\n",
" }\n",
" return null\n",
" }\n",
" function is_loaded(root) {\n",
" var Bokeh = get_bokeh(root)\n",
" return (Bokeh != null && Bokeh.Panel !== undefined)\n",
" }\n",
" if (is_loaded(root)) {\n",
" embed_document(root);\n",
" } else {\n",
" var attempts = 0;\n",
" var timer = setInterval(function(root) {\n",
" if (is_loaded(root)) {\n",
" clearInterval(timer);\n",
" embed_document(root);\n",
" } else if (document.readyState == \"complete\") {\n",
" attempts++;\n",
" if (attempts > 200) {\n",
" clearInterval(timer);\n",
"\t var Bokeh = get_bokeh(root)\n",
"\t if (Bokeh == null || Bokeh.Panel == null) {\n",
" console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
"\t } else {\n",
"\t console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
"\t embed_document(root)\n",
"\t }\n",
" }\n",
" }\n",
" }, 25, root)\n",
" }\n",
"})(window);</script>"
],
"text/plain": [
":DynamicMap []\n",
" :Image [x,y] (value)"
]
},
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"execution_count": 15,
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"metadata": {
"application/vnd.holoviews_exec.v0+json": {
"id": "p1003"
}
},
"output_type": "execute_result"
}
],
"source": [
"# hiển thị kết quả phân loại sử dụng đất\n",
"colorval = list(range(len(colors)))\n",
"options = {\n",
" 'title': 'Phân loại sử dụng đất',\n",
" 'cmap': colors,\n",
" 'clim': (0, 8),\n",
" 'aspect': 'equal',\n",
" 'colorbar_opts': {\n",
" 'major_label_overrides': dict(zip(colorval, labels)),\n",
" 'major_label_text_align': 'left',\n",
" 'ticker': FixedTicker(ticks=colorval),\n",
" },\n",
"}\n",
" \n",
"region_result.hvplot(\n",
" rasterize = True, # Use Datashader, particularly useful for dask arrays\n",
" aggregator = reductions.mode(), # Datashader selects mode value, requires 'hv.Image'\n",
").options(opts.Image(**options))"
]
},
{
"cell_type": "code",
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"execution_count": 16,
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"id": "43580ab8-c637-4e79-b842-0131f970bfac",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"# Lưu lại kết quả\n",
"region_result.rio.to_raster(\"KetQuaPhanLoaiDat.tif\")"
]
},
{
"cell_type": "code",
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"execution_count": 17,
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"id": "890a9291-4516-4c1b-b831-0cd0fdbf53a8",
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"độ chính xác: 38.13%\n"
]
}
],
"source": [
"# Load dữ liệu test\n",
"test_path = \"ThuanHoa/DataTest/ThuanHoa_DKS_Kappa.shp\" # đường dẫn shp file train\n",
"test = load_train_data(test_path)\n",
"test.head()\n",
"\n",
"# đánh giá độ chính xác\n",
"accuracy_test(test, data_array)"
]
},
{
"cell_type": "code",
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"execution_count": 18,
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"id": "a23a5bd1-1a8c-448d-b239-8ba2d8e104f2",
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"metadata": {
"tags": []
},
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"outputs": [],
"source": [
"# đóng client, cluster\n",
"client.close()\n",
"cluster.close()"
]
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